biological determinants of therapeutic response to l

BIOLOGICAL DETERMINANTS OF THERAPEUTIC RESPONSE TO L-

ASPARAGINASE IN CHILDREN WITH ACUTE LYMPHOBLASTIC

LEUKAEMIA.

A thesis submitted to the University of Manchester for the degree of Doctor in Philosophy

In the Faculty of Medical and Human Sciences

2012

Dr. Ashish Narayan Masurekar

Supervisor

Professor Vaskar Saha

School of Cancer and Enabling Sciences Division of Cancer

Contents

2

Contents

Pages

Title 1 Contents 2 Figures and Tables 6 Abbreviations 9 Abstract 12 Declaration 13 Copyright Statement 14 Dedicated to 15 Gratitude 16 Acknowledgements 17 Chapter 1 Introduction 19 1.1 Background of childhood ALL 19 1.1.1 Clinical aspects 19 1.1.2 Aetiology 20 1.1.3 Therapy of ALL 24 1.1.4 Current outcome in childhood ALL 25 1.1.5 Heterogeneity observed in the clinical response to therapy 26 1.1.6 Current issues in treatment of childhood ALL 27 1.1.7 Relapse in childhood ALL 28 1.2 L-Asparaginase 29 1.2.1 Rationale for studying the determinants of response to ASNase 29 1.2.2 Structure of ASNase 30 1.2.3 Mechanism of action of ASNase 31 1.2.4 ASNase- source and products 31 1.2.5 Problems with ASNase therapy 32 1.2.6 Determinants of therapeutic response to ASNase 33 1.2.7 Preliminary data 35 1.3 Asparaginase Study 35 1.3.1 Rationale of this study 35 1.3.2 Hypothesis 37 1.3.3 Eligibility 37 1.3.4 Aims of the study 37 1.3.5 Objectives of the study 37 1.3.6 Study design 37 Chapter 2 Material and Methods 39 2.1 Reagents 39 2.2 Asparaginase study 39 2.2.1 Patient sample collection 39 2.2.2 Sample processing 39

Contents

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2.3 Techniques 40 2.3.1 Tissue culture 40 2.3.1.1 Cell lines 40 2.3.1.2 Cell culture, passage and collection of cell pellets and

supernatants 40

2.3.2 Molecular methods 41 2.3.2.1 RNA extraction 41 2.3.2.2 cDNA synthesis 42 2.3.2.3 Real time TaqMan gene expression assay for AEP 43 2.3.2.4 MicroRNA (miRNA) array 44 2.3.3 Biochemical methods 46 2.3.3.1 Protein extraction 46 2.3.3.2 Protein quantification 46 2.3.3.3 L-Asparaginase activity assay 46 2.3.4 Immunological methods 48 2.3.4.1 Chemiluminescent AEP ELISA 48 2.3.4.2 Immunoblotting 50 2.3.4.3 Immunoprecipitation assay 54 2.3.5 Other techniques 55 2.3.5.1 Capture of microvesicles 55 2.3.5.2 Immunoblotting of microvesicle lysate 58 2.3.5.3 In-vivo labelling of cells for AEP by fluorescent probe 58 2.3.5.4 Statistical methods 58 Chapter 3 Development of assays 60 3.1 Plasma Asparaginase activity assay-Indoxine method 60 3.1.1 Background for the assay 60 3.1.2 Principle of the assay 60 3.1.3 Performance of the assay 61 3.1.4 Pre-analytical effect of sample transport on Asparaginase activity 64 3.1.5 Summary 64 3.2 Expression of AEP by RQ-RTPCR in cell lines and patient

samples 66

3.2.1 Quality of RNA obtained from patient samples 66 3.2.2 Dynamic range of the assay 68 3.2.3 Consistency of the step of reverse transcription 68 3.2.4 Amplification efficiency of the assay 68 3.2.5 Selection of control gene 68 3.2.6 Expression of AEP by RQ-RTPCR in cell lines 72 3.2.7 Expression of AEP by RQ-RTPCR in patient samples 72 3.3. AEP ELISA 73 3.3.1 Development history of the assay 74 3.3.1.1 1st generation AEP ELISA 74

3.3.1.2 2nd generation AEP ELISA 77

3.3.1.3 3rd generation AEP ELISA 80

3.4 Quantifying active AEP 82 3.5 Summary of assays tested for AEP expression 89 Chapter 4 Asparaginase Study: L-Asparaginase activity 90 4.1 Background 90 4.1.1 Aims of the Asparaginase Study 94 4.1.2 Objectives of the Asparaginase Study 94 4.1.3 Design of the Asparaginase Study 95 4.1.4 Recruitment in the Asparaginase Study 97

Contents

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4.2 Results 98 4.2.1 Recruitment in the UKALL2003 arm of the Asparaginase Study 98 4.2.1.1 Patient characteristics 99 4.2.1.2 ASNase activity at individual time points 100 4.2.1.3 Serial ASNase activity results 102 4.2.1.4 Correlation of induction ASNase activity with biological factors and

therapeutic outcome 104

4.2.1.4 Time to event analysis 106 4.2.2 Results of patiens recruited in ALLR3 arm of the Asparaginase

Study 109

4.2.2.1 ALLR3 ASNase activity results 109 4.2.2.2 Outcome analysis of patients in ALLR3 who did not get PEG-

ASNase 110

4.3 Discussion 112 Chapter 5 Asparaginase Study: Determinants of ASNase activity 115 5.1 Background 115 5.2 Results 115 5.2.1 Role of cysteine proteases as predictive biomarkers to ASNase

therapy 115

5.2.2 Impact of Anti L-Asparaginase antibodies 121 5.2.2.1 Anti L-Asparaginase antibodies: Patients enrolled in the

UKALL2003 trial 121

5.2.2.1.1 The correlation between serial ASNase activity and antibodies to L-Asparaginase

121

5.2.2.1.2 Correlation between anti L-Asparaginase antibodies and clinical hypersensitivity

124

5.2.2.2 Anti L-Asparaginase antibodies: Patients enrolled in the ALLR3 study

124

5.2.3 Toxicity after PEG-ASNase 124 5.3 Discussion 128 Salient points of chapters 4 and 5 131 Chapter 6 Role of Bone Marrow Stromal Exosomes in Conferring Chemoprotection to Leukaemic Cells

133

6.1 Background 133 6.1.1 Drug resistance in ALL is multi-factorial 133 6.2 Results 137 6.2.1 Bone marrow stromal cell derived conditioned medium (BMSC-

CM) confers chemoprotection to SUPB15 cell line 137

6.2.2 Generation of SUPB15 MR cells 138

6.2.3 Exosomes in the BMSC-CM contributed to the BMSC-CM mediated chemoprotection

139

6.2.4 HS5 derived exosomes are taken up by SUPB15 and primary ALL cells

140

6.2.5 BMSC derived exosomes conferred broad spectrum chemoprotection to SUPB15 cells

141

6.2.6 Horizontal transfer of Micro-RNS (miRNA) from BMSC to leukaemic cells- a mechanism by which BMSC derived exosomes could confer broad spectrum chemoprotection to SUPB15MR cells

142

6.2.7 BMSC derived exosomal miRNAs target ROS pathway in leukaemic cells

150

Contents

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6.2.8 Further characterisation of SUPB15MR cells 151

6.3 Discussion 154 Chapter 7 Work in progress 158 7.1 Background 158 7.1.1 Nomenclature of membrane-limited vesicles 158 7.1.2 Functional role of vesicles 161 7.2 Preliminary results- Harvesting B cell derived MV 163 7.2.1 Pellet obtained after stage one of the method was enriched in

microvesicle markers and contained CD19 164

7.2.2 Immobilisation of CD19 expressing SD1 microvesicles on UltraLink A/G resin

166

7.2.3 Quantifying PKH67 labelled cell line MV by flow cytometry 168 7.2.4 Immobilised vesicles expressed microvesicle markers 170 7.2.5 MV from patient plasma 170 7.3 Discussion 172 Chapter 8 Concluding remarks 174 References 189 Achievements 213 Appendix Appendix 1 216 Appendix 2 219 Appendix 3 223 Appendix 4 235 Appendix 5 236

Total word count, including reference and appendix: 49,284

Tables and Figures

6

Figures and tables Pages

Chapter 1

Figure 1.1 Cytogenetic abnormalities in childhood ALL 22

Figure 1.2 Overview of standard chemotherapy treatment in childhood ALL

24

Figure 1.3 Outcome of ALL in successive MRC chilhood ALL trials 25

Figure 1.4 Event free survival according to cytogenetics 27

Figure 1.5 Schedule of 1st two weeks of therapy in UKALL2003 30

Figure 1.6 Quartenary structure of ASNase 31

Table 1.1 Genetic alterations in childhood ALL 23

Table 1.2 ASNase products in clinical use 33

Table 1.3 Predicted pattern of response to PEG-ASNase 36

Chapter 2

Figure 2.1 Composition of mix 1 and 2 for cDNA synthesis 42

Figure 2.2 Schematic diagramm of AEP gene and the region of binding of TaqMan probe

44

Figure 2.3 Composition of the reverse transcription mix 45

Figure 2.4 Capture of microvesicles 57

Table 2.1 Reagents used for infra red and chemiluminescent immunoblotting

53

Table 2.2 Concentrations and source of antibodies 58

Chapter 3

Figure 3.1 MAAT assay 61

Figure 3.2 Linear range of the Indoxine assay 62

Figure 3.3 Performance of the Indoxine assay 63

Figure 3.4 Effect of sample transport on ASNase activity 65

Figure 3.5 Quality of patient RNA 67

Figure 3.6 Dynamic range of the assay 69

Figure 3.7 Consistency of the RT step 70

Figure 3.8 Performance of the control gene 71

Figure 3.9 Expression of AEP by RQ-RTPCR in cell lines 72

Figure 3.10 Expression of AEP by RQ-RTPCR in clinical samples 73

Figure 3.11 Performance of the 1st generation AEP ELISA 75

Figure 3.12 Quantification of AEP in SD1 cells using a 1st generation AEP ELISA

76

Figure 3.13 Optimisation of capture antibody of the 2nd generation AEP ELISA

78

Figure 3.14 Linear range and intra-assay variation of the 2nd generation AEP ELISA

79

Figure 3.15 Quantification of AEP in SD1 cells using a 2nd generation AEP ELISA

80

Figure 3.16 3rd Generation AEP ELISA 81

Figure 3.17 Basis of action of LP1 probe 83

Figure 3.18 Localisation of active AEP in SD1 cells 84

Tables and Figures

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Figure 3.19 Expression of active AEP by flow cytometry/Image stream 85

Figure 3.20 Suitability of LP 1 probe to measure active AEP 87

Figure 3.21 Correlation of expression of AEP at transcrip and protein levels

88

Chapter 4

Figure 4.1 Schedule of L-Asparaginase and sample time points 96

Figure 4.2 Overview of the statistical methods used to analyse the results

97

Figure 4.3 Recruitment in the Asparaginase Study-UKALL2003 arm 98

Figure 4.4 ASNase activity at individual time points 100

Figure 4.5 ASNase activity levles at TP1 and TP2 in NCI SR, precursor B ALL patients with good risk cytogenetics

106

Figure 4.6 Time to event analysis of patients in UKALL2003 with respect to response to PEG-ASNase

108

Figure 4.7 ASNase activity in ALLR3 patients 109

Figure 4.8 Contribution of PEG-ASNase at relapse 110

Table 4.1 Use of L-Asparaginase in chilhood ALL 91

Table 4.2 Patient characteristics 99

Table 4.3 Median ASNase activity levels 101

Table 4.4 Serial ASNase activity 103

Table 4.5 Correlation between induction ASNase and baseline characteristics

104

Table 4.6 Correlation between induction ASNase levels and outcome 105

Chapter 5

Figure 5.1 Correlation between AEP expression and baseline characteristics

117

Figure 5.2 Correlation between AEP expression, response to PEG-ASNase and outcome (SER/MRD)

118

Figure 5.3 Correlation between CTSB expression and baseline characteristics

119

Figure 5.4 Correlation between CTSB expression, response to PEG-ASNase and outcome (SER/MRD)

120

Figure 5.5 Correlation between hypersensitivity and ASNase activity 123

Table 5.1 Correlation between ASNase activity and anti L-Asparaginase antibodies

121

Table 5.2 Incidence of toxicity to PEG-ASNase 125

Table 5.3 Reported adverse reactions to ASNase 126

Chapter 6

Figure 6.1 Comparision between 2D and organotypic 3D culture systems

137

Figure 6.2 BMSC-CM confers non selective chemoprotection to leukaemic cells

138

Figure 6.3 Protective ability of <3kd fraction of BMSC 139

Tables and Figures

8

Figure 6.4 Transmission electron microscopy of <3kd fraction of BMSC pelleted by ultracentrifugation

140

Figure 6.5 Cellular uptake of BMSC exosomes 140

Figure 6.6 BMSC derived exosomes confer chemoprotection. 141

Figure 6.7 Exosomes contain small RNA 143

Figure 6.8 miRNA expression profiles in host and tumour- drug sensitive and drug resistant

148

Figure 6.9 Connection between miRNA and ROS 151

Figure 6.10 Gene expression in SUPB15MR cells 152

Figure 6.11 ROS levels in SUPB15 compared with SUPB15MR 153

Figure 6.12 Origin of exosomes 155

Table 6.1 Pharmacological heterogeneity in childhood ALL 135

Table 6.2 Expression of miRNAa in HS5, HS5 exosomes, SUPB15 and SUPB15MR cells

145

Table 6.3 Previously described role of miRNA in chemoprotection and or cell survival or cell cycle or cell metabolism

149

Chapter 7

Figure 7.1 Characteristics of pellet obtained after stage one of MV isolation method

165

Figure 7.2 Immobilisation of SD1 microvesicles on to protein A/G Ultralink resin

167

Figure 7.3 Quantification of MV in cell supernatants 169

Figure 7.4 Protein content of immobilised MV 170

Figure 7.5 Isolation of MV from patient plasma 171

Table 7.1 Key features of membrane limited vesicles 160

Table 7.2 Vesicles in health and disease 162

Table 7.3 Microvesicle cargo and cancer 163

Chapter 8

Figure 8.1 Proposed central role of BMSC derived soluble factors in conferring chemoprotection to leukaemic cell

178

Figure 8.2 Concise summary of normal processes involved in regulating coagulation during homeostasis

185

Figure 8.3 Mechanism involved in clot formation in response to vessel injury

187

Table 8.1 MV participate in coagulation 184

Abbreviations

9

Abbreviations

AEP Asparaginyl Endopeptidase

AIEOP Associazione Italiana Ematologia Oncologia Pediatrica

ALL Acute Lymphoblastic Leukaemia

Ara C Cytosine Arabinoside

ARID AT-rich interaction domain

Asn Asparagine

ASNase Asparaginase

ASNS Asparagine Synthetase

Asp Aspartic acid

BCR B cell receptor

BFM Berlin Frankfurt Münster

BM Bone marrow

BMSC Bone marrow stromal cells

BMSC-CM Bone marrow stromal cell-conditioned medium

BSA Bovine serum albumin

CD Cluster of differentiation

cDNA Complementary deoxyribonucleic acid

CI Confidence interval

CIGMR Centre of Integrated and Genomic Medical Research

CNS Central nervous system

CR Complete remission

CSF Cerebrospinal fluid

CS Citrate Synthetase

CT Cycle threshold

CTSB Cathepsin B

CV Coefficient of variation

D/D Double-distilled (deionised)

DAPI 4',6-diamidino-2-pheylindole

DEPC Diethylpyrocarbonate

DMSO Dimethylsuplhoxide

DNA Deoxyribonucleic acid

DTT Dithiotreitol

E.coli Escherichia coli

EBV Ebstein Barr Virus

ECL Enhanced chemiluminescence

EDTA Ethylenediamine tetra acetic acid

ELISA Enzyme Linked Immunosorbitant Assay

FAB French American British

FAM 6-carboxy-fluorescein phosphoramidite

FBS Fetal bovine serum

FISH Fluorescent in situ hybridisation

g Relative centrifugal force

GAPDH Glyceraldehyde-3-phosphate dehydrogenase

GLS Glutaminase

HCl Hydrochloric acid

HH High hyperdiploid

HR High risk

HRP horseradish peroxidise

ICAM1 Inter-cellular adhesion molecule 1

IDH Isocitrate dehydrogenase

IKZF1 Ikaros family zinc finger protein 1

Im Intramuscular

Abbreviations

10

IR Intermediate risk

IT Intrathecal

Iv Intravenous

JAK Janus Kinase

JmjC Jumonji domain-containing

kDa Kilodalton

LFA Leukocyte funtion-associated antigen-1

LIMS Laboratory information management system

MFI Mean fluorescent intensity

MGG May-Grünwald Giemsa

MHC Major Histocompatibility

miRNA micro RNA

MMP Matrix metalloproteinase

MNC Mononuclear cells

MRC Medical Research Council

MRD Minimal residual disease

MREC Multi Regional Ethical Committee

MTx Methotrexate

MV Microvesicles

MW Molecular weight

NAD Nicotinamide adenine dinucleotide

NADH Nicotinamide adenine dinucleotide, reduced form

NADP Nicotinamide adenine dinucleotide phosphate

NADPH Nicotinamide adenine dinucleotide phosphate, reduced form

NOPHO Nordic Society for Pediatric Hematology

OAA Oxaloacetate

OD Optical density

PAGE Polyacrylamide gel electrophoresis

pBALL Precursor B acute lymphoblastic leukaemia

PBS Phosphase buffered saline

PCR Polymerase chain reaction

PEG Polyethyleneglycol

PEG-ASNase Pegalyted E coli L-Asparaginase

PEITC Phenethyl isothiocyanate

Ph+ALL Philadelphia chromosome positive ALL

PI Protease inhibitor

PICR Paterson Institute for Cancer Research

PVDF Polyvinylidene fluoride

r2

Pearson coefficient of determination

RNA Ribose nucleic acid

ROC Receiver operating characteristic curve

ROS Reactive oxygen species

RPMI Roswell Park Memorial Institute

RQ-RTPCR Real time reverse transcriptase polymerase chain reaction

RT Room temperature

SD Standard deviation

SDS Sodium dodecyl sulphate

SE Standard error

SER Slow early response

SIL SCL(stem cell leukaemia) interrupting locus

SR Standard risk

TAL1 T cell acute lymphoblast leukaemia 1

TAMRA 6-carboxy-tetramethyl-rhodamine

Abbreviations

11

TCCSG Tokyo Children's Cancer Study Group

TCF3-PBX Transcription factor 3- pre b cell leukaemia homeobox 1

TCR T-cell receptor

TEMED Tetramethylethylenediamine

TET2 tet methylcytosine dioxygenase 2

TGF-β Transforming growth factor beta

Tris Tris(hydroxymethyl)aminomethane

UNG Uracil-N-Glucosidase

v/v Volume/volume

VAMP3 Vesicle associate membrane protein 3

w/v Weight/volume

WCC White cell count

α KG Alpha ketoglutarate

β2M Beta-2 microglobulin

2-HG 2 hydroxyglutarate

Abstract

12

Institution: The University of Manchester Name: Dr Ashish Narayan Masurekar Degree Title: Doctor of Philosophy (PhD) Thesis title: Biological Determinants of Therapeutic Response to L-Asparaginase in Children with Acute Lymphoblastic Leukaemia. Introduction: Intensification of chemotherapeutic agents in use since the 1970’s has led to over 80% survival in childhood ALL. The price of cure is treatment related morbidity and mortality that now approaches the incidence of relapse. Further improvement in outcome need better understanding the biological basis behind disease heterogeneity and identifying new targets and therapeutic strategies. Patients and Methods: We monitored trough ASNase activity at one or more time points in 451 patients treated in UKALL2003 and ALLR3 trials. The activity was correlated with prognostic determinants using assays mostly developed in house and data collated from the national trials. Two in-vitro models were created, one to test microenvironment mediated drug resistance and the second to test tumour related thrombosis. Results: Over 85% of patients [n=451; 427 (UKALL2003) and 24 (ALLR3)] had adequate ASNase activity levels. For UKALL2003 patients, the incidence silent neutralising antibodies (4.7%); clinical hypersensitivity (3.7%); thrombosis (3.1%) and pancreatitis (1.5%) was lower than previously reported. Hypersensitivity was mostly (n=16/17) seen in regimen C. There was a significant association between inadequate activity in induction and MRD levels in regimen A (p=0.03), especially so if they additionally had good risk cytogenetics (p=0.006). Older patients had higher incidence of inadequate ASNase activity during induction (p=0.0097). Patients in regimen C were more likely to inactivate ASNase in post induction phase (p=<0.01); less likely to recover from inadequate response to ASNase during induction (p=<0.01) more likely to experience toxicity to ASNase. ALLR3 patients: Silent antibodies were not observed in 16/24 patients that were tested. ASNase did not appear to influence outcome of patients in ALLR3. A model of microenvironment mediated multi-drug resistance showed a role of exosomal miRNA, of bone marrow stromal cell origin, in altering the redox state and chromatin pattern of leukaemic cell. In the second model, tumour associated microvesicles were shown to have a thrombogenic potential. Conclusion: Patients with good risk features depend on ASNase for disease clearance in the early phase. Routine testing would identify those with inadequate ASNase levels and improve the resolution of the current prognostic system used to decide post induction therapy. High risk patients have higher incidence of toxicity to ASNase and show a multidrug resistant phenotype where response to ASNase is not sufficient. A better understanding of disease biology is needed to design new treatment strategies in these patients.

Declaration

13

DECLARATION: I hereby declare that no portion of the work referred to in the thesis has been

submitted in support of an application for another degree or qualification of

this or any other university or other institute of learning.

Dr Ashish Narayan Masurekar

Copyright statement

14

COPYRIGHT STATEMENT:

i. The author of this thesis (including any appendices and/or schedules

to this thesis) owns any copyright in it (the “Copyright”) and s/he has given The University of Manchester the right to use such Copyright for any administrative, promotional, educational and/or teaching purposes.

ii. Copies of this thesis, either in full or in extracts, may be made only in accordance with the regulations of the John Rylands University Library of Manchester. Details of these regulations may be obtained from the Librarian. This page must form part of any such copies made.

iii. The ownership of any patents, designs, trade marks and any and all other intellectual property rights except for the Copyright (the “Intellectual Property Rights”) and any reproductions of copyright works, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property Rights and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property Rights and/or Reproductions.

iv. Further information on the conditions under which disclosure, publication and exploitation of this thesis, the Copyright and any Intellectual Property Rights and/or Reproductions described in it may take place is available from the Head of School of (insert name of school) (or the Vice-President) and the Dean of the Faculty of Life Sciences, for Faculty of Life Sciences’ candidates.

Dedicated To

15

This thesis is dedicated to my parents Narayan Achyutrao

Masurekar and Ranjan Narayan Masurekar and to all my

teachers.

Gratitude

16

Gratitude

I am most grateful to Professor Vaskar Saha for providing me the opportunity

to pursue a PhD and for his constant help, encouragement and guidance as a

mentor. Under his leadership I experienced a sense of abundance of

resources and enjoyed total freedom to pursue lateral ideas.

I am thankful to Dr Jizhong Liu, for supervising me in the laboratory and for

being a friend, philosopher and guide during my journey.

Dr Mark Holland and Dr David Gilham for their input and help in optimising

AEP ELISA.

Members of the Children’s Cancer Group (CCG) both past and present for

their support.

Paterson Institute for Cancer Research for providing an academic and

scientific environment.

Housemates at 33 Morningside Drive for their constant support and

encouragement and for putting up with my unsocial hours.

Cancer Research UK for giving me the fellowship and Leukaemia and

Lymphoma Research Fund for funding the project

Parents of children, young adult patients and clinical colleagues who supported the project.

Acknowledgement

17

Acknowledgements

I am grateful to the following people for their advice, help and support

Sample tracking Charlie O' Horo, Catriona Parker, Parisa Mahjoob Afag, Neelofar Charfer

Sample Processing Centre of Integrated and Genomic Medical Research: Rebecca Cole, Genevieve Pridham,

Late John-Paul Allen, Debbie Payne & Hazel Platt

Maintaining of Database Adiba Hussain, Catriona Parker AEP ELISA Jizhong Liu, Mark Holland, David

Gilham, John Bridgeman AEP RQ-RTPCR Stuart Pepper. Molecular biology

core facility, PICR Providing baseline patient characteristics & data on toxicity

Professor Ajay Vora, Sue Richards

Anti Asparaginase Antibodies Hans-Jürgen Kühnel, Monica

Essink; Medac GmbH, Wedel, Germany

Native E.coli Asparaginase Lorna Livingstone, Medac GmbH

(UK), Stirling, UK Ewinase Jonathan Morgan; EUSA

Pharma, Stevenage, UK Cytogenetics Professor Anthony Moorman MRD Jeremy Hancock Statistical analysis Sue Richards, Rachel Wade, Ric

Swindell Helping hand in generating results Asparaginase activity assay

(Adiba Hussain, Caroline Fong);

Acknowledgement

18

Protein quantification (Adiba Hussain, Caroline Fong); CTSB

ELISA (Caroline Fong); RNA extraction (Adiba

Hussain). Imaging Achille Dunne, Steve Bagley Flow cytometry Morgan Blaylock, Geoff Barry dRVVT assay Lynne Keighley, Central

Manchester Foundation Trust Hospitals

Informal advice Dave Gilham, Geoff Margison,

Karim Labib, Nullin Divecha, Iman van Debout, Mandy

Watson, Christopher Morrow

Introduction

19

Chapter 1 INTRODUCTION

______________________________________________________________

1.1 BACKGROUND OF CHILDHOOD ALL:

The normal development of B and T lymphocytes is characterised by an

orderly and progressive differentiation of haematopoietic stem cells into

common lymphoid progenitor cells followed by lineage restricted B and T

precursor cells and then the development of mature lymphocytes. Acute

lymphoblastic leukaemia (ALL) is a neoplasm affecting lymphocytes at any

stage during their development in the bone marrow (B cells) or in thymus (T

cells). It is classified into two categories: precursor B lymphoblastic leukaemia

and T lymphoblastic leukaemia according to the 2008 World Health

Organisation classification of acute leukaemia (1). In the UK approximately

400 children are diagnosed to have ALL each year. It accounts for

approximately 80% of all cases of childhood leukaemia and a quarter of all

childhood cancers making it the most common paediatric malignancy.

Amongst children with ALL, approximately 80% of the cases are children have

precursor B ALL (pBALL).

1.1.1 Clinical aspects: ALL has a peak incidence between 2 and 5 years of

age. pBALL originates in the bone marrow, while T-cell ALL on occasion

originate in the thymus. Children present with symptoms and signs of bone

marrow failure, with or without additional involvement of extra medullary sites

such as the liver, spleen, lymph nodes, thymus, meninges and gonads. The

presenting blood white cell count (WCC) can vary from being undetectable to

greater than 100 x 109/L (hyperleukocytosis) [Normal WCC: 4 -11 x 109/L].

The ensuing bone marrow failure leads to multi-organ failure and death of a

child in the absence of prompt treatment.

The diagnosis of ALL is suspected on the basis of a combination of clinical

findings, abnormal blood counts and presence of lymphoblasts in blood

smears. Tests done to confirm the diagnosis of ALL include a bone marrow

Introduction

20

aspirate with or without trephine biopsy, and immunophenotyping of blast cells

in bone marrow or peripheral blood.

ALL follows a heterogeneous clinical course. With therapy, >85% of children

will be cured (2, 3). The most important adverse event in the treatment of ALL

is disease recurrence. The current relapse rate is ~ 10% (4-6), which is

associated with a high incidence of CNS involvement ~ 40%, compared to ~

2% at presentation (5, 7, 8). The outcome of children who relapse is poor

with survival rates between 15 to 69% (9-11).

1.1.2 Aetiology of ALL: The aetiology of ALL is unknown. Only in <5% of

cases do we find an underlying inherited predisposing condition such as

Down syndrome, Bloom syndrome, Ataxia-Telangiectasia or Nijmegen

breakage syndrome. Ionising radiation (2), prior therapy involving DNA

topoisomerase II inhibitors (12) and germline polymorphisms of IKZF, a gene

encoding for transcription factor IKAROS, as well as the ARID5 genes (13, 14)

have been implicated in ALL as well. The role of a host of other potential

environmental factors predisposing to ALL such as parental occupation,

maternal reproductive history, parental tobacco or alcohol use maternal diet,

exposure to pesticides and magnetic fields have been studied. The evidence

for these factors is conflicting and their roles have not been established (15).

Clustering of cases of ALL between 2-5 years of age has fuelled two

hypotheses suggesting a role of abnormal response to infection: population

mixing hypothesis and the delayed infection hypothesis. Population mixing

hypotheses suggests that the peak in ALL observed in this age group is due

to exposure of non immune children to infections after population mixing with

carriers. The delayed infection hypothesis in addition suggests a mechanism

whereby a pre existing pre-leukaemic clone transforms to leukaemia following

an abnormal response to infection (16).

Conventional cytogenetics and FISH detects genetic abnormalities in greater

than 75% of cases of ALL(3). Newer high resolution techniques such as a)

microarray based gene expression profiling, comparative genomic

Introduction

21

hybridization arrays and single nucleotide polymorphism analysis; b) DNA

methylation arrays and c) whole genome sequencing techniques can identify

changes in virtually all cases of ALL. ALL is biologically a heterogeneous

disease. Broadly the lesions in ALL can be classified into recurrent

chromosomal aberrations including balanced or reciprocal translocations,

aneuploidies (hyperdiploidy or >50 chromosomes; hypodiploidy or <45

chromosomes and trisomies of chromosome 4, 10, 17 and 21) and gene-

specific alterations [Figure 1.1 and Table 1.1]. The genes most commonly

altered are those that are involved in regulation of lymphoid differentiation, cell

cycle, apoptosis and cell signalling (3).

Whilst the above mentioned techniques have identified a number of somatic

genetic abnormalities, they do not in all cases separate mutations that drive

the leukaemia (driver mutations) from passenger mutations. Of the genetic

abnormalities identified, chromosomal translocations are the most well

described. The exchange of material between two chromosomes leads to

either i) a promoter substitution mutation where a normally quiescent

oncogene becomes constitutively active under the influence of the new

promoter or ii) creation of an in-frame chimeric or fusion gene which is

oncogenic. Promoter substitution mutations are more common in T

lymphoblastic leukaemia whereas fusion genes are more common in B

lymphoblastic leukaemia. These translocations involve either transcription

factor genes that are crucial in B or T cell differentiation or genes that are

involved in key signalling pathways such as protein kinases and they disrupt

key pathways of cell differentiation, proliferation and survival.

Chromosomal translocations are important in the initiation of leukaemia and in

most instances arises in-utero (16-21). They induce, expand and sustain a

pre-leukaemic clone. For example the ETV6-RUNX1 fusion is thought to

sustain the pre-leukaemic clone by a reduced sensitivity of the pre-leukaemic

clone to TGF-β mediated inhibition of cell proliferation (22).

Introduction

22

Chromosomal translocations differ in their capacity to generate a full

leukaemic phenotype (3, 23, 24). ETV6-RUNX1 fusions arise in B lineage

progenitor/stem cells and are seen in 1% of normal prenatal haematopoiesis

but only 1% of those cases go on to develop ALL (21). ETV-RUNX1 ALL is

associated with on average six copy number variations (CNV). This indicates

that the malignant transformation of lymphocytes bearing the ETV6-RUNX1

fusion is a multistep process that requires additional gene specific ‘co-

operating oncogenic lesions (23). Contrary to this, MLL translocations have a

greater leukaemogenic potential as evidenced by their ability to cause ALL

during infancy, show concordance rates that are close to 100% in identical

twins and be associated with less than one CNV per case(2, 3).

Currently, chromosomal translocations are considered to be chance events

(25) that occur following DNA double strand breaks coupled with illegitimate

recombination by non homologus end joining processes (17, 26). At the DNA

level, most gene fusions remain poorly characterized and why only a select

few genes, mostly encoding transcription factors or tyrosine kinases, are

involved in chromosomal translocations is unknown (25). Potentially, these

genetic recombination events produce aberrant expression of genes that

provide a mechanism of survival.

Hyperdipliody, 25%

Hypodiploidy, 1%

ETV6-RUNX1, 25%

ERG deletion, 7%

CRLF2 over expression, 6%

E2A-PBX1, 5%

iAMP21, 2%

Others, 7%

T cell, 12%

MLL rearrangements, 8%

BCR-ABL, 3%

Hyperdipliody, 25%

Hypodiploidy, 1%

ETV6-RUNX1, 25%

ERG deletion, 7%

CRLF2 over expression, 6%

E2A-PBX1, 5%

iAMP21, 2%

Others, 7%

T cell, 12%

MLL rearrangements, 8%

BCR-ABL, 3%

Introduction

23

Figure 1.1: Cytogenetic abnormalities of childhood ALL. The lesions illustrated

in the dark pink colour are observed in exclusively in B lymphoblastic

leukaemia. Lesions illustrated in light pink (not characterised) are observed

exclusively in T lymphoblastic leukaemia and includes rearrangements

involving HOX11L2, LYL1, TAL1, HOX11 genes. MLL rearrangements shown

in grey are more common in B cell than T cell lymphoblastic leukaemia.

Lesions found in the ‘others’ category in dark blue are more common in T cell

than B cell lymphoblastic leukaemia and include normal karyotype which is

observed in ~50% of cases of T lymphoblastic leukaemia. Adapted from (3,

27).

Table 1.1: Genetic alterations in ALL

ALL is biologically a heterogeneous disease involving a number of different

mutations ranging from gross cytogenetic abnormalities to gene specific point

mutations identified only by single nucleotide polymorphism (SNP) arrays.

MLL-ENL fusion* is observed in both T cell and B cell acute lymphoblastic

leukaemia. CALM-AF10 is observed in acute myeloid leukaemia as well as in

both T and B ALL. Adapted from (17).

Subtype of ALL molecular lesion Functional product

B cell acute lymphoblastic leukaemia

i) translocations

t(12;21) ETV6-RUNX1 fusion Chimeric transcription factor

t(1;19) TCF3-PBX1 fusion Chimeric transcription factor

t(9;22) BCR-ABL fusion Activated kinase

t(17;19) TCF3-HLF fusion Chimeric transcription factor

11q23 translocations MLL rearrangements Chimeric transcription factor

ii) aneuploidy

hyperdiploidy Altered gene dose

hypodiploidy Altered gene dose

trisomsy 4, 10, 17 & 21 Altered gene dose

iii) gene specific abnormalities

>50

T cell acute lymphoblastic leukaemia

i) translocations

7q34 translocations multiple TCRB & TCRG rearrangements promotor substitution involving transcription factors

14q11 translocations multiple TCRA & TCRD rearrangements promotor substitution involving transcription factors

t(10;11) CALM-AF10 fusion Chimeric transcription factor

11q23 translocation MLL-ENL fusion* Chimeric transcription factor;

t(4:11) translocation NUP98-HOXA9 Chimeric transcription factor

iii) extrachromosomal amplification

NUP214-ABL1 fusion Activated kinase

iv) gene duplication

MYB MYB over-expression

v) gene mutations

NOTCH1, FLT3, NRAS, FBW7 Activating mutations

vi) chromosomal deletions

9p21 P15, P16 cell cycle deregulation

6q Unknown Unknown

1p SIL-TAL1 fusion Chimeric transcription factor

Introduction

24

1.1.3 Therapy of ALL: Standard treatment consists of combination

chemotherapy involving often more than 10 drugs. Additionally for some

children central nervous system (CNS) radiotherapy or a bone marrow

transplant is required for cure. The treatment spans over a minimum of 24

months and is divided into following phases: induction, CNS directed therapy,

post induction intensification and continuation [Figure 1.2]. The absolute

minimum goal of induction phase is to reduce the population of lymphoblasts

(leukaemic cells) present at diagnosis in the bone marrow to less than 5%

along with the restoration of normal bone marrow function. This is defined as

a complete morphological remission (CR). The incidence of CR at the end of

induction phase is greater than 95% with current protocols. The goal of

induction therapy is recently directed towards achievements of a molecular

remission. This is defined as minimal residual disease (MRD) of <1 leukaemic

cell/10,000 cells in bone marrow on assessment by techniques such as flow

cytometry or quantitative polymerase chain reaction (RQ-PCR) (28).

Subsequent therapy is still needed in order to aim for a cure. CNS directed

therapy and post induction intensification are essential in order to reduce the

incidence of CNS relapse (29-32) and to consolidate further upon the initial

therapeutic response (33-37). The exact mechanism underlying the protective

effect of continuation therapy is unclear (38). Attempts to taper continuation

therapy have led to inferior results (39).

Figure 1.2: Overview of standard chemotherapy treatment in childhood ALL.

Some children require cranial radiotherapy ± bone marrow transplant. Total

therapy lasts well over 2 years and involves at least 10 drugs delivered in 4

Induction 5 weeks

ContinuationCNS directed therapy/

Consolidation Post inductionintensification

5 weeks 3-9 weeksDivided into 2-4 different

blocks each over 6-7 weeks

125-140 weeks

5-6 drugs 2-6 drugs 8-9 drugs 5 drugs

•Dexamethasone•L-Asparaginase•Vincristine•Daunorubicin*•IT MTx•Mercaptopurine

•IT MTx•Mercaptopurine•Ara C•L-Asparaginase•Vincristine•Cyclophosphamide

•IT MTx•IV MTx•L-Asparaginase•Vincristine•Dexamethasone•Cyclophosphamide•Cytarabine•Doxorubicin•Mercaptopurine

•IT MTx•Oral MTx•Dexamethasone•Vincristine•Mercaptopurine

Introduction

25

main blocks. The intensity of treatment in each phase and the number and

design of each phase especially in the post intensification period depends on

the risk stratification. MTx= Methotrexate; Ara C= Cytosine Arabinoside; iv=

intravenous; IT= intrathecal

1.1.4 Current outcome in childhood ALL: During the last three decades,

the outcome of paediatric ALL has steadily improved from around 50% to over

80% across the developed world (2, 3), including the UK (40), as shown in

Figure 1.3. No new drugs have been incorporated into therapeutic regimens

during this time. This achievement is a result of: i) carefully planned large

scale multicentre trials across the world which have optimised the delivery of

drugs given in the above mentioned phases. ii) adoption of risk stratification

strategies that segregate patients into standard, intermediate and high risk

groups based on their relapse risk and tailors treatment accordingly (30) and

iii) the availability of better supportive therapy.

Figure 1.3: Outcome of ALL in successive Medical Research Council

Childhood ALL trials. UKALL VIII: 1980-1985, UKALL XI: 1985-1997 & ALL

97/99/01: 1997-2002. (Courtesy Professor Ajay Vora).

0 1 2 3 4 5 6 7 8 9 100

25

50

75

100

Per

cen

t ev

ent

free

su

rviv

al

Time in years

UKALL VIII (1980-1985) – 54%

UKALL X & XI (1985-1997) – 60%

UKALL 97/99/01 (1997-2002) - 74%

UKALL 2003 ~85%

Introduction

26

1.1.5 Heterogeneity observed in the clinical response to therapy: There

are a number of risk factors that are predictive of relapse such as age ≥ 10

years and/or presenting white cell count ≥ 50 x109/L (41), adverse

cytogenetics [Hypodiploidy, t(9;22), iAMP21, E2A-HLF and MLL gene

rearrangements] (42), figure 1.3, slow response to early therapy (SER),

defined as presence of ≥ 25 leukaemic cells/100 cells on morphological

assessment of bone marrow after 1-2 weeks of starting therapy, failure to

achieve complete morphological remission at the end of induction phase (2)

and persistence of disease at a molecular level after the end of induction

phase (43). The importance of SER and persistence of disease at molecular

level is expanded below. The advent of new techniques mentioned above

have led to the identification of new lesions associated with poor outcome

such as the deletion of IKZF1(24, 44, 45); over expression of CRLF2 in some

but not all studies (46-49) and presence of JAK mutations (in case of

precursor B ALL) (50); and a distinct gene expression profile associated with

HOX11L2 (51)(in case of T ALL).

The current UKALL 2003 protocol has the following 3 risk groups:

a) Standard risk: all children > 1 & < 10 years with a highest white cell

count before starting treatment of < 50x109/L and who do not have

adverse cytogenetics

b) Intermediate risk: all children ≥10 years old and/or with a diagnostic

white cell count ≥50x109/L(41) and who do not have adverse

cytogenetics

c) High risk: all children, irrespective of initial white cell count or age who

have a SER and or adverse cytogenetics [Hypodiploidy, t(9;22),

iAMP21, E2A-HLF and MLL gene rearrangements] (42) (Figure 1.4).

Children with standard, intermediate and high risk are treated respectively on

regimen A, B and C of the UKALL 2003 protocol. The greater the clinical risk,

the more intense the therapy is in terms of the total number of drugs used,

Introduction

27

their maximum dose, the frequency of administration and the duration of

overall therapy.

Figure 1.4: Event free survival according to their cytogenetics at diagnosis in

childhood ALL-MRC ALL 97 trial. Courtesy Dr. Anthony Moorman, LRF,

cytogenetic group, Newcastle.

1.1.6 Current issues in the Treatment of Childhood ALL: There are two

main issues in the treatment of childhood ALL. Firstly, the improvement in the

outcome of ALL has come at a price. Current treatment protocols have

progressively intensified therapy over the last four decades; as a result a

significant number of children are over-treated on current protocols compared

to the ones used in the 1980’s. This is true even when we take the current risk

stratification strategy into account and compare children on Regimen ‘A’ of

UKALL 2003, who are less likely to relapse and receive least therapy, with all

those treated in UKALL VIII (1980-1985). Current protocols are complex,

expensive and associated with long term toxicities including cardiotoxicity,

secondary neoplasms, osteonecrosis and radiation induced endocrinopathies

or decline in neurocognitive function. Children who have had a bone marrow

transplant are at risk of additional long term side effects in the form of chronic

graft vs host disease of the skin, gut and lungs. Secondly, even on current

treatment protocols the disease relapses in 10-20% of children (4-6) and

EFS According to Cytogenetics - ALL

t(12;21)

High Hyperdiploid

Other

<Hypodiploid

t(9;22)

iAMP21

0.0

00

.20

0.4

00

.60

0.8

01.

00

Eve

nt F

ree

Sur

viva

l

0 1 2 3 4 5 6 7 8 9

Time from diagnosis (years)

Introduction

28

relapse is the most important adverse event in childhood ALL. The clinical

variation in the treatment response is most likely to be due to the underlying

biological heterogeneity of the disease. The two main challenges in childhood

ALL are i) to accurately identify at diagnosis all children who are at a high risk

of disease relapse and separate them from the subgroup of children who can

be cured with the less intensive treatment given in the protocols of the 1980’s

and ii) to understand the mechanisms behind disease relapse in-order to

optimise therapy and improve outcome in this subgroup.

1.1.7 Relapse in childhood ALL: Within all risk factors, slow early response

(SER) (34, 52, 53) and persistent MRD either at the end of induction phase

(43, 54-56) or at day 15 (57) are the most important determinants of poor

outcome (58). While SER is an indicator of speed of response to therapy,

persistent MRD is an indicator of the depth of response. Children with SER

have a worse outcome in all risk categories defined by clinical and biological

features (59, 60). SER is also linked with adverse cytogenetics as over 50%

of children with t(9;22) ALL have a SER (7).

Analysis of genomic copy number abnormalities (CNAs) in samples at

diagnosis and relapse suggests that in >90% of cases disease recurrence is

due to a subpopulation of cells present at diagnosis (61, 62). This suggests

that the clone responsible for relapse is able to survive front line therapy and

therefore undergoes further selection and expansion. Protection from

chemotherapy could be either due to intrinsic drug resistance to one or more

chemotherapeutic agents or extrinsic where the leukaemic blasts are

protected by the host or a combination of the two reasons.

In this thesis I chiefly investigated the incidence of intrinsic resistance to L-

Asparaginase in childhood ALL, it’s possible causes and it’s contribution to

treatment failure (Chapters 4 and 5). In collaboration with Dr. Liu, I looked at

the role of soluble factors secreted by bone marrow mesenchymal cells in

conferring chemoprotection to ALL cells (Chapter 6). My primary task was to

investigate the biological determinants of the response to L-Asparaginase

Introduction

29

(ASNase) (Chapter 4). I shall therefore give an introduction to ASNase in this

chapter.

1.2 L-ASPARAGINASE

ASNase is the only example of a bacterial enzyme used in cancer therapy.

1.2.1 Rationale for studying the determinants of response to ASNase: As

relapse is linked to adverse outcome variables such as SER and or high MRD,

it is plausible that the clone responsible for relapse is resistant to one or more

drugs used during the first 1-2 weeks of therapy. The drugs used during this

phase are steroid, vincristine, ASNase, intrathecal methotrexate and

additionally an anthracycline in patients who are at a higher risk of relapse

[Figure 1.5]. These drugs have different mechanisms of actions and in theory

will tackle the problem of clones with differing chemosensitivity. Clinical trials

over three decades show that ASNase is probably the single most effective

agent used in the induction phase and it has further benefits when repeated in

the post induction period (32, 63-70). It is the only drug used in the first 1-2

weeks of therapy where we have not reached dose limiting toxicities, making

it possible to further optimise its dose (71). There is evidence to suggest that

optimal ASNase activity potentiates the efficacy of dexamethasone which is

another key drug used in ALL induction therapy (72). Thus, ineffective

ASNase therapy could be a major determinant of the response to induction

therapy.

Introduction

30

Days 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Dexamethasone

Vincristine

PEG-ASNase

Daunorubicin*

IT MTx

Figure 1.5 Schedule of first 2 weeks of therapy in UKALL 2003.

Dexamethasone (6 mg/m2) is given as a daily oral dose, PEG-ASNase (1000

U/m2) is given as a single intramuscular injection and Daunorubicin (25 mg/m2)

and vincritsine (1.5 mg/m2) are given intravenously. Daunorubicin * is given

only to high risk patients. IT MTx= intrathecal methotrexate.

1.2.2 Structure of ASNase: The enzyme forms a tetramer in a soluble state

that consists of 4 identical subunits: A, B, C and D arranged in 2-2-2

symmetry [Figure 1.6]. Amongst these subunits the interaction between A and

B and between C and D are the most extensive, resulting in a tetramer which

is in fact a dimer of identical intimate dimers (73). ASNase is active only as a

tetramer. Residues in the N-terminal domain of subunit A interact with

residues of the C-terminal domain of subunit B to create one half of the active

substrate binding pocket. Identical interactions between subunits C and D

contribute to the other half of the binding pocket.

Introduction

31

Figure 1.6: Quaternary structure of E.coli-ASNase. Each monomer (subunit)-

A(pink), B(blue), C(green) & D(coffee) is identical and has a molecular mass

of 35.6 kDa. The green spheres in the centre of the tetramer represent

asparagine molecule sitting inside the active catalytic site that is made by

contributions from all four monomers. The orange regions in each monomer

represent the known B cell epitopes [Paul Bates, London Research Institute].

1.2.3 Mechanism of action of ASNase: ASNase has been used in ALL since

the 1970’s. It converts asparagine and glutamine to aspartate and glutamate

respectively resulting in their depletion from the extracellular fluid

compartment. This is thought to lead to impaired protein synthesis and

apoptosis of leukaemic blasts which are selectively susceptible to ASNase

owing to low/absent Asparaginase Synthetase (ASNS) activity (74).

1.2.4 ASNase- source and products: ASNase used in clinical practice is

either derived from either E.coli (E.coli-ASNase) or from Erwinia (Erwinase).

E.coli-ASNase includes Elspar (Merck Sharp & Dohme, USA) and Medac

(Medac GmbH, Germany) amongst other products (Table 1.2). E.coli-ASNase

and Erwinase have identical mechanisms of action and side effects, although

they do differ in potency. E.coli-ASNase is more potent than Erwinase (75)

A=pink

B=blue C=green

D=coffee

Introduction

32

1.2.5 Problems with ASNase therapy: Apart from drug related toxicities,

there are two major issues with the use of ASNase in clinical practice. Firstly it

is a bacterial protein. Frequent administration leads to the development of

silent neutralising antibodies and/or clinical hypersensitivity to ASNase (76,

77). Secondly, ASNase degradation is probably primarily via the reticulo-

endothelial system (78) leading to wide inter-patient variability in levels after

administration. In small cohort studies using E.coli ASNase, up to 35% of

patients developed neutralising antibodies and 15% developed clinically

significant hypersensitivity reactions (79, 80). The immune response to

ASNase appears to be more prevalent in high-risk ALL patients of whom up to

60% may develop antibodies (79).

The pharmacokinetics of the drug varies between different products; E.coli

ASNase has a longer half life compared to Erwinase. Not all patients achieve

adequate therapeutic levels of ASNase (81), considered to be ≥ 100 IU/Litre

of serum (76, 82, 83). This has clinical implications. Not all children show an

adequate response to ASNase. An adequate therapeutic response is

correlated with both a rapid early response (76) and an improved outcome in

de novo and relapsed ALL (84, 85).

To improve the pharmacokinetic profile of E.coli ASNase, Elspar and Medac

Asparaginases are now available conjugated with polyethylene glycol (PEG-

ASNase). PEG-ASNase has a longer half-life (5.7 days for PEG-ASNase

compared to 1-1.5 days with Erwinase and E.coli-ASNase) (75, 76, 86) and

produces similar ASNase activity with a lower dose. This permits the use of

PEG-ASNase at a lower and less frequent dosage interval when compared to

ASNase (76). PEG-ASNase is also associated with a reduced incidence of

immune response (76, 87), reflecting the lower antigen load. Several studies

have shown the efficacy of PEG-ASNase during induction and post induction

phases when used in newly diagnosed as well as in relapsed patients (32, 76,

84, 88). As a result, PEG-ASNase has replaced ASNase in the frontline and

relapse ALL protocols in the UK. Patients who develop clinical hypersensitivity

to PEG-ASNase can be give Erwinase as antibodies to E. coli ASNase are

Introduction

33

not cross reactive. More recently recombinant PEG-ASNase has been tested

in the setting of a randomised phase 2 clinical trial. This showed that the

recombinant product is comparable to PEG-ASNase in terms of its efficacy,

pharmacokinetics and toxicity (89).

Table 1.2: ASNase products in clinical use.

In the United Kingdom we use PEG-Asparaginase (PEG-ASNase) in front line

treatment protocols. The native product is Medac Asparaginase which is

pegylated by Enzon and marketed by Medac as Oncaspar™ (Recently,

Enzon was bought by Sigma-Tau which will now market PEG-ASNase

directly). Erwinase is used in case of clinical hypersensitivity to PEG-ASNase.

It is manufactured by the health protection agency (HPA) and marketed by

EUSA pharmaceuticals.

1.2.6 Determinants of the therapeutic response to ASNase: A number of

studies have investigated whether resistance to ASNase is due to the

production of asparagine synthetase (ASNS) by lymphoblasts. Some such

studies have demonstrated a correlation between cellular levels of ASNS and

in vitro resistance to ASNase in cell lines and experimental models of

leukaemia (90-92). A correlation between ASNS expression, in vitro

resistance to ASNase and inferior treatment outcome has also been reported

in some but not all genetic subtypes of ALL (93, 94). However, other studies

ASNase Manufacturer Marketed by

E.coli -ASNase

Elspar MSD (Ireland) MSD

Kidrolase Kyowa-Hakka (Japan) EUSA

Colaspase Kyowa-Hakka (Japan)

Medac Asparaginase Kyowa-Hakka (Japan) Medac

E.coli PEG-Asparaginase

Oncospar (UK) Enzon/Kyowa-Hakka (Japan) Sigma-Tau

Oncospar (US) Enzon/MSD Sigma-Tau

Erwinia -ASNase

Erwinase HPA (UK) EUSA

Introduction

34

have failed to find a correlation between the expression of ASNS and in vivo

sensitivity to ASNase or response to therapy in ALL (93, 95). For example,

ALL with t(12;21) is characterised by up-regulation of ASNS in response to

ASNase and yet it is exquisitely sensitive to ASNase with a good clinical

outcome (96) (Figure 1.4).

Despite systemic asparagine depletion lymphoblasts have been shown to

have high levels of intracellular asparagine (97). Recently we have shown that

the glutaminase activity of ASNase is critical to cytotoxicity, i.e the asparagine

depletion alone is insufficient for killing the cancer cell (98). Cancer cells are

dependent on glutamine for many cellular functions, including

chemoresistance. Thus glutamine depletion by ASNase may also sensitise

lymphoblasts to cytotoxicity by other agents. These data cast doubt on the

role of asparagine depletion alone as the main mechanism of cytotoxicity and

the expression of ASNS as the main mechanism behind drug resistance.

Furthermore, in response to systemic asparagine depletion, mesenchymal

cells up-regulate the synthesis of asparagine and protect leukaemic cells by

preventing apoptosis in response to ASNase (99).

We have recently identified that two lysosomal cysteine proteases, Cathepsin

B (CTSB) and Asparaginyl Endopeptidase (AEP) which degrade ASNase

(100). CTSB is ubiquitously expressed by most cells including lymphoblasts

and may play a crucial role in the pharmacokinetic clearance of the drug. AEP

is normally expressed by renal cells. It is aberrantly expressed primarily by

pre-B lymphoblasts of high risk cytogenetic subtypes (101). While CTSB

degrades both Erwinase and E.coli ASNase, AEP is specific for E.coli

ASNase. AEP cleaves at distinct sites carboxy-terminus to either an

asparagine or aspartate (102), in contrast CTSB cleavage sites are non-

specific. In the case of E.coli ASNase AEP was shown to cleave ASNase at

N24, D124 & N143 (100). The AEP induced cleavage fragments retain intact

known antigenic epitopes of E.coli-ASNase. AEP has been previously shown

to accelerate the presentation of tetanus toxin fragment to MHC class II

molecules (103). Thus our observations suggest that the co-expression AEP

Introduction

35

and CTSB by lymphoblasts may hasten the degradation of ASNase leading to

inadequate levels of ASNase during induction therapy. As ASNase modulates

the dexamethasone response, this process may significantly contribute to the

SER in high risk cytogenetic subtypes. Additionally AEP may induce

development of allergic reactions such as hypersensitivity or the development

of neutralising antibodies. The latter would lead to inadequate drug levels

during the delayed intensification phase.

1.2.7 Preliminary data: In a pilot study (n=86, collaboration with Prof. Tim

Eden), we have noted 4 different patterns of response to PEG-ASNase.

Around 60% of patients had good ASNase activity (>100U/L) throughout all

phases of treatment. Twenty percent show good activity during induction but

not subsequently, suggesting the development of neutralising antibodies

during subsequent therapy. 15% show inadequate activity during induction but

satisfactory activity later on as disease burden starts to reduce on therapy.

This suggested that the inhibition of ASNase activity could be due to the

leukaemic state, possibly mediated by cysteine proteases in the leukaemic

cells. About 5% never develop adequate ASNase activity. These patients are

all in the high risk category where a combination of above reasons would lead

to inadequate ASNase activity.

1.3 ASPARAGINASE STUDY

1.3.1 Rationale of this study: The current trial data (UKALL 2003) shows a

major improvement in outcome compared to the previous trial. This can to be

attributed in part to the introduction of PEG-ASNase for all risk groups

(personal communication Professor Vora, Sheffield). Thus optimal usage of

PEG-ASNase is likely to underpin all future clinical trials in childhood ALL in

the UK. There are no studies done to date that link pharmacokinetic response

of PEG-ASNase with early response to therapy and outcome in ALL. As

observed in the pilot study, patients can be classified into four categories

(Table 1.3). Table 1.3 also suggest possible mechanisms for the variations in

the therapeutic response. If these hypothesis and preliminary observations

Introduction

36

are correct, then routine pharmacokinetic monitoring of PEG-ASNase could

become mandatory for all patients. If patients with AEP over-expression show

a poor initial response to PEG-ASNase, they could benefit from the primary

use of Erwinase. It is also possible to inhibit the action of the proteases using

AEP specific inhibitors or develop a cleavage resistant ASNase. Any of these

strategies would optimise ASNase therapy and potentially improve the

outcome of high risk patients with ALL. In patients who show immunological

response, one could further undertake T cell activation studies to identify

allergic epitopes of PEG-ASNase. This will permit the development of

modified PEG-ASNase that is likely to be less immunogenic and equipotent to

the parent drug.

Table 1.3 Predicted pattern of response to PEG-ASNase

Patient groups

I

II

III

IV

Expected resultsAsp activity (induction)

Good

Poor

Good

Poor

Asp activity (post induction)

Good

Good

Poor

Poor

Likely explanation

Good response

Biological factors (blasts or mesenchymalcells) at diagnosis

Immune related

Combination offactors in II & III

Anticipated therapeutic response

RER, followed by CR; MRD week 5 neg and week 11 neg

RER/SER, followed by CR; MRD week 5 neg/pos and week 11 neg

SER/RER, followed by poor(no CR) or inadequate(MRD pos) response

SER and a poor response or inadequate (MRD pos) response.

The major determinants of poor response to the drug are likely to be

neutralising biological factors (such as AEP and/or CTSB) in the initial phase

and major mechanism of destruction in the subsequent phase would be due

to immune response to ASNase. In either case a poor response to ASNase

will result in an inadequate therapeutic response. RER= rapid early response

(≤25% lymphoblasts on morphology of bone marrow aspirate done 1-2 weeks

after starting therapy); SER= slow early response (>25% lymphoblasts on

morphology of bone marrow aspirate done 1-2 weeks after starting therapy);

CR= complete remission (<5 lymphoblasts/100 cells on morphology of bone

marrow aspirate at the end of induction therapy); MRD= minimal residual

disease (>1 lymphoblasts/10,000 cells on assessment by techniques including

Introduction

37

flow cytometry and quantitative polymerase chain reaction (RQ-PCR) at

weeks 5 & 11 of therapy); pos= positive; neg=(negative)

1.3.2 Hypothesis:

1) PEG-ASNase at 1000 U/m2 given i.m. fortnightly during induction will

produce adequate activity levels throughout induction for most children

with ALL

2) Variations in ASNase pharmacokinetics will influence the early

response to therapy and outcome

3) Lymphoblast proteases regulate inadequate ASNase activity levels and

the allergic response to ASNase.

1.3.3 Eligibility: Following approval by a Multi Regional Ethical committee,

this study was incorporated into two current national trials for childhood ALL -

UKALL 2003 (de novo patients) and ALL R3 (relapsed cases) in 2008.

1.3.4 Aims of the study (discussed further in Chapter 4):

1) To provide recommendations on whether routine pharmacokinetic

monitoring of ASNase is required in clinical practice

2) To further optimise PEG-ASNase therapy in childhood ALL.

3) To investigate whether AEP and/or CTSB emerged as prognostic

biomarkers in childhood ALL.

1.3.5 Objectives of the study (discussed further in chapter 4): At

diagnosis we measured the expression of AEP and CTSB. We serially

measured ASNase activity and determined the incidence of anti-ASNase

antibodies in children who either had clinical hypersensitivity to ASNase or

who showed inadequate activity. We determined if initial inactivation of

ASNase correlated with SER and or high MRD and if this could be predicted

by expression of AEP and/or CTSB and lastly if late inactivation of ASNase is

indeed due to an immune response that is facilitated by high expression of

AEP.

Introduction

38

1.3.6 Study design (discussed further in chapter 4): Asparaginase activity

was serially measured during induction and post induction phases. Induction

ASNase activity results were correlated with expression of AEP and CTSB at

diagnosis, cytogenetic subtype, therapeutic response (SER, MRD at week 5

and 11 for de novo ALL and week 5 and 13 for children with relapsed ALL)

and eventual outcome. The expression of AEP and CTSB was correlated with

PEG-ASNase activity and with the occurrence of clinical hypersensitivity.

Samples with inadequate activity were assayed for antibody development

using risk matched controls from the study population.

Material and Methods

39

Chapter 2 MATERIALS AND METHODS

______________________________________________________________

2.1 REAGENTS: Details of the reagents and buffers used in this thesis are

shown in appendix 1 and appendix 2 respectively.

2.2 ASPARAGINASE STUDY

The study recruited patients from two national trials: the frontline UKALL2003

and the relapsed ALLR3 trials. Details of the biological samples collected,

their time points, along with the laboratory assays employed in this study are

described in detail in chapter 4.

2.2.1 Patient Sample Collection: Consent for enrolment in the Asparaginase

Study was obtained by treating physicians. Diagnostic samples were sent by

dedicated courier and subsequent samples by a post box drop service.

Samples were received and processed by the Centre for Integrated Genomic

Medical Research (CIGMR) at the University of Manchester. They were bar-

coded and tracked on a dedicated LIMS system. Samples were subsequently

collected from CIGMR and assayed at the Paterson Institute for Cancer

Research, Manchester.

The Children’s Cancer Group has a trial office based at the Christie Hospital.

This unit was notified electronically about all new registrations and also about

the occurrence of SAE (serious adverse events) related to ASNase in both

above mentioned trials. Dr. Catriona Parker and Charlotte O’Horo based in

the trial office then tracked the flow of diagnostic and followed up samples for

each patient. This was done by electronically reminding individual treatment

centre each time before the next sample time point and also by liaising with

CIGMR to confirm whether the sample was received or not.

2.2.2 Sample Processing: All stages of sample processing and storage have

been optimised and standard operating procedures (SOP’s) established,

Appendix 3.


40

2.3 TECHNIQUES

2.3.1 Tissue Culture

2.3.1.1 Cell Lines: ALL cell lines; SD1, SUPB15 and REH (appendix 4) were

used to validate the TaqMan gene expression (Applied Biosystems, Europe

BV, Warrington, UK) and ELISA assays. SD1 is an EBV-immortalised

polyploid human precursor B-lymphoblastic leukaemia cell line with t(9;22).

REH is a human diploid precursor B-lymphoblastic leukaemia cell line with

t(12;21). SUP B15 is a human precursor B-lymphoblastic cell line with a

t(9;22). SD1 expresses AEP at the protein level whereas REH and SUP B15

don’t (100).

2.3.1.2 Cell culture, passage and collection of cell pellets & supernatants:

Cell lines were cultured for 48-96 hours at 37°C/5%CO2 in BioWhitaker®

RPMI-1640 Ultraglutamine (Lonza, Wokingham, UK) supplemented with 10%

foetal calf serum (Sera Laboratories Ltd, Haywards Heath, UK). Cells were

grown in 162 cm2 cell culture flasks with 0.2 um Vent cap (Corning

Incorporated, N.Y, USA). The initial concentration of cells was 2 x105/ml. At

the end of 48-96 hours the cells were either sub cultured or collected for

downstream applications. Decision to sub culture cells was influenced by the

cell count (>1x 107/ml), colour of media and confluency. Excess cells at the

end of a given experiment were cryo-preserved using 90% foetal calf serum

and 10% DMSO (Sigma-Aldrich, Dorset, UK). The number of cells preserved

was 10-30 x 107/vial and the volume of the cryo-protectant was 0.8- 1.5µl/vial.

Cells were also cultured for 48 hours in 6 well plates in low serum medium

(RPMI- 1640 glutamax supplemented with 0.75% foetal calf serum) and

serum free medium (RPMI-1640 glutamax) under identical conditions

described above. The starting concentration of the cells in these cases was 1

x107/ml. Cell viability was determined using 0.4% Trypan blue (Sigma-Aldrich,

Dorset, UK) staining and the cell count were performed using a

haemocytometer. Cells were checked daily by inverted phase contrast

microscopy to determine their morphology, the degree of confluency and also

to rule out presence of sediments or obvious microbial contamination. Testing


41

for Mycoplasma was done routinely once a month. After doing an initial cell

count, cells in medium were centrifuged at 200g for 7 minutes at R.T.

Resultant supernatants were collected and split into either 1ml aliquots in

1.5ml microfuge tubes containing 20µl of P.I. cocktail (Roche, Welwyn, UK)

for future protein work or 300µl aliquots along with 1ml of TRIzol in 1.5ml

microfuge tubes for RNA isolation. Aliquots were snap frozen on dry ice and

stored in freezer at -80°C. Cell pellets were generated only from cells grown in

conditioned medium. They were re-suspended in appropriate volume of ice

cold PBS so that the final concentration of these cells was 1x107/ml. Cells

were washed twice with ice cold PBS in a micro centrifuge at 400g for 7

minutes at 4° C. After discarding the supernatant, cell pellets were lysed

either in 1.0ml of TRIzol L.S. for RNA extraction or in lysis buffer for

proteomics.

2.3.2 Molecular Methods

2.3.2.1 RNA extraction: The entire procedure was performed in a fume

cabinet with strict aseptic precautions and use of pipette tips and microfuge

tubes dedicated for this procedure. The work surfaces were pre-treated with

RNAase Zap (Sigma-Aldrich, Dorset, UK). Frozen samples in TRIzol reagent

(Invitrogen, Paisley, UK) were defrosted and incubated at R.T. for 5 minutes

to allow complete dissociation of nucleoprotein complexes. Next, 200μl of

chloroform (VWR International Ltd. Poole, UK) was added per 1ml of initial

TRIzol reagent. Samples were shaken vigorously for 15 seconds and

incubated at R.T. for 5 minutes. They were then centrifuged at 12,000 x g for

10 minutes at 2 to 8°C. 400μl of upper aqueous phase containing RNA was

isolated and transferred to a fresh 1.5ml microfuge tube. 500μl of propan-2-ol

(Fisher Scientific, Loughborough, UK) was added to this aqueous phase to

precipitate the RNA. The samples were mixed and incubated at R.T. for 10

minutes and then centrifuged at 10,000 x g for 10 minutes at 2 to 8°C. The

supernatants were removed and RNA pellets washed by adding 1ml of 75%

ethanol (Fisher Scientific, Loughborough, UK). The samples were mixed by

vortexing and centrifuged at 7500 x g for 5 minutes at 2 to 8°C. Ethanol was


42

discarded and the RNA pellets were allowed to air dry by inverting the

microfuge tubes for 10-15 minutes. RNA was re-suspended in 50μl of DEPC

(Ambion, Warrington, UK) treated water. 2μl aliquots were taken in order to

determine the chemical purity of RNA by measuring the A260/280 and A260/230

ratios on a spectrophotometer (Nanodrop ND-100 Labtech International,

Ringmor, UK). The remaining samples were stored in 10-20 μl aliquots in a

freezer at -80°C. The integrity of RNA was determined by measuring the RIN

(RNA integration number) on 2001 Bio-analyser (Agilent Technologies UK Ltd.

Stockport, UK).

2.3.2.2 cDNA synthesis: cDNA synthesis was done using random hexamers

(Promega, Southampton, UK) and SuperScript™ II Reverse Transcriptase

(Invitrogen, Paisley, UK). This enzyme is an engineered version of M-MLV RT

(Moloney Murine Leukemia Virus Reverse Transcriptase) with reduced RNase

H activity and increased thermal stability. Higher temperatures increases the

specificity of the enzyme and reduced RNase H activity results in higher yields

of cDNA compared to conventional M-MLV RT. As shown in figure 2.1 below,

Mix 1 and Mix 2 were prepared separately in PCR tubes. Mix 1 was vortexed

and centrifuged briefly to ensure that the components collected to the bottom

of the PCR tubes and then incubated at 65°C for 5 minutes. It was then

quickly chilled on ice for 5 minutes. Mix 2 was made up just before use and

7μl of Mix 2 was added to each Mix 1 sample

Mix1

Total RNA sample 1000ng of RNA in DEPC H2O; max 9l

Random Hexamer 500 ng/µl 2l

dNTP mix (10mM each) 1l

DEPC H2O Volume necessary to adjust to 12 μl in total

Figure 2.1 Composition of Mix 1 and Mix 2 prepared during cDNA synthesis.

5X first strand buffer 4l

DTT (0.1M) 2l

RNaseOUT 1l

Mix 2


43

The contents were mixed by pipetting gently up and down several times.

Samples were then incubated at 25°C for 10 minutes (to maximize primer-

RNA template binding), and then at 42°C for 2 minutes. Following this 1l of

SuperScript™ II Reverse Transcriptase was added and mixed by pipetting

gently up and down several times followed by brief centrifugation. Samples

were then incubated at 42°C for 50 minutes followed by 70°C for 15 minute to

inactive the reaction. Samples were stored at -80°C.

2.3.2.3 Real time TaqMan gene expression assay for AEP (Legumain;

LGMN): Real time TaqMan gene expression assay for AEP (gene of interest)

and β2 microglobulin (control gene) were performed using inventoried (on-

demand) reagents from Applied Biosystems (Foster City, CA, USA). The AEP

probe hs00271599_ml spans boundaries of exon 5 and 6 in case of transcript

NM_005606.6 and exon 6 and 7 in case of transcript NM_001008530.1 In

each case the resultant amplicon is identical and has a length of 79 base

pairs, Figure 2.2. The probe for β2 microglobulin gene hs99999907_m1 spans

exon 2 and 3. The reaction was performed in a 384 well plate on a 7900HT

Fast Real-Time PCR System (Applied Biosystems). The total volume of

reaction per well was 10μl and the proportion of reagents in each well was as

follows: 0.4μl of cDNA, 4.1μl of DEPC treated water, 0.5μl of probe and

primers and 5.5μl of mastermix. The reagents were pipetted in each well with

the help of a automated robotic system (Eppendorf). The reaction was carried

on for 40 cycles each consisting of the following steps: i) UNG (uracil N

glycosylase) incubation at 50°C for 2 minutes, ii) AmpliTaq Gold Activation at

95°C for 10 minutes, iii) Denaturation at 92°C for 15 seconds and finally iv)

Annealing/extension at 60°C for 1min. In this assay the 5’reporter dye was

FAM and the 3’quencher dye was TAMRA. The CT value for was obtained

using SDS2.1 software and the threshold was selected automatically by the

software. Analysis of AEP expression was done by relative quantification

using the 2 -∆∆CT method (104).


44

Figure 2.2 Schematic diagram of AEP (Legumain/LGMN) gene on

chromosome 14q32.1 showing the position of exon spanning TaqMan probe.

The gene has two transcript variants NM_001008530.1 & NM_005906.5. The

former has an additional exon in the 5’UTR of the gene. Both variants encode

for the same isoform. Modified from Entrez Gene, NCBI.

2.3.2.4 MicroRNA (miRNA) array: Expression of 754 human miRNAs per

sample was performed using a two card set consisting of TaqMan human

MicroRNA A+B cards Set v3.0 (Applied Biosystems, part number 4444913).

Included on each card were three TaqMan® MicroRNA assay endogenous

controls to aid in data normalisation and one TaqMan® MicroRNA assay not

related to human to function as a negative a control.

RNA was extracted as described above. Reverse transcription was performed

in fume cabinet with all the precautions described under RNA extraction.

Reverse transcription mix was made in a 1.5ml microcentrifuge tube, figure

2.3 A. Primers for reverse transcription were specific for each card (Megaplex

™ RT primers: Human pool A v2.1 part number 4399966 for card A and

human pool B v3.0 part number 4444281 for card B). Rest of the components

of reverse transcription mix were common for cards A and B. For each

reverse transcription reaction, 3μl of RNA (at least 350ng) was added to 4.5μl

of the above mix. The 1.5ml microcentrifuge tube was incubated on ice for 5

minutes and went through the thermal cycling conditions on DNA Engine

Dyad ® Peltier Thermal Cycler (BioRAD) as described in figure 2.3B. For a

NM_005606.6

NM_001008530.2

AEP Ch 14q32.193,170,152 93,215,047

5 ’ 3 ’

TaqMan Probe

Untranslated region

Coding region

NM_005606.6

NM_001008530.2

AEP Ch 14q32.193,170,152 93,215,047

5 ’ 3 ’

TaqMan Probe

Untranslated region

Coding region


45

real time polymerase chain reaction reagents were mixed as shown in figure

2.3C. Samples were then dispensed into each probe of the TaqMan

MicroRNA array cards and PCR reactions were done as per manufacturer’s

instructions on the 7900HT Fast Real-Time PCR System (Applied

Biosystems).

Figure 2.3 Composition of reverse transcription mix (A), the thermal cycling

condition for reverse transcription (B) and the components of the polymerase

chain reaction (C).

Stage Temp Time

Hold

50°C

85°C 5min

1 sec

1 min

2 min

42°C

16°C

Cycles (40 cycles)

RT Reaction Mix Components Volume for ten samples (μl)‡

Megaplex™ RT Primers (x10)†

9.00

dNTPs with dTTP (100mM) 2.25

MultiScribe Reverse Transcriptase (50U/μl) 16.88

x10 RT Buffer 9.00MgCl2 (25mM) 10.12

Rnase Inhibitor(20U/μl) 1.12

DEPC nuclease free water 2.25

Total 50.62†

Primers were specific for Cards A and B‡

Includes 12.5% excess for volume loss from pippetting

Component Volume for one Array‡ (μl)

Total

444

900

6

450TaqMan® Universal PCR Master Mix, no

AmpErase® UNG,2X

Megaplex™ RT product

Nuclease-free water

A

B

C


46

2.3.3 Biochemical Methods

2.3.3.1 Protein extraction: Cell pellets were incubated with 150μl mixture

made up of lysis buffer and PI cocktail solution (125ul of lysis buffer per 1x107

cells and 25ul of PI) for 35 minutes on ice. Initially cell pellets were lysed

using CelLytic M (Sigma-Aldrich, Dorset, UK) lysis buffer. From March 2009

onwards, CelLytic M buffer was replaced by modified NP-40 lysis buffer (in

house) as initial testing shows that in some patients CelLytic M interferes with

the quantification of AEP by ELISA. Following the incubation step, samples

were centrifuged at 16,000 x g for 35min at 4°C. The resultant supernatant

containing cytosolic proteins was collected and split into 15-150μl aliquots and

stored at -80°C.

2.3.3.2 Protein quantification: This was done using a protein assay method

(Bio-Rad, Hemel Hempstead, UK) based on the Lowry assay (105). In order

to generate a standard curve, bovine serum albumin (Sigma-Aldrich, Dorset,

UK) was used as a reference protein and serially diluted in PBS to achieve

concentrations between 1.44 and 0.08875 mg/ml. Cell lysates were diluted in

PBS at 1:5 and 1:10. For each concentration, 5μl of standards and samples

were added in duplicates into wells of the 96 well microplate. 25µl of freshly

made Reagent A‘ was added into each well followed by 200μl of reagent B.

After 15 minutes, absorbance was read at 650 nm in FLUOstar Omega

microplate reader (BMG Labtech, Aylesbury, UK). The amount of protein in

each well was quantified by reading the OD value off the standard curve.

2.3.3.3 L-Asparaginase activity assay:

Reagents:

1) Native E. coli Asparaginase, Medac GmbH, Germany: A vial containing

10000 Units of E. coli Asparaginase was reconstituted with 10 ml of normal

saline. The drug is unstable for long term storage in aqueous solution. Hence

2994μl of volunteer fresh frozen plasma (FFP) was spiked with 6μl of drug

solution to give a concentration of 2000 Units/L of plasma and stored at -80°C

in 80μl aliquots.


47

2) 10mM L-aspartic β-hydroxamate (AHA, Sigma-Aldrich, A6508) in 0.015

MTris buffer, pH 7.3, supplemented by 0.015% (w/v) Bovine Serum Albumin

(BSA):Dissolve 1.82 gms of Trizma® base (Sigma-Aldrich, T1503) in 80 ml of

DD H2O. Adjust pH to 7.3 with help of HCl, bring volume to 1000 ml by adding

required volume of DD H2O. Add 150 mg of lyophilized BSA (Sigma-Aldrich,

A9647). Pass through 0.2 micron filter. Take 67.5 ml of this buffer to re-

suspend 1 vial of lyophilized AHA (100 mg) to make a 10mM solution. Store

the solution in 5 to 10 ml aliquots at -80° C.

3) 24.5% Trichloro Acetic Acid (Sigma-Aldrich, T9159): 24.5 gm of Trichloro

Acetic Acid in 100 ml of DD H2O. Stored at room temperature.

4) 8 hydroxyquinoline solution: Made freshly each time just before use by

mixing one volume of 2% 8-hydroxyquinoline (Sigma-Aldrich, 252565) in

absolute ethanol to three volumes of 1M sodium carbonate solution. Both the

above reagents were stored separately at room temperature.

5) Non reagent components:

Finnpipette ®F2 (30-300μl) Multi-channel pipette (Thermo Scientific)

MULTIWELL ™ 24 well flat bottom tissue culture polystyrene non pyrogenic

plates (Becton Dickinson, Oxford, UK).

Sterile 1.5ml polypropylene microcentrifuge (Eppendorf) tubes

Sterile flat bottomed polystyrene 96 well plate (BD)

Heating block

Incubator or water bath at 37°C

BMG FLUOstar Omega microplate reader (BMG LABTECH, Aylesbury, UK)

for absorbance spectrometry.

Method:

1) ASNase standards were freshly made each time by serially diluting the

stored drug at concentration of 2000 Units/L with volunteer FFP to give a

range between 0-800 Units/L. Unspiked volunteer FFP was used as blank

concentration.


48

2) Patient plasma samples were thawed at room temperature.

3) Then, 20μl of standards and patient plasma were added in duplicate into

each well of the MULTIWELL ™ 24 well flat bottom tissue culture polystyrene

non pyrogenic plates (Becton Dickinson, Oxford, UK). The positions of the

standards and patient plasma were accurately recorded.

4) With the help of Finnpipette®F2 (30-300μl) multi-channel pipette, 180μl of

10mM AHA solution is next added to each well of the plate. The sequence of

step 3 and 4 was always preserved to ensure uniform incubation times with

AHA for all samples.

5) Plate was then incubated in an oven at 37°C for exactly 15 minutes.

6) Next, with the help of Finnpipette®F2 (30-300μl) multi-channel pipette,

250μl of 24.5% TCA was added to each well of the plate and it was

centrifuged at 1000g for 10 minutes at 37° C.

7) 2mls of freshly prepared 8 hydroxyquinoline solution was added to each

well of the plate following which the plate was put into the oven at 95°C for

exactly 12 minutes.

8) Plate was then allowed to cool at room temperature for 10 minuter.

9) 100μl of supernatant from each well of the 24 well flat bottom plate was

carefully aspirated and transferred into a 96 well flat bottom plate. The

absorbance from each well was measured at 710nm on a BMG FLUOstar

Omega microplate reader.

10) Plasma ASNase activity in patient samples was read off linear standard

curve obtained by joining the OD values of ASNase standards.

2.3.4 Immunological methods

2.3.4.1 Chemiluminescent AEP ELISA:

Material and Reagents:

1) White opaque 96 well microplate- Lumitrac 600, catalogue number 15042,

ThermoFisher Scientific.

2) Capture Antibody: Monoclonal mouse anti human AEP antibody, clone

322109, catalogue number MAB21992, R&D Systems. Lyophilized powder


49

of capture antibody was reconstituted in 1ml of sterile PBS to give a

concentration of 500 μg/ml. Antibody is stored at -80°C in 50μl aliquots.

3) Reagent diluent (0.5% Bovine Serum Albumin PBS): 19 parts of D/D water

mixed to 1 part of Reagent Diluent Concentrate.

4) Calibrator Solution: 9 parts of Reagent Diluent and 1 part of Lysis

buffer/Protease inhibitor solution.

5) Standard: Recombinant human AEP protein (R&D systems, Catalogue

Number 2199-D Y-100 accession #Q99538). The recombinant protein is

available as 20μl of 0.2 micron filtered solution in 20mM Tris and 150mM

NaCl, pH 7.5 at a concentration of 0.5mg/ml. Protein was diluted in

Tris/NaCl buffer to give a concentration of 5ng/μl and stored in 5μl aliquots

at -80°C.

6) Detection Antibody: Biotinylated polyclonal goat anti human AEP antibody,

catalogue number BAF2199. Lyophilized powder of detection antibody

was reconstituted in 1ml of Tris-buffered saline pH 7.3 (20 mM Trizma

base, 150 mM NaCl) containing 0.1% BSA to give a concentration of

50ng/μl. Antibody was stored at -80°C in 90μl aliquots.

7) Streptavidin-Horse Radish Peroxidase (HRP), R&D systems Minneapolis,

US. Catalogue no DY998 (1/2500 solution): Add 4μl of Streptavidin-HRP

to 10 ml of reagent diluent just before use.

8) Chemiluminescent Substrate (Reagent A & B): Super Signal West Pico,

37070, Thermo Scientific. The two reagents were stored at room

temperature in dark and mixed in 1:1 proportion just before use.

9) FLUOstar OMEGA plate reader, BMG Labtech.

Each well of the white opaque 96 well microplate was coated with 100μl of

capture antibody that was diluted in coating buffer at a concentration of

2μg/ml. Plate was sealed and kept at 4°C overnight. The following morning

unbound antibody was aspirated and each well was washed 3 times with

400μl of washing buffer. This aspiration/washing step was repeated each time

before successive steps. Blocking was achieved by adding 400μl of blocking

buffer per well and incubating the plate for 2 hours at room temperature.

Standard, controls and samples were all diluted in calibrator solution and


50

loaded in duplicates in volumes of 100μl per well. Using 2-fold serial dilutions

in calibrator solution, 7 concentrations of standards were generated ranging

from 50ng/ml (highest) to 75pg/ml (lowest). Samples consisted of cell lysates

at 1: 9 dilutions and plasma at 1:99 dilutions. Cell lysates of AEP+REH cell

lines were used as positive control and volunteer plasma was used as a

negative control. Next, plate was sealed and kept at 4°C overnight. Detection

of bound AEP protein used sequential incubation at room temperature in dark

conditions of 100μl detection antibody at a concentration of 400ng/ml

incubated for 2 hours, followed by 100μl of Streptavidin/HRP solution for 1

hour and lastly 100μl of chemiluminescent substrate for 5 minutes. The

luminescence was measured in relative light units using a luminescent probe

on the FLUOstar OMEGA plate reader.

2.3.4.2 Immunoblotting:

a) Chemiluminescent immunoblotting

SDS-Polyacrylamide gel electrophoresis (SDS-PAGE)

Glass plates, spacers and combs of the mini-PROTEAN II electrophoresis cell

(Biorad) were first cleaned with 20% ethanol to remove any contaminating

proteins and assembled as per instructions from the manufacturer. The

discontinuous SDS-PAGE gel electrophoresis system was achieved by first

pouring resolving gel between the two layers of glass and overlaying it with

isopropanol. The gel was left to polymerise. Isopropanol ensures a smooth

top surface of the polymerised gel. Following polymerisation, isopropanol

layer was removed by gently tilting the assembly and the glass plate washed

with D/D water to remove any trace of alcohol. The stacking gel was next

poured on top of the polymerised resolving gel. Combs were placed to create

sample loading well. Following polymerisation, the combs were removed and

the wells were washed with 1x running buffer. Cell lysates were diluted

appropriately with x 5 SDS reducing buffer to ensure at least 10μg of protein

per 20μl volume. Samples were boiled for 5 minutes at 95° C and 20 μl of

reduced sample lysates were loaded into the wells using Gel loading tips (2-

20μl, Anachem). To reference the molecular weight of protein of interest, each

run had a protein standard (Precision Plus Dual Colour, BioRad) to estimate


51

the protein size. Electrophoresis was performed at 55 V whilst the samples

ran though the stacking gel and 100 V through the resolving gel.

Semi-dry protein transfer:

Polyvinylidene fluoride (PVDF) microporous membrane (Immobilon-P

Transfer Membrane; Milipore) was first activated by 1 minute exposure to

methanol. After washing off methanol from the activated membrane, it; along

with the extra think blot paper were pre soaked in transfer buffer. Proteins

separated at the end of SDS-PAGE electrophoresis were transferred on to a

methanol exposed activated by applying 25mV of current for 34 minutes

across the gel nitrocellulose sandwich. The sandwich had the following

sequence from top to bottom consisting of thick filter paper, resolving gel,

activated PVDF membrane and finally another thick filter paper.

Western blotting

Following transfer, the membrane was rinsed in wash buffer and blocked by

incubating it with non fat milk blocking buffer on a rocking platform unit for 1

hour at R.T. Membranes were extensively washed with wash buffer and then

incubated overnight on a rocking platform unit with a primary antibody solution

against protein of interest. The following day, the membranes were washed x5

with wash buffer to remove primary antibody and were incubated with

appropriate species specific horseradish-peroxidase conjugatged secondary

antibody for one hour. Following the one hour incubation, the membranes

were washed x 5 with wash buffer to remove any free (unbound) secondary

antibody.

Detection

Membranes were then placed on a clean Cling-Film (Saran™ ClingPlus®

Wrap) sheet and layered with 10 ml of 1:1 mix of Luminol/Ehancer and

Peroxide buffer solutions contained in the SuperSignal® West Dura Extended

Duration Enhanced Chemiluminescent Substrate Kit. Following its incubation

for 5 minutes, the excess solution was drained off and the membranes were

placed in the film cassette and exposed on X-ray films (Kodak Medical X-ray

films) for varying intervals and developed using a Film Processor to visualise

protein band.

Loading control


52

In order to show uniform loading the sample proteins in each lane,

membranes were stripped using ‘Restore’ proprietary membrane stripping

buffer and re-blotted with GAPDH.

b) Infrared Fluorescent immunoblotting

In the Infrared fluorescent immunoblotting detection system, the secondary

antibodies are conjugated with infra red dyes that show emission at 680 and

800nm. Employing a combination of primary antibodies from two distinct

species and secondary antibodies from one species having two distinct

fluoropores corresponding to two distinct primary antibodies allows two-colour

multiplexed detection and quantification of proteins on the Odyssey® CLx

Infrared Imaging System (LI-COR). Table 2.1 summarises the steps that are

distinct to the chemiluminescent immunoblotting. Aside from the distinct

detection system, table 2.1 shows the specifics of primary and secondary

antibodies for AEP and CTSB and the key differences, highlighted in bold,

between the chemiluminescent and infra immunoblotting techniques.


53

Table 2.1 Reagents used for infra-red and chemiluminescent immunoblotting

Steps Infra-red immunoblotting (LICOR) Chemiluminescent immunoblotting

a) Membrane Millipore FL Millipore P

b) Blocking 5% BSA (w/v) PBS (no tween) PBST (0.1%) + Marvel

c) Primary Antibody AEP R & D Systems, AF2199 R & D Systems, AF2199 Type Goat, polyclonal Goat, polyclonal Dilution 1 in 2500 5% BSA (w/v) PBST (0.1%) 1 in 2300 in 5% Marvel PBST (0.1%) CTSB Biomol SA-361, Enzo Life Sciences) Biomol SA-361, Enzo Life Sciences) Type Rabbit, poly clonal Rabbit, poly clonal Dilution 1 in 20000 5% BSA (w/v) PBST (0.1%) 1 in 20000 5% Marvel (w/v) PBST (0.1%) GAPDH Abcam ab8245 Abcam ab8245 Type Monse, monoclonal Monse, monoclonal Dilution 1 in 20000 5% BSA (w/v) PBST (0.1%) 1 in 20000 5% Marvel (w/v) PBST (0.1%)

d) Secondary Antibody AEP LICOR 926-32224 Santa Cruz, sc-2020 Type IRDye 680LT donkey anti goat HRP conjugated Donkey anti goat Dilution 1:25000 5% BSA (w/v) PBST (0.1%) 1:10000 5% Marvel (w/v) PBST (0.1%) CTSB LICOR 926-32213 Pierce Type IRDye 800CW donkey anti rabbit HRP conjugated goat anti rabbit Dilution 1:25000 5% BSA (w/v) PBST (0.1%) 1:4000 5% Marvel (w/v) PBST (0.1%) GAPDH LICOR 926-68022 Pierce 31430 Type IRDye 660LT donkey anti mouse HRP conjugated goat anti mouse Dilution 1:25000 5% BSA (w/v) PBST (0.1%) 1:10000 5% Marvel (w/v) PBST (0.1%) *Highlighted text refers to the key differences between the two techniques


54

2.3.4.3 AEP Immunoprecipitation assay:

The protocol was obtained from Dr Nullin Divecha’s group based at the

Paterson Institute for Cancer Research

Day 1

a) Pre clear step:

Fifty micro-litres Protein A/G UltraLink resin (Thermo Scientific, catalogue

number PN53132) was added to three 1.5ml eppendorf tube containing 250μg

of SD1 lysates in 200μl of lysis buffer. The samples were incubated on a

rotator at 10RPM for 1 hour at 4°C and then centrifuged at 3000g for 3

minutes at 4°C. Clear supernatants free of non specific immunoglobulin and

containing the protein of interest were collected.

b) Pull down:

Two micrograms each of 1) monoclonal mouse anti-human AEP antibody:

MAB21992, R&D Systems-pull down antibody; 2) Polyclonal goat antihuman

AEP antibody: AF2199, R&D System-positive control; and 3) mouse IgG

antibody: negative control; were added to the clear supernatants and the

samples were incubated at 10RPM on the rotator overnight at 4°C. AF2199

was previously optimised for AEP immunoblotting in the lab served.

Day 2

Fifty micro-litres of Protein A/G UltraLink resin was added to each tube and

the samples were incubated on a rotator at 10RPM for 2 hours at RT.

Samples were then centrifuged at 3000g for 3 minutes at 4°C, clear

supernatant was discarded and the resins re-suspended in 500μl of lysis

buffer. This centrifugation step was repeated three times. A mixture of 10μl x2

loading buffer, 0.5μl 1 M DTT and 7.5 μl of DD H2O was added to resins in

each tube and the samples were heated to 96°C for 10 minutes do denature

and detach the protein(s) captured onto the resins. Finally samples were

incubated in dark with 2μl of 500mM iodoacetamide for 20 minutes at R.T. to

break apart the pull down antibody into heavy and light chains. The proteins


55

were separated by SDS-Polyacrylamide gel electrophoresis. The recognising

antibody was a polyclonal goat anti-human AEP antibody at conditions

optimised in the AEP immunoblotting protocol and the detecting antibody was

a true blot anti-goat antibody at 1:10,000 dilution that was incubated for 1 hour

at R.T.

2.3.5 Other techniques

2.3.5.1 Capture of microvesicles: Microvesicles (MV) were isolated from the

cell suspensions and plasma samples by a combination of centrifugation

protocols described in the literature and using an antibody based approach

that adopted the principle of the immunoprecipitation (IP) assay, figure 2.4.

The novelty in the technique consisted of capturing microvesicles instead of

capturing proteins in a standard IP assay. The “pull down antibody” was a

mouse anti human anti CD19 antibody, clone HIB19, BD Pharmingen™;

catalogue number 555410.

Technique: On day 1, debris free SD1 supernatant was obtained by

subjecting 5ml of SD1 cell suspension to 2 successive spins consisting of 750

g for 5 minutes (to pellet the SD1 cells), 1500 g for 15 minutes (to pellet

debris). Microvesicles were pelleted by subjecting the debris free SD1

supernatant to 3rd spin consisting of 15,000 g for 45 minutes at 4 C.

Microvesicles were labelled with PKH-67 (SigmaAldrich, Dorset, UK;

Catalogue number PKH67GL-1KT) as per manufacturer’s instructions. PKH-

67 incorporates into cell membrane lipid bilayer and contains a green

fluorochrome that has an excitation and emission spectrum of 490nm and

504nm respectively. Labelled MVs were re-suspended in 800 μl of PBS and

incubated with either anti-CD19 antibody (BD Biosciences, clone HIB19,

catalogue number 555410) at 4 C at 5 RPM (revolutions per minute). The

anti-CD3 antibody (Thermo Scientific, clone RIV9, catalogue number MA1-

7639)) and Protein A/G UltraLink resin were used as negative controls for

anti-CD19 antibody.


56

On day 2, 50 μl of Protein A/G UltraLink resin was added MV suspensions

and samples were incubated at room temperature for 2 hours under dark

condition to immobilise the anti-CD19 antibody/labelled MV complex.


57

Figure 2.4 Capture of MV. Schematic description of method developed to

isolate CD19 expressing MV. For labelling of MV with green fluorescent

Isolating CD19 expressing micro vesicles from extracellular compartmentDay 1

Collect supernatant

1st spin 750g x 5min; pellet cells

2nd

spin 1500g x 15min; pellet debris

3rd

spin 15000g x 45min, 4°C;

Stop the staining reaction +

4thspin 15000g x 45min 4 °C

Re-suspend MV 800 μl of PBS

5mls SD1 suspension

Collect supernatant

Label MV with PKH67 dye*

Pellet microvesicles (MV)

Re suspend MV in 1ml Diluent C

Add 50μl of Ultralink A/G

incubate RT, 2hrs, 10RPM

Day 2

Spin 3000g with PBS, 4°C for 5min

Collect 1st supernatant for time lapse microscopy

Wash beads x3

Collect beads for time lapse microscopy


58

PKH67 dye, both the initial incubation step (ϯ) and the subsequent stopping of

the reaction by adding bovine albumin (*) was done as per manufacturer’s

instructions.

2.3.5.2 Immunoblotting of microvesicle lysates: Concentrations of primary

antibody used in the immunoblotting experiments is shown in table 2.2

Table 2.2 Concentration and source of antibodies:

2.3.5.3 In-Vivo labelling of cells for AEP by Fluorescent probe:

Ten million SD1, REH, SD1kd, REH+AEP cells were suspended in 2 ml of

culture medium described above and incubated at 37°C for 1 hour with a

fluorescent labelled, cell permeable AEP probe (LP-1) (106) at a

concentration of 1μmolar.. Unbound probe was removed by x2 PBS washes

at 200g for 5 minutes and cell pellets were re- suspended in 10 ml of excess

media and left in the incubator at 37°C for 1 hour. Finally media was removed

by x2 PBS washes at 200g for 5 minutes and expression of AEP was

analysed by flow cytometry on the BDTM LSR II flow cytometer (Becton

Dickinson Biosciences, Oxford, UK) and on Amnis ImageStreamX flow

cytometer (Amnis Corporation, Ipswich, UK)

2.3.5.4 Statistical methods: Categorical variables were compared with the

Chi-squared test and continuous variables with Mann-Whitney or a Kruksal-

Walis test depending upon the number of groups being compared. SPSS-16

Table

Target Protein Host species Clone Company Catalogue number Concentration of Antibody

MMP2 Mouse F14P4D3 Biolegend 303602 1 in 500

MMP9 Mouse F11P2C3 Biolegend 635002 1 in 500

Actin Mouse AC-15 Sigma-Aldrich A5441 1 in 5000

Cathepsin B Rabbit Polyclonal BioMol, Alexis BML-SA361 1 in 10000

CD11a Rabbit EP1285Y Abcam ab52895 1 in 1000

VAMP3 Rabbit Polyclonal Fisher Scientific PA1-767A 1 in 1000

CD19 Goat Polyclonal Santa Cruz SC-8498 1 in 400

CD63 Rabbit MEM-259 Abcam ab8319 1 in 1000

LAMP1 Rabbit Polyclonal Abcam ab24170 1 in 1000

TSG101 Mouse 4A10 Abcam ab8319 1 in 1000

CD81 Mouse 5A6 Biolegend 349501 1 in 1000

Table

Target Protein Host species Clone Company Catalogue number Concentration of Antibody

MMP2 Mouse F14P4D3 Biolegend 303602 1 in 500

MMP9 Mouse F11P2C3 Biolegend 635002 1 in 500

Actin Mouse AC-15 Sigma-Aldrich A5441 1 in 5000

Cathepsin B Rabbit Polyclonal BioMol, Alexis BML-SA361 1 in 10000

CD11a Rabbit EP1285Y Abcam ab52895 1 in 1000

VAMP3 Rabbit Polyclonal Fisher Scientific PA1-767A 1 in 1000

CD19 Goat Polyclonal Santa Cruz SC-8498 1 in 400

CD63 Rabbit MEM-259 Abcam ab8319 1 in 1000

LAMP1 Rabbit Polyclonal Abcam ab24170 1 in 1000

TSG101 Mouse 4A10 Abcam ab8319 1 in 1000

CD81 Mouse 5A6 Biolegend 349501 1 in 1000


59

software was used for statistical analysis. For time to event outcome, Kaplan-

Meier curves were calculated and compared with the log-rank test. Event free

survival was defined as time to relapse, secondary tumour or death, counting

only the first event. Overall survival was defined as time to death. Relapse

free survival was defined as time to relapse, excluding those who never

achieved remission.

.

Development of assays

60

Chapter 3 DEVELOPMENT OF ASSAYS ______________________________________________________________

Most of the assays used in this thesis were developed in house and therefore

I have devoted a chapter to describe them in detail.

3.1 PLASMA ASPARAGINASE ACTIVITY ASSAY- Indoxine Method:

3.1.1 Background for the assay: Plasma ASNase activity is expressed in

Units/L. One unit of activity is defined as the amount of enzyme which

releases 1μmol of ammonia and L-Aspartic acid from 1μmol of L-Asparagine

per minute at 37°C. The liberated ammonia can be measured

spectophotometrically after nesslerization. Alternatively, assays use an L-

Asparagine analogue substrate that is cleaved by ASNase in plasma to

produce an intermediate product. This intermediate product in turn reacts with

a chromogen to produce a colour that is measured at a specific wavelength in

a plate reader.

Initially we used a commercially available substrate assay, MAAT (Medac

Asparaginase Aktivitäts-Test) kit from Medac GmbH Wedel, Germany was

used. Optimisation of the MAAT assay identified one difficulty. The standard

curve generated using the reagents provided in the kit was linear only when

the ASNase was reconstituted in a proprietary calibrator solution. This was

not the case (Figure 3.1) when the standard curve was generated using

volunteer plasma, which is a better comparator for measuring plasma ASNse

activity in clinical samples. Hence the “indoxine method”(107) was adopted

and standardised.

3.1.2 Principle of the assay: Plasma containing ASNase is incubated for 15

minutes at 37°C with an excess amount of L-Aspartic β Hydroxamate (AHA).

Plasma ASNase cleaves AHA to generate proportionate amount of

hydroxylamine. The reaction is stopped by adding Trichloroacetic acid (TCA).

TCA is then neutralised by adding sodium carbonate (Na2CO3).


61

Hydroxylamine when condensed with 8-hydroxyquinoline at 95°C undergoes

oxidation to produce green coloured indoxine that is read at 710nm.

Figure 3.1: MAAT assay (Medac, GMBH, Wedel Germany). X axis is the

concentration ASNase in U/L, Y axis is the optical density value obtained by

measuring absorbance at 700nm.

3.1.3 Performance of the assay: Figure 3.2 shows the dynamic range, intra-

assay variation and limit of detection of the assay and figure 3.3 shows the

inter-assay and inter-person variation of the assay. The assay is linear for

plasma ASNase concentrations of up to 800U/L. The limit of detection (LOD)

of the assay is the lowest concentration of analyte that can be detected and

reliably differentiated from the background values. It can be calculated by two

methods. In the first method, LOD is expressed in Units of ASNase/Litre of

plasma and is calculated as the lowest concentration of ASNase standard that

had a value that was greater than (3.3 x σ of background value)/Slope of the

calibration curve (108). The second method first calculates limit of blank (LOB)

which is mean background OD value + 1.645 σ of background value. LOD is

then expressed as a raw OD value obtained by adding LOB to 1.645 x σ low

concentration sample (109). Limit of detection for this assay was 33.8 Units of

ASNase/Litre of plasma by method 1 or a raw OD value of 0.082 by method 2.

Volunteer plasma

0

0.5

1

1.5

2

2.5

3

0 100 200 300 400 500 600

L-Asparaginase U/L

0.2

0.4

0.6

0.8

1.2

1.4

1.6

Proprietary calibrator

R2

= 0.9952

0

1.0

0 100 200 300 400 500 600 700

L-Asparaginase U/L

OD

Valu

e

OD

Valu

e


62

Figure3.2: Linear Range of the Indoxine assay. X axis represents

concentrations of ASNase in plasma and Y axis represents the optical density

values obtained by measuring absorbance at 710nm. The error bars

represent ± 1 Standard Deviation. STDEV=standard deviation. CV=

Coefficient of variation.

y = 0.0005x + 0.0653

R2

= 0.9983

0.1

0.2

0.3

0.4

0.5

0 100 200 300 400 500 600 700 800

Plasma L-Asparaginase (U/L)

OD

valu

e

L-Asparaginase Standards: Linearity and Intra Assay Variation

1 2 3 4 Mean

800 0.467 0.438 0.439 0.423 0.442 0.016 3.598

400 0.262 0.277 0.282 0.245 0.267 0.014 5.415

200 0.156 0.158 0.159 0.172 0.161 0.006 3.907

100 0.121 0.117 0.114 0.115 0.117 0.003 2.296

50 0.082 0.093 0.095 0.084 0.089 0.006 6.317

25 0.069 0.069 0.071 0.074 0.071 0.002 2.8920 0.060 0.057 0.068 0.069 0.064 0.005 8.068

Limit of Detection

Method 1=3.3xSD(blank)/slope [U/L] 33.815

Method 2 =LOB+1.645*SD of low conc [OD value] 0.082


Optical Density Values

STDEV CV (%)

A

B


63

Figure3.3: Performance of the Indoxine assay: A Linear Range of the Indoxine

Asparaginase assay. X axis represents concentrations of ASNase in plasma

and Y axis represents the optical density obtained by measuring absorbance

at 710nm. The error bars represent ± 1 Standard Error of the mean (SEM). B

Inter Assay and inter person variation using a uniform patient sample between

the runs as internal control. CV= Coefficient of variation.

y = 0.0005x + 0.0844

R2

= 0.9953

0.1

0.2

0.3

0.4

0.5

0 100 200 300 400 500 600 700 800

OD

valu

e


A

B

Run 1 2 3 4 5 6

R2 Value of the run 0.989 0.994 0.995 0.988 0.991 0.993

Plasma L-Asparaginase (U/L) SEM

800 0.403 0.382 0.462 0.439 0.461 0.449 0.023

400 0.261 0.231 0.288 0.285 0.290 0.293 0.017

200 0.172 0.163 0.193 0.202 0.203 0.196 0.011

100 0.115 0.106 0.139 0.138 0.140 0.150 0.012

50 0.086 0.079 0.108 0.110 0.103 0.115 0.010

25 0.074 0.071 0.089 0.088 0.087 0.096 0.006

0 0.057 0.060 0.074 0.074 0.074 0.087 0.007

Run 1 2 3 4 5 6 CV (%)

Plasma L-Asparaginase (U/L) 235 214 229 205 227 214 3.6

Mean Optical Density Values

L-Asparaginase Standards: Inter Assay Variation

Internal control: Inter Assay Variation

Internal control: Inter Person Variation

Run 1 2 3 4 5 6 CV (%)

Plasma L-Asparaginase (U/L) 227 263 247 210 260 212 11.9

7

243

8

243


64

3.1.4 Pre-analytical effect of sample transport on Asparaginase activity:

All samples have been processed within 8 days of sample collection, Figure

3.4. The median time from sample collection to processing in the initial 18

months of the study was 2 days (n=593). To look at the effect of sample

transport on plasma ASNAse activity, a pilot study was done where 15

randomly selected blood samples were split into three parts on arrival and

processed on the day of arrival or were left on the bench and processed on

day 4 and 5 respectively. All samples that had adequate ASNase activity

(>100U/L, n=13) remained above this threshold even after leaving them on

the bench for upto 4 days. Given that these samples took between 1-4 days to

arrive to us from the participating centres, the processing interval in this pilot

study was well beyond the median of 2 days observed in the parent study. It is

reassuring to conclude that the current standard operating procedures for

sample collection, processing and storage, are suitable for analyses of

ASNase activity for all samples.

3.1.5 Summary: The linear range of the previously published indoxine

method (107) was either 2.5-7.5 U/L or 75-1250 U/L. This was dependent on

the volume of reagents used and the incubation time. Both of these were

changed on a trial and error basis so that the asparaginase standards

achieved a linear range between 0-800 Units of asparaginase/litre of plasma.

An additional strength of this method is that all reactions of the assay until the

step of putting the samples on a spectrophotometer are performed in one

plate without having to transfer volumes of intermediate product into separate

tubes. This makes the assay less cumbersome, less prone to errors and

higher throughput thus making it feasible to test clinical samples in batches of

40 samples over 3 hours.


65

Figure 3.4: Effect of sample transport on ASNase activity A) Box and whisker

plot showing the interval in days between sample collection and processing in

593 clinical samples. Box encompasses values between the 25th and 75th

centiles Lower whisker represents minimum value, upper whisker is the

maximum value that is 1.5 x inter-quartile range (IQR) beyond the 75th

percentile. The bar represents the median (2 days) and + represents the

calculated mean (2.48 days). Outliers are shown as circle (n=4) that are ≤ 3x

IQR and asterix (n=5) that are > 3x IQR. B) Pilot study to determine the effect

of pre analytical phase of sample transport on plasma ASNase activity to

show that samples up to 4 days in transit are suitable for measuring ASNase

activity. The dotted line represents the threshold of adequate activity (≥ 100

U/L).

+

8

4

6

2

Blood samples

Pro

cessin

g tim

e (

da

ys)

n= 593

0

100

200

300

400

500

600

processed on

day of arrival

processed

4 days later

processed

5 days later

L-A

spa

ragin

ase a

ctivity (

U/L

)

*


66

3.2 Expression of AEP by RQ-PCR in cell lines and patient samples:

3.2.1 Quality of the RNA obtained from patient samples: RNA is very

sensitive to degradation. Assessment of the quality of RNA obtained from

clinical samples is a pre-requisite to obtaining meaningful gene expression

data. One of the methods to assess the quality of RNA is to determine its

integrity on Bioanalyser 2100 (Agilent Technologies, USA) (110). RNA

intercalated with a dye undergoes electrophoretic separation on a micro-

fabricated chip. An electropherogram is then generated, figure 3.5 by the

emission of fluorescence from the intercalated dye in presence of laser. The

software of the analyser measures the amount of 18S and 28S ribosomal

RNA and comes up with a ‘RIN’ (RNA integration number) value based on the

fluorescence signal from the peaks and the shape of the curve respectively. A

RIN > 5 is considered good for downstream applications such as RQ-PCR

(110).

To determine if the incubation period between sample collection and

processing affects the RNA, we analysed its chemical purity (A260/280), quantity

(ng/μl) and integrity (RIN) and correlated these with the incubation period as

shown in the table. The majority of samples yielded >100ng/μl of RNA when

RNA precipitates were suspended in standard volume of 50μl of DEPC water.

For patient samples LA 0066, LA0080, LA 0114, LA 0115 and LA0117 the

software of the bio analyser did not give a RIN value.


67

Figure 3.5: Quality of patient RNA. Majority of samples (8/10) yielded >100

ng/μl of RNA and an A260/280 > 1.8 when RNA precipitates were re suspended

in 50μl of DEPC water. N.A= Not available. Electopherogram of RNA samples

from 10 patients showing fluorescent peaks from left to right corresponding to:

background marker, 5S RNA, 18S and 28S rRNA. A high quality RNA has a

clearly visible 28/18S rRNA peak ratio and a small 5S RNA and a RIN value ≥

7.5 (110)

NA2.0567.72LA 0117

9.61.9215.31LA 0087

9.81.9254.12LA 0107

NA1.9160.71LA 0115

NA1.9144.51LA 0114

9.11.8139.81LA 0100

9.31.774.02LA 0079

NA1.721.04LA 0080

NA1.9113.11LA 0066

91.9419.43LA 0069

Processing time (days) RNA (ng/μl) RINA260/280Patient Samples

A

B


68

3.2.2 Dynamic range of the assay: Figure 3.6 shows the dynamic range of

the assay for AEP (gene of interest) & β2 microglobulin (housekeeping gene)

in SD1 cell lines (positive control).

3.2.3 Consistency of the step of reverse transcription: In order to

determine the consistency in the step of reverse transcription, 3 cDNA

samples out of a total of 43 samples were randomly selected and serially

diluted to generate CT values for AEP and β2 microglobulin, figure 3.7. The

error bars represent standard error of the mean CT value obtained for each

sample that was run in triplicates. This shows that the step of reverse

transcription was consistent. In order to determine any variation in the

performance of real time quantitative PCR assay between any two runs of

clinical samples, the cDNA that was generated in above experiment was

pooled, aliquoted in 20μl volumes and stored at -20°C. This cDNA was used

to generate standard curves during each run of the assay for the entire length

of the study.

3.2.4 Amplification efficiency of the assay: The amplification efficiency for

AEP and β2 microglobulin was calculated from the slope of the standard

curves using the equation of Efficiency (E) expressed in percentage = (10-

1/slope-1) x100. The basis of this equation is that if the assay is 100% efficient,

the PCR product will increase by 10 fold every 3.32 cycles. Using this

equation, the efficiency amplification of AEP and β2 microglobulin was 96 and

91% respectively and the co-efficient variation for the efficiencies of AEP and

β2M in the three randomly selected samples was 2.5% and 1.4% respectively.

3.2.5 Selection of control gene: β2 microglobulin was chosen as a control

gene based on its consistent expression in lymphoblasts during micro-array

analysis of 120 patient samples done in the laboratory previously (Prof. V.

Saha, Manchester; personal communication). Moreover, in this study, using a

CT cut off between 18.37 and 21.43, the expression of β2 microglobulin

followed a normal distribution pattern, figure 3.8 A. In 28 samples the


69

amplification efficienciencies of the 2 genes were calculated using LinReg

software and figure 3.8B shows that the amplification efficiencies correlated

with each other, indicating that β2 microglobulin was a good indicator of the

stability of the AEP transcript.

Figure 3.6 Dynamic range of the assay. A: Y axis represents the cycle

threshold values plotted against log nanogram (ng) of the starting amount of

RNA per well in case of AEP and β2 microglobulin on X axis. B: Shows the

data by plotting difference in CT values of AEP and β2 microglobulin on y axis.

The curves are parallel until log ng value of -1.1 which corresponds to 78

picograms of starting concentration of RNA per well. Error bars represent ± 1

SEM.

Log ng of starting RNA

∆C

T

R2

= 0.9958

R2

= 0.9993

5

10

15

20

25

30

35

40

-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5

CT

Valu

es

R2

= 0.9958

R = 0.9993

5

10

15

20

25

30

35

40

-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5

AEP

β2

CT

Valu

es

R2= 0.2652R

2= 0.2652

1

2

3

4

5

6

7

8

9

10

-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5


A

B


70

Figure 3.7: Consistency of the RT step. A: Y axis represents the cycle

threshold values plotted against log nanogram (ng) of the starting amount of

RNA per well in case of AEP and β2 microglobulin on X axis. B: Shows the

data by plotting difference in CT values of AEP and β2 microglobulin on y axis.

The curves are parallel. Error bars represent ± 1 SEM.

R2= 0.99

= 0.99

5

10

15

20

25

30

-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2

SD1 AEP

SD1 β2M

R2

CT

Valu

es

y = 0.0883x + 5.845

R2= 0.3177

1

2

3

4

5

6

7

8

9

10

-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2

∆C

T



y=-3.1807x + 25.56

y=-3.269x + 19.715

A

B


71

Figure 3.8 Performance of control gene. A: Histogram showing expression of

β2 microglobulin in clinical samples. CT values of 18.37 and 21.43 represent

±1 standard deviations from the mean expression and these values were

used as cut offs for accepting all samples for data analyses. B & C:

Comparison of the amplification efficiency of β2 microglobulin with that of AEP

in 28 patient samples.

Fre

quency Mean = 19.9

Std. Dev = 1.6C.V. = 7.7%n = 74± 1SD = 18.4 - 21.4

262422201816

20

15

10

5

0

CTValues

R2 = 0.0593

0

0.5

1

1.5

2

2.5

1.65 1.7 1.75 1.8 1.85 1.9

AE

P

β2 microglobulin

β2M AEP

Efficiency (%) 91.05 95.35

mean 1.82 1.90

stdev 0.04 0.15

CV (%) 2.42 8.10

n=28

A

B

C


72

3.2.6 Expression of AEP by RQ-PCR in cell lines: Figure 3.9 shows

expression of AEP in SD1, REH and SUP B15 cells lines. Expression of AEP

in SD1 cells is more than 550 fold of that in REH cells and more than 50 fold

of that in SUP B15 cells.

R

ela

tiv

e fo

ld e

xp

ress

ionX2 fold less

X4 fold less

X8 fold less

X16 fold less

X32 fold less

X64 fold less

X128 fold less

X256 fold less

X512 fold less

0

1

2

3

4

5

6

7

8

9

10

11

SD1 REH SUP B15

X same

Log scale

500 fold less

80 fold less

Figure 3.9: AEP expression by RQ-RTPCR in cell lines. Y axis represents the

relative fold expression of AEP. REH and SUP B15 cell lines expressed less

AEP compared SD1 cells. The negative controls for this assay were no

template sample and genomic DNA from SD1 cells.

3.2.7 Expression of AEP by RQ-PCR in patient samples: Using the criteria

of accepting only samples that have RNA A260/280 of >1.8 and where the CT

values of β2 microglobulin fall within the defined cut offs (19.90 ± 1SD),

normalised expression of AEP is available for 76 patient samples, figure 3.10.

The difference in expression of AEP between the highest and lowest values is

greater than 1000 fold. As we expected to find, there is a small population of

patient samples that highly express AEP as reflected by the outliers (green

circles) and the skew of the mean (+) from the median (bar).


73

Figure 3.10: Expression of AEP by RQ-RTPCR in clinical samples. The data

is shown in box and whisker plots. The box represents the interquartile range.

The bar is the median, + is the calculated mean, circles are the outliers and

the asterisk is an extreme outlier. The whiskers represent the upper adjacent

value (upper quartile + 1.5x interquartile range) and the lower adjacent value

(lower quartile -1.5x interquartile range).

3.3 AEP ELISA:

We decided to additionally quantify the expression of AEP at the protein level

because ultimately it is the AEP protein that degrades ASNase. To quantify

the expression of AEP at the level of protein in clinical samples, a sandwich

ELISA assay was developed. I inherited the ‘first generation’ assay from Dr.

Jizhong Liu that used a chromogenic substrate in the detection system. Over

a period of 3 years, this assay underwent modifications and further

optimization at each step to evolve into a chemiluminescent ELISA that was fit

for clinical use.


74

3.3.1 Developmental history of the assay

3.3.1.1 The first generation assay: This assay was performed on Immuno

Plate F96 MaxiSorp microplates (Scientific Laboratory Supplies Ldt.

Nottingham, UK) and used a monoclonal mouse anti human AEP primary

antibody which only recognised the immature, 56kd form of AEP (R&D

Systems, Minneapolis, US, Catalogue no. MAB2199). The standards,

samples and controls were all diluted in ELISA General Buffer (AbD Serotech,

Oxford, UK, Catalogue no BUF037A) but the samples and control additionally

contained a mixture of a proprietary cell lysis buffer (CellLyticM, Sigma-Aldrich,

Dorset, UK. Catalogue no C2978) and protease inhibitor cocktail. The

detection system consisted of biotinylated polyclonal goat anti-human AEP

antibody (BAF2199), Streptavidin-Horse radish peroxide enzyme and a 1-

StepTM Turbo TMB (3,3’,5,5’-tetramethylbenzidine) chromogenic ELISA

substrate (Thermo Scientific, Rockford, USA). The reaction was stopped after

30 minutes of adding substrate by adding 100ul of 2N H2SO4 stopping buffer

and the absorbance from each well measured at 450 nm using a FLUOstar

OMEGA plate reader. Figure 3.11 summarises the performance of this assay.

The assay was linear when recombinant AEP protein was use to generate the

standard curve. However in order to get a readout from and AEP expressing

SD1 cell line, at least 50μg cell lysate protein had to be loaded per well,

requiring around 108 cells. This was not practically feasible for clinical

samples. Additionally there was >25% variation in the expression of AEP

protein in SD1 cell lystates at this concentration, figure 3.12 A and B. To rule

out other problems besides poor sensitivity of the assay for measuring AEP in

cell lines, a single experiment was performed where I loaded upto 200μg of

SD1 protein lysates. This showed that the assay gave readout only at a higher

protein concentration (Figure 3.12 C).


75

Figure 3.11 Performance of the 1st generation AEP ELISA. A= the linearity of

the assay B= precision and the limit of detection of the assay.

Intra-assay variation: error bars=1SD Inter-assay variation: error bars=1SEDM

R2 = 0.9957

0

0.1

0.2

0.3

0.4

0.5

0.6

0 5 10 15 20

Recombinant AEP ( ng/ml)

OD

va

lue

OD

va

lue

R2 = 0.9916

0

0.1

0.2

0.3

0.4

0.5

0.6

0 5 10 15 200

0 5 10 15 20


Concentration of the analyte(ng/ml) SEM SEDM

Recombinant AEP 1 2 3

20 0.584 0.535 0.615 0.040 0.023

10 0.356 0.315 0.388 0.037 0.021

5 0.211 0.153 0.232 0.041 0.024

2.5 0.117 0.103 0.126 0.012 0.007

1.25 0.074 0.059 0.079 0.011 0.006

0.625 0.057 0.045 0.062 0.009 0.005

0.3125 0.044 0.036 0.042 0.004 0.002

0 0.042 0.036 0.045 0.004 0.002

Inter assay variation

Optical density values

Limit of detction: Intra assay variation

Concentration of the analyte(ng/ml) Mean SD


20 0.553 0.516 0.535 0.535 0.018

10 0.309 0.321 0.315 0.315 0.006

5 0.145 0.160 0.153 0.153 0.008

2.5 0.103 0.103 0.103 0.103 0.000

1.25 0.058 0.059 0.059 0.059 0.001

0.625 0.047 0.043 0.045 0.045 0.002

0.3125 0.037 0.036 0.036 0.036 0.001

0 0.040 0.033 0.037 0.037 0.004

Optical density values

Linearity and intra assay variation

0.044 OD value0.503 ng/ml

Method 1= 3.3xSD(blank)/slope Method 2= LOB+1.645SD(low conc)

A

B


76

Figure 3.12 Quantification of AEP in SD1 cells by 1st generation AEP ELISA.

A, B and C essentially showing that the first generation assay required at least

50μg of SD1 cell lysates protein to get a readout and there was a wide

variation (CV of >10%) in AEP measurement in SD1 cells if lower (50μg)

amount protein lysates was loaded per well of the ELISA plate.

10

0

1

2

3

4

5

6

7

8

9

SD1 50μgmSD1 100μgmSD1 200μgm

0

0.5

1

1.5

0

0.5

1

1.5

AE

P (

ng

/ml)

SD1 50μgm

CV = 24.8%

AE

P (

ng

/ml)

A

B

C

SUPB15 50μgmREH 50μgm

SD1 50ug lysate Mean SE SEM CV (%)1 2 3 4

ng/ml 0.78 1.03 0.96 1.40 1.05 0.26 0.13 24.75

Days


77

3.3.1.2 2nd generation assay To address the issue of poor sensitivity of the

assay, in the first instance, the capture antibody, MAB2199 was replaced with

a mouse monoclonal anti human AEP antibody, MAB21992 (R&D systems).

This new antibody captured both the immature (56kd) and the mature (36kd)

forms of AEP. Additionally, the commercial cell lysis buffer (Cell LyticM,

Sigma Dorset, UK) was replaced with an in-house NP40 buffer as the

commercial buffer interfered with the assay, figure 3.13 A and B. These

interventions however, failed to improve the detection limit of the assay.


78

Figure 3.13: Optimisation of capture antibody of the 2nd Generation AEP

ELISA. A: Immunoprecipation (IP) experiment to show that MAB21992 (R&D

Systems) used as a capture antibody in ELISA detects both mature and the

immature forms of AEP. 1st three lanes from left to right represent SDS PAGE

of immunoprecipitate of REH cell lines transduced with AEP (AEP+REH).

Lane 1, 2 and 3 represent antibody combinations used in ELISA, standard in-

house antibodies for AEP IP optimized in the laboratory and negative control

respectively. AF21992 (R&D Systems) is a polyclonal goat anti human AEP

antibody. B: Inhibition of the assay when recombinant AEP standards

contained CelLytic M (CLM) but not the same with NP40 based lysis buffer.

MAB21992 AF2199 Mouse IgG -----Pull down Antibody

Recognising antibody

IP (REH transduced with AEP) Immunoblot (SD1)

AF2199 AF2199 AF2199 AF2199

Detecting antibody - goat antibody Donkey anti-Goat

56 kDa

36 kDa

-----

True blot anti- -

0

0.1

0.2

0.3

0.4

5 10

AEP

AEP+PI

AEP+CLM LB

AEP+PI+LB CLM LB


OD

valu

e

0

0.1

0.2

0.3

2.5 5 10

AEP+PI+ NP40 LB

AEP

OD

valu

e


0

0.1

0.2

0.3

2.5 5 10

AEP+PI+ NP40 LB

AEP

OD

valu

e


A

B

(Precursor form)

(Mature form)


79

Each individual steps of the 2nd generation assay were optimised by

performing grid experiments in a 96 well format that interrogated variables at

each step of the assay appendix 5. Performance of the optimised 2nd

generation absorbance assay is summarised in figure 3.14 & 3.15.

Figure 3.14 A Linear range (A) and intra-assay variation (B) of the 2nd

generation AEP ELISA.

Concentration of analyte (ng/ml)

Mean SDRecombinant AEP

1 2 3 4

2.5 0.852 0.825 0.819 0.763 0.815 0.037

2 0.710 0.666 0.727 0.723 0.707 0.028

1.25 0.530 0.510 0.542 0.551 0.533 0.018

1 0.454 0.461 0.443 0.412 0.443 0.022

0.625 0.338 0.344 0.348 0.341 0.343 0.004

0.5 0.301 0.307 0.321 0.304 0.308 0.009

0.3125 0.242 0.257 0.214 0.250 0.241 0.019

0.25 0.265 0.223 0.249 0.237 0.244 0.018

0.15625 0.213 0.213 0.227 0.229 0.221 0.009

0.125 0.205 0.204 0.208 0.214 0.208 0.005

0 0.176 0.161 0.164 0.178 0.170 0.008

Optical density Values

Linearity and intra assay Variation of 2nd

generation assay

Limit of detection

Method 1= 3.3xSD(blank)/slope Method 2= LOB+1.645SD(low conc)

0.191 OD value0.106 ng/ml

y = 0.2625x + 0.1766

R2

= 0.9966

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 0.5 1 1.5 2 2.5

OD

valu

e

Recombinant AEP (

y = 0.2625x + 0.1766

R2

= 0.9966

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 0.5 1 1.5 2 2.5

Recombinant AEP (ng/ml)

A

B


80

Figure 3.15: Quantification of AEP in SD1 cells using a 2nd generation AEP

ELISA. The assay could be detected using as little as 12.5μg of SD1 protein

lysates. The figure also demonstrates the appropriateness of the antibody

combinations using in the assay. * represent p=<0.05 and ** represents

p=<0.005. Error bars represent ± 1 SE.

This assay still had one flaw in that it had a high background, figure 3.14.

Attempts to reduce the background were invariably associated with a

reduction in detection limit of the assay. Hence the assay was redesigned into

a 3rd generation chemiluminescent assay.

3.3.1.3 3rd generation assay: The detection system of the assay was changed

to measure end point luminescence instead of absorbance. Performance of

this assay is summarized in figure 3.16

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Row A= Capture Antibody

Row B= Detection Antibody

MAB21992 MAB21992 MAB21992 Mouse -

BAF2199 BAF 2199 BAF2199 BAF2199

IgG

SD1

50 μg

SD1

50 μg

SD1

50 μg

SD1

50 μg

SD1

50 μg

SD1

-

- -

-MAB21992

BAF2199

SD1

25 μg

MAB21992

BAF2199

SD1

12.5 μg

*

* *

*A

EP

(ng/m

l)

A

B


81

Figure 3.16 3rd Generation AEP ELISA. A: Linear range of the assay using the

recombinant protein on the left and in REH cell line transduced with AEP

(REH+AEP), courtesy Dr Alexander. B: Inter-assay variation and the limit of

0

1

2

3

4

5

6

7

8

SD

1 1

0µ

g

RE

H 1

0µ

g

SU

P B

15

10µ

g

SD

1 A

EP

KD

10µ

g

AE

P+

RE

H1µ

g

AE

P+

RE

H 0

.1µ

g

AE

P (

ng/μ

g o

f p

rote

in)

* * *

*

* *

* * *

**

* * *

56 kDa

36 kDa

GAPDH

SD

1 1

0 μ

g

RE

H 1

0 μ

g

SU

P B

15

10

μg

SD

1 K

O 1

0 μ

g

AE

P+

RE

H 1

μg

D

Concentration of analyte (ng/ml) Mean SD


20 21768 22711 21925 22135 505

10 10559 10441 9988 10329 301

5 5141 5137 5028 5102 64

2.5 2618 2537 2683 2613 73

1.25 1605 1654 1552 1604 51

0.625 1049 1014 1028 1030 17

0.3125 858 932 865 885 40

0.15625 789 635 745 723 79

0 644 549 655 616 58

Optical density Values

Linearity and intra assay Variation of 3rd

generation assay

Method 1= 3.3xSD(blank)/slope Method 2= LOB+1.645SD(low conc )

842 RLU0.179 ng/ml

Limit of detection of the 3rd

generation assay

R2= 0.9968

0

5000

10000

15000

20000

25000

5 10 15 20

Recombinant AEP ng/ml

Re

lative

lig

ht u

nits (

RL

U)

R2= 0.9995

0

10000

20000

30000

40000

50000

60000

0.1 0.2 0.3 0.4 0.5REH +AEP cell lysate μg/well

Re

lative

lig

ht u

nits (

RL

U)

B

C

A


82

detection of the assay. C: AEP expression in ng/ml in cell lines using the 3rd

generation ELISA. SD1 AEP KD represents SD1 with a stable transcript

depletion of AEP using a lentiviral shRNA. * represents p= <0.05, **

represents p=<0.005 and *** represents p=<0.0005. Error bars represent ± 1

SE. D: expression of AEP in cell lines by western blotting.

3.4 QUANTIFYING ACTIVE AEP: The inactive AEP zymogen undergoes an

N and C terminal proteolytic cleavage to yield a mature active form, figure

3.17 A. None of the previously described techniques measure specifically the

active (46 and 36 kd) forms of AEP and the ELISA assay does not estimate

the expression of AEP across sub-populations of cells within the same sample.

Flow-cytometry based technique using cell permeable fluorescent labelled

AEP probe (LP-1) (106) had a potential to measure both these parameters

that ELISA could not. Such a technique if developed successfully would be

easy to use, and could be rapidly integrated in clinical practice. The LP-1

probe binds to active AEP Figure 3.17B.

ImageStream (multispectral image flow cytometer) results showed that active

AEP (red) co-localised to lysosomes in SD1 cells, figure 3.18. This was

consistent to previously published finding seen on formalin-fixed cytospins of

SD1 cells(100). Majority (71.5%) of SD1 cells expressed active AEP

compared to REH (4%, data not shown) and there was a skew towards right

of AEP expression in sub-population of SD1 cells, figure 3.19


83

Figure 3.17 Basis of action of LP-1 probe A: The 56 kd zymogen undergoes a

sequential N and C terminal cleavage that is pH dependent to lead to the

46kd intermediate form. The exact mechanism by which this form is further

processed to the mature and 36kd form is unknown. B: Cartoon to describe

the chemistry and specificity of the LP1 probe (Courtesy Dr. Shekhar

Krishnan).

Pre-pro AEP 56kDa

Intermediate

Forms 46 kDa

Mature AEP 36kDa

lysosome

↓pH

Other

proteases

N - ter

AA24D N

297 110

C - ter

Endo lysosomes

Prepro AEP

Mature active AEP

Fluorophore

Aliphatic spacer sequence – influences

cell permeability

Proline residue – stabilises

substrate/enzyme interaction

Azaepoxy-ASN residue –

determines reactivity & specificityCell

membrane

A

B


84

Figure 3.18 Localisation of active AEP in SD1 cells. SD1 cells were dually labelled with LysoTracker® green DND-26 and LP1

probe followed by image acquisition in ImageSteam in 1) bright field, 2) 502nm filter that detects lysosomes stained with

LysoTracker® green DND-26, 3) 633nm filter that detects LP1 probe and finally 4) merged image that shows co-localization of AEP

within the SD1 lysosomes. Courtesy Jeff Barry & Morgan Blaylock.

Selected images

Bright field Overlay Lysotracker green AEP probe Merged

Ch01 br/ch2/ch5 Ch02 Ch05 Ch02/Ch05

37396


36145


28565


29753


85

Figure 3.19 Expression of active AEP by Flow cytometry/Image stream. Tandem flow cytometry acquisition of mean fluorescent

intensity in SD1 cells incubated with LP-1 probe along with single cell imaging showing variable expression of AEP within

subpopulation of SD1 cells.

Intensity_MC_Ch05

Expression of Active AEP Flow Cytometry/Image stream

0-1e3 1e3-1e4 1e5-1e5 1e61e4

0

6

8

4

10

2

Norm

alise

d F

req

ue

ncy

71.54% are positive (4.00% Positive REH)

Majority are weakly fluorescent but with a skew to the right

SD1 AEP

Dim

boosted intensity

Centre

boosted intensity

Bright

Ch01 Ch05 Ch01/Ch05

375

Ch01 Ch05 Ch01/Ch05

66

Ch01 Ch05 Ch01/Ch05

8589


86

Protein electrophoresis of cell lysate of in-vivo labelled cells confirmed that the

probe binds only to the mature (36kd) and intermediate (41kd) forms of AEP,

figure 3.20 A. However, there was no difference in intensity of the AEP band

between SD1 and SD1AEPkd. Live cell labelling with LP1 followed by

measurement of mean fluorescence intensity on flow cytometry also showed

no difference between SD1 and SD1AEPkd cell lines, figure 3.20 B. SD1AEPkd

had less AEP protein compared to SD1 cell by immunoblotting, figure 3.20 C

and by ELISA, figure 3.20 D. However there was still enough AEP protein by

ELISA in 1 million SD1AEPkd cells for the probe to bind unlike in 1 million REH

cells. Additionally there is no difference in the mean fluorescence between

SD1 and REH+AEP despite the latter having greater than 10 times AEP protein

than the former. Thus either the kinetics of the binding of LP1 to active AEP is

not linear or there is saturation of fluorescence. Either way, the LP1 probe is

currently not suitable to quantify AEP in clinical samples.

Though the expression of AEP correlate at the level of transcript and protein

in case of cell lines, there was no correlation in the expression of AEP by

these two techniques in clinical samples (n=16), figure 3.21.


87

Figure 3.20 Suitability of LP1 probe to measure active AEP. A: Protein lysates

were first labelled with LP1 probe following which AEP was

immunopreciptated as described in chapter 2 and subjected to

electrophoresis and visualisation of the bands on LICOR system. It confirms

that the LP1 probe bind to the intermediate and mature (active) forms of the

B Live cell labelling by AEP probe followed by

Flow cytometry

C AEP Western blot cell lysates: 10μg protein per lane except for REH+AEP(0.1 μg )

A Immunoprecipitation of 1 million cell lysates labelled

with AEP probe

SD1REHSD1AEPkdREH+AEP

36 kd

46 kd

0

5000

10000

15000

20000

25000

30000

35000

Rela

tive

Lig

ht

Units

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

Re

lative

Lig

ht

Un

its

Media

n F

luore

scent In

tensity

100

150

200

250

300

350

400

450

SD1 REH SD1AEPkd

D AEP ELISA cell lysates: 10μg protein per laneexcept for REH+AEP(0.1 μg )

SD1 REH SD1AEPkd REH+AEP

E One million cells labelled with AEP probe in-vivofollowed by AEP ELISA of cell lysate

SD1 REH SD1AEPkd REH+AEP

Marker

56kd

GAPDH

36 kd

SD1 REH SUPB15 SD1AEPkdREH+AEP


88

AEP protein. B: Flow cytometry of live cells labelled with LP-1 probe showed a

difference in the mean fluorescent intensity between SD1 (AEP expressing

cell line) and REH (AEP non expressing cell line). However there was no

difference in the mean fluorescent intensity between SD1 and SD1AEPkd cells.

C: AEP expression by immunoblotting in the 4 cell lines. Compared to SD1,

SUPB15 shows intermediate and REH shows no expression of AEP whilst

REH+AEP has much greater amount of AEP. Note total protein loaded in the

lane for the REH+AEP lysates was 1/10th of the quantity loaded in lanes of other

cell lines. D: AEP expression in the four cell lines by ELISA. Results mirror

those obtained by immunoblotting. E: One million cells that were labelled live

with LP-1 probe followed by cell lysis and quantification of AEP from 1 million

cell lysates protein by ELISA.

Figure 3.21: Co-relation of expression of AEP at transcript and protein level.

Sixteen samples were selected based on the differences in the expression of

AEP at the level of transcript by TaqMan gene expression assay, X axis. Cell

lysates of these samples were used to measure the expression of AEP at the

level of protein by chemiluminescent ELISA, y axis. There was poor co-

relation of expression of AEP between the two assays (R2=0.2236).

R2= 0.2236

500

0 2 4 6 8 10 12 148

Pg o

f A

EP

/100

μg o

f p

rote

in 400

300

200

100

∆ CT

Value

n=16

R2= 0.2236

500

0 2 4 6 8 10 12 148

Pg o

f A

EP

/100

μg o

f p

rote

in 400

300

200

100

∆ CT

Value

n=16


89

3.5 Summary of assays tested for AEP expression:

1) In cell lines, there was a correlation between AEP expression at the

level of transcript by RQ-RTPCR and at the level of protein by western

blotting and by ELISA.

2) Of these techniques, RQ-RTPCR and ELISA could be used to quantify

AEP.

3) In clinical samples there was poor correlation of expression of AEP

between RQ-RTPCR and ELISA.

4) The only technique that quantifies active AEP is the one using the LP-1

probe but then this technique was not suitable for use in clinical

samples.

In the end, AEP ELISA was taken forward as it measured AEP at a protein

level, accepting the limitation that it measured total AEP and could not

specifically measure the active AEP.

Asparaginase Study: L-Asparaginase activity

90

Chapter 4 Asparaginase Study: L-Asparaginase activity

______________________________________________________________

4.1 BACKGROUND

Clinical trials over three decades have established a clear role for the anti-

leukaemic drug L-Asparaginase (ASNase) in childhood ALL (32, 63-70).

ASNase is an enzyme and its optimal action requires precise dosing to

achieve a consistent therapeutic level of enzymatic activity. Despite this, the

clinical practice of employing ASNase in childhood ALL varies in terms of the

type of preparation of the drug used its dose, the route of administration and

the schedule (Table 4.1) (32, 76, 89, 97, 111-120). As described in the

introduction, the PEG-ASNase offers a more stable pharmacokinetic profile

than the native product. The UK was one of the first countries in the world to

routinely use E.coli ASNase conjugated to polyethylene glycol (PEG-ASNase)

during both induction and post induction phases of the UKALL2003 trial and

ALLR3 protocols (Table 4.1).

Though the drug has been in routine clinical use for over 4 decades, little is

known about the mechanisms by which it is degraded and inactivated. The

enzyme is a bacterial protein. First-pass kinetics suggests that the drug is

possibly eliminated by the reticulo-endothelial system (78). Another method of

inactivation is due to the development of antibodies. Within this mechanism

lies a spectrum from anaphylaxis (IgE or IG4 mediated) to silent inactivation

which is presumably IgG mediated. Work done previously by our group

showed that a dyad of lysosomal cysteine proteases, Asparaginyl

Endopeptidase (AEP) and Cathepsin B (CTSB) expressed in leukaemic blasts,

degraded ASNase in-vitro (100). AEP was additionally over expressed in a

subset of children with precursor B ALL predominantly with poor risk

cytogenetic features (101). We showed that while CTSB cleavage was non-

specific, AEP cleavage inactivated the drug while retaining intact known

antigenic sites. As reticulo-endothelial cells are enriched in lysosomal

proteases, this observation supports the previous conjecture of how ASNase


91

Pro

toco

lR

isk g

roup

Schedule

Ris

k g

roup

Phase

Schedule

AIE

OP

-ALL-9

5A

llL-A

spara

gin

ase: 5,0

00 IU

/m2

IM e

very

72 h

ours

; 8 d

oses

All

a)

Rein

duction

pro

tocol II

L-A

spara

gin

ase: 10,0

00 I

U/m

2IM

every

72 h

ours

; 4 d

oses

CC

G1962

SR

PE

G-A

spara

gin

ase 2

500 IU

/m2

IM s

ingle

dose

SR

a)

Dela

yed Inte

nsific

ation

PE

G-A

spara

gin

ase 2

500 IU

/m2

IM s

ingle

dose

vs

vs

L-A

spara

gin

ase: 6,0

00 IU

/m2

IM 3

tim

e a

week;

9 d

oses

L-A

spara

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L-A

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tandard

thera

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I L-A

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6 d

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vs

Incre

ased inte

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Descri

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a)

Consolidation

PE

G-A

spara

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500 IU

/m2

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weeks a

part

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Inte

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Main

tenance

PE

G-A

spara

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500 IU

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IM tw

o d

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weeks a

part

c)

DI

PE

G-A

spara

gin

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500 IU

/m2

IM s

ingle

dose

d)

Reconsolid

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PE

G-A

spara

gin

ase 2

500 IU

/m2

IM s

ingle

dose

ALL-B

FM

95

All

L-A

spara

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ase: 5,0

00 IU

/m2

IV 3

tim

e a

week;

8 d

oses

SR

/MR

a)

Rein

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L-A

spara

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00 I

U/m

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every

72 h

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; 4 d

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PE

G-A

spara

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000 o

r 2

500 IU

/m2

IV s

ingle

dose

HR

a)

Inte

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onsolid

ation

L-A

spara

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ase: 25,0

00 I

U/m

2IV

once p

er

blo

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6 b

locks

b)

Rein

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L-A

spara

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ase: 10,0

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U/m

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every

72 h

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; 4 d

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or

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G-A

spara

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Po

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Ind

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Ta

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4.1


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Pro

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Schedule

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Po

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Ind

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Ind

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ALL-B

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2000

All

L-A

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/m2

IV 3

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8 d

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SR

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No f

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ase: 45,0

00 I

U/m

2IV

day 8

0P

EG

-Aspara

gin

ase:

2500 I

U/m

2IV

HR

days 3

2,4

6 a

nd 8

7L-A

spara

gin

ase: 45,0

00 I

U/m

2IV

day 1

08

PE

G-A

spara

gin

ase:

2500 I

U/m

2IV

Ta

ble

4.1

co

nti

nu

ed


93

Pro

toco

lR

isk g

roup

Schedule

Ris

k g

roup

Phase

Schedule

2

Po

st

Ind

ucti

on

Ind

ucti

on

DF

CI

91-0

1A

ll N

o A

spara

gin

ase

All

a)

Inte

nsific

ation

L-A

spara

gin

ase: 25000 IU

/mIM

every

fort

nig

ht, 1

5 d

oses

random

isation

or

PE

G-A

spara

gin

ase:

2500 I

U/m

2IM

every

week,

30 d

oses

NO

PH

O

ALL-2

000

All

L-A

spara

gin

ase: 6,5

00 IU

every

3-4

days; 4 d

oses

All

a)

DI

L-A

spara

gin

ase:6

,500 I

U e

very

3-4

days;

4 d

oses

Tota

l T

hera

py

XIV

All

L-A

spara

gin

ase:1

0,0

00 U

/m2

IM 3

X w

eek;

9 d

oses

All

a)

Rein

duction

PE

G-A

spara

gin

ase:

2500 U

/m2

IM e

very

week f

or

2 w

eeks

UK

ALL2003

All

PE

G-A

spara

gin

ase:

1000 I

U/m

2IM

, fo

rtnig

htly; 2 d

oses

SR

/IR

a)

1 v

s2 D

I ra

ndom

isation

PE

G-A

spara

gin

ase:

1000 I

U/m

2IM

once

HR

a)

Aug B

FM

consolid

ation

PE

G-A

spara

gin

ase:

1000 I

U/m

2IM

; tw

o d

oses

b)

ICM

IP

EG

-Aspara

gin

ase:

1000 I

U/m

2IM

; tw

o d

oses

c)

DI I

PE

G-A

spara

gin

ase:

1000 I

U/m

2IM

; tw

o d

oses

d)

ICM

II

PE

G-A

spara

gin

ase:

1000 I

U/m

2IM

; tw

o d

oses

e)

DI II

PE

G-A

spara

gin

ase:

1000 I

U/m

2IM

; tw

o d

oses

Ta

ble

4.1

co

nti

nu

ed

SR

= S

tan

da

rd R

isk

IR

=

In

term

ed

iate

Ris

k

MR

=

Me

diu

m R

isk

HR

=

Hig

h R

isk

RE

R

=

Ra

pid

Earl

y R

espo

nse

SE

R

=

Slo

w E

arl

y R

esp

on

se

DI

= D

ela

yed

In

ten

sific

atio

n

Au

g B

FM

=

Au

gm

en

ted

BF

M

ICM

=

In

teri

m C

ap

izziM

ain

ten

an

ce


94

is eliminated by the body. However the selective expression by leukaemic

blasts suggested that this could also be a novel mechanism for drug

resistance. Thus the proteases could lead to early direct inactivation of the

drug by proteolytic activity or late inactivation related to antigen processing

and antibody formation.

This chapter reports on the results of the Asparaginase Study in ALL2003 and

ALLR3. This was a prospective, observational study measuring trough

ASNase activity levels in children receiving PEG-ASNase and correlation with

lymphoblast expression of AEP and CTSB. Patients were recruited, after

consent, from two national trials in childhood ALL: the frontline UKALL2003

and the relapsed ALLR3 trial.

4.1.1 Aims of the Asparaginase Study

1) Evaluate the ASNase activity in newly diagnosed and relapsed patients

receiving 1000 u/m2 of PEG-Asnase

2) To provide recommendations on whether routine pharmacokinetic assay

after PEG-ASNase is required or not in clinical practice and if so, which

subgroup of patients are most likely to benefit from such strategy.

3) To determine whether the expression of AEP and CTSB by lymphoblasts

are predict response to PEG-ASNase.

4) To study the clinical impact of sub-therapeutic response to PEG-ASNase

during the induction and post induction phases.

4.1.2 Objectives of the Asparaginase Study

1) To measure serially ASNase activity during the induction and post induction

phases in order to determine the pattern of drug activity.


95

2) To correlate plasma ASNase activity during induction with

a) Baseline biological characteristics such as age, presenting white cell count,

cytogenetics, immunophenotype and the expression of AEP and CTSB

b) Outcome variables such as early response to therapy and the burden of

disease at a molecular level at the end of induction.

3) To correlate plasma ASNase activity during post induction phase with the

development of clinical hypersensitivity or silent neutralising antibodies to

ASNase.

4.1.3 Design of the Asparaginase Study

Figure 4.1 shows the schedule of PEG-ASNase, the sampling time points for

each of the assay done in this study and an overview of the sample

processing. Figure 4.2 gives an overview of the statistical methods used for

correlating the analytical variables such as expression of AEP and CTSB in

leuakemic cells, development of antibodies to PEG-ASNase and native E.coli

Asparginase and ASNase activity levels with outcome variables such as early

response and MRD at the end of induction and with baseline characteristics

such as National Cancer Institute risk category, gender, cytogenetics and

immunophenotype. Data on the baseline variables, outcome variables, patient

characteristics and toxicity to PEG-ASNase was kindly provided by the

Professor Anthony Moorman (Cytogenetics), Dr Jeremy Hancock (MRD) and

Dr Sue Richards and Rachel Wade from the Clinical Trials Office (all the rest

of the data) which also provided the support for the statistical analysis of the

data.


96

Figure 4.1 Schedule of L-Asparginase the sample time points for measuring

ASNase activity in UKALL2003 (A), ALLR3 (B) and an overview of the sample

processing and the assays done at each time point in the Asparaginase Study

Regimen A

Weeks:1 6 9 17 24 32 25 -164 ( 1DI)/ 39 -164 (2 DI)

Weeks:1 6 11 19 26 34 26 -164 ( 1DI)/ 41-166 (2 DI)

Regimen B

Weeks: 1 6 15 23 31 39 47 170

= Subject to randomisation

PEG ASNase

Regimen C

DI 1IM 1 MaintenanceConsolidation

d4 d4 d4

Induction DI 1IM 1 Maintenance

d4 d4 d4

Induction IM 2DI 1 DI 2IM 1 Maintenance

d4 d4 d4

Induction IM 2DI 1 DI 2IM 1 MaintenanceStd. BFM Consolidation

d4 d4 d4d18

Induction ICM 2DI 1 DI 2ICM 1 Maintenance

d16 d3d4 d18 d44 d4 d43 d3 d4 d43

Induction ICM 2DI 1 DI 2ICM 1 MaintenanceAug BFM Consolidation

d16 d3d4 d18 d44 d23 d4 d43 d3 d23 d4 d43

L-Asparaginase activity

A: UKALL2003

C: Overview of assay time points

L-Asparaginase Activity &Anti L-Asparaginase Antibody

L-Asparaginase Activity

Anti L-Asparaginase AntibodyFinal sample:

blood

mRNA

Proteins

RQ -RTPCR: AEP

ELISA: AEP, CTSBDiagnosis

Sample:

Blood & bone

marrow

Serial follow up

Samples: blood

Leukaemic cells

Blood plasma

d4d18

(at baseline in selected patients)

B:ALLR3

Phase I

Allo-SCT

SR

HR

Phase IV

<10-3

≥10-3

IR

Phase III Phase VI

1 5

6 9 13

RT* Phase V

14 30 104

Weeks

MRD <10-4

MRD >10-4

Phase I Phase II

Phase IIIPhase IIPhase I

Weeks 1

Weeks 1

4 5 1011 15

d18d15

d3;

w6

d3;

w7d3;

w9

MRD

IM 2 DI 2IM 2 DI 2

d2,4

w11

d2,4

w12d2

w14

d18d3 d18d17

d18d3 d18d17

d2

w6

d2,4

w9

d2,4

w10d2

w12

Erwinase

L-Asparaginase activity on any one occasion 24 hr after Erwinase


97

(C). Aug= Augmented, Std= Standard, IM= interim maintenance, DI= delayed

intensification, ICM= interim Capizzi maintenance,

.

Figure 4.2 Overview of the statistical methods used to analyse the results.

4.1.4 Recruitment in the Asparaginase Study: A pilot for sample collection

and for the development of standard operating procedure (SOPs) for sample

processing and storage was opened in December 2007. The study was then

opened to limited centres in May 2008 and then to all paediatric haematology

centres in the UK in September 2008. After doing an initial trial run in the last

quarter of 2008, the study opened to 19 of the 22 paediatric oncology and 8

adult oncology centres in the UK from January 2009. At the point of censoring

February 2011, the study had recruited a total of 593 patients in the

UKALL2003 and 25 patients in ALLR3 studies. The study had to be stopped

because the ALL2003 trial closed and the opening of ALL2011 trial was

delayed Applying the criteria of analysing only those samples that were taken

between 7 and 14 days post PEG-ASNase results are available for 427

patients in the UKALL2003 trial and 22 patients in the ALLR3 trial.

Statistical Analysis

AEP & CTSB

Analytical variables

L-Asparaginase activity

Outcome variables

•Early response (1-2 weeks

Slow/Rapid

•MRD (5 weeks):

Low/Intermediate/High

Baseline Characteristics

•Gender

•National Cancer Institute Risk Category

•Cytogenetics

•Immunophenotype (precursor B or non precursor B)

Anti L-Asparaginase

antibodies

Mann-Whitney Test

Mann-Whitney Test

Mann-Whitney Test for Early Response

Kruskal-Wallis Test for MRD

Chi squared test

Chi squared test

Mann-Whitney Test


98

4.2 RESULTS:

The results of the Asparaginase study have been split into two chapters for

ease of reading. The bulk of the work presented in this chapter pertains to the

results and analysis of ASNase activity in 427 patients recruited from the

UKALL2003 trial. The next chapter investigates the biological determinants of

therapeutic response to ASNase.

4.2.1 RECRUITMENT IN UKALL2003 ARM OF THE ASPARAGINASE

STUDY

The study recruited 77% of the target population. Figure 4.3 is a graphical

representation of the recruitment of patients between January 2009 and

February 2011 when the study was fully opened to all the centres

Figure 4.3: Recruitment in the Asparaginase Study- UKALL2003 arm.

Magenta and green colours respectively represent the number of new cases

of ALL diagnosed each month at the participating centres and the number of

cases recruited in the Asparaginase Study. Courtesy Dr Catriona Parker.

UKALL2003: Asparaginase Study Recruitment

0

5

10

15

20

25

30

35

Jan

Feb

Ma

r

Ap

r

Ma

y

Jun

Ju

l

Au

g

Sep

Oct

Nov

Dec

Jan

Feb

Ma

r

Ap

r

Ma

y

Jun

Ju

l

Au

g

Sep

Oct

Nov

Dec

Jan

Feb

2009 2010 2011

Num

be

r o

f P

atien

ts

UKALL2003: Asparaginase Study Recruitment

0

5

10

15

20

25

30

35

Jan

Feb

Ma

r

Ap

r

Ma

y

Jun

Ju

l

Au

g

Sep

Oct

Nov

Dec

Jan

Feb

Ma

r

Ap

r

Ma

y

Jun

Ju

l

Au

g

Sep

Oct

Nov

Dec

Jan

Feb

2009 2010 2011

Num

be

r o

f P

atien

ts


99

4.2.1.1 Patient characteristics

As shown in table 4.2 the baseline biological and demographic characteristics

of the patients and the response to induction treatment of patients in the

Asparaginase Study.

Table 4.2 Patient characteristics Characteristics

In Asp Study

n=427

Gender

256 (59.9%)Male

Female 171 (40.1%)

Age (years)

296 (69.3%)

161 (30.7%)

3.2

5.4

11.3

<10

>10

25th

percentile

Median

75th

percentile

Range 1.2 to 23.5

White cell count (x10 9/L)

323 (75.6%)

104 (24.4%)

5.1

14.7

47.1

<50

>50

25th

percentile

Median

75th

percentile

Range 0.5 to 800

Immunophenotype

368 (86.4%)B cell

Non B cell ( T=58; null=1) 59 (15.4%)

Cytogenetic classification of B; n=368

(Moorman et al Lancet Oncology, 2010)

196 (53.4%)

120 (32.5%)

24 (6.5%)

good

intermediate

poor

no result 28 (7.6%)

Regimen at diagnosis

234 (54.8%)A

B 193 (45.5%)

Early Response to therapy

46 (10.8%)slow

rapid 381 (91.2%)

MRD response

95 (22.2%)

172 (40.3%)

low

intermediate

high 160 (37.5%)

Table 4.2Not In Asp

Study n=2705

1521 (56.2%)

1184 (43.8%)

1992 (73.6%)

713 (26.4%)

p value

(heterogeneity)

0.1

0.3

0.4

0.7

2119 (78.3%)

589 (21.7%)

2319 (85.7%)

381 (14.3%)

N.A

N.A

N.A

N.A


100

4.2.1.2 ASNase activity at individual time points ASNase activity was

measured in 1074 samples from 427 patients at 6 time points during the

course of therapy. The median number of sample time points per patient was

2.5 (Range: 1-6). Figure 4.4 shows the distribution of activity results in box

and whisker plots at each of the six time points.

Figure 4.4: ASNase activity at individual time points. The box encompasses

ranges between the 1st and 3rd quartiles (Inter-quartile range-IQR; 25th-75th

percentiles). The horizontal bar represents the median value, the lower

whisker represents minimum value, the upper whisker represents maximum

value that lies within 1.5 x IQR of the upper quartile. Outliers (beyond the

2000

1500

1000

500

0

Pla

sm

a L

-Aspara

gin

ase A

ctivity U

/L

TP 6

n=96

TP 5

n=39TP 4

n=206TP 3

n=54

TP 2

n=354

TP 1

n=325

ALL TP

n=1074

Time point (TP)

TP1: 7-14 days post induction day 4 PEG-ASNase 91

TP2: 7-14 days post induction day 18 PEG-ASNase 85

TP3: 7-14 days post Capizzi I day 23 PEG-ASNase 83

TP4: 7-14 days post DI I day 4 PEG-ASNase 96

TP5: 7-14 days post Capizzi II day 23 PEG-ASNase 87

TP6: 7-14 days post DI II day 4 PEG-ASNase 97

% with adequate activity

Overall 90


101

upper whisker) are represented by circles (≤ 3 x IQR of the upper quartile and

the asterisk (> 3 x IQR of the upper quartile). The dotted horizontal line

represents cut off for adequate plasma ASNase activity of 100 U/L.

Conclusion 1 – From a trial perspective 85-97% of patients have adequate

trough activity at any time point.

Table 4.3 shows the median activity in those who have adequate ASNase

activity at TP1 and or TP2 and those who don’t. Most patients with inadequate

levels have levels below the level of detection of the assay and much below

the therapeutic threshold. Conversely, most patients with adequate activity

had levels that were well above the therapeutic threshold. Thus increasing the

dose of PEG-ASNase is unlikely to benefit those with inadequate levels and is

likely to increase toxicity for the majority who already have high levels.

Table 4.3 Median ASNase activity levels.

Conclusion 2 - Increasing the dose to 2,500 – 3,500 U/m2 is unlikely to

improve the percentage of patients who will have adequate levels and is likely

to lead to increased toxicity.

Inadequate activityTime point (TP)

TP1: 7-14 days post induction day 4 PEG-ASNase

TP2: 7-14 days post induction day 18 PEG-ASNase

TP3: 7-14 days post Capizzi I day 23 PEG-ASNase

TP4: 7-14 days post DI I day 4 PEG-ASNase

TP5: 7-14 days post Capizzi II day 23 PEG-ASNase

TP6: 7-14 days post DI II day 4 PEG-ASNase

Median level U/L

Adequate activity

Median level U/L

45

Below LOD*

278

349

1027

387

547

687

Table 4.3 L-Asparaginase activity levels in patients split into two group: Those with adequate

and those with inadequate L-Asparaginase activity levels.

LOD*= limit of detection of the assay

Below LOD*

Below LOD*

Below LOD*

Below LOD*


102

4.2.1.3 Serial ASNase Activity results: Results of serial ASNase activity

(induction and post induction) are shown for all patients in Table 4.4. A: Five

percent of patients had inadequate activity levels at one or more time points

and 4% had inadequate levels during post induction. Eighty-three percent of

patients had adequate levels during induction and 90% during post induction.

B: shows serial activity results of patients who had inadequate activity

(ASNase activity level of <100 U/litre of plasma) at TP1 &/or TP2 (n=44),

grouped according to the regimen they were assigned to at the end of

induction. All patients were initiated on either regimen A or B based on the

NCI risk stratification. During the course of induction they were assigned to

regimen C if they had poor cytogenetics &/or slow early response. Patients in

regimen A and B who had high MRD at the end of induction underwent a

randomisation of continuing on their assigned regimens or changing to

regimen C. Patients transferred to regimen C showed a higher incidence of

persistent post induction inactivation (p=<0.001). C: shows serial activity

results in patients with adequate activity (ASNase activity level of ≥ 100 U/litre

of plasma) at TP1 & or TP2, again grouped according to the regimen they

were on at the end of induction (n=216). Those who were in regimen C at the

end of induction showed a higher incidence of post induction inactivation

compared to those in regimen A and or B (p=<0.002, Fisher exact test)


103

Table 4.4 A: Serial ASNase activity, n=258/427

Induction Post induction n (%)

Adequate Adequate 204 (79)

Adequate Inadequate 11 (04)

Inadequate Adequate 29 (11)

Inadequate Inadequate 14 (05)

Table 4.4 B: Serial ASNase activity in patients who had inadequate levels during induction, n=44/427

Inadequate ASNase in Post induction

induction - Regimen (n) Recovered Not recovered

Regimen C (14) 5 9

Regimen A/B (30) 25 5

Table 4.4 C Serial ASNase activity in patients who had adequate activity during induction, n=216/427

Adequate ASNase in Post induction

induction - Regimen (n) Remained adequate Became inadequate

Regimen C (58) 50 8

Regimen A/B (158) 155 3


104

Conclusion 3 - Patients transferred to regimen C at the end of induction have

higher incidence of inactivation of ASNase.

4.2.1.4 Correlation of induction ASNase activity with biological factors

and therapeutic outcome: Table 4.5 shows the correlation of ASNase

activity during induction with baseline characteristics and table 4.6 with

outcome variables. Univariate analysis showed a significant correlation of

inadequate activity with NCI high-risk patients. This was determined by the

age at diagnosis (p=0.0016) and not the presenting white cell count (p=0.6).

Using a Wilcoxon match-pairs signed-rank test, there was a difference in the

age distribution of patients with adequate ASNase activity (Median age 5.08

years, range 1.17-23.2) as compared with those with inadequate ASNase

activity (Median age 7.71 years, range 1.67-22.92), p=0.021.

Table 4.5 Correlation between induction ASNase and baseline characteristics

p value χ2

Adequate Inadequate

Gender 0.2396

Male 209 47

Female 147 24

Immunophenotype 0.5328

B cell 306 63

T cell and null (1 pt) 50 8

Age 0.0016

< 10 years 258 38

> 10 years 98 33

NCI RISK 0.0097

Standard 205 29

high risk 151 42

WCC on presentation 0.6052

<50 x10 9/L 271 52

>50 x10 9/L 85 19

B cell Cytogenetic Subgroups 0.3914

No results 23 5

159 38

104 16

20 4

Table 4.5 Correlation Induction Asparaginase levels with baseline characteristics

No results

Good Risk

Intermediate Risk

Poor Risk

Good Risk

Intermediate Risk

Poor Risk

heterogeneity

Asparaginase Activity (TP1 &or TP2)


105

Conclusion 4 - Older patients had increased incidence of inadequate

ASNase activity during induction.

Overall, there was no significant association between response to ASNase

during induction and outcome variables such as early response or the burden

of disease at the molecular level (MRD). However, in the NCI low risk patients,

who receive a three drug induction, inadequate response to ASNase activity

was associated with high MRD at the end of induction, p=0.0289 and

especially so in the NCI low risk patients who belonged to good risk

cytogenetic group, p=0.006 (Table 4.6). Figure 4.5 shows the distribution of

ASNase activity levels in these patients at TP1 and TP2.

Table 4.6 Correlation between induction ASNase and outcome

Patients who had high MRD at the end of induction had significantly lower

ASNase activity at TP2 compared to those with low/intermediate MRD

(p=<0.01). Similar analysis done at TP1 showed no difference in the ASNase

activity levels between the two subgroups (p=<0.871), figure 4.5.

p value χ2

Adequate Inadequate heterogeneity

ALL patients 0.3

SER 36 10

RER 320 61

ALL patients 0.07

MRD low/intermediate 228 39

MRD high 128 32

NCI high risk 0.8


MRD high 64 17

NCI Std. risk 0.0289


MRD high 64 15

NCI Std. risk, good risk cytogenetics 0.0059


MRD high 33 13

Asparaginase Activity (TP1 &or TP2)

Table 4.6 Correlation Induction Asparaginase levels with outcome characteristics

Regimen at end of induction

Assigned - A or B

Changed to C

259 46

96 26

0.12


106

Figure 4.5 ASNase activity levels at TP1 and TP2 in NCI SR, precursor B ALL

patients who had good risk cytogenetics. These patients were split into two

groups depending on the MRD result obtained at the end of induction phase

of treatment (TP2). ASNase levels at TP2 co-related with MRD status,

p=0.009.

Conclusion 5 - ASNase activity results at TP2 correlate with MRD at the end

of induction in patients with precursor B ALL who belong to NCI standard risk

and have good risk cytogenetics

4.2.1.5 Time to event analysis: The follow up of patients in the ASNase

study is currently short (median 2 years). Figure 4.6 compares event free,

relapse free and overall survival by univariate analysis of 423/427 patients in

the study divided into two sub groups of adequate and inadequate ASNase

2000

1500

1000

500

0

n= 86 n= 39

MRD

low/intermediateMRD high

Aspara

gin

as

e a

ctivi

ty U

/litre

of pla

sm

a

Asparaginase acti vity at TP1 & T P2 in pati ents who belonged to NCI standard risk & who had good risk precursor B ALL cytogenetics: MRD high vs MRD low/intermediate

p= <0.01

MRD low/intermediate

MRD high

p= <0.871

n= 83 n= 30

TP1 TP2


107

activity during induction. Patients with adequate activity had ASNase activity

levels of ≥ 100 U/litre of plasma at one or both available time points during

induction (TP1 &/or TP2). If at either or both time points patients had ASNase

activity level of <100 U/litre of plasma then they were considered to have

inadequate activity. For both, the event free survival and relapse free survival,

there was a trend towards inferior outcome in patients who had inadequate

ASNase activity at TP1 and or TP2. As regards to overall survival, there was

an association between inadequate ASNase activity during induction and an

inferior outcome, figure 4.7C.

Conclusion 6 - Early data seems to indicate the response to PEG-ASNase

during induction is influencing the outcome in children with ALL.


108

Figure 4.6: Time to event analysis of patients in UKALL2003 with respect to

response to PEG-ASNase. Kaplan-Meier (K-M) curves were compared with

the log-rank test.

OVERALL SURVIVAL BY ASPARAGINASE ACTIVITY AT TP1/TP2

0 1 2 3 4 50

25

50

75

100

% O

S

Time (years)

95%

68%

At risk:Adequate 398 357 195 60 0 0

Inadequate 25 22 9 1 0 0

No.Patients

No.Events

Obs./Exp.

Adequate 398 13 0·9Inadequate 25 3 3·7

2P = 0·05

Adequate

Inadequate

C

B

EVENT FREE SURVIVAL BY ASPARAGINASE ACTIVITY AT TP1/TP2

0 1 2 3 4 50

25

50

75

100

% E

FS

Time (years)

94%

82%

At risk:

Adequate 398 356 192 60 0 0Inadequate 25 22 8 1 0 0

No.Patients

No.Events

Obs./Exp.


2P = 0·09

Adequate

Inadequate

A

RELAPSE FREE SURVIVAL BY ASPARAGINASE ACTIVITY AT TP1/TP2

0 1 2 3 4 50

25

50

75

100

% R

FS

Time (years)

97%

86%

At risk:Adequate398 356 193 60 0 0

Inadequate24 22 8 1 0 0

No.Patients

No.Events

Obs./Exp.


2P = 0·09

Adequate

Inadequate


109

4.2.2 RESULTS OF PATIENTS RECRUITED IN ALLR3 ARM OF THE

ASPARAGINASE STUDY

4.2.2.1 ALLR3 ASNase activity results: Patients who relapse have already

been treated intensively with ASNase. In the UK, the majority of patients on

the relapsed ALLR3 trial will have received PEG-ASNase. Patients in the

ALLR3 received same dose of PEG-ASNase as patients in the UKALL2003

trial. We hence tested trough ASNase activity levels post PEG-ASNase during

phase 1 and phase 2 of the treatment protocol in 24 patients. In total there

were 35 sampling time points. Twenty of the twenty four patients had

adequate activity at 31/35 of the sampling time points, figure 4.7. Three

patients had inadequate activity during phase 1 and there were no

subsequent samples in these patients. The fourth patient had adequate

activity in phase 1 but inadequate activity in phase 2.

Figure 4.7: ASNase activity in ALLR3. Box and whisker plot showing trough

ASNase activity levels in 24 patients at 35 time sampling time points in phase

1 and phase 2 of the treatment protocol. Asterisk represents an extreme

outlier.

Aspara

gin

ase a

ctivity U

/L

0

1200

1000

800

600

400

200

Patients in the ALLR3 trial, n=35

sampling time points in 24 patients


110

4.2.2.2 Outcome analysis of patients in ALLR3 who did not get PEG-

ASNase: We reported a correlation between higher MRD and inadequate

ASNase activity in patients in regimen A. Preliminary survival data for all

patients also suggests a correlation between inadequate ASNase actively and

overall survival (OS). As there were only 4 patients that had inadequate

ASNase activity, to assess the impact of PEG-ASNase at relapse, we

compared the overall and progression free survival (PFS) of all patients who

did not received PEG-ASNase either because of prior hypersensitivity to

PEG-ASNase or the development of ASNase induced pancreatitis (n=16) with

that observed in the matched controls who did receive PEG-ASNase (n= 214),

figure 4.8. The OS and the (PFS) were not different in the two groups.

Figure 4.8: Contribution of PEG-ASNase at relapse. The PFS and OS of

1.0

0.8

0.6

0.2

0.4

0

0 12 24 36 48 60 72 84 96

Pro

po

rtio

n s

urv

ivin

g

Months from registration

Log-rank p = 0.377

46.4 (35.0 – 57.1)

28.6 (18.1 – 40.0)

Progression-free survival: PEG-aspraginase vs. none

All patients on ALL R3

Log-rank p = 0.365

1.0

0.8

0.6

0.2

0.4

0

0 12 24 36 48 60 72 84 96

Pro

po

rtio

n s

urv

ivin

g

Months from registration

53.5 (41.8 – 63.9)

38.1 (27.1 – 49.1)

Overall survival: PEG-asparaginase vs. none

All patients on ALL R3


111

patients in the ALLR3 trial who did and did not receive PEG-ASNase

Conclusion 7- The number of patients analysed for ASNase activity in ALLR3

are small but early data indicates that inadequate ASNase activity does not

occur more frequently in patients at relapse. Outcome of patients who did not

received PEG-ASNase at relapse is not statistically inferior to those who did

receive the drug. The dosing strategy in the ALLR3 achieved adequate

ASNase activity in >90% of patients.


112

4.3 DISCUSSION:

Age influenced NCI high risk patients have a poorer outcome despite

intensification of treatment. This is related to increase incidence in toxicity and

adverse cytogenetics, lack of compliance to treatment and alterations in the

pharmacokinetics of steroids (2, 121-125). In addition to these possibilities,

our findings show increased incidence of ASNase inactivation in this group.

Routine testing in this group may help identify those who have inadequate

levels. This may be important as the time to event analysis shows a trend to

inferior event free survival and relapse free survival, p=0.09, figure 4.6 and an

inferior overall survival in patients who show sub-therapeutic response to

induction PEG-ASNase, p=0.09. There are limitations in the analysis done

thus far that are important to highlight. The correlation between high MRD and

inadequate induction ASNase activity in patients receiving a 3 drug containing

induction regimen as well as the time to event analysis have been done by

univariate analysis. It remains to be seen if the conclusions derived thus far

hold true on multivariate analysis. The data on time to event analysis will

additionally need to mature over time before it can be safely concluded that

response to ASNase during induction is crucial in determining the outcome of

children with ALL

In this study, PEG-ASNase made the greatest impact in patients belonging to

the NCI standard risk group with good risk cytogenetics. Though this is a

heterogeneous group (126), current prognostic classification used in clinical

practice is unable to further separate the ones in this group who will relapse

from the ones who don’t. Consequently all patients receive a 3 drug induction.

Steroid clearance is possibly enhanced in those who have an inadequate

response to ASNase (72). Thus there is suboptimal exposure to two of the

three drugs used in induction, a possible explanation for the significantly

higher MRD levels. This relationship is now being explored in the current

ALL2011 trial. Monitoring response to PEG-ASNase in this group has the

possibility of improving upon the resolution of the current prognostic


113

classification especially in the ones where MRD is indeterminate. These

patients could potentially benefit from post induction intensification of therapy.

The impact of PEG-ASNase in patients who receive a 4 drug induction is less

clear. This might be because of the additional anthracycline used as part of

the 4 drug induction regimen that salvages them from inadequate response to

PEG-ASNase. Alternatively, patients in this group are more likely to be

resistant to one or more drugs used in induction. Patients in this group are

more likely to have high MRD compared to those receiving 3 drug induction

despite treatment intensification.

Patients in Regimen C, not only have a lower chance of recovering PEG-

ASNase activity in the post induction phase if they have inadequate PEG-

ASNase during the induction phase; but they also have higher incidence of

inactivation to PEG-ASNase during post-induction. Patients in Regimen C are

also far more likely to develop clinical hypersensitivity to PEG-ASNase in the

post induction phase (chapter 5). Thus patients in Regimen C with inadequate

activity during induction could be at a double disadvantage of having sub

therapeutic drug levels and increased incidence of drug toxicity. Currently all

patients in regimen C receive post induction intensification with PEG-ASNase.

PEG-ASNase during post induction phase in this group possibly only exposes

them to more sensitising episodes in the context of inadequate levels of the

drug. Thus the importance of intensification of PEG-ASNase in high risk

patients is called into question and needs further evaluation.

Extending the argument further is the effect of ASNase in patients who

relapsed and who were treated in the ALLR3 protocol. Though the majority of

relapsed patients (>80%) showed adequate activity, matched pair analysis of

those who received ASNase and those who did not showed no difference in

either progression free survival or overall survival. Though the number of

patients in this analysis are small it may well be that the lymphoblasts at

relapse are intrinsically resistant to a number of drugs including PEG-ASNase

and so response to PEG-ASNase may not be the only factor that would


114

determine outcome. Reassuringly the dosing strategy of PEG-ASNase in

ALLR3 achieved adequate ASNase activity levels in vast majority of the

patients and these patients were not more likely to inactivate ASNase

compared to patients in the UKALL2003 trial.

Asparaginase Study: Determinants of ASNase activity

115

Chapter 5 Asparaginase Study: Determinants of ASNase activity

______________________________________________________________

5.1 BACKGROUND

As mentioned in the previous chapter, the results of the Asparaginase Study

are split into two chapters for the purpose of easy of reading. This chapter

describes:

1) The correlation of expression of AEP and CTSB with

a) ASNase activity

b) The development of immune response to PEG-ASNase.

c) Baseline biological characteristics and

d) Outcome variables

2) The impact of anti-L-Asparaginase antibody on the ASNase activity.

3) The incidence of toxicity such as hypersensitivity and thrombosis after

PEG-ASNase

The first and third sets of results are from patients recruited from the

UKALL2003 arm of the Asparaginase Study, whilst for the second set of

results are from patients recruited from both the UKALL2003 and the ALLR3

arms of the study.

5.2 RESULTS

5.2.1 Role of cysteine proteases as predictive biomarkers to ASNase

therapy:

A total of 144 and 208 patients were tested for the expression of AEP and

CTSB respectively. AEP and CTSB were measured by ELISA in leukaemic

blasts at diagnosis and were correlated with baseline characteristics such as


116

gender, NCI risk, immunophenotype and cytogenetics; response to PEG-

ASNase therapy such as ASNase activity, development of anti-L-

Asparaginase antibodies, occurrence of clinical hypersensitivity; and with

outcome variables such as early response and the residual disease at a

molecular level in Figures 5.1 to 5.4. These figures show expression of

proteases by ELISA in the form of box and whisker plots. To analyse the

expression proteases across each variable on the X axis, patients are split

into two or more groups depending on the nature of the variable. In order to

compare the means in each group the p values were generated by either

Mann-Whitney test (where there are two groups) or Kruskal Wallis Test

(where there are more than two groups). Circles represent outliers and

asterisks represent extreme outliers. The patients were classified into

cytogenetic sub groups based on recently published paper (42).


117

Figure 5.1: Correlation of expression of AEP by ELISA in leukaemic blasts at

diagnosis with baseline characteristics.

M:

n=

97

NC

I ri

sk

P=

.45

9

Pre

B &

T c

yto

ge

ne

tics

P=

.76

0

Pre

B c

yto

ge

ne

tics

P=

<0

.01

F: n=

47

Ge

nde

r

P=

.15

0

Std

: n=

69

Hig

h: n=

75

Poor:

n=

69

Non-p

oor:

n=

75

Int: n

=46

Poor:

n=

10

ngof AEP/μg of cell lysateprotein

126 0

Good: n=

54

Imm

un

op

he

no

typ

e

P=

.79

7

Pre

B: n=

121

T: n=

23


118

Figure 5.2: Correlation of expression of AEP by ELISA in leukaemic blasts at

diagnosis with ASNase levels, antibody, hypersensitivity and therapeutic

outcome

Asp

ara

gin

ase

activity

p=

.73

9E

arl

y r

esp

on

se

p=

.64

9

Rapid

: n=

125

Adq: n=

118

In-a

dq: n=

26

Slo

w:

n=

19

An

ti-A

spa

ragin

ase

an

tibo

die

s p

=.7

10

Pre

: n=

11

Abs:

n=

59

Hyp

ers

en

sitiv

ity

p=

.67

1

Pre

: n=

08

Abs:

n=

136

MR

D p

=.6

05

Low

: n=

37

Int: n

=48

Hig

h: n=

59

ngof AEP/μg of cell lysateprotein

126 0


119

Figure 5.3: Correlation of expression of CTSB by ELISA in leukaemic blasts at

diagnosis with baseline characteristics

ngof CTSB/ 100μg of cell lysateprotein12 8 6 4 2 0

Ge

nde

r

P=

.18

3

M:

n=

132

F: n=

76

NC

I ri

sk

P=

.68

7

Std

: n=

106

Hig

h: n=

102

Pre

B: n=

176

T: n=

32

Imm

un

op

he

no

typ

e

P=

.61

9

Poor:

n=

14

Non-p

oor:

n=

194

Pre

B &

T c

yto

ge

ne

tics

P=

.34

6P

re B

cyto

ge

ne

tics

P=

.71

4

Poor:

n=

12

Int: n

=69

Good: n=

79


120

Figure 5.4: Correlation of expression of CTSB by ELISA in leukaemic blasts at

diagnosis with ASNase levels, antibody, hypersensitivity and therapeutic

outcome

ngof CTSB/ 100μg of cell lysateprotein

Asp

ara

gin

ase

activity

P=

.29

6

Adq: n=

176

In-a

dq: n=

32

Pre

: n=

13

Abs:

n=

74

An

ti-A

spa

ragin

ase

an

tibo

die

s p

=.7

80

Pre

: n=

09

Abs:

n=

199

Hyp

ers

en

sitiv

ity

p=

.87

8

Ea

rly r

esp

on

se

p=

.24

2

Rapid

: n=

184

Slo

w:

n=

124

MR

D p

=.3

50

Low

: n=

47

Int: n

=80

Hig

h: n=

81

8 6 4 2 012


121

Neither the expression of AEP, nor CTSB by ELISA show any correlation with

any of baseline characteristics, response to PEG-ASNase or the outcome

variables.

Conclusion 8 - Cellular expression of AEP or CTSB in leukaemic blasts was

not significantly influenced by any of the know risk factors in childhood ALL,,

ASNase activity levels, development of immune reactions against PEG-

ASNase or other outcome variables such as early response to therapy and

the level of MRD.

5.2.2 Impact of Anti L-Asparaginase Antibodies: Antibodies were

measured against both PEG-ASNase and the native E.Coli ASNase by

indirect ELISA by Medac GmbH, Wedel, Germany. Its impact was studied in

patients recruited from UKALL2003 as well as from ALLR3

5.2.2.1 Anti-Asparaginase antibodies: Patients enrolled in the

UKALL2003 trial (n=129)

5.2.2.1.1 The correlation between serial ASNase activity and antibodies

to L-Asparaginase: This is shown in the table below.

Table 5.1 Correlation between ASNase activity and anti L-Asparaginase

antibodies

Groups Serial ASNase activity Anti-L-Asparaginase antibodies

Induction Post induction n (%) Number tested Number positive

I Adequate Adequate 204 (79) 75 1

II Adequate Inadequate 11 (04) 11 5

III Inadequate Adequate 29 (11) 29 3

IV Inadequate Inadequate 14 (05) 14 7

In the first group of patients, 197/204 had no clinical hypersensitivity. Seven of

the 204 patients had adequate activity despite having reported clinical

hypersensitivity. These will be discussed later. Of the 197 patients; 101/197,

49/197 and 41/197 were in regimen A, B and C respectively. From this group


122

75/197 patients across regimen A, B and C (A=29, B=26 and C=20) were

tested for anti- PEG-ASNase and anti-ASNase antibodies at 92 time points

during induction and post induction. 5/75 patients were tested during both

induction and post induction phases, 7/75 were tested only during induction

phase whilst the majority (63/75) were tested during the post induction phase.

Only one sample in this group of patients tested positive for anti PEG-ASNase

which was transiently detected only during the DI I1 phase and not during the

subsequent Capizzi 2 phase. This suggests that the assay for measuring

antibodies against ASNase is specific.

In the second group of 11 patients who had adequate activity during induction

but inadequate activity during post induction phase, 5 patients developed

antibodies- 4 against both PEG-ASNase and ASNase and 1 against PEG-

ASNase. Four out of these five patients were tested for presence of

antibodies in the diagnostic sample and were all found to be negative.

In the third group of patients who had inadequate activity during induction but

adequate activity during post induction phase (n=29), only 3 patients tested

positive for antibodies during induction. In each the antibody was only against

PEG-ASNase and was not detected subsequently in the post induction phase.

In the last group of patients who never achieved adequate activity (n=14), 7

were positive for anti-L-Asparaginase antibodies. Six of these patients had

both anti- PEG-ASNase and anti-ASNase, whilst one had anti ASNase. None

of these patients tested positive for either of the antibodies in the sample at

diagnosis indicating that the antibodies were acquired during the course of

treatment. In each of these 7 patients samples at multiple subsequent time

points were positive for antibodies indicating that the antibodies were

persistently positive in this group.

In 26 patients at 40 time points, there was simultaneous data for anti-

Asparaginase antibodies and ASNase activity. At 33/40 time points, the

development of anti-ASNase antibodies was associated with inadequate


123

ASNase activity from the sample at the corresponding time points. Four

patients constituted the 7/40 time points where there was a discrepancy

between ASNase activity and anti-ASNase antibodies. All these patients had

clinical hypersensitivity and it was not clear if they were on Erwinase at the

point when sample was sent for ASNase activity. The indoxine assay gives

readout if patients were on Erwinase as it detects ASNase activity. This is

also likely to account for the adequate activity noted in 7 patients who had

clinical hypersensitivity. In this group of patients 6 were tested for antibodies.

Three patients had both anti-PEG-ASNase and anti ASNase whilst 3 had no

detectable antibodies against either PEG-ASNase or ASNase.

Correlation between clinical hypersensitivity and serial ASNase activity was

available for two patients. Both these patients has adequate activity at the first

measured time point followed by a drop in activity level that preceded the

development of hypersensitivity. Both patients recovered ASNase activity

levels on Erwinase, figure 5.5

Figure 5.5 Correlation between hypersensitivity and ASNase activity. Serial

ASNase activity results in two patients who developed clinical hypersensitivity

to PEG-ASNase at time points indicated by arrow. In both these patients,

there was a drop in ASNase activity that preceded the development of

0

100

200

300

400

500

600

700

800

900

1000

Pla

sm

a L

-Aspa

ragin

ase

activity le

ve

ls (

U/L

)

= PEG ASNase

= Erwinase

Induction Post Induction

= Clinical Hypersensitivity


124

hypersensitivity and subsequent replacement of PEG-ASNase by Erwinase

resulted in the recovery of plasma ASNase activity.

5.2.2.1.2 Correlation between anti L-Asparaginase antibodies and

clinical hypersensitivity There were 16 patients who developed clinical

hypersensitivity to PEG-ASNase as shown in the next section. 14/16 patients

were tested for the presence of antibodies against ASNase at one or more

time points. 10/14 patients tested were positive for both anti- PEG-ASNase

and anti ASNase antibodies. In 9/10 patients we looked for the presence of

antibodies in the sample obtained at diagnosis and all of them were negative

Conclusion 9 – Whilst neutralising antibodies against ASNase explains

inadequate ASNase activity during post induction phase in half of the patients,

mechanism of late inactivation in the other half and that of early inactivation of

the drug remains unknown.

5.2.2.2 Anti-Asparaginase antibodies: Patients enrolled in the ALLR3

study (n=16)

Sixteen of the 24 patients were tested for anti-Asparaginase antibodies at one

or more time points. This includes two of the four patients with inadequate

activity. None of the samples tested were positive for anti-Asparaginase

antibodies.

Conclusion 10 - Whilst the numbers are small, there does not appear to be

an increased incidence of anti-Asparaginase antibodies at relapse.

5.2.3 Toxicity after PEG-ASNase: Toxicity to PEG-ASNase was reported in

31 of the 427 patients (7.3%). Of these, 16 (3.7%) developed clinical

hypersensitivity, 10 (3.1%) thrombosis and 5 (1.1%) pancreatitis. Table 5.1

shows the incidence of toxicity to PEG-ASNase across regimen A, B and C.

Patients in regimen C had significantly higher incidence of reported toxicity to

PEG-ASNase (22/122) compared to those in A and B (10/305), p=<0.001.

Hypersensitivity almost exclusively occurred in patients on regimen C. Data


125

on the onset of hypersensitivity is available in 7 patients and the median onset

was 15 weeks into therapy.

Table 5.2 Incidence of toxicity to PEG-ASNase

The overall incidence of hypersensitivity, thrombosis and pancreatitis in this

study are lower to those that reported by other groups (76, 127-129), Table5.3.

Table 4.8 Reported side effects to PEG-ASNase

Hypersensitivity

Thrombosis

Pancreatitis

Regimen A Regimen B Regimen C

1 - 16

4 3 3

2 - 3

Side effect

Table 4.8 Reported side effects to PEG-ASNase

Hypersensitivity

Thrombosis

Pancreatitis

Regimen A Regimen B Regimen C

1 - 16

4 3 3

2 - 3

Side effect


126

Table 5.3 Reported Adverse reactions to ASNase

Patient number

Patient Group Advers even/incidence Type of Asparaginase Comment Reference

ALL-BFM 76 new diagnosis Hypersensitivity (24%) Native E.coli ASNase (128)

Silent antibodies (0%)

Dana-Farber 386 new diagnosis allergic reactions=15% Native E.coli ASNase Older patients higher incidence of thrombosis and pancreatitis

(32)

pancreatitis 7% vs (Randomisation) PEG-ASNase: lower incidence of allergic reactions. Reactions more likely to be mild

thrombosis=4.5% PEG-ASNase

Dana-Farber 463 new diagnosis Allergic reactions=11% Pancreatitis=11% Thrombosis=9%

PEG-ASNase (iv vs im) Doses 2500 U/m

2

(129)

St. Jude 410 new diagnosis Clinical allergy (41%) Silent antibodies (36.9%)

Native E.coli ASNase (130)

St Jude 35 new diagnosis Clinical allergy (62.8%) Native E.coli ASNase (131)

CCG 1001 new diagnosis high risk patients

Silent antibodies (61%) Native E.coli ASNase Vs PEG-ASNase in a

Silent antibodies lead to inadequate ASNase levels in 94% of patients

(79)

randomised setting during post induction


127

CCG 118 new diagnosis L-Asparaginase antibodies: depended on

PEG-ASNase Vs

high titre antibodies: (76)

the product used (Randomisation) PEG-ASNase=2%

Native E.coli ASNase Native E.coli ASNase=26%

Thrombosis= 5.17%

NOPHO 42 new diagnosis silent antibodies: (132)

3/27: Erwiniase Erwiniase

1/15: Native E.coli ASNase

Native E.coli ASNase

NOPHO 39 Relapse silent antibodies: 8% Erwiniase (133)

Meta analysis 1752 new diagnosis Thrombosis: 5.2% 17 prespective trials (134)

Current study 427 New diagnosis Hypersensitivity 3.9% Thrombosis 2.3% Pancreatitis 1.6%


128

Conclusion 11 - The incidence of toxicities to PEG-ASNase in the study was

lower compared to those reported by other international groups. Almost all

hypersensitivity reactions occurred in patients on regimen C

5.3 DISCUSSION

The dose and schedule of PEG-ASNase achieved adequate activity in

majority of patients that were enrolled from both the UKALL2003 and the

ALLR3 arms of the Asparaginase study.

For patients enrolled from the UKALL2003 study, toxicity to PEG-ASNase was

predominantly observed in regimen C, p=<0.001. Overall, the incidence of

toxicity to PEG-ASNase was lower than that reported by other international

groups. This could be due to a the use of PEG-ASNase instead of native

E.coli ASNase and the use of PEG-ASNase at a lower dose of 1000 U/m2 in

comparison to the other groups such as the BFM, CCG and the Dana-Farber

who gave PEG-ASNase at 2500 U/m2.

In those patients who had inadequate ASNase activity, serial activity

measurements revealed 3 major patterns of drug inactivation. These

consisted of early (during induction phase), late (during post induction phase)

and persistent (both early and late) inactivation. Whilst the mechanism for late

inactivation seems to be related to development of antibodies to ASNase in

approximately half of the patients and will be discussed first, the mechanism

of late inactivation in the other half and that of early inactivation remains

unknown.

The incidence of silent neutralising antibodies causing late inactivation in this

study was 4.7%. Both anti-ASNase and anti PEG-ASNase antibodies had the

potential to inactivate PEG-ASNase. These antibodies were not detected in

the diagnostic samples indicating that these were acquired during the course

of therapy following exposure to PEG-ASNase. As they could explain only 50%

of patients who had late inactivation, one possibility is that the assay is not


129

sufficiently sensitive to detect antibodies in all patients. The other possibility is

that there are additional, yet unidentified, mechanisms that account for late

inactivation. Further studies that correlate serial ASNase activity with anti-L-

Asparaginase antibodies are needed to assess the exact incidence of silent

neutralising antibodies and their contribution to the late inactivation of PEG-

ASNase and to study whether this has an impact in the overall outcome. The

latter objective will need long term follow that measures overall survival as

unlike in the early phase of treatment there are no surrogate markers to

assess the impact of inadequate therapy. Such studies may also pick up a

pattern where the drop in ASNase levels precedes clinical hypersensitivity in

which case an earlier intervention could potentially prevent toxicity.

A higher incidence of relapse has been reported in those with anti-ASNase

antibodies (130). In our study there was no increase in the incidence of anti-

Asparaginase antibodies at relapse. This could again be due to the small

cohort of patients in our study or the use of PEG-ASNase in front line UK

protocols after 2003 which could have changed the incidence of anti-

Asparaginase antibodies or due to the difference in the sensitivity of the assay

that measured anti-Asparaginase antibodies.

It is likely that early inactivation is due to yet unexplained biological factors

such as AEP and CTSB that are either secreted or expressed by the

leukaemic cell. Additionally we expected AEP, a protease previously

described to be over expressed in high risk ALL, to play a role in the

development of immune response to PEG-ASNase. The expression of AEP

and CTSB in leukaemic cells by ELISA showed nearly a six (AEP) to twelve

(CTSB) fold variation between individual patients. However, when their

expression was assessed in individual patient subgroups based on the known

risk factors in ALL, their expression in most of the patient subgroups was

statistically uniform. On univariate analysis, the only factor that influenced the

expression of either of these proteases was the presence of poor risk

cytogenetics in patients with pBALL. Patients in this sub-group had lower

expression of AEP compared to those in the good and intermediate sub-


130

groups. There are two points to note. Firstly, the definition of poor risk

cytogenetics referred in this thesis (42) is different to the one use in the

previously published analysis of AEP expression in clinical samples(101).

Secondly, the numbers of patients are small and the AEP expression was

measured at the level of protein.

Though AEP and CTSB have been identified to degrade ASNase in-vitro, they

did not emerge as predictive biomarkers for either the response to PEG-

ASNase or to the development of immune response to PEG-ASNase or to

poor response to induction therapy. This was not surprising given that the

level of inactivation of ASNase was low whilst most of the patient’s leukaemic

cells were found to express AEP and CTSB. One explanation for this could be

choice of the ELISA assay used to study the expression of both AEP and

CTSB. While ELISA was the most suitable technique to study the expression

of proteases in leukaemic blasts, as shown in chapter 3, it measured total

protein and not specifically the active form of the protein. Both AEP and CTSB

are lysosomal cysteine proteases that undergo sequential N and C terminal

cleavage before they become active. The processing of these proteases is

dependent on acidic pH which is likely to influence their in-vivo activity and

possibly limit their action locally to the microenvironment around the acidic

bone marrow mesenchymal stem cell niches. Secondly, we know little about

the half life and stability of AEP and CTSB and the effect of pre analytical

variables such as conditions during sample transport. Thirdly, expression of

AEP and CTSB was measured in the leukaemic cells. If the drug mediates its

effect by extracellular depletion of asparagine and if AEP and or CTSB

expressed by the leukaemic cells degrade ASNase in-vivo, it begs a question

on where the interface between the drug and the proteases is. It is not clear if

measuring cellular expression of AEP and CTSB would be reflective of the in-

vivo capacity of tumour to inactivate the drug that is in the extracellular

compartment.

.

Asparaginase Study: Salient points

131

Salient points of chapters 4 and 5 :

Conclusion 1 - From a trial perspective 85-97% of patients have adequate

trough activity at any time point.

Conclusion 2 - Increasing the dose to 2,500 – 3,500 is unlikely to improve the

percentage of patients who will have adequate levels and is likely to lead to

increased toxicity.

Conclusion 3 - Patients transferred to regimen C at the end of induction have

higher incidence of inactivation of ASNase.

Conclusion 4- Older patients had increased incidence of inadequate ASNase

activity during induction.

Conclusion 5 - ASNase activity results at TP2 correlate with MRD at the end

of induction in patients with precursor B ALL who belong to NCI standard risk

and have good risk cytogenetics.

Conclusion 6 - Early data seems to indicate the response to PEG-ASNase

during induction is influencing the outcome in children with ALL

Conclusion 7- The number of patients analysed for ASNase activity in ALLR3

are small but early data indicates that inadequate ASNase activity does not

occur more frequently in patients at relapse. Outcome of patients who did not

received PEG-ASNase at relapse is not statistically inferior to those who did

receive the drug. The dosing strategy in the ALLR3 achieved adequate

ASNase activity in >90% of patients.

Conclusion 8 - Cellular expression of AEP or CTSB in leukaemic blasts was

not significantly influenced by any of the know risk factors in childhood ALL,

ASNase activity levels, development of immune reactions against PEG-

Asparaginase Study: Salient points

132

ASNase or other outcome variables such as early response to therapy and

the level of MRD.

Conclusion 9 - Whilst neutralising antibodies against ASNase explains

inadequate ASNase activity during post induction phase in half of the patients,

mechanism of late inactivation in the other half and that of early inactivation of

the drug remains unknown.

Conclusion 10- Whilst the numbers are small, there does not appear to be an

increased incidence of anti-Asparaginase antibodies at relapse.

Conclusion 11 - The incidence of toxicities to PEG-ASNase in the study was

lower compared to those reported by other international groups. Almost all

hypersensitivity reactions occurred in patients on regime

Chemoprotection by BMSC derived exosomes

133

Chapter 6 Role of bone marrow stromal exosomes in conferring chemo-

protection to leukaemic cells

6.1 BACKGROUND:

This chapter presents work I did under the supervision of Dr JiZhong Liu in

the laboratory. His work is presented to provide a background for my role in

his project.

6.1.1 Drug resistance in ALL is multi-factorial

Though ASNase inactivity does not seem to influence MRD levels in Regimen

B, nevertheless patients in this group are more likely to have higher MRD than

patients in regimen A (unpublished data from UKALL2003, personal

communication, Rachael Wade). Whilst the interaction between

ASNase/steroids contributes to one part of the spectrum of drug resistance,

there are clearly other factors. Though poor response to treatment has been

intensively investigated (table 6.1) and a number of risk factors for poor

response identified (41, 42, 62, 135, 136), there is yet no unifying mechanism

that explains resistance to combination chemotherapy (61, 62). This may be

related to the fact that many factors contribute to drug resistance, including

the use of multiple drugs and the biological heterogeneity of the disease

Focussing on ASNase, at least two alternative mechanisms of drug resistance

have been proposed. In the first mechanism leukaemic cells show intrinsic

resistance to ASNase mediated by the up-regulation of Asparagine

Synthetase (ASNS). However, the expression of ASNS correlates with in-vitro

sensitivity of ASNase in some but not all genetic subtypes of ALL (93, 94).

Moreover the expression of ASNS in patients failed to correlate with the in-

vivo response to ASNase monotherapy (95). Another proposed mechanism is

an extrinsic mechanism wherein the leukaemic cells when exposed to

ASNase were protected from its cytotoxicity by mesenchymal cells that up-


134

regulate Asparagine Synthetase (ASNS) resulting in secretion of asparagine

(99). This may result in adequate asparagine levels in the cellular niches

despite successful systemic asparagine depletion following adequate

response to ASNase. Given the lack of intrinsic genetic abnormalities that

can explain therapeutic failure the latter is an area for investigation.

In ALL, significant proportions of late relapses are inherently chemo sensitive

and are cured without the need for a bone marrow transplant (11). This

suggests that they survive due to reasons that are beyond intrinsic drug

resistance. This suggest that extrinsic mechanisms such as microenvironment

meditated chemoprotection may play a significant role in therapeutic failure

(137-139).The microenvironment has been shown to mediate drug resistance

by both contact (140) and non contact mediated mechanisms (99, 141). We

in the group are investigating the role of microenvironment in conferring broad

spectrum chemoprotection.


135

Table 6.1 Pharmacological heterogeneity in childhood ALL

Drug Clinical group/material investigated for differential response Findings/Explanation for differential response Reference

Steroids a) early precursor B ALL: CR vs no CR ~ no CR-high levels of glucocorticoid receptors (142)

b) cell lines: resistant vs sensitive ~ resistant- higher expression of MCL1 (143)

c) cell lines: resistant vs sensitive ~ resistant- preservation of mitochondrial respiratory function

(144)

d) precursor B ALL patients: resistant vs sensitive by MTT assay ~ resistant- 33 genes differentially expressed (62)

Vincristine a) SR ALL patients: incidence of relapse ~ relapse-higher plasma clearance (145)

b) precursor B ALL patients: resistant vs sensitive by MTT assay ~ resistant- 40 genes differentially expressed (62)

Thiopurines a) ALL patients: Correlation of RBC TPMT with 6 TGN levels and incidence of relapse

~ Children with higher RBC TPMT activity had lower 6TGN levels and a higher incidence of relapse

(146)

b) ALL patients treated in ALL-BFM-2000: MRD SR vs HR ~ TPMT genotype had a substantial impact on the MRD

(147)

c) ALL patients treated in Total Therapy protocol XIIIB: high vs low TGN levels after MP alone

~ higher levels of TGN associated with up-regulation of genes encoding MP metabolic enzymes and transporters (SLC29A1)

(148)

high vs low TGN levels after MP+TGN involved in protein and ATP biosynthesis

d) TEL-AML1 fusion ALL vs other subtypes including T-ALL: ~ TEL-AML patients had (149)

de novo purine synthesis (DNPS) lower DNPS

genes involved in purine metabolism lower expression of 16 genes

Anthracyclines a) precursor B ALL patients: resistant vs sensitive by MTT assay ~ resistant- 20 genes differentially expressed (62)

(Daunorubicin)

Methotrexate a) ALL patients:MTX levels, RFC1 (SLC19A1) polymorphisms & event free survival

~ G80A polymorphism was associated with higher plasma MTX levels and inferior event free survival

(150)

b) Hyperdiploid ALL patients vs T lineage ALL ~ Higher accumulation of MTX-PG in hyperdiploid ALL due to higher expression SLC19A1 as a result of extra copies of Ch 21

(151)


136

c) Hyperdiploid ALL patients vs other subtypes of pre B and T ALL

~ higher accumulation of MTX-PG in hyperdiploid ALL associated with higher expression of SLC19A1

(152)

~ lower accumulation of MTX-PG in E2A-PBX associated with lower expression of SLC19A1

~lower expression of MTX-PG in TEL-AML1 associated with higher expression of ABCG2

~lower expression of MTX-PG in T ALL associated with higher expression of FPGS

d) ALL patients ~additional Ch 8 associated with higher GGH activity and lower MTX-PG

(153)

e) ALL patients ~genetic variant with triple repeat in promotor region of TYMS is associated with higher TYMS expression

(154)

and an inferior EFS

L-Asparaginase a) precursor B ALL patients: resistant vs sensitive by MTT assay ~ resistant- 35 genes differentially expressed (62)

b) cell lines: resistant vs sensitive ~higher expression of ASNS is associated with resistance

(92)

c) Only in TEL-AML1 negative patients ~higher expression of ASNS is associated with resistance

(94)

Vincristine & a) ALL patients: resistant vs sensitive by LC50 values 139 genes differentially expressed (155)

L-Asparaginase

Induction poly ALL patients treated in ALL-BFM-2000: 54 genes associated with cell cycle progression (156)

chemotherapy MRD Standard vs High Risk & apoptosis differentially expressed

Abbreviations:

Ch Chromosome TGN Thioguanine

CR Complete Remission TPMT Thiopurine methyltransferase

EFS Event free survival TYMS Thymidylate synthetase

FPGS Folylpolyglutamate Synthetase MTX Methotrexate

GGH Gamma glutamyl hydrolase MTX-PG Methotrexate Polyglutamate

MP Mercaptopurine RCF Reduced folate carrier

MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide


137

6.2 RESULTS

6.2.1 Bone marrow stromal cell derived conditioned medium (BMSC-CM)

confers chemoprotection to SUPB15 cell line: In order to recapitulate the

in-vivo host tumour interaction in the laboratory, we created an organotypic 3-

D model (157). To develop this model, bone marrow stromal cells (BMSC’s)

were cultured and then alkali stripped to kill the cells but to retain the

cytoskeleton. Next BMSC’s were replated on this 3-dimensional extracellular

matrix (ECM). At about a week, the ECM could be demonstrated to contain

collagen and fibronectin and stromal cells had differentiated into

mesenchymal cells and osteoblasts (Figure 6.1). Growing stromal cells on a

lattice allows a more natural spatial development (158, 159). BMSC grown on

this organotypic 3-D model acquired spindle shape figure 6.1. Cell lines grow

unsupported in this system. Primary cells also survive without the addition of

growth factors for at least 4 weeks.

Figure 6.1: Comparison between 2D model and organotypic 3D culture

systems. Bone marrow stromal cells cultured in a plate (2D model) on the left

and on a cell free extracellular matrix (3D organotypic system) on the right..

Compared to the BMSC grown in the 2D system, the BMSC grown in the 3D

model had a more defined organisation and the cells in 3D system were more

spindle in shape. Both images were obtained on 20x inverted microscope.

Medium obtained from this organotypic 3D model is referred to as bone

marrow stromal cell derived conditioned medium (BMSC-CM). BMSC-CM


138

protected SUPB15, an inherently sensitive cell line, against number of drugs

used in ALL, figure 6.2. As these drugs have diverse mechanisms of action,

the chemoprotection was broad spectrum and not-selective.

Figure 6.2: BMSC-CM confers non selective chemoprotection to leukaemic

cells. SUPB15 cells were cultured in medium or conditioned medium (CM)

from a human bone marrow stromal cell line HS-5. Following exposure to

drugs between 3-4 days, cell viability was measured by MTT assay. X axis

represent mean values and error bars represent standard error obtained after

3 independent experiments. P values are calculated using Student’s t test; **

represents <0.01, *** represents <0.001. Y axis represents the fold change

viability compared to the control where cells were cultured in normal medium.

6.2.2 Generation of SUPB15MR cells: SUPB15 cells cultured in BMSC-CM

were next exposed to sub-lethal dose of Mitoxantrone. Those that survived

after exposure to Mitoxantrone had a multidrug resistant phenotype and were

called SUPB15MR. These SUPB15MR were subsequently cultrured in normal

medium without further exposure to BMSC-CM and retained the multidrug

resistant phenotype until 50 passages.

0

0.2

0.4

0.6

0.8

1

1.2

cont

rol

Dox

orub

icin

Mito

xant

rone

Idar

ubicin

clof

arab

ine

Aspar

aginas

e

Vincr

istin

e

Dex

amet

haso

ne

ce

ll via

biit

y(%

of

co

ntr

ol) M

TT medium

CM

******

****** ***

*** **

BMSC-CM confers non selective chemoprotection to leukaemic cells


139

6.2.3 Exosomes in the BMCS-CM contributed to the BMSC-CM mediated

chemoprotection: To further characterise and identify the components in the

BMSC-CM that conferred chemoprotection BMSC-CM was subjected to ultra-

filtration, heating at 95°C for 10 minutes, treatment with proteinase K, or

RNAse. The chemo-protective effect of the BMSC-CM was present within a

trypsin, RNAse and heat resistant, <3kDa fraction (figure 6.3).

Figure 6.3 Protective ability of the <3kd fraction of BMSC. Ability of various

fractions of the BMSC-CM in providing chemoprotection of SUPB15 against

Mitoxantrone was compared against control medium. The Y axis represents

fold change in cell viability of SUPB15 cells exposed to Mitoxantrone for 3

days. Error bars represent standard error. P values were calculated using

Student’s t test. **= p<0.01, ***= p<0.001. Ctrl (Control) represents; </>3kd

represents fractions of the CM; CM-heated is HS5 CM heated at 95°C for 10

minutes; CM-Proteinase K= CM treated with 50μg/ml of Proteinase K at 50°C

for 1 hour and then heated at 95° for 10 minutes to inactivate Proteinase K;

CM RNAse A= CM treated with RNAse A 5 IU/ml for 1 hour at 37°C.

Electron microscopy of the pellet obtained by ultracentrifugation of the <3kDa

fraction of BMSC-CM revealed presence of exosomes (Figure6.4).

0

0.5

1

1.5

2

2.5

3

3.5

4

ctrl CM >3kDa <3kDa CM-heated CM-Proteinase K CM-RNase A

cell

via

bili

ty(r

ela

tive

to c

ontr

ol)

***

**

*** ******

***


140

Figure 6.4: Transmission electron microscopy of the pellet obtained after

ultracentrifugation of <3kDa fraction of BMSC-CM showing presence of cup

shaped exosomes. (Dr. Jizhong Liu, Dr. Johnson, Dr. Mironov)

6.2.4 HS5 derived exosomes are taken up by SUPB15 and primary ALL

cells In order to determine if exosomes were taken up by leukaemic cells

(figure 6.5), they were fluorescently labelled by PKH67 (green colour) were

incubated with SUPB15 and primary ALL cell lines that were co-stained using

Cell Mask (cytoplasm-red) and Dapi (nucleus-blue).

Figure 6.5 Cellular uptake of BMSC exosomes by SUPB15 (Top panel) and

primary ALL cells (bottom panel) on co-culture. Images were captured on a

low-light system utilising Metamorph software based around a Zeiss Axiover

DAPI MergePKH67Cell Mask

200 nm bar size

30-100nm size membrane limited vesicles (exosomes)


141

200M microscope with a 300W Xenon light sourse using either a

Photometrics Cascads 512B or Andor iXon DU888+ camera. Original

magnification is x160 provided by x100 oil immersion lens in conjunction with

a 1.6x Optivar magnification enhancer (Dr S Johnson)

6.2.5 BMSC derived exosomes conferred broad spectrum

chemoprotection to SUPB15 cells: In order to determine if the exosomes

conferred chemoprotection, the BMSC-CM was filtered through a 0.2μm

membrane filter and then ultra-centrifuged at 100,000xg for 160 minutes to

pellet the exosomes. The supernatant was named as Exo-depleted CM1.

Exo-depleted CM1 was subjected to further ultracentrifugation step as

described above to give rise to Exo-depleted CM2. The ability of BMSC-CM

to confer chemoprotection progressively decreased as the exosomes were

depleted from the medium, figure 6.6

Figure 6.6 BMSC derived exosomes confer chemoprotection.

Chemoprotection of BMCS CM decreased after depletion of exosomes. The

ability of the BMSC-CM and its two fractions to confer protection to SUPB15

was compared against normal medium (Control). SUPB15 cells were exposed

to 8nM of Mitoxantrone for 3 days and cell viability was measured by MTT

assay. The data on Y axis is presented as fold change compared to the

p=0.0575

p=0.0188

chemoprotection of CM decreased after Exosomes depletion

0

0.5

1

1.5

2

2.5

3

3.5

medium BMSC-CM Exo-depleted CM1 Exo-depleted CM2

ce

ll v

iab

ility


142

control. Error bars represent standard error from 3 independent experiments.

P values were calculated by using paired t test.

6.2.6 Horizontal transfer of Micro-RNA (miRNA) from BMSC to leukaemic

cell- a mechanism by which BMSC derived exosomes could confer

broad spectrum chemoprotection to SUPB15MR cells: Due to the limited

size of the exosomal sample material, its RNA content was analysed.

Exosome were enriched in small RNA as shown in figure 6.7, (160).

Horizontal transfer of exosomal RNA and miRNA, a subset of small RNA, has

been described to occur between the host and the tumour (161-164). The

transfer of RNA has also been shown to change the biology of the recipient

cell (161, 165-167). To analyse whether there was a transfer of miRNA from

BMSC to the SUPB15 cells, we next examined the miRNA pattern of the

BMSC, SUPB15 and SUPB15MR cells as well as the BMSC derived exosomes.

TaqMan human MircoRNA A+B cards Set v3.0 9Applied Biosystems, part

number 4444913) were used to compare the miRNA expression profile of

SUPB15, SUPB15MR and the BMSC derived exosomes. All miRNAs that had

a cycle threshold (CT) that was within 11 cycles from the endogenous control

genes were included in the analysis.


143

Figure 6.7 Exosomes contain small RNA. Pictures of RNA electrophoresis on

the left and of electrophoregrams obtained on a bio-analyser from Agilent on

the right. The exosomal RNA is much smaller in size compared to the cellular

RNA (Dr Liu, Dr Johnson).

Table 6.2 shows the list of miRNAs expressed in each of the samples.

Compared to HS5, a BMSC cell line used in the experiment, HS5 exosomes

were enriched in miRNA. Compared to SUPB15, SUPB15MR had 52 unique

miRNA. Of these 6 miRNA were removed as they were either orthologs or

paralogs of a miRNA in the list and the remaining 46 miRNA are coloured in

either plum if they could be traced back to the HS5 exosomes, n= 40 or blue if

Cellular RNA

18S 28S

Pattern of RNA in HS5 cells compared to that in HS5 derived exosomes

BMSC derived Exosomal RNA

RNA ladder sample

Bases

Bases

RNA ladder sample

RNA length

RNA length


144

not, n=6). Figure 6.8 describes the data by proportion Venn diagrams:

SUPB15 (green circles), SUPB15MR (red circles), HS5 (blue circles with grey

background) and HS5 exosomes (blue circles with interrupted border). The 46

miRNAs uniquely present in SUPB15MR and in HS5 derived exosomes can be

grouped into 35 miRNA families. More than 3/4th (n=40/46; 87%) of the unique

miRNAs found in SUBB15 could be matched to miRNA in the HS5 derived

exosomal (Table 6.2 and figure 6.8).

Table 6.3 summarises key evidence that is currently available that links the

“matched miRNAs” identified in this experiment to cell survival and or

adaptation of cell’s metabolism to stress.

Most of the miRNAs in the SUPB15MR that cannot be matched to the HS5

exosomes are involved in haematopoiesis: miR-150=B and T cell

development (168-172); miR-181= B cell development (173, 174), miR-

223=granulopoiesis (175), haematopoietic cell proliferation(176),

erythropoiesis(177), miR-338= PU.1 dependent haematopoiesis (178).


145

SUPB15 HS5 HS5 exosomes SUPB15MR

Unique to SUPB15MR

hsa-miR-106a hsa-miR-106a hsa-let-7a hsa-let-7b hsa-let-7b

hsa-miR-126 hsa-miR-138 hsa-let-7b hsa-let-7e hsa-let-7e

hsa-miR-142-3p hsa-miR-146a hsa-let-7e hsa-let-7g hsa-let-7g

hsa-miR-146a hsa-miR-155 hsa-let-7g hsa-miR-106a hsa-miR-106b

hsa-miR-155 hsa-miR-16 hsa-miR-100 hsa-miR-106b hsa-miR-1233

hsa-miR-16 hsa-miR-17 hsa-miR-103 hsa-miR-106b# hsa-miR-125a-5p

hsa-miR-17 hsa-miR-191 hsa-miR-106a hsa-miR-1233 hsa-miR-126#

hsa-miR-186 hsa-miR-19b hsa-miR-106b hsa-miR-125a-5p hsa-miR-1260

hsa-miR-191 hsa-miR-222 hsa-miR-10a hsa-miR-126 hsa-miR-140-5p

hsa-miR-19a hsa-miR-24 hsa-miR-125a-5p hsa-miR-126# hsa-miR-146b-5p

hsa-miR-19b hsa-miR-29a hsa-miR-125b hsa-miR-1260 hsa-miR-149#

hsa-miR-20a hsa-miR-31 hsa-miR-126 hsa-miR-140-5p hsa-miR-150

hsa-miR-218 hsa-miR-484 hsa-miR-126# hsa-miR-142-3p hsa-miR-151-3p

hsa-miR-222 hsa-miR-939 hsa-miR-1260 hsa-miR-146a hsa-miR-151-5P

hsa-miR-24 hsa-miR-1271 hsa-miR-146b-5p hsa-miR-15b

hsa-miR-30c hsa-miR-127-3p hsa-miR-149# hsa-miR-181a

hsa-miR-331-3p hsa-miR-1290 hsa-miR-150 hsa-miR-18b

hsa-miR-454 hsa-miR-130a hsa-miR-151-3p hsa-miR-193b

hsa-miR-484 hsa-miR-130b hsa-miR-151-5P hsa-miR-195

hsa-miR-720 hsa-miR-130b# hsa-miR-155 hsa-miR-196b

hsa-miR-132 hsa-miR-15b hsa-miR-197

hsa-miR-134 hsa-miR-15b# hsa-miR-20b

hsa-miR-138 hsa-miR-16 hsa-miR-223

hsa-miR-140-3p hsa-miR-17 hsa-miR-26a

hsa-miR-140-5p hsa-miR-181a hsa-miR-26b

hsa-miR-145 hsa-miR-186 hsa-miR-29a

hsa-miR-146a hsa-miR-18a hsa-miR-30b

hsa-miR-146b-5p hsa-miR-18b hsa-miR-30d


hsa-miR-149# hsa-miR-193b hsa-miR-338-5P

hsa-miR-151-3p hsa-miR-195 hsa-miR-342-3p

hsa-miR-151-5P hsa-miR-196b hsa-miR-345

hsa-miR-152 hsa-miR-197 hsa-miR-34a#

hsa-miR-155 hsa-miR-19a hsa-miR-374a

hsa-miR-15b hsa-miR-19b hsa-miR-374b

hsa-miR-16 hsa-miR-19b-1# hsa-miR-378

hsa-miR-17 hsa-miR-20a hsa-miR-425

hsa-miR-186 hsa-miR-20b hsa-miR-520D-3P

hsa-miR-18b hsa-miR-218 hsa-miR-590-5p

hsa-miR-191 hsa-miR-222 hsa-miR-625#


hsa-miR-193a-5p hsa-miR-24 hsa-miR-92a

hsa-miR-193b hsa-miR-26a hsa-miR-93

hsa-miR-195 hsa-miR-26b hsa-miR-93#

hsa-miR-196b hsa-miR-29a hsa-miR-939

hsa-miR-197 hsa-miR-30a-5p hsa-miR-99b

hsa-miR-199a-3p hsa-miR-30b

hsa-miR-19a hsa-miR-30c

hsa-miR-19b hsa-miR-30d

hsa-miR-20a hsa-miR-320

hsa-miR-20b hsa-miR-331-3p

hsa-miR-21 hsa-miR-338-5P

hsa-miR-210 hsa-miR-342-3p

Table 6.2 Expression of micro-RNAs


146


Unique to SUPB15MR

Table 6.2 continued

hsa-miR-214 hsa-miR-345

hsa-miR-214# hsa-miR-34a#

hsa-miR-218 hsa-miR-374a

hsa-miR-221 hsa-miR-374b


hsa-miR-222# hsa-miR-425



hsa-miR-25 hsa-miR-520D-3P

hsa-miR-26a hsa-miR-590-5p

hsa-miR-26b hsa-miR-625#


hsa-miR-27a# hsa-miR-720

hsa-miR-28-3p hsa-miR-766

hsa-miR-29a hsa-miR-92a

hsa-miR-29c hsa-miR-93

hsa-miR-301a hsa-miR-93#

hsa-miR-30a-3p hsa-miR-939

hsa-miR-30b hsa-miR-99b

hsa-miR-30c

hsa-miR-30d

hsa-miR-30e-3p

hsa-miR-31

hsa-miR-31#

hsa-miR-320

hsa-miR-320B

hsa-miR-323-3p

hsa-miR-331-3p

hsa-miR-339-3p

hsa-miR-339-5p

hsa-miR-342-3p

hsa-miR-345

hsa-miR-34a

hsa-miR-34a#

hsa-miR-34b

hsa-miR-365

hsa-miR-370

hsa-miR-374a

hsa-miR-374b

hsa-miR-376a

hsa-miR-376c

hsa-miR-378

hsa-miR-409-3p

hsa-miR-411

hsa-miR-425

hsa-miR-431

hsa-miR-432

hsa-miR-454

hsa-miR-483-5p

hsa-miR-484

hsa-miR-494

hsa-miR-539

hsa-miR-574-3p

hsa-miR-590-3P


147


Unique to SUPB15MR

Table 6.2 continued

hsa-miR-590-5p

hsa-miR-625#

hsa-miR-629

hsa-miR-650

hsa-miR-664

hsa-miR-720

hsa-miR-744

hsa-miR-766

hsa-miR-886-3p

hsa-miR-886-5p

hsa-miR-9

hsa-miR-92a

hsa-miR-92b#

hsa-miR-93

hsa-miR-93#

hsa-miR-935

hsa-miR-939

hsa-miR-99a

hsa-miR-99b


148

Figure 6.8 miRNA expression profiles in host and tumour-drug sensitive &

drug resistant. Proportion Venn diagrams that compares the miRNA

expression profiles of SUPB15 (green circles), SUPB15MR (red circles), BMSC

cell line-HS5 (blue circles with grey background) and HS5 derived exosomes

(blue circles with interrupted border). Top left: HS5 compared to SUPB15. Top

right: HS5 compared to HS5 exosomes. Bottom Left: HS5 exosomes

compared to SUPB15MR. A vast majority of miRNAs present in SUPB15MR,

59/72 (82%), match with the list of miRNAs present in HS5 exosomes. Bottom

right: Of the 52 unique miRNAs in SUPB15MR compared to SUPB15. This

figure trims further to 46 after removing 6 orthologs and paralogs. Again, a

vast majority of unique miRNA in SUPB15MR, 40/46 (87%) matches to the list

of miRNAs present in the HS5 exosomes

10 10 0414112

52 205967 13

SUPB15 HS5

SUPB15MR

SUPB15

HS5 exosomes

HS5

HS5 exosomes

SUPB15MR

miRNA unique to

SUPB15MR n=52

Orthologs/paralogs n=6

n=46

Match to HS5 exosomes

n=40/46 (87%)

Do not match to HS5 exosomes

n=6/46 (13%)


149

Table 6.3 Previously described role of miRNA in chemoprotection and or cell survival and or cell cycle and or cell metabolism Unique to SUPB15

MR miRNA family described role Reference

let7 family protects hepatocytes against oxidant injury (179) let7 family histone demethylase KDM2B suppresses let-7b: regulation of ageing, proliferation (180) let7 family essential for panabinostat mediated downregulation of HMGA2 (181) let7 family let-7 family involved in glucose homeostasis and insulin sensitivity (182) let7 family modulates acquired resistance to taxanes (183) hsa-miR-106b miR-17 family functions as oncogene by suppressing p21 and Bim in oesophageal Ca (184) suppresses p21, overrides doxorubicn induced DNA damage checkpoint (185) funtions as oncogene by targeting PTEN (186) targets Smad, activates TGFβ signalling, induces EMT; breast cancer (187) dysfunction of p53 pathway in Hodgkins lymphoma cell lines (188) increases E2F1 expression and is upregulated in hepatocellular Ca (189) modulates E2F in neuronal lineage differentiation (190) targents retinoblastoma in laryngeal carcinoma (191) hsa-miR-125a-5p targets key proteins regulating apoptotis, immunity, inflammation (192) hsa-miR-126# plays a role in angiogenesis (193) hsa-miR-140-5p mediates chemoresistance in osteosacroma and colon cancer cells (194) hsa-miR-150 promotes gastric cancer proliferation by negatively regulating ERG2 (195) hsa-miR-151-3p miR-151 facilitates tumour cell migration & spreading by downregulating RhoGDIA (196) hsa-miR-195 implicated in acquired teomzolomide resistance in glioblastoma multiforme cells (197) hsa-miR-196b targets both HOXA9/MEIS1 and FAS in MLL rearranged leukemia (198) hsa-miR-20b mirR-17 family modulates VEGF expression by targeting HIF-1 α & STAT3 in breast cancer cells (199) hsa-miR-223 promotes gastric cancer invasion and metastasis by targeting EPB41L3 (200) hsa-miR-26a represses PTEN in a murine glioma model enhances de novo tumor formation (201) hsa-miR-34a# miRNA34 links p53 with Wnt (202)


150

Abbreviations used in Table 6.3: KDM2B= lysine (K) specific demethylase 2 B;

HMGA2= high mobility group AT- hook 2; PTEN= phosphatase and tensin

homolog; EMT= epithelial to mesenchymal transformation; E2F= eukaryotic

transcription factor; HOXA9/MEIS1= homeobox gene A9/myeloid ectopic viral

integration site 2; ERG= Ets related gene; HIF= hypoxia inducible factor;

signal transducer and activator of transcription; EPB41L3= erythrocyte

membrane protein band 4.1 like protein 3 and VEGF= vascular endothelial

growth factor.

6.2.7 BMSC derived exosomal mi-RNAs target ROS pathway in

leukaemic cells

Ingenuity pathway analysis was done on the uniquely expressed miRNAs in

SUPB15MR cells. The core analysis was performed using Ingenuity miRBase

18 (hosted at Manchester) and interrogates > 600.00 known miRNA targets. It

used all available data sources (Ingenuity IPA; Application: Build 140500 and

Content: Version12710793). Analysis considered direct and indirect

relationships between miRNA and endogenous chemical and genes and set

the confidence interval of the data sources at “experimentally observed” and

“high(predicted)” for miRNA in humans, mice and rats. Analysis revealed 9

networks, 3 of them were overlapping with each other and contained 86% of

all miRNAs. These 3 networks were merged and are shown in figure 6.10.

H2O2, an indicator of production of reactive oxygen species (ROS), emerged

as a major node of the network. The connections were with a) 13 miRNAs

identified by the analysis (red) and 2 that were unidentified (miRNA28 &

miRNA342) and b) 7 proteins that included Insulin, Vascular endothelial

growth factor (VEGF), RAC1, oestrogen and progesterone receptors, DNA

damage inducible transcript 3 and CD86.


151

Figure 6.9 Connection between miRNAs and ROS. Map showing connections

between miRNAs, proteins and endogenous chemicals present in three

overlapping networks generated by Ingenuity Pathway Analysis software

using a list of unique miRNAs that were present in SUPB15MR cells. It shows

H2O2 to be a major node having connections to 15 miRNA and 7 proteins.

6.2.8 Further characterisation of SUPB15MR cells: Gene expression

analysis of SupB15 and SupB15MR (U133 v2.0 array showed an overall down

regulation of the global gene expression (left panel figure 6.10) but an up-

regulation of histones (right panel, figure 6.10) in SUPB15MR cells compared

to SUPB15. This suggests epigenetic down regulation of gene expression in

resistant cell lines. Four sets of predefined genes related to AKT, ROS,

ATPase and apoptosis pathways were chosen and gene set enrichment

analysis (GSEA) was used to measure enrichment scores between SUPB15

and SUPB15MR cells, figure 6.10 B. All four set showed high scores

suggesting differential expression of these genes in the two cells lines.


152

Figure 6.10 Gene expression in SUPB15MR cells. A Gene expression

analysis using U133 v2.0 array- Left panel: Overall, the expression of genes is

higher in Sup B15 Darker colours reflect increased fold expression. However

(right panel) expression of histones is up-regulated in SupB15MR. B

Enrichment plots comparing the expression of predetermined set of genes

SupB15 SupB15MR SupB15

Histones

SupB15 MR

A

B GSEA analysis: Genes upregulated in SUPB15 MR compared to SUPB15

Gene expression analysis (U133 v2.0 array): SUPB15MR compared to SUPB15


153

identified in each of the 4 pathways involving AKT, apoptosis, ROS and ATP

pathways between SUPB15 and SUPB15MR cells.

Finally, SUPB15MR had lower levels of ROS compared to SUPB15 cells, figure

6.11, that was coupled with cell quiescence (personal communication, Dr. Liu).

Figure 6.11 ROS levels in SUPB15 cells compared with SUPB15MR.

Dichlorofluorescein diacetate (DFC-DA) was used to measure cellular ROS

levels. DFC-DA is cleaved by intracellular esterases to yield fluorophore,

intensity of which is measured by flow cytometry.

Lower levels of ROS in SUPB15MR compared to SUPB15

0

0.2

0.4

0.6

0.8

1

1.2

SUPB15 SupB15-MR

Me

an

F

luo

resce

nce

(fo

ld)


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6.3 Discussion:

This chapter highlights a number of important discoveries that will potentially

change our understanding of how leukaemic cells survive and proliferate in a

normal microenvironment and how this milieu can in fact protect the blast cells

from the effect of chemotherapy. Traditional models have examined the

mechanisms of resistance in the cell itself as is detailed in table 6.1. These

models have failed to provide a unifying mechanism of cell survival in the

context of multiagent chemotherapy. Though cell to cell contact is indeed

viewed as a mechanism of cell survival, the loss of which leads to anoikis,

leukaemic cells have been traditionally viewed as non-adherent and thus

unable to use these mechanisms for survival. This chapter shows that stromal

cells are able to use paracrine mechanisms to regulate lymphoblast cell

survival. Indeed our observations suggest that microvesicle/exosomes

mediated cell signalling is a key component of normal and transformed cell

behaviour.

Dr Liu’s work clearly shows that stromal cell derived exosomes are taken up

leukaemic cells and this process confers chemoresistance. Exosomes are

exocytosed 30-100 nm size intraluminal vesicles of endosomal origin (203).

Figure 6.12 summarises key steps involved in production of exosomes

suggesting that the generation of exosomes is an active process. Exosomes

are one of the several ways by which cells can communicate with one

another(204).


155

Figure 6.12 Origin of exosomes. Alphabets A to H sequentially depict the key

steps involved in the production of exosomes. The key factors associated with

each step are shown in blue legends. Little is known about the process that

determines the fate of sorting endosomes. Adapted from (204-207).

We now show that the exosomes are enriched in a miRNA population.

Lymphoblasts once exposed to these miRNA, sustain the pattern of miRNA

Origin of Vesicles: Exosomes = A to H; Microvesicles =1

Clathrin-dependent endocytosis Clathrin -independent endocytosis

Ubiquitination of transmembrane proteins

Lipid rafts: cholesterol, SYT I, VAMP2, SYN*

Binding of AP2 to SYN*

Early endosomes

Sorting endosomes

ESCRT dependent MVB

Degradation

Lysosome

Recycling endosomes

TGN

Clathrin- ACAP1

Clathrin- AP1B Clathrin-GGA3

Retromer

SNX27

SNX17

RAB5EEA1ESCRT 0

ESCRT 0/I/II/IIIVps4 ComplexTsg101AlixLBPACD63LAMP

ESCRT independent MVB

Proteolipidprotein cargoCeramidenSMase2LBPACD63CD9CD81Rab27,11 & 35

LBPACD63LAMP

Ptdins3P

overlap

Rab27ASlp4- aSNARESNAP-25Syntaxin (SYN)

C

D

E

G Exosome secretion

Budding microvesicle

*

ACAP1

AP

EEA

ESCRT

LAMP

LBPA

nSMase2

Ptdins3P

SNARE

SYN

SYP

SYT

TGN

Tsg

Vps

A

B1 B2

F2F1

H

=described with clathrin dependent endocytosis

=ADP ribosylation factor GTPase-activating protein with Coiled coil ANK repeat & pleckstrin homology domains

=adaptor protein complexes

=early endosome antigen

=endosomal sorting complex required for transport

=lysosome associated membrane protein

=lysobisphosphatidic acid

=neutral sphingomyelinase 2

=phosphatidly inositol 3 phosphase

=soluble n-ethyl-maleimide-sensitive factor attachment protein receptors

=syntaxin

=synaptophysin

=synaptotagmin

=transgolgi network

=tumour susceptibility gene

=vacuolar protein sorting

1

VAMP

SYP

cholesterol


156

expresson for many months and retain chemoresistance. Additionally these

cells enter a G1/G0 phase and down regulate oxidative phosphorylation. The

gene expression data suggests that the exosomes miRNA lead to an

epigenetic down regulation of global gene expression, possibly via higher

order regulation at the level of histones (131, 208-210). Such epigenetic

programming has been shown to generate prolonged but ultimately reversible

chemoresistance in cancer cells (211).

Thus we can explain both early and late relapses with this mechanism. In

early relapses, gene expression suggests that cell cycle genes are over

expressed, while late relapses do not appear to have any clear differences in

GEP(212). Cancer cells that have mutations in cell cycle checkpoint genes

such as p53 and CDKN1B (p27) however maintain their ability to proliferate

(personal communication, Dr Liu). Both early and late relapses have been

rendered chemoresitance via the exosome/miRNA transfer, but the early

retains the ability to proliferate and thus this disease is relatively incurable

with conventional chemotherapy. The late relapses, slowly lose

chemoresistance and thus are now vulnerable to intensive therapy. Thus one

approach would be to add drugs that target the epigenome – an approach that

has recently been described to have successful results(213)

In our model, the uniquely acquired miRNAs in SUPB15MR can be broadly

separated into 2 groups. The first one consists of 36 miRNAs that match to

the BMSC derived exosomes and the second one which contains 6 miRNA

that are unique to SUPB15MR cells. The miRNAs in the first group have

previously been shown to target a number of pathways associated with

alteration in cell metabolism and/or chemoprotection, table 6.3. The miRNAs

in the second group have a pivotal role in haematopoiesis and in particular the

B cell development suggesting that cells hold on to their original

developmental programme. The next step would be to individually assess the

role of uniquely identified miRNAs in conferring protection via epigenetic

reprogramming of the cell. This can be done by first measuring their

expression by RQ-RTPCR in clinical samples from patients that show poor

response to therapy as well as in cells that survive chemotherapy in an in-vivo


157

mouse model, followed by knockdown and enforced expression experiments

involving individual miRNA to study their effects on conferring broad spectrum

chemoprotection. Such an approach has a potential to find a mechanistic

explanation behind broad spectrum chemoprotection when current strategies

using genome wide studies have failed to provide an explanation (61, 62).

Several of the unique miRNAs indentified in our experiment have been

reported to be differentially expressed by primary lymphoblasts (214-217).

However, as yet the mechanism behind their differential expression remains

unknown. Our findings suggest that the differential expression of miRNAs in

lymphoblasts may well be due to the effect of the stroma.

Finally, results from the gene expression analysis and miRNA array show that

a number of miRNAs are involved in regulating a number of genes related to

diverse pathways. Thus targeting one gene, miRNA or pathway may not

necessarily yield desired therapeutic results. If dynamic regulation of ROS is

indeed an important downstream effect whereby the leukaemic cells acquire

broad spectrum chemoprotection, then it increasing the cellular ROS level

could become a potential therapeutic strategy. This could be achieved by

combining ASNase with β-phenethyl isothiocyanate (PEITC). ASNase

depletes glutamine; one of the principle building block in the production of

antioxidant glutathione which in turn is a key mediator in maintaining cellular

redox balance(218, 219). Glutamine is also a principle source of energy for a

cell that is deprived with glucose and it plays a crucial role in cell survival in

this setting which in the field of cancer metabolism is also referred to as the

beyond Warburg effect (220). PEITC is a compound known to increase ROS

generation and suppress the BCL-2 family molecules at the same time that is

shown to selectively kill cancer cells. The combination of these two agents

thus shows promise in overcoming multidrug resistance in childhood ALL.

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Chapter 7 Work in progress

______________________________________________________________

7.1 BACKGROUND

As discussed in chapter 5, we could not demonstrate an association between

the expression of AEP and/or CTSB in the leukaemic cells with early

inactivation of PEG-ASNase. Additionally, if these proteases were indeed

mediating the in-vivo degradation of PEG-ASNase, we do not know the exact

interface between the proteases and PEG-ASNase where the degradation

may occur. As the drug leads to extracellular asparagine depletion, the

interaction between PEG-ASNase and the proteases may well be taking place

in the extracellular compartment. Proteases in their active forms are packaged

into vesicles inside the leukaemic cells (100). It is possible that these vesicles

are then secreted into the extracellular compartment. Microvesicles (MV), one

of the subtypes of extracellular membrane limiting vesicles, do indeed contain

proteases (221-224). Thus, MV may well represent the interface between the

drug and the proteases. To investigate this was beyond the scope of this

thesis but in this chapter I describe early results of a technique I developed to

enrich B cell derived MV from cell supernatant. This method is also suitable

for harvesting MV from clinical samples.

7.1.1 Nomenclature of Membrane-limited vesicles:

The extracellular compartment contains mobile membrane-limited vesicles,

variably referred to as “extracellular vesicles”(225) or “membrane

vesicles”(203) or “extracellular organelles”(226). They range from 50 nm to 5

μm in size and are sub-classified into smaller (<100 nm) size vesicles that

include exosomes (227, 228), prominin 1- enriched membrane particles (229)

and exosomes-like vesicles(230); and larger (>100 nm) size heterogenous

vesicles that include MV,100-1000 nm(231-236); ectosomes (237, 238), 50-

200 nm; and apoptotic bodies. (203, 239). Perhaps a biologically more

meaningful classification is the one that is based on their origin. Whilst

exosomes and exosomes like vesicles originate from intra-luminal vesicles of

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the multivesicular bodies (MVB); MV, ectosomes and apoptotic bodies are

“shed” directly from the plasma membrane (203). There is a lack of

standardised nomenclature to define membrane-limited vesicles (225). For

example, the term “MV” has also been used as an umbrella term to describe

all extracellular vesicles (240). To confuse the matter further “MV” as defined

by (203) are also referred to as “shedding MV” by (226), shedding vesicles by

(240) and ectosomes by (204). In this thesis exosomes are defined

exocytosed 30-100 nm size intra-luminal vesicles of endosomal origin and MV

as 100-1000nm size vesicles produced by direct plasma membrane blebbing.

Table 7.1 shows defining features of MV, exosomes and apoptotic bodies.

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Table 7.1 Key features of membrane limited vesicles:

Exosomes Microvesicles Apoptotic bodies

Size 30-100 nm 100-1000nm 50-500nma; >1000nm

b

Mechanism of generation Exocytosis of MVB Budding from plasma membrane Budding from plasma membrane,

Mode of extracellular release

constitutive and regulated Regulated Regulated

Main protein markers Tetraspanins (CD63, CD9, CD81) Proteases: MMP2, MMP9, uPA, CTSB Histones

Alix Membrane associated: VAMP3, β1 integrin

TSG101 Cytoskeleton associated: Actin, myosin

Rab11, Rab27a, Rab27b, Rab35

Lipid composition Enriched in cholesterol, ceramide, SM, enriched in cholesterol and DAG Not determined

nSMase2, lipid rafts, LBPA high phosphatidylserine exposure high phosphatidylserine exposure

low phosphatidylserine exposure

Density in Surcose 1.13-1.19g/ml Not determined 1.16-1.28

EM appearance Cup shpae Irregular and electron dense Heterogeneous

Isolation Differential gradient ultracentrifugation Differential centrifugation Established protocols lacking

Sucrose gradient ultracentrifugation 18,000-20,000g

1,00,00-2,00,000 g

Table 7.1 Adapted from (203, 225, 226, 240-242). MVB= multivesicular bodies; nSMase2=neutral sphingomyelinase 2; LBPA=

lysobisphosphatidic acid, EM= electron microscopy; SM=sphingomyelin; MMP= matrix metalloprotinases; CTSB=Cathepsin B;

VAMP= vesicle associated membrane protein; uPA= urokinase plasminogen activator; DAG=Diacylglycerol; a= as described in

(203) ; b= as described in (204).

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7.1.2 Functional role of vesicles

Release of membrane vesicles is a process that is evolutionarily conserved

across the prokaryotic and eukaryotic cells. Table 7.2 highlights some of roles

of vesicles that have been identified in health and disease including cancer

(225, 241). Vesicles have been identified as one of the mechanism by which

cells communicate (204). Table 7.3 highlights the example of cargo contained

in the MV that affects a number of processes in cancer.

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Table 7.2 Vesicles in health and diseases

Categories References

Physiological Processes: (203, 204, 225, 243-245)

Actin cytoskeleton/integrin/

Rho A/synaptic signalling,

Caveolar mediated endocytosis,

Acute phase response, conveying of

immune response, bone mineralisation,

angiogenesis, intercellular communication

Diseases

Autoimmmune diseases (246-256)

(Systemic lupus erythromatosis,

anti phospholipid antibody syndrome,

rheumatoid arthritis, vasculitis,

systemic sclerosis, type 1 diabetes

Cardiovascular diseases (257-266)

Acute coronary syndrome, hypertension,

pulmonary hypertension, Buerger's

disease, atherosclerosis, deep vein

thrombosis, congestive cardiac failure

Cerebrovasuclar diseases (267-269)

Transient ischaemic attack, multi-infarct

dementia, subarachnoid haemorrhage

Haematological diseases (270-273)

Paroxysmal nocturnal haemoglobinuria,

sickle cell crisis, immune thrombocytopenia, thrombotic thrombocytopenia

Cancer (161, 274-279)

lung adenocarcinoma, glioblastoma, oral/ovarian/prostatic/colorectal/

gastric cancers, melanoma,

cancer associated thrombosis

Other diseases (280-285)

Alzheimer's disease, metobolic syndrome,end stage renal disease,

sepsis, pre-ecclampsia, obstructive sleep apnoea

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Table 7.2 Adapted from (204, 225, 242, 245)

Table 7.3 Microvesicle cargo in cancer

Microvesicle Cargo Function References

Proteins

Soluble Factors: Angiogenesis, inflammatory (161, 286-288)

(VEGF, FGF, IL8, IL6 cytokines, regulators of

MMPs, TIMPs) Proteolysis

Membrane receptors: Chemokine receptor, receptor (230, 289-295)

(CCR5, CCR6, TNFR1, p55, EGFR, AXL, FasL)

tyrosine kinase, Death ligand

Oncoproteins and tumour suppressors:

Oncogenic EFGR, RTK, GTPase

(161, 290-292, 295-297)

(EGFR, EGFRvIII, HER2, Mutant EGFR

MET, K-ras, Akt, PTEN) Tumour suppressor

Lipids cell signalling (298)

(Sphingomyelin) Angiogenesis

Nucleic acids tumour growth (161, 279, 299-301)

(mRNA, micro RNA, DNA, gene regulation

mt DNA, gDNA) cell communication

Table 7.3 Adapted from (242). VEGF= vascular endothelial growth factor;

FGF= fibroblast growth factor; IL= interleukins; MMP= matrix

metalloproteinase; TIMP= tissue inhibitor or metalloproteinase; TNFR=

tumour necrosis factor receptor; CCR= chemokine receptor; EGFR=

endothelial growth factor receptor; HER2= human epidermal growth factor

receptor 2

7.2 PRELIMINARY RESULTS- Harvesting B cell derived MV:

Technique described in this thesis to isolate MV consists of two stages. In the

first stage cell supernatant and plasma is subjected to a series of

centrifugation steps based on previously published method to pellet MV from

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cell free supernatant and patient plasma. The differential centrifugation steps

consisted of 750 g for 5 minutes and 1500 g for 15 minutes to remove cells

and debris respectively; followed by a final spin of 15000 g for 45 minutes to

pellet the MV (302). As the method did not employ ultra-centrifugation

procedure, exosomes were not expected to be in the pellet (234). The

second stage of the technique added specificity to the process by isolating

just the B cell derived MVs. This is important in the context of isolating tumour

derived MV from plasma of patients with precursor B ALL. In this stage the

pellet was first labelled with a green fluorescent lipid staining dye PKH-67 and

the labelled MV were re-suspended in PBS. These labelled MV “pulled out”

from the PBS solution and immobilised on to the protein A/G Ultralink resin by

using a modified immunoprecipitation technique. Immunoprecipitation was

originally used to precipitate proteins of interest from a solution. Instead of

precipitating the protein, mouse anti human anti-CD19 antibody (clone HIB19,

BD Biosciences, catalogue number 555410) was used as a “pull down

antibody” to harvest the MV.

7.2.1. Pellet obtained after stage one of the method was enriched in

microvesicles markers and contained CD19

The pellet was lysed and its protein content was analysed by immunoblotting.

Immunoblotting showed presence of VAMP3, a marker described to be

associated with MVs (241) and absence of proteins associated with

exosomes, such as LAMP1, TSG101, CD63 and CD81, figure 7.1A.

Immunoblotting revealed the presence of CD19, a pan B cell marker, figure

7.1A. The pellet was re-suspended in PBS and analysed for surface

expression of phosphatidylserine by flow cytometry using Annexin V

conjugated to FITC (Annexin V-FITC). Annexin binds to phosphatidylserine

and when tagged with a fluorophore (FITC), it can be use to study the surface

expression of phosphatidylserine. The shift in mean fluorescent intensity seen

between the two populations, figure 7.1 B, shows that at least 55% of the

pellet vesicles have phosphatidylserine externalisation. Phosphatidylserine

externalisation is a defining feature of microvesicles (303-305).

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Figure 7.1 Characterisation of pellet obtained after stage one of MV isolation

method. A: pellets were lysed and immunoblotted for a number of markers.

The lysates expressed CD19 (pan B cell antigen) and VAMP3 (vesicle

associated membrane protein, characteristically shown to be associated with

MV). There was an absence of detectable CD63, LAMP1, TSG101 and CD81

(markers known to be associated with exosomes). B: Mean fluorescent

Fluorescent intensity (FI) FITC 502nm

SD1 vesicles

SD1 vesicles Annexin V-FITC labelled

Co

un

ts %

B FLOW CYTOMETRY

250 kd

150 kd

100 kd

75 kd

50 kd

37 kd

25 kd

20 kd

15 kd10 kd

1 2

1 VAMP3 13 kd

2 CD19 95 kd

GAPDH 36 kd

3 CD63 50 kd

4 LAMP1 120 kd

5 TSG101 44 kd

6 CD81 26 kd

3 4 5 6

A IMMUNOBLOTTING

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intensity by flow cytometry of pellets re-suspended in phosphate saline buffer

with and without prior staining with Annexin V-FITC, a dye that stains

phosphatidylserine on the membranes. The shift in mean fluorescent intensity

of the labelled vesicles compared to the unlabelled vesicles indicates that 55%

of vesicles had externalisation of phosphatidylserine, a feature that is

characteristic of MV. As the sensitivity of the flow cytometer was pushed to its

limits to count all the MV, the data set would have picked any particles in the

fluid stream. Hence the actual proportion of MV showing phosphatidylserine

externalisation is likely to be far higher.

7.2.2 Immobilisation of CD19 expressing SD1 microvesicles on Ultralink

A/G resin:

As the microvesicle pellet lysate expressed CD19 antigen and as

microvesicles are shed from B cell surface, it was possible that CD19 was

expressed on MV surface. We hence used anti-CD19 antibody to immobilise

MV on to Protein A/G Ultralink resing. Figure 7.2 A shows PKH67 dye labelled

SD pellet (green) immobilised onto the Protein A/G Ultralink resin using anti-

CD19 antibody. The negative controls used to demonstrate the specificity of

interaction between CD19 antigen on the MV and the “pull down” mouse anti

human anti-CD19 antibody consisted of mouse anti human anti CD3 antibody

(Figure 7.2 B) and protein A/G Ultralink resin alone (Figure 7.3 C) Images

were acquired on the time lapse system that consisted of Zeiss 200M inverted

microscope and a Zeiss 20x lens for images. ImageJ software showed that

immobilied round bodies had a vesicular shape and their size varied between

380 nm to 850nm in diameter.

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Figure 7.2 Immobilisation of SD1 pellet microvesicles on to protein A/G

Ultralink resin. Images from left to right represent bright field images using

phase contrast (Left); images using a Sedat 488nm filter from Chroma and a

metamorph acquisition software from Molecular Devices (centre) and merged

image created on ImageJ software (right). A, B & C are generated using Zeiss

20x lens.

C: No antibody

B: anti-CD 3 antibody

A: anti-CD19 antibody

50μ scale bar

Ultralink A/G resin PKH67(green) labelled vesicles

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7.2.3 Quantifying PKH67 labelled cell line MV by flow cytometry:

Replacing larger beads in protein A/G UltraLink resin with smaller 6.0-8.0 μm

protein G polystyrene particles, SPHERTM (Catalog no PGP-60-5, Spherotech,

Illinois, US) permitted us to quantify the amount of PKH labelled vesicles

immobilized on to the beads. Figure 7.3 A, shows the mean fluorescent

intensity of PKH67 labelled MV obtained from 1 ml of SD1 and REH debris

free supernatants. Both the cell lines were cultured under identical conditions

that included a starting cell concentration of 1 million per ml and the MV were

harvested 48 hours later. Compared to REH cell supernatant, SD1 cell

supernatant had greater concentration of PKH labelled MV. Figure 7.3 B,

shows increase in mean fluorescent intensity that was proportional to the

amount of MV.

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Figure 7.3: Quantification of MV in cell supernatants A Shift in mean

fluorescent intensity (MFI) seen PKH67 labelled MV of SD1 and REH cell

lines on flow cytometry when using anti CD19 antibody (blue) compared to the

MFI obtained with anti-CD3 antibody (red, negative control). For identical

culture conditions, there were more MVs in SD1 supernatant that REH

supernatant. B: Increase in mean fluorescent intensity that is proportional to

the amount of labelled MV: bead alone (red), MV from 1 ml (blue) and 6 ml

(orange) of debris free SD1 supernatant.

MFI

anti CD3 1475anti CD19 2061

27%17%

SD1 MVREH MV

Fluorescent intensity (FI) PKH67 502nm

Co

un

t (%

) MFI

anti CD3 1410anti CD19 1528

Co

un

t (%

)

Fluorescent intensity (FI) PKH67 502nm

6ml of SD1 supernatant MV: 54% positive compared to beads alone

1ml of SD1 supernatant MV: 34% positive compared to beads alone

Beads alone

SD1 MV anti CD19

A

B

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7.2.4 Immobilised vesicles expressed microvesicles markers : In order to

further demonstrate that the vesicles immobilised to protein A/G UltraLink

resin were indeed MV, the vesicles were lysed and the protein content was

blotted for presence of markers previously shown to be associated with MV:

matrix metalloproteinase-2 and 9 (MMP2, MMP9) (223), Cathepsin B (CTSB)

(224), Actin and Leukocyte Function Adhesion (LFA) molecule (CD11a),

figure 7.4.

Figure 7.4 Protein content of immobilised MV. Immunoblot showed presence

of markers previously been described to be associated with MV (introduction).

All results were generated from a common microvesicle lysates.

7.2.5 MV from patient plasma: Figure 7.5 A shows the appearance on

electron microscopy of a pellet obtained after subjecting the bone marrow

plasma to the same spin employed to pellet the MV. It shows presence of

membrane bound vesicles that are heterogeneous with respect of size and

shape. Figure 7.5 B shows PKH67 labelled vesicles immobilised on the

protein A/G UltralLink resin using anti CD19 antibody. The size of the vesicles

range from 350 nanometers to 1.4 micrometers

MMP9 92-86 kd

MMP2 77-66 kd

LFA 160 kd

CTSB 43-46 kd

31 kd

24-25 kd

Actin 37kd

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Figure 7.5 Isolation of MV from patient plasma. A: Transmission electron

microscopy image of MV pellet obtained from a bone marrow plasma of a

patients at presentation of ALL. B: Images from left to right represent bright

field images using phase contrast (Left); images using a Sedat 488nm filter

from Chroma and a metamorph acquisition software from Molecular Devices

(centre) and merged image created on ImageJ software (right). A, B & C are

generated using Zeiss 20x lens.

200 nm scale bar 500 nm scale bar

5000 nm scale bar

Ultralink A/G resin PKH67(green) labelled vesicles

A: Transmission electron microscopy image of a pellet obtained from bone marrow plasma at

diagnosis

B: Images acquired on the time lapse system of bone marrow plasma derived, PKH labelled

vesicles immobilised on Ultralink A/G resin using anti CD-19 antibody

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7.3 DISCUSSIO|N:

The in-vitro and in-vivo isolation, detection, quantification and characterisation

of MV is complicated by the heterogeneity in their size, the lack of

standardised methods/protocols that selectively harvest them from other

vesicles and the potential influence of pre-analytical variables such as shear

stress caused during venepuncture, anticoagulant in the sample, sample

storage, processing time and the temperature conditions during transit (225).

The most common approach to isolate MV employs differential centrifugation

followed by flow cytometric detection. However detecting smaller (<500nm)

MV using forward scatter and convincingly separating them from the

background instrument noise created by salt crystals, microparticles, plasma

lipoproteins and platelet fragments remains a challenge for most modern flow

cytometers even after using calibrated sub-microscopic beads (306-309).

Optical methods such as transmission electron microscopy, atomic force

microscopy and dynamic light scattering whilst are able to give an accurate

size of particles, are not suitable for routine clinical practice or laboratory

research. None of the techniques can specifically separate tumour derived

MV from non tumour derived MV in clinical samples. The method described in

this chapter attempts to address some of the above mentioned difficulties that

limit accurate isolation of tumour derived MV. The anti CD-19 antibody was

chosen primarily because CD19 is specific for pre-B cells. Thus in diagnostic

plasma, CD19 positive MV are more likely to originate from lymphoblasts.

This approach could in the future be used to relatively quantify the amount of

tumour derived MV in clinical samples using different concentrations SD1

supernatant MV to create a standard curve.

The technique described in this chapter needs further validation. Firstly, the

immunoblotting results shown in this chapter need appropriate controls to

demonstrate that the antibodies used for exosomal markers are suitable. This

can be done by pelleting exosomes by ultracentrifugation of MV free cell

supernatant, followed by lysis of pellet and performing immunoblotting using

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the same antibodies to demonstrate the presence of exosomes. Secondly, the

anti CD3 antibody used as negative control for immobilising SD1 (precursor B

cell line) MV on the protein A/G UltraLink resin, needs to be validated. This

can be done by demonstrating its ability to immobilise MV from a T ALL cell

line where the anti CD19 antibody would serve as a negative control. Thirdly,

it is possible that not all precursor B ALL derived MV bear CD 19 antigen and

hence the technique may not catch all tumour derived MV. Fourthly, MV

cannot be reliably differentiated from apoptotic bodies at this point. Apoptotic

vesicles bleb off from the cell membrane, show phosphatidylserine

externalisation and contain fragmented DNA(310). A strategy that employs

Annexin V or Hoescst staining is unlikely to discriminate the two as both show

phosphatidylserine externalisation and the presence of mitochondrial DNA in

the MV is likely to give a false positive signal. I thought of immunoblotting MV

lysates for histones. Mitochondrial DNA (mtDNA) unlike the mammalian DNA

is packaged into discrete units know as “nucleoids” that are reported to be

devoid of histones(311, 312). However other publications have isolated

histones from mitochondria(313-315). An explanation for this apparent

discrepancy is due to the binding of histones to the outer mitochondrial

membrane where they have an unidentified function (315).

Nevertheless, the technique described in this chapter provides a starting point

in the attempt to isolate tumour derived MV from clinical samples. Once

validated, the technique offers the option of characterising tumour derived MV

in terms of its RNA, protein or lipid content. Such an approach may advance

our understanding of the potential role of MV in mediating a number of

biological processes such as cell survival and cell to cell communication.

Concluding remarks

174

Chapter 8: Concluding remarks

______________________________________________________________

Childhood acute lymphoblastic leukaemia is one of the great success stories

in the field of cancer treatment as well as in the field of translational research

aimed at understanding the tumour biology to improve outcome.

Therapeutically the regimens devised for childhood ALL have give rise to the

principles that drive current chemotherapeutic protocols for patients with

cancer and provide the rationale for combination therapy. Leukaemia biology

led to the first identification of somatic genetic change associated with cancer,

the fusion of BCR-ABL genes. It also remains the most successful example of

targetable genomic mutation, with the use of tyrosine kinase inhibitor in

Philadelphia chromosome positive leukaemias.

Serendipity has played a major role in the success story. By and large almost

all early chemotherapy agents proved to be effective as single agents in

childhood ALL. Initially the remission was short lived, but we discovered that

the prolonged use of combination chemotherapy could sustain remissions. No

new drugs have entered routine clinical use since the 1970’s. Risk

stratification and progressive intensification with the same agents has lead to

over 80% survival with current chemotherapeutic regimens (3), This success

comes at a price; that of treatment related short and long term toxicity (316-

321) that is balancing the relative risk of relapse (322). Over 25% of NCI

standard risk and 40-50% of high risk patients now report therapy related

severe adverse events whilst on therapy (personal communication, Professor

Ajay Vora). Treatment related deaths now match the numbers who relapse.

(personal communication, Professor Ajay Vora). Additionally, the disease is

heterogeneous with cure rates in cytogenetic high risk sub-groups (42) , still

less than 50% (323). Thus additional intensification with existing drugs is

unlikely to improve cure rates further. The focus has therefore shifted towards

finding new drugs and compounds, both to improve outcome and decrease

toxicity. So far, apart from the afore-mentioned tyrosine kinase inhibitors,

there has been little success in finding more effective anti-leukaemic agents.

Concluding remarks

175

Broad-spectrum new anti-cancer agents such as Clofarabine occupy a niche

in relapsed disease, though there is little data to show that any of the new

chemotherapeutic drugs have improved outcome when compared to the

existing ones. Given that ALL relapses occur after multi-agent therapy, it is

likely that the returning leukaemic cells have acquired broad-spectrum

chemoresistance. Thus non-specific chemotherapeutic agents are more likely

to increase toxicity than effect a cure..

As with other cancers, most pharmaceutical companies are now trying to

develop targeted therapy. This can be broadly classified into two types. The

first group consists of antibodies that target molecules expressed on the cell

surface. For example, we recently described the expression and targeting of

5-T4 in high risk childhood ALL(324). The more interesting result has been

with the use of a bi-specific anti CD19 antibody, Blinatumomab. In a phase I

study in adult patients with relapsed ALL, as a single agent, it achieved a 72%

CR rate. Almost all patients in CR achieved a molecular remission. However,

in a phase II study, the emergence of CD19 negative clones has been

reported. One of the disadvantages of Blinatumomab is that it is dependent on

the presence of active T cells and thus cannot be given with other cytotoxic

chemotherapeutic agents. It remains to be seen whether resurgent CD19

negative cells will respond to subsequent therapy or not.

The second group of targeted therapy consists of compounds that are directed

at somatic mutations that are peculiar to the cancer cell. An example is the

use of Gefitinib to target epidermal growth factor receptor (EGFR) expressing

lung and breast cancers. Whole genome sequencing in childhood ALL reveals

relatively few non-random mutations, they occur at about 6-8 per genome.

Mutations described occur primarily in genes regulating B-cell development

(e.g. IZKF, PAX5), cell cycle (p53, Rb) or are involved in normal cell signalling

(e.g. RAS). Thus clear targets for therapy in lymphoblasts have yet to be

identified.

Concluding remarks

176

Our data suggests that while we wait for more effective new agents, it is

possible to optimise therapy using current existing drugs, both to reduce

toxicity and to improve efficacy. The first one pertains to the drug ASNase.

Routine monitoring of ASNase could play a role in both the low risk and high

risk groups. In the former it might help in identifying patients who might benefit

from post induction intensification of therapy whereas in the latter it identifies

patients not achieving adequate ASNase activity levels after post induction

intensification of ASNase. In those with inadequate activity, one could

consider using alternative PEG formulations, the use of recombinant PEG-

ASNase or for example using additional daunorubicin in those receiving a 3-

drug induction. Additionally, the current UKALL2011 trial presents with the

opportunity to prospectively study the interaction of PEG-ASNase and

Dexamethasone and we may be able to further optimise the potential synergy

by optimising the scheduling of the two drugs.

An alternative approach at improving the outcome is directed to targeting the

microenvironment. In childhood ALL, there are a number of observations that

suggest the role of bone marrow microenvironment in supporting the tumour.

(325-327). ALL is peculiar amongst cancers where the best results have been

obtained by intensive use of the same class of drugs in a repetitive fashion,

followed by a prolonged phase of thiopurine therapy. The best outcomes are

observed in patients who develop repeated episodes of uncomplicated

cytopenias. This is illustrated by our observations with Mitoxantrone in

relapsed ALL (11).

At least a third of patients who experience late relapse can still be cured using

essentially chemotherapeutic agents belonging to the same classes as in

frontline protocols, albeit in more intensified relapse regimens. Thus treatment

failure cannot be attributed to intrinsic chemoresistance alone. Those patients

who relapse early require allogeneic transplant which not only provides fresh

source of haematopoietic stem cells but the conditioning therapy first disrupts

the haematopoietic stem cell niches. Our data shows BMSC mediated

chemoprotection to ALL cells involves chromatin regulation and pathways that

Concluding remarks

177

governs cell’s AKT activity, oxidative metabolism and apoptosis. Figure 8.1

proposes a conceptual model of how the bone marrow stromal cells might

protect leukaemic cells from chemotherapy by alteration of above mentioned

processes and suggests non cytotoxic approaches that can be combined with

conventional therapy to improve outcome and reduce toxicity.

Concluding remarks

178

Figure 8.1: Proposes a central role of BMSC derived soluble factors in conferring chemoprotection to the leukaemic cell. Blue

legends refer to molecules and blue arrows to their connections for which evidence exists for their role in altered cancer cell

1: Asparaginase

induced extracellular

Asparagine depletion

2: BMSCs secrete soluble factors: Primarily

or in response to chemotherapy

2a Asparagine ϯ 2b Cysteine*2c: Other: amino acids (AA), lipids, RNA, cytokines, MV, exosomes,

Exosomal: miRNA, small RNA, lipids, proteins, AA

Repletion of Asparagine

3a:Reprogramming of cell

metabolism & alteration of gene

expression, possibly mediated by

epigenetic changes #

BMSC

Leukaemic cell

Glutamate

α KGOAA

Aspartate

CS

Citrate

Isocitrate

NADPH NADP+

GSHGSSG

IDH2

3b: Increased uptake of

glutamine- number of pathways

(Beyond Warburg effect)

4a:GSH-Antioxidant

Glycine

GLS

ROS H2O

CysteineNAC

↓ROS

IDH2

α KG

3 c:IDH

Mutant

Type

effect

Glutamine

Glutamine

depleting

ASNasePEITC

TET2 DNA

hydroxylase

JmjC histone

demethylase

2HG2HG

3d:DNA CpG

hypermethylation

Hypomethylating agents

TET2 inhibitors

IDH inhibitors

NUCLEUS

CYTOPLASM

MITOCHONDRIA

Concluding remarks

179

metabolism and/or cell survival, either in ALL or in other cancers. In response to ASNase induced extracellular depletion of

asparagine, BMSC up-regulates and secretes asparagine: Ϯ =(99). BMSC confer chemoprotection by secreting cysteine, one of the

three building block of glutathione (GSH): * =(328). Work done by our group show the role of BMSC derived exosomes in

mediating chemoprotection. While this may not be the sole mechanism by which cells acquire chemoprotection, we propose a role

of BMSC derived exosomal miRNA in mediating downstream effects such as low levels of ROS, global decrease in gene

expression, up-regulation of histones (black dotted lines). The exact sequence of events is currently unknown. A number of

pathways such as PI3K and AKT are affected. We propose a central role of glutamine, one of the most important sources of energy

to a cancer cell after glucose and a key mediator of the beyond Warburg phenomenon(220) in mediating the downstream effects of

exosomal miRNA. While mutations in IDH resulting in generation of an oncometabolite, 2-hydroxyglutarate (2-HG) followed by DNA

hypermethylation is described in myelodysplastic syndromes (329-331), exosomal miRNA induced repression of wild type IDH may

induce similar downstream effects in ALL.

Legends in red propose new therapeutic targets. Attempts to block exosomal secretion by targeting Rab27a (figure 6.12) would

lead to unacceptable side effects as all cells secrete exosomes. Besides exosomes may not be the only secreted soluble factor that

mediates chemoprotection as suggested in figures 6.3 and 6.6. Likewise there are a number of miRNAs (figure 6.9) that could

target ROS and hence would not be an easy therapeutic target. Both the PI3K & AKT pathways are linked to a number of cellular

physiological processes. Targeting them is unlikely to be tumour specific and might be associated with unacceptable toxicity.

However, both the epigenetics and the oxidative metabolism of the leukaemic cells could be targeted to disrupt the host tumour

interactions. Use of hypomethylating agents such as Azacytidine have shown promise in acute myeloid leukaemia and

myelodysplastic syndrome (332) Early results show agents such as Piperlongumine and Phenethyl isothiocyanate (PEITC) can

Concluding remarks

180

selectively kill cancer cells by upregulating ROS levels (219, 333). These could be combined with agents such as ASNase that is

engineered to have enhanced glutaminase activity (334). Such an approach might deplete extra cellular glutamine and further

decrease the ability of tumour cells to scavenge ROS. Figure was adapted from:(220, 335, 336)

Concluding remarks

181

The work carried out in this thesis, shows that we still have a lot to learn about

the drug ASNase. In addition to asparagine depletion, our work suggests the

glutaminase activity of ASNase is essential for lymphoblast toxicity. The work

presented in this thesis also suggests that the glutaminase activity of ASNase

is potentiated by drugs that increase ROS. Of the currently used agents, only

the anthracyclines elevate ROS. Thus the conjunctive usage of anthracyclines

with ASNase in induction and intensification may well be a fortuitous one.

We describe that 1000 units/m2 of PEG-ASNase is sufficient for trial purposes

in childhood ALL. This results in adequate levels in most children and a lower

incidence of inactivation than previously reported. In this study, antibodies

were reported both against the PEG as well as against the native E.coli

ASNase. The incidence of silent inactivation was 4.7%. As all patients with

inactivation benefit from therapy with the Erwinia carotovera derivative

(Erwinase), this is an argument for the routine use of ASNase activity assays

in patients on therapy.

How do we decrease the incidence of antibodies against PEG-

ASNase? A new recombinant ASNase that is more tightly linked to PEG

reportedly has a longer half-life and may also be less antigenic. We have

previously shown that ASNase can be engineered to be less degradable and

more potent (98). Another option would be to identify the antigenic epitopes of

PEG-ASNase by exposing overlapping peptide fragments of PEG-ASNase to

T cells and performing T cell activation assays in patients who have

completed therapy. These antigenic epitopes can then be modified so that the

drug becomes less antigenic while retaining its efficacy at the same time.

Why the inactivation of PEG-ASNase and the development of hypersensitivity

are both more commonly observed in patients in regimen C remains

unresolved. One possibility is the frequency of administration, but the

experience from EsPhALL where Ph+ patients continue to experience a high

rate of hypersensitivity reactions but do not receive frequent ASNase suggest

Concluding remarks

182

that the tumour biology, by yet unidentified mechanisms, determines the

development of immune response as well. The UKALL 14 trial

(Clinicalrials.gov no NCT01085617) for adult ALL patients is studying the role

of anti-CD 20 antibody (Rituximab) is reducing the incidence of antibodies to

PEG-ASNase (personal communication, Professor David Marks). This is an

interesting approach as Rituximab could have a dual role of working as a

targeted therapy and being an immunosuppressant at the same time.

What are the mechanism of inactivation of Asparaginase which are unrelated

to antibody formation? Currently this remains unknown. A clue that proteases

may govern the pharmacokinetics of ASNase comes from animal studies.

Mice have a more complex degradome compared to humans (337) and the

half life of ASNase in mice is much shorter compared to that in humans. To

answer the question of whether proteases such as AEP and CTSB do mediate

in-vivo inactivation of ASNase, one can develop techniques that can

specifically quantify catalytically active proteases in leukaemic cells. Future

studies need to additionally address the question of where the in-vivo

inactivation occurs. Proteases containing, secretory, tumour derived

microvesicles may well mediate the degradation of ASNase in the extracellular

compartment.

A number of other clinical features remain unresolved, particularly the issue of

toxicities peculiar to ASNase. Hypersensitivity we have discussed.

Development of pancreatitis remains a problem as the drug in all forms has to

be discontinued, potentially affecting survival. We do not why some patients

develop pancreatitis (338, 339), though there is evidence from animal models

to suggest that the pancreas is one organ in the body that suffers the most

from asparagine depletion.

The other problem is that of thrombosis. I would like to speculate on the

mechanism of thrombosis in childhood ALL and the possible role of MV in

supporting venous thrombosis, not only in ALL but also in other cancers.

Concluding remarks

183

Figure 8.2 depicts a concise summary of normal processes involved in

regulating coagulation during homeostasis and Figure 8.3 show mechanisms

involved in clot formation in response to vessel injury.

Currently there are no clinical predictive biomarkers for thrombosis seen in

childhood ALL. A common pre-requisite for thrombin generation is a

phosphatidylserine platform on which both the tenase and prothrombinase

complex are formed (Figure 8.3). In the context of either a low or normal

platelet count, the question is who substitutes the physiological role of

activated platelets during induction phase of the treatment? MV have been

shown to have phosphatidylserine externalisation (303-305) and to express

tissue factor on their surface (340-342). I decided to investigate if the tumour

derived MV can substitute the role of activated platelets. If this was the case

then quantifying tumour derived MV in diagnostic bone marrow plasma by

flow cytometry may predict the risk of thrombosis in children undergoing ALL

therapy. I chose to test this hypothesis using dilute Russell Viper Venom Time

(dRVVT). To the best of my knowledge, such an approach has not been

reported before. The result shown in table 8.1 is only a pilot experiment done

once to demonstrate the proof of the concept. MV used in this experiment

were pelleted from 10 ml of SD1 supernatant. The experiment will clearly

have to be repeated, ideally with titrating amount of SD1 MV and then after

spiking standard plasma with patient derived MV. However, if this approach

works, its advantage over measuring parameters such as tissue factor or

generation of thrombin on the surface of tumour derived MV is that this would

be a functional assay that not only measures the thrombogenic potential in

patient plasma but offers an explanation to the mechanism of thrombosis in

childhood ALL. The other priority would be to validate a flow cytometry based

assay in order to quantify the MV. Once this is done, spiking standard plasma

with a fixed amount of MV will generate a more meaningful dRVVT times that

would hopefully be able to predict thrombosis that occurs during induction

phase in ALL.

Concluding remarks

184

Table 8.1: MV participate in coagulation. Standard plasma when spiked with

MV result in shortening of dRVVT times and by blocking the

phosphatidylserine sites by prior incubation with Annexin V, their efficiency in

coagulation as measured by dRVVT times, is limited. dRVVT test was done

on Stago STA-R Evolution Analyser. The dRVVT reagent (STA®-Staclot

dRVV Screen 5-ref –00333) was supplied by Stago. The standard plasma (SP)

pool was supplied by Siemens.

dRVVT (sec)

Standard plasma (SP) 48.9

Standard plasma plus SD1 MV (SPMV) 40.9

Standard plasma plus SD1 MV blocked with annexin (SPMV-A) 43.1

% correction of dRVVT time [(SP-SPMV)/SP]*100

SPMV 18%

Effect of Annexin 11%

Concluding remarks

185

Figure 8.2: Concise summary Central role of intact endothelial to preventing

thrombin generation. Tissue factor bearing extra-vascular cell generates

activated IXa, Xa and limited amount of thrombin (basal, priming phase of

coagulation). IXa enters the vascular compartment but is unable to form a

tenase complex with VIII. VIII is bound to globular form of vWF. Xa that

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Concluding remarks

186

generates limited amount of thrombin is inactivated by TFPI in the

extravascular space. Endothelium prevents platelet activation directly by

secretion of NO & PGI2 and indirectly via endonucleotidase that inactivates

ADP. In resting state, platelet membrane has phosphatidlyserine on the inside

and phosphatidlycoline on the surface. Any excess of thrombin either gets

inactivated by anti-thrombin bound to heparan-sulphate proteoglycan or

associates with thrombomodulin and endogenous protein C receptor and

converts protein C to activated protein C (APC). APC inactivates any

circulating activate factor V (Va) and factor VIII (VIIIa).

Concluding remarks

187

Figure 8.3: Mechanisms involved in clot formation in response to vessel injury.

Vascular injury and damage to endothelium leads to shear stress and a

conformational change in vWF which mediates initial indirect binding of

platelets to collagen and “slowing” of platelets. This is followed by change in

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Concluding remarks

188

platelet shape and a stable, direct binding of platelets to collagen via integrin

receptors; inside out and outside in signalling in platelets that results in

generation of platelet agonists such as ADP, thromboxane A2 and thrombin.

These agonists can then activate other platelets. Thrombin forms a crucial

role in generating Va and VIIIa. Activated platelets having phosphatidlyserine

externalisation, in association with Ca (not shown) provides a crucial platform

on which Gla domains of Factor IXa and Va dock to sequentially generate

tenase (IXa/VIIIa) and prothrombinase (Va/Xa) complexes. Prothrombinase

complex is responsible for the final ‘burst’ of thrombin that cleaves of the

Fibrinopeptide A and B (not shown) from fibrinogen to form fibrin and

eventually a fibrin clot.

References

189

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PUBLICATIONS:

2010 Lucas G, Culliford S, Green F, Sidra G, Calvert A, Green A, Harrison P,

Harvey J, Allen D, Smilie D, Masurekar A, Marks D, Russell N, Massey E.

Recipient-derived HPA-1a antibodies: a cause of prolonged thrombocytopenia

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2010 Parker C, Waters R, Leighton C, Hancock J, Sutton R, Moorman A,

Ancliff P, Morgan M, Masurekar A, Goulden N, Green N, Revesz T,

Darbyshire P, Love S, Saha V. Effect of Mitoxantrone on outcome of children

with first relapse of acute lymphoblastic leukaemia (ALL R3): an open-label

randomised trial. The Lancet, Dec; 376 (9757):2009-17.

2011 Holland M, Castro F, Alexander S, Smith D, Liu J, Walker M, Bitton D,

Mulryan K, Ashton G, Blaylock M, Bagley S, Connolly Y, Bridgeman J, Miller

C, Krishnan S, Dempsey C, Masurekar A, Stern P, Whetton A, Saha V.

RAC2, AEP, and ICAM1 expression are associated with Central Nervous

System (CNS) disease in mouse model of pre-B childhood acute

lymphoblastic leukemia. Blood. Jul;113 (3):638-649.

PEER-REVIEWED ABSTRACTS

2010 Masurekar A, Parker C, Choudhuri S, Leighton C, Hancock J, Sutton

R, Moorman A, Ancliff P, Morgan M, Goulden N, Green N, Revesz T,

Hoogerbrugge P, Darbyshire P, Love S, Saha V. Mitoxantrone

improves the outcome of children with central nervous system involvement at

First relapse of acute lymphoblastic leukemia-results of the international

ALLR3 study. Abstract number 3303. American Society of Hematology

Annual Meeting. For presenting this poster, I received a 2010 ASH Travel

award.

2011 Fong C, Parker C, Hussain A, Liu J, Essink M, Kuehnel H, Lancaster D,

Pridham G, Payne D, O’Horo C, Krishnan S, Hancock J, Goulden N,

Achievements

214

Moorman A, Richards S, Vora A, Saha V, Masurekar A. Intramuscular PEG-

Asparaginase (PEG-ASNase) at 1000 U/m2 achieves adequate trough activity

levels in the majority of patients treated on the UKALL 2003 Childhood Acute

Lymphoblastic Leukaemia (ALL) protocol. Abstract. American Society of

Hematology Annual Meeting. The abstract will be presented by Caroline

Fong a 4th year medical student, who I supervised in the laboratory during her

MRes project. She has received a 2011 ASH Travel Award and her MRes

project report was ranked as first..

CHAPTER IN BOOK

2011 Krishnan S, Masurekar A and Saha V. Identifying targets for new

therapies in children with acute lymphoblastic leukemia. New Agents for the

treatment of acute lymphoblastic leukemia; Saha V, Kearns P (eds.); Springer

Science, (ISBN: 978-1-4419-8458-6)

MANUSCRIPT UNDER PREPARATION

Masurekar A, Parker C, Choudhuri S, Leighton C, Hancock J, Sutton R,

Moorman A, Ancliff P, Morgan M, Goulden N, Green N, Revesz T,

Hoogerbrugge P, Darbyshire P, Love S, Saha V. Mitoxantrone improves the

outcome of children with central nervous system involvement at First relapse

of acute lymphoblastic leukaemia-results of the international ALLR3 study.

Liu J, Masurekar A, Holland M, Johnson S, Krishnan S, Alexander S, Parker

C, Dempsey C, Saha V. Bone Marrow microenvironment regulates drug

resistance in acute lymphoblastic leukaemia via exosomal transfer of miRNA

and regulation of reactive oxygen species.

Masurekar A, Fong C, Parker C, Hussain A, Liu J, Essink M, Kuehnel H,

Lancaster D, Pridham G, Payne D, O’Horo C, Krishnan S, Hancock J,

Goulden N, Moorman A, Richards S, Vora A, Saha V. Intramuscular PEG-

Achievements

215

Asparaginase (PEG-ASNase) at 1000 U/m2 achieves adequate trough activity

levels in the majority of patients treated on the UKALL 2003 Childhood Acute

Lymphoblastic Leukaemia (ALL) protocol.

Masurekar A, Fong C, Parker C, Hussain A, Liu J, Essink M, Knehnel H,

Lancaster D, Pridham G, Payne D, O’Horo C, Krishnan S, Saha V. Role of

Asparaginase in Relapsed Acute lymphoblastic leukaemia (ALL).

Appendix

216

Appendix 1: Reagents Reagents Source

0.1 M DTT, D0632 Sigma Aldrich

10mM AHA A6508 Sigma Aldrich

8 hydroxyquinoline H6878-100G Sigma Aldrich

Acetic Acid 3% with methylene blue stored at RT 07060 Stem Cell Technologies

Aldehyde/Sulfate Latex, 4%w/v 4μm A37304 Invitrogen

Ammonium persulphate 17-1311-01 Amershem Biosciences

Annexin V-FITC, catalog number 556547 BD Pharmingen

Beta mercaptoethanol M7522 Sigma Aldrich

Biotinylate polyclonal goat anti-human Legumain Antibody; 50μg; lyophilized Catalog no BAF2199 R&D Systems

bovine serum albumin Sigma Aldrich

bromophenol blue, B8026 Sigma Aldrich

CelLytic M C2978 Sigma Aldrich

Chloroform:Isoamyl alcohol 24:1 C0549-1QT VWR International Ltd

Complete Protease Inhibitor Cocktail , Catalogue number 11697498001 Roche

DEPC treated water, AM9915G Ambion

Diluent C CGLDIL-6X Sigma Aldrich

DMSO D8418 AnalaR

dNTP Mix 10mM , PCR Grade Catalog no 18427-013 Invitrogen

Ethanol absolute E/0650DF/17 Thermo Scientific

First-Strand Buffer (250mM Tris-HCl, pH 8.3 at R.T; 375 mM KCl; 15mM MgCl2) Invitrogen

FITC Annexin V, Catalogue number 51-65874X BD Biosciences

Foetal bovine serum, S1830500 Biosera

Glycerol 100mL Cat No G5516-100mL Sigma Aldrich

Glycine G7126 Sigma Aldrich

Horseradish Peroxidase conjugated Donkey Anti-goat IgG antibody (sc-2020) Santa Cruz Biotechnology

Hydrochloric acid; 43,557 Sigma Aldrich

Igepal CA-630, Catalogue number 11 697 498 001 Roche

Appendix

217

Iodoacetamide, 1149-56 Sigma Aldrigh

Lymphoprep TM

stored at RT wrapped in foil

Axis-Shield PoCAS

LysoTracker® Green DND-26, Catalogue number L7526 Invitrogen

Methanol M/4000/17 Fisher Chemical

Monoclonal mouse anti human Actin antibody, Catalogue number A5441, Clone AC-15 Sigma-Aldrich

Monoclonal mouse anti human anti-CD3 antibody, Catalogue number MA1-7639, Clone RIV9 Thermo Scientific

Monoclonal mouse anti human anti-MMP2 antibody, Catalogue number 303602, Clone F14P4D3 Biolegend

Monoclonal mouse anti human anti-MMP9 antibody, Catalogue number 635002, Clone F11P2C3 Biolegend

Monoclonal mouse anti human CD19 antibody, Catalogue number 555410, Clone HIB19 BD Pharmigen

Monoclonal mouse anti human CD81 antibody, Catalogue number 349501, Clone 5A6 Biolegend

Monoclonal mouse anti human TSG101 antibody, Catalogue number ab8319, Clone 4A10 Abcam

Monoclonal mouse anti-human Legumain Antibody; 100μg; lyophilized Catalog no MAB2199, Clone 312114 R&D Systems

Monoclonal rabbit anti human CD63 antibody, Catalogue number ab8319, Clone MEM-259 Abcam

PBS tablets P44171 Sigma Aldrich

Phosphate-buffered saline, Mg/Ca free, stored at RT Laboratory Services, PICR

Polyclonal goat anti human CD19 antibody, Catalogue number SC-8498 Santa Cruz Biotechnology

Polyclonal rabbit anti human Cathepsin B antibody, Catalogue number BML-SA361 BioMol Alexis

Polyclonal rabbit anti human CD11a antibody, Catalogue number ab52895 Abcam

Polyclonal rabbit anti human LAMP1 antibody, Catalogue number ab24170, Abcam

Polyclonal rabbit anti human VAMP3 antibody, Catalogue number PA1-767A Thermo Scientific

Pro-Cathepsin B Assay Diluent RD1-34 Concentrate (Part 895865) R&D Systems

Pro-Cathepsin B Calibrator Diluent RD5-34 Concentrate (Part 895828) R&D Systems

Pro-Cathepsin B Color Reagent A ( Part 895000; Stabilized hydrogen peroxide) R&D Systems

Pro-Cathepsin B Color Reagent B (Part 895001; Stabilized chromogen- tetramethylbenzidine). R&D Systems

Pro-Cathepsin B Conjugate (Part 892537) R&D Systems

Pro-Cathepsin B Microplat (Part 892536) coated with mouse monoclonal antibody against pro-Cathepsin B R&D Systems

Pro-Cathepsin B Standard (Part 892538) R&D Systems

Pro-Cathepsin B Wash Buffer Concentrate (Part 895003) R&D Systems

Propan-2-ol p/7490/17 Fisher Chemical

Protein A/G UltraLink resin PN53132 Thermo Scientific

Appendix

218

ProtoGel 30%(w/v) Acrylamide 0.8% (W/v) bis-acrylamide solution AA EC 810 National Diagnostics

Purified recombinant Annexin V, Catalogue number 51-65871A BD Biosciences

Random Hexamers 20μg, Catalogue no C1181 Promega

Reagent A Alkaline copper tartrate solution 500-0113 Biorad

Reagent B Dilute folin reagent 500-0114 Biorad

Reagent diluent concentrate DY995 R&D Systems

Reagent S 500-015 Biorad

RestoreTM

western blot stripping buffer, 46430 Thermo Scientific

RNAase Zap, R2020 Sigma Aldrich

RPMI- 1640 ultra glutamine 5965 Lonza

SDS. Cat number L3771-100g Sigma Aldrich

Sodium Bicarbonate 99.7-100.3% Catalogue number S7277 Sigma Aldrich

Sodium Carbonate Catalogue number S7795 Sigma Aldrich

Sodium chloride, Catalogue number S7653 Sigma-Aldrich

Streptavidin-Horse Radish Peroxidase (HRP) Catalogue no DY998 R&D Systems

Sulphuric acid; 25,810 Sigma Aldrich

Super Signal West Pico (Reagent A&B) 37070 Thermo Scientific

SuperScript™ II Reverse Transcriptase, Conc: 200U/μl, Cataloge No. 18064-071 Invitrogen

SuperSignal®West Dura Extended Duration Enhanced Chemiluminescent Substrate Kit 34076 Thermo Scientific

TaqMan Universal PCR Master Mix Part number 4304437 Applied Biosystems

Trichloroacetic acid, T9159 Sigma Aldrich

Trizma base 1KG, catalogue no T1503 Sigma Aldrich

TRIzol® (store at 4°C) 15596-C18 Invitrogen

TRIzol® LS (store at R.T.) 10296028 Invitrogen

Trypan blue 0.4%, T8154 Sigma

Tween® 20 P1379 Sigma Aldrich

Appendix

219

Appendix 2: Buffers: 1) 0.1% NP-40 lysis buffer/Protease inhibitor solution:

(100ml solution)

Tris base 50mM 0.606g

Sodium chloride 150mM 0.88g

Adjust pH to 8.0 with concentrated HCl

Add distilled/deionised (D/D) water to make up the volume to 100ml

Add 100μl Igepal CA-630

Filter the solution through a 0.2 micron filter

Add 2 Complete Protease Inhibitor Cocktail tablet (Roche), mist to dissolve

and store in 1ml aliquots in microcentrifuge tube at -80°C

2) ELISA coating buffer, 0.05 M Carbonate buffer pH 9.6:

Dissolve 0.795 g of Sodium Bicarbonate and 1.465 g of Sodium Carbonate in

500 ml of D/D water.

Filter the solution through 0.2 micron filter.

Store the buffer in aliquots of 10mls at -20°C

3) Phosphate Buffer Saline (PBS)

Dissolve 5 tablets of PBS in 1 litre of D/D water.

Filter the solution through a 0.2 micron filter

Store the solution at 4°C for a maximum of 2 weeks.

4) ELISA wash Buffer (PBST):

Add 500μl of Tween® 20 to 1 litre of PBS.

Filter the solution through a 0.2 micron filter.

Store the solution at 4°C for up to 2 weeks.

5) ELISA blocking buffer (1% Bovine Serum Albumin PBST)

Add 27.7μl of Tween® 20 to 50ml of D/D water.

Pass through a 0.2 micron filter.

Take 45mls of the above solution and add 5ml of reagent diluent concentrate.

Appendix

220

6) 10% SDS

Dissolve 10 g of SDS in D/D water to make up a total volume of 100ml. Store

at R.T.

7) Resolving gel buffer (1M Tris HCl pH 6.8)

Dissolve 12.1g of Tris base in 80 ml of D/D water.

Adjust pH to 6.8 with concentrated HCl.

Bring up the total volume to 100 ml by adding D/D water.

8) Staking gel buffer (1.5M Tris HCl pH 8.8)

Dissolve 27.23 g of Tris base in 80 ml of D/D water.

Adjust pH to 8.8 with concentrated HCl.

Bring up the total volume to 150 ml by adding D/D water.

Pass through a 0.2 micron filter.

9) Resolving gel (10%)

For a 20 ml volume, add

D/D water 8.00 ml

Protogel 30% bis-acrylamide solution 6.60 ml

Resolving gel buffer 5.00 ml

SDA 10% 0.20 ml

Ammonium persulphate (10%)*+ 0.20 ml

TEMED* 0.008 ml

10) Stacking gel

For a 10 ml volume, add

D/D water 6.80 ml

Protogel 30% bis-acrylamide solution 1.70 ml

Stacking gel buffer 1.25 ml

SDS 10% 0.10 ml

Ammonium persulphate 10%*+ 0.10 ml

TEMED* 0.01 ml

* Added just before use

Appendix

221

+ 0.5g in 5 ml of D/D water, stored at -20°C in 500 μl aliquots.

11) SDS Reducing buffer/Loading buffer

For a 10ml of x5 solution

2M Tris HCl pH 6.8 1.25 ml

10% SDS 1.00 ml

Glycerol 3.00 ml

0.5% Bromophenol blue 0.20 ml

D/D water 5.55 ml

Store at R.T. Add 50 μl of β mercaptoethanol to 950 μl of SDS reducing buffer

just before use. One part of above buffer is mixed with 4 parts of sample

lysates diluted in water to ensure loading of at least 10 μg of protein in 20 μl

volume per well.

12) Running buffer x10

Dissolve in 800 ml of D/D water

Tris base 30.3 g

Glycine 144.0 g

SDS 10.0 g

Bring up the total volume to 1 litre by adding D/D water

Before use, dilute with D/D water to achieve running buffer x1

13) x10 Transfer buffer (Before use dilute 100 mls to 700 ml of D/D water and

add 200 mls of methanol and 3.75ml of 10% SDS)

Dissolve 58.2g to Tris Base and 29.3 g of Glycine in 1L of D/D water. Store at

R.T.

14) Blocking buffer - 5% (w/v) solution of Non-Fat Milk

Dissolve 2.5 g of non fat skimmed mild powder (Marvel, Premier Foods, UK)

into 50 ml wash buffer (PBS-Tween® 20 0.1%).

15) Blocking buffer when using biotinylated antibodies

Dissolve 5 gm of BSA in 100 ml of wash buffer

Appendix

222

16) Blocking buffer when using the LICOR detection system

Dissolve 5 g of BSA into 100 ml of PBS (no tween)

Appendix

223

Title: Appendix 3: ALL2003 and ALLR3 Sample Processing

Document

No:

Version

No:

2 CopyNo/Hold

er:

Issue Date: 22/12/20

08

Review

Date:

Issued by: Rebecca

Cole

INTRODUCTION

Serial research samples are collected at diagnosis and various time-

points throughout treatment:

Samples included peripheral blood-ACD, bone marrow aspirate, and

cerebrospinal fluid.

Processed aliquots included:

Peripheral blood plasma + PIC (PBP+)

Peripheral blood plasma + TRIzol® (PBPT)

Bone marrow plasma + PIC (BMP+)

Bone marrow plasma + TRIzol® (BMPT)

Peripheral blood cells + TRIzol® (PBCT)

Peripheral blood cells + CelLytic M + PIC (PBCLB)

Peripheral blood cells + cryoprotectant (PBC)

Bone marrow cells + TRIzol® (BMCT)

Bone marrow cells + CelLytic M + PIC (BMCLB)

Bone marrow cells + cryoprotectant (BMC)

Cerebrospinal fluid supernatant (CSFS)

Cerebrospinal fluid cells + TRIzol® (CSFCT)

Appendix

224

This SOP applies to samples received with the following proformas:

Asparaginase and AEP Study Form ALL2003 – Samples stored for the

ALL2003 LASP study. Additional samples not currently

required will be banked for future studies.

UKALL2003 Storage Request Form – Samples to be banked for future

studies. These should ONLY be received from the Royal

Manchester Children’s Hospital.

Asparaginase and AEP Study Form ALLR3 – Samples stored for the

ALLR3 LASP study. Additional samples not currently

required will be banked for future studies.

ALLR3 Storage Request Form – Samples to be banked for future

studies.

EsPhALL Storage Request Form – Samples should be sent to The

Patterson Institute. Contact Shekhar or Ashish (see 1.4.2).

Duplicate samples taken on the same day but with different

timepoints must NOT be pooled. This includes UKALL2003 Day

28/ALL2003 LASP Day 30 samples.

Contact information for the Patterson Institute:

Catriona Parker – for issues concerning samples

0161 446 3093

[email protected]

Ashish Masurekar – for issues concerning the protocol

0161 446 3234

[email protected]

Scope

This SOP applies to all personnel processing samples from the

ALL2003, ALLR3, and EsPhALL studies.

Responsibilities

Sample storage and documentation:

All samples awaiting collection at reception should be stored at 4C.

Appendix

225

Sample forms must be completed and filed in external reference order,

together with corresponding proformas.

Samples must be logged in before being stored.

Aliquot ID’s must be scanned into the correct location of the

corresponding box plan.

Aliquots must be correctly located in LIMS.

PBC and BMC aliquots to be left in ‘Mr Frosty’ at -80C overnight

must be located to the correct position within freezer 31 freezer

and then moved to freezer 31 the following day. Aliquots must

be correctly located in LIMS and scanned into the corresponding

box plan.

General guidelines:

Always work in a class II biosafety cabinet.

Observe strict aseptic techniques including wearing gloves and lab

coats. Use dedicated pipettes and filter tips.

Ensure appropriate labelling of all samples.

related documents

LAB/005/5 Sample Receipt, Destruction and Sample Requests (NOT sections

6.1, 6.2 or 6.9).

LAB045/2 Allocating Samples to Locations.

health and safety

Observe standard precautions regarding organic solvent, biohazard,

and sharps disposal.

Observe standard safety precautions when storing samples in liquid

nitrogen.

Equipment/Materials/Reagents

Equipment

Equipment Manufacturer CIGMR ID#

Refrigerated bench-top centrifuge Jouan 275/276

Refrigerated microcentrifuge Sigma 438

Appendix

226

Dedicated 1ml, 100l and 20l pipettes Star Labs

(Nichiryo)

Unknown

Light microscope Olympus 40

‘Mr Frosty’ containing 250ml isopropanol

(refreshed after every 5 uses. Store at R.T

when not in use)

Nalgene n/a

Liquid nitrogen freezer (-192C) MVE Cryogenics 78

-20◦C freezer Liebherr 325

-80◦C freezer Sanyo 298

Refrigerator Wolf Labs (Lech) 470

Materials

Material Supplier Cat#

1.5ml microfuge tubes (sterilised by

autoclaving)

Greiner Bio-One 616201

Sterile 15ml screw-cap (Falcon) tubes Greiner Bio-One 188271

Sterile Cryo.sTM

2ml cryovials Greiner Bio-One 122263

1ml, 200l and 20l filter tips Star Labs (Nichiryo) S1122-1830

S111-1806

S1120-1810

Sterile pastette® pipettes (10 pack) Alpha Labs LW4113

C-Chip disposable haemocytometers Labtech DHC-N01

Biohazard incineration carton Scienceware 132050001

Designated phenol-chloroform (TRIzol) waste

container

VWR Unknown

Ice n/a n/a

Reagents

Reagent Supplier Cat#

Protease inhibitor cocktail in molecular biology

Grade H2O (store in 20µl and 25µl aliquots in

cryovials at-20C). Remaining PIC should be

stored in 2ml aliquots at -20C to prevent

multiple freeze-thaw cycles

Sigma P2714

LymphoprepTM

(store at R.T wrapped in foil) Axis-Shield PoC AS 1053980

Mg/Ca-free Phosphate-buffered saline (store at

R.T)

Invitrogen 20012019

Acetic acid 3% with methylene blue (store at

R.T wrapped in parafilm)

Stem Cell

Technologies

07060

0.4% Trypan blue Sigma

T8154

TRIzol® LS (store at R.T) Invitrogen

10296-010

CelLytic M (store at 4C) Sigma

C3228

Appendix

227

Cryoprotectant: 10% DMSO 90% foetal calf

Serum (store at -20◦C in 5ml aliquots). Foetal

calf serum should be stored in 45ml aliquots at

-20C

AnalaR

Sigma

103234-L

F9665

Gigasept®FF Schulke & Mayr 19227-A

PROCEDURE

Samples should be KEPT ON ICE throughout.

Sample documentation

Log samples into the file S:/childhood leukaemia/incoming samples.xls

(password ‘chl’). Include the following information:

Week beginning

Date

Study (LASP Diagnostic, LASP F/U, UKALL2003, ALLR3

LASP, ALLR3 Storage, or ESPHALL)

Centre name

Patient initials

External reference

Timepoint

Date sampled

Time arrived

Advance notification (if any)

Any notes (e.g if a follow-up sample arrived by courier

instead of Royal Mail)

Complete the corresponding patient information list (ALL2003 or

ALLR3) at S:/childhood leukaemia/study name patient list.xls

(password ‘chl’) as follows:

New samples: patient initials, trial, trial number (if known),

date sampled, and centre name. Assign the next

consecutive external reference in the format: LA001 for

ALL2003 patients or 001 for ALLR3.

Follow-up samples: date sampled.

Appendix

228

Any issues with the sample/proforma or for samples which

arrive > 48 hours following collection, contact Catriona (see

1.4.1) and make a note on the patient list.

Complete a sample information form. This can be obtained from

L:/CIGMR/project folders/childhood leukaemia/sample

information form.doc. File in the corresponding folder in

external reference order, together with the accompanying

proforma. Include the following information:

Trial

Trial number (if known)

Patient initials

Timepoint

Date sampled

Date of last asparaginase treatment (not necessary for

diagnostic samples or for tissue banking)

External reference (see 7.1.2)

Date of birth (if known)

Date sample arrived and processed

Your initials

Processing samples where ONLY plasma is required

Process as soon as possible. Keep at 4C prior to processing.

Centrifuge the sample tube at 2,000g for 10 minutes at room

temperature to obtain a plasma supernatant (programme 31).

Remove the upper ¾ of the plasma supernatant with a sterile Pastette

and dispense 1ml aliquots into sterile cryovials containing 20 µl

of PIC. Label tubes as follows:

External reference

Sample type (see 1.1.2 for abbreviations)

Date sampled

Login and store samples as per 7.6.

Processing samples where plasma AND cells are required

Appendix

229

Process as soon as possible, however samples may be left up to 48 hours

following collection. Keep horizontally at room temperature prior

to processing.

Centrifuge the sample at 200g for 10 minutes at room temperature to

obtain a plasma supernatant (programme 39 on centrifuge

#276).

Remove the upper ¾ of the plasma supernatant with a sterile Pastette

and dispense into sterile CONICAL-BOTTOMED 1.5ml

microcentrifuge tubes.

Centrifuge plasma in a chilled microcentrifuge at 15,000g for 10

minutes.

Carefully aspirate plasma supernatant into sterile labelled (see 7.2.3)

cryovials as follows:

1 x 300l. Add 1ml TRIzol and vortex mix.

900l aliquots into cryovials containing 20l of PIC.

Keep plasma tubes on ice and proceed to 7.4.

Isolating mononuclear cells (MNCs)

Process immediately following step 7.3.

Add 3-4 ml PBS to the cellular sediment and transfer to a fresh sterile

15ml Falcon tube. Add PBS to a final volume of 10ml. Gently

invert to mix.

Using a sterile Pastette, gently layer the 10ml cell suspension over 5ml

of LymphoprepTM

in a 25ml sterile universal.

Centrifuge at 400g for 30 minutes at 20C using a NO BRAKE

deceleration setting (programme 35 centrifuge #276).

Using a sterile Pastette, carefully isolate the MNC layer formed at the

interface of Lymphoprep with PBS and place contents in a

fresh sterile 15ml Falcon tube. Add PBS up to 15ml. Note:

isolate as much of the MNC layer as possible - RBC

contamination is acceptable (make a note on the sample

information form if this is particularly apparent).

Remove 50l from each cell suspension and place into sterile

microcentrifuge tubes.

Appendix

230

Centrifuge the Falcon tubes containing cell suspensions at 400g for 10

minutes at 20C (programme 36).

Aliquot samples from 7.4.6 into sterile microcentrifuge tubes for cell

counting as follows:

Normal MNC interface (most PB/follow-up BM samples):

Dilute 10l of cell suspension with 10l of 3% acetic acid-

methylene blue for a 1 in 2 dilution

Thick MNC interface (most diagnostic BM samples): Dilute

10l of the cell suspension with 40l of PBS in a sterile

microcentrifuge tube. Further dilute 10l of this sample in

10l of 3% acetic-acid methylene blue for a 1 in 10 dilution

Greater dilutions may be required if the cell count exceeds 50-

60 cells per large square

To assess cell viability, dilute 10l of the cell suspension with 10l of

0.4% Trypan blue in a sterile microcentrifuge tube.

Dispense 10l of the diluted sample from 7.4.8 into chamber A of a

disposable haemocytometer.

Dispense 10l of the diluted sample from 7.4.9 into chamber B of the

same disposable haemocytometer.

Determine the total cell count as follows:

Count the total number of cells within the 4 large squares

of chamber A (red blood cells are lysed by the methylene

blue and so should not be visible)

Divide by 4 to obtain an average count

Multiply by the dilution factor (e.g 2 or 10)

Multiply by the total volume of the cell suspension (usually

15ml)

Multiply by the volume correction constant of 104

Record cell count on the sample information sheet

Determine cell viability as follows:

Count 100 cells within one of the large square of chamber B

– note the number of blue (unviable) cells

Record the percentage of viable cells on the sample

information sheet

Appendix

231

Low viability (<90%) should be recorded in the ‘comments’

section of LIMS during sample login

Cells are processed dependent upon cell count:

Discard the supernatant

Resuspend the cell pellet in the volume of PBS specified in

table 1

Split cell suspension into sterile 15ml Falcon tubes as

described in table 1

Note: Cells extracted from the final follow-up sample

(intrathecal MTX) for the ALL2003/ALLR3 LASP studies

should ONLY be stored in cryoprotectant

Split cell suspension as follows:

Cell Count Volume of PBS to

resuspend pellet in

Cells +

TRIzol®

Cells +

CelLytic M

Cells +

cryoprotectant

10×106 1ml 1 x 1ml (10x10

6)

10-20×106 2ml 1 x 1ml (10x10

6) 1 x 1ml (10x10

6)

>20×106 10x10

6 cells/ml 1 x 1ml (10x10

6) 1 x 1ml (10x10

6) 1 x Xml

Table 1

Centrifuge the cell suspensions at 400g for 10 minutes at 20C

(programme 36).

Discard the supernatant, leaving behind a small volume (≤150l).

Gently resuspend the pellet with a sterile Pastette.

Process aliquots as follows:

Cells + TRIzol®

Add 1ml of TRIzol® to the aliquot and vortex mix

Dispense into a sterile labelled (see 7.2.3) cryovial

Cells + CelLytic M

Appendix

232

Add 125l of chilled CelLytic M to the cells and mix well

Dispense into a sterile labelled (see 7.2.3) cryovial containing

25µl of PIC and place immediately on ice

Cells + cryoprotectant

Estimate the volume of cryoprotectant required:

For cell counts <100x106 add 1.5ml per 10-20x10

6 cells

For cell counts >100x106 add 1.5ml per 30-50x10

6 cells

Do not exceed 50x106 cells per 1.5ml of cryoprotectant

Using a sterile pastette add 1 drop of cryoprotecant to the cell

suspension every 10 seconds for 1 minute and then slowly add

the remaining volume along the sides of the tube. Regularly

mix the suspension by gently agitation

Dispense 1ml aliquots into sterile labelled (see 7.2.3) cryovials

Appendix

233

Make a note of cell count per vial on the sample information form.

Login and store samples as per 7.6.

Processing cerebrospinal fluid (CSF)

Process as soon as possible. Keep at 4C prior to processing.

Aspirate contents into a sterile 1.5ml microcentrifuge tube.

Centrifuge in a chilled microcentrifuge at 10,000g for 10 minutes.

Record on the sample information form whether a pellet was seen and

if it was tinged with blood.

Dispense the supernatant into 500μl aliquots in sterile labelled (see

7.2.3) cryovials. If the sample volume exceeds 1ml, dispense

into 1ml aliquots.

Resuspend the pellet in 100μl TRIzol® by vortexing. Should the

solution remain excessively viscous add an additional 400μL of

TRIzol® and vortex. Dispense into a sterile labelled (see 7.2.3)

cryovials.

Login and store samples as per 7.6

Sample login and storage

Samples must be kept on ice and logged in as soon as possible.

Log aliquots into LIMS by following the corresponding workflows:

Peripheral blood – ACD

Bone marrow aspirate

Cerebrospinal fluid

Aliquots should be logged into the relevant study in LIMS:

ALL2003 samples into the L-asparaginase and AEP study

ALLR3 samples into the Childhood leukaemia study

Input the date sampled into LIMS

Input the following information in order into the ‘comments’ section

in LIMS:

Timepoint: ‘Diagnosis’, ‘Day 28’ etc

Appendix

234

Proforma type if sample is for tissue banking:

‘UKALL2003’ or ‘ALLR3 storage’

Date of last asparaginase treatment: ‘Date of last asp

01/01/01’ or ‘Date of last asp unknown’

Samples must be correctly stored as soon as possible:

PBC and BMC + cryoprotecatant: Place in ‘Mr Frosty’

overnight in freezer 10 (-80C). Record the location, both

in LIMS and the corresponding freezer-box plan at

S:/childhood leukaemia/freezer 31 locations/box locations.xls,

where you will store the samples within the liquid nitrogen

freezer 31 (-192C)

The following morning move the samples from ‘Mr Frosty’

to the correct positions within freezer 31

Document history

This is the second version of the SOP.

Document changes

Plasma aliquots without PIC are no longer required as PIC was not

found to have an adverse effect on downstream applications.

Cells containing cryoprotectant are now stored as 1ml instead of

1.5ml aliquots.

Appendix

235

Appendix 4 Leukaemic cell lines

SD1 SUPB15 REH

Type B precursor ALL B precursor AL B precursor ALL

Genetic subtype BCR-ABL1, p190 BCR-ABL1, p190 ETV6-RUNX1

Karyotype human near-

tetraploid karyotype

- 92(88-

92)<4n>XXXX,

t(9;22)(q34;q11)x2 -

carries two

balanced Ph

translocations -

tetraploid derivate

of original diploid

karyotype

Pseudodiploid -

46<2n>XY,

der(1)t(1;1)(p11;q3

1), add(3)(q2?7),

der(4)t(1;4)(p11;q3

5),

t(9;22)(q34;q11),

add(10)(q25),

?del(14)(q23q31),

der(16)t(9;16)(q11;

p13)

46(44-47)<2n>X, -

X, +16, del(3)(p22),

t(4;12;21;16)(q32;p

13;q22;q24.3)-

inv(12)(p13q22),

t(5;12)(q31-

q32;p12),

der(16)t(16;21)(q24

.3;q22) - sideline

with

inv(5)der(5)(p15q31

),+18 - carries

t(12;21) and del(12)

Growth medium RPMI + 10% FCS RPMI + 10% FCS RPMI + 10% FCS

AEP expression Positive Negative Negative

Doubling time 28-32 hours 60-72 hours 60-72 hours

Source CRUK Central

services

DSMZ CRUK Central

services

Appendix

236

Appendix 5: Example of a grid experiment to optimise AEP ELISA:

04/0

3/2

010

05/0

3/2

010

07/0

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010

08/0

3/2

010

09/0

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0.3

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0.2

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0.3

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LB

+ P

I1

% B

SA

+ P

BS

+ L

B+

PI

1%

BS

A+

PB

S+

LB

+ P

I1

% B

SA

+ P

BS

+ L

B+

PI

1%

BS

A+

PB

S+

LB

+ P

I0

.5%

BS

A +

PB

S+

LB

+P

I0

.5%

BS

A +

PB

S+

LB

+P

I0

.5%

BS

A +

PB

S+

LB

+P

I0

.5%

BS

A +

PB

S+

LB

+P

I0

.5%

BS

A +

PB

S+

LB

+P

I0

.5%

BS

A +

PB

S+

LB

+P

I0

.5%

BS

A +

PB

S+

LB

+P

I0

.5%

BS

A +

PB

S+

LB

+P

I0

.5%

BS

A +

PB

S+

LB

+P

I0

.5%

BS

A +

PB

S+

LB

+P

I0.5

% B

SA

+ P

BS

+ L

B+

PI

0.5

% B

SA

+ P

BS

+ L

B+

PI

vol

100µ

l100µ

l100

µl

100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100

µl

100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l

time

1.5

hrs

2h

rs2

hrs

2h

rs2

hrs

2h

rs2

hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

2h

rs2

hrs

2h

rs2

hrs

2h

rs2

hrs

2h

rs2

hrs

2h

rs2

hrs

2h

rs2

hrs

tem

p37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

RT

RT

RT

RT

RT

RT

RT

RT

RT

RT

RT

RT

Se

co

nd

ary

03/0

3/2

010

reag

en

t1

% B

SA

+ P

BS

1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1

% B

SA

+ P

BS1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1

% B

SA

+ P

BS1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1

% B

SA

+ P

BS

1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0.5

% B

SA

+ P

BS

0.5

% B

SA

+ P

BS

vol

100µ

l100µ

l100

µl

100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100

µl

100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l

co

n4

00

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

200

ng

/ml

200

ng

/ml

400

ng

/ml

400

ng

/ml

200

ng

/ml

200

ng

/ml

400

ng

/ml

200

ng

/ml

400

ng

/ml

100

ng

/ml

400

ng

/ml

200

ng

/ml

100

ng

/ml

400

ng

/ml

300

ng

/ml

200

ng

/ml

100

ng

/ml

400

ng

/ml

300

ng

/ml

300

ng

/ml

100

ng

/ml

100

ng

/ml

100

ng

/ml

100

ng

/ml

100

ng

/ml

100

ng

/ml

100

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

400

ng

/ml

time

2.5

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

1.5

hrs

2h

rs2

hrs

2h

rs2

hrs

2h

rs2

hrs

2h

rs2

hrs

2h

rs2

hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

2hrs

tem

p37C

37C

37C

37C

37C

37C

37C

Str

ep

HR

P

co

mp

an

yR

&D

R&

DR

&D

DA

KO

DA

KO

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DD

AK

OD

AK

OR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DD

ak

oD

ak

oD

ak

oD

ako

Da

ko

Da

ko

Da

ko

Da

ko

Dak

oD

ak

oD

ak

oD

ako

reag

en

t1

% B

SA

+ P

BS

1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1

% B

SA

+ P

BS1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1

% B

SA

+ P

BS1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1

% B

SA

+ P

BS

1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S1%

BS

A+

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0

.5%

BS

A +

PB

S0.5

% B

SA

+ P

BS

0.5

% B

SA

+ P

BS

vol

100µ

l100µ

l100

µl

100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100

µl

100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l

co

n1to

200

1to

200

1to

500

1to

1000

1to

1000

1 to 2

00

1 to 5

00

1to

200

1to

200

1to

200

1to

350

1 t

o 3

50

1to

500

1to

500

1to

200

1to

200

1to

400

1to

200

1to

1000

1to

800

1to

400

1to

200

1to

1000

1to

800

1to

1000

1to

1000

1to

200

1to

200

1to

400

1to

400

1 to 2

00

1 to 4

00

1to

750

1to

750

1to

750

1to

750

1to

750

1to

750

1to

750

1to

750

1to

750

1to

750

1to

750

1to

750

time

45m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in3

0m

in3

0m

in3

0m

in3

0m

in3

0m

in3

0m

in3

0m

in3

0m

in3

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in1

hr

1h

r1

hr

1h

r1

hr

1h

r1

hr

1h

r1

hr

1h

r1h

r1

hr

tem

p37C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

37 C

RT

RT

RT

RT

RT

RT

RT

RT

RT

RT

RT

RT

Su

bs

tra

te

co

mp

an

yR

&D

R&

DR

&D

Pie

rce

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

R&

DR

&D

PO

D r

och

R&

DP

OD

R&

DP

OD

PO

DP

ierc

eP

ierc

eR

&D

R&

DP

ierc

eP

ierc

eR

&D

R&

DP

ierc

eP

ierc

eR

&D

R&

D

vol

100µ

l100µ

l100

µl

100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100

µl

100µ

l100µ

l100µ

l100µ

l100µ

l100

µl

100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100µ

l100ul

100ul

100ul

100ul

100ul

100ul

100ul

50

µl

100µ

l50µ

l100µ

l50

µl

100

µl

50

µl

100

µl

50µ

l100µ

l50µ

l

time

20m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in1

0m

in1

0m

in1

0m

in1

0m

in1

0m

in1

0m

in1

0m

in1

0m

in1

0m

in1

7m

in1

7m

in1

7m

in1

7m

in2

5m

in2

5m

in2

5m

in2

5m

in2

5m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in2

0m

in1

5 m

in1

5 m

in1

5 m

in1

5 m

in1

5 m

in1

5 m

in1

5 m

in1

5 m

in1

5 m

in1

5 m

in15 m

in1

5 m

in

tem

p37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37C

37 C

37 C

37 C

37 C

37 C

37 C

RT

RT

RT

RT

RT

RT

RT

RT

RT

RT

RT

RT

Sto

p

So

lutio

n2

N H

2S

O4

volu

me

time

Co

mm

en

tsH

igh b

ackg

rou

nd

R&

D s

ubstr

ate

bett

er

tha

n P

ierc

eco

mb

inatio

n o

f 400ng/m

l o

f 2°

with

1 to 2

00 o

f H

RP

giv

e a

hig

h b

ackg

rou

nd

last

co

mb

inatio

n is

the

be

st

2.5

ug

/ml p

rim

ary

, 20

0n

g/m

l se

c,

1to

500

hrp

, r&

D s

ubstr

ate

od v

alu

es o

f b

est

co

mb

inatio

ns a

re h

ighlit

ed in

ita

lics a

nd

bo

ld le

tte

r

stil

l w

ould

like

to

re

duce

th

e b

ackg

rou

nd,

ad

d t

we

en

to

blo

ckin

g b

uff

er,

re

du

ce

prim

ary

co

mp

are

co

lum

n 5

with

9:o

ld p

rim

ary

is p

erf

orm

ing le

ss w

ell

co

mp

are

d t

o n

ew

eve

n t

ho

ug

h it

wa

s s

tore

d a

t -8

0

Pla

nre

du

ce

1°

co

mp

are

old

prim

ary

with

new

one

, co

mp

are

low

er

co

nc o

f n

ew

prim

ary

, co

mp

are

2ug/m

l 1°,

200ng/m

l o

f 2°,

1to

350

/400 H

RP

incre

ase

blo

ckin

gco

mp

are

diffe

ren

t co

nc o

f se

co

nd

ary

and

HR

P vs

incre

ase

pro

t2ug/m

l 1°,

100ng/m

l o

f 2°,

1:2

00 H

RP

redu

ce

2°

redu

ce

str

ep/H

RP

tim

eto

eva

luate

diffe

ren

t co

nce

ntr

atio

ns o

f H

RP

co

mp

are

R&

D s

ubsta

te v

s P

ierc

e

co

mp

are

Dako

HR

P t

o R

&D

Appendix

237

biological determinants of therapeutic response to l

Documents