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IMMUNE REGULATION IN
PLASMA CELL
MYELOMA
Esther Aklilu
Submitted for the degree of Master of Science at the University of Technology, Sydney in December 2013
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CERTIFICATE OF ORIGINAL AUTHORSHIP
I certify that the work in this thesis has not previously been submitted for a degree nor has it been submitted as part of requirements for a degree except as fully acknowledged within the text.
I also certify that the thesis has been written by me. Any help that I have received in my research work and the preparation of the thesis itself has been acknowledged. In addition, I certify that all information sources and literature used are indicated in the thesis.
Signature of Student:
Date:
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Acknowledgements
I wish to express my sincere gratitude to my supervisors Dr Ross Brown, Mrs Narelle
Woodland and Dr Najah Nassif for their magnanimous support, encouragement and
patience throughout the duration of my degree.
To Ross, thank you for the opportunity to work for you and for allowing me to take on such
an interesting project for my degree. I truly appreciate your exceptional advice and guidance
throughout this project.
To Narelle and Najah, thank you for accepting me as your Masters Degree student and for
all the excellent advice, support and encouragement. I truly appreciate all your immense
help.
To my fellow research team and colleagues, your assistance and support is greatly
appreciated. Thank you to Shihong Yang for imparting to me your knowledge of flow
cytometry, cell sorting and cell culture work. It has been an absolute joy working with you.
Thank you to James Favaloro for your editorial advice, support and friendship. Although we
had only worked together for a short time, it has been a real pleasure working with you.
Also, I would like to appreciate your assistance in the analysis of the 10 year survivor
samples.
Thank you to the haematology staff of RPAH, for making my time in RPA thoroughly
enjoyable and to the volunteers, for the kind donation of your blood.
Thank you to Professor Doug Joshua and Dr P Joy Ho, for your suggestions and advice during
our weekly meetings.
I also wish to acknowledge the financial support provided by the Sydney Foundation for
Medical Research and the Cancer Institute, NSW.
Finally, I wish to thank my family and friends for their support and encouragement.
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Manuscripts and presentations arising from the work completed as part of this thesis
Articles published in peer-reviewed journals
Favaloro J, Brown R, Aklilu E, Yang S, Suen H, Hart D, Fromm P, Gibson J, Khoo L, Ho PJ, Joshua D (2013) Myeloma skews regulatory T and pro-inflammatory T helper 17 cell balance in favour of a suppressive state. Leukaemia & lymphoma. 55(5):1090-8
Bryant C, Suen H, Brown R, Yang S, Favaloro J, Aklilu E, Gibson J, Ho PJ, Iland H, Fromm P, Woodland N, Nassif N, Hart D, Joshua D (2013) Long-term survival in multiple myeloma is associated with a distinct immunological profile, which includes proliferative cytotoxic T-cell clones and a favourable Treg/Th17 cell balance. Blood Cancer journal 3:e148.
Conference abstracts
Favaloro J, Brown R, Aklilu E, Yang S, Suen H, Gibson J, Ho PJ, Joshua D. (2013) The ratio of Treg/Th17 cells is of prognostic significance in multiple myeloma. Australian Flow Cytometry group (AFCG) meeting.
Bryant CE, Brown RD, Yang S, Suen H, Aklilu E, Favaloro J, Hart DNJ, Fromm P, Woodland N, Nassif N, Iland H, Gibson J, Ho PJ, Joshua DE. (2011) Immunological Biomarkers in 10 year Survivors of Multiple Myeloma. Proceedings of the Haematology Society of Australia and New Zealand. O/021.
Bryant CE, Brown RD, Yang S, Suen H, Aklilu E, Favaloro J, Hart DNJ, Fromm P, Woodland N, Nassif N, Iland H, Gibson J, Ho PJ, Joshua DE. (2011) Ten year survivors of multiple myeloma demonstrate a differential expression of immunological biomarkers including a high incidence of cytotoxic T-cell clones which have not acquired myeloma-associated anergy. Blood. 118:S38865.
Aklilu E, Brown R, Yang S, Kabani K, Woodland N, Nassif N, Ho P, Gibson J, Joshua D. (2010) Treg number, Treg function and Th17 cells in plasma cell dyscrasias. Proceedings of the Haematology Society of Australia and New Zealand. A94.
Aklilu E, Brown R, Yang S, Kabani K, Woodland N, Nassif N, Ho PJ, Gibson J, Joshua D (2010) Treg number, Treg function and Th17 cells in plasma cell dyscrasias. Australian Flow Cytometry group (AFCG) meeting. A87.
Aklilu E, Brown R, Yang S, Kabani K, Woodland N, Nassif N, Ho PJ, Gibson J, Joshua D (2010) Treg number, Treg function and Th17 cells in plasma cell dyscrasias, The XXVIIth Annual scientific research meeting. P42.
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Abbreviations
Ab/ Abs Antibody (-ies)
AF-647 Alexa Fluor 647
AML Acute myeloid leukaemia
Anti- Antibody against
APC Allophycocyanin
APCs Antigen presenting cells
ATLL Adult T-cell leukaemia/lymphoma
B cell B lymphocyte
2M Beta-2 microglobulin
BM Bone marrow
BMMC Bone marrow mononuclear cells
Bort- Bortezomib (Velcade)
C Degrees Celsius
CD Cluster of differentiation
CFSE Carboxyfluorescein succinimidyl ester
CLL
CLMF
Chronic lymphocytic leukaemia
Cytotoxic lymphocyte maturation factor
CRAB Hypercalcaemia, renal failure, anaemia and bone lesion
CRP C-reactive protein
CTLA-4 Cytotoxic T lymphocyte-associated antigen-4
CTLA-8 Cytotoxic T lymphocyte-associated antigen-8
DC Dendritic cells
Dex Dexamethasone
DMSO Dimethyl sulfoxide
DVT Deep vein thrombosis
EDTA Ethylenediamine tetra-acetic acid
FACS Fluorescence activated cell sorting
FISH Fluorescent in situ hybridisation
FITC Fluorescein isothiocyanate
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FoxP3 Forkhead box P3
FSC Forward scatter
g Gravitational force
G-CSF Granulocyte-colony stimulating factor
GITR Glucocorticoid-induced tumour necrosis factor -receptor-related
GvHD Graft versus host disease
HCl Hydrochloric acid
HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid
hi High
HLA Human leukocyte antigen
IFN Interferon
Ig Immunoglobulin
IL Interleukin
IMiD/ IMiDs Immunomodulatory drug (s)
iTreg Induced regulatory T cell
ISS International staging system
kDa- Kilo Dalton
LAP Latency associated peptide
Len Lenalidomide
Len + Dex Lenalidomide in combination with dexamethasone
mAB Monoclonal Antibody
MFI Mean fluorescence intensity
MGUS Monoclonal gammopathy of undetermined significance
MHC Major histocompatibility complex
min Minutes
MM
MRI
Plasma cell myeloma
Magnetic resonance imaging
NK
NKSF
Natural killer
Natural killer cell stimulatory factor
NS Not significant (P>0.05)
nTreg Natural regulatory T cell
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PB Peripheral blood
PBMC Peripheral blood mononuclear cells
PBS Phosphate buffered saline
PCLI Plasma cell labelling index
PE Phycoerythrin
PerCP Peridinin chlorophyll protein
PMA Phorbol 12-myristate 13-acetate
Pom Pomalidomide
Rh Recombinant human
ROR Retinoid-related orphan receptor
RPMI Roswell Park Memorial Institute
RT Room temperature
SAM Significance analysis of microarray
SSC Side scatter
SCT Stem cell transplantation
SD Standard deviation
SEM Standard error of mean
SM Smouldering myeloma
SPE Serum protein electrophoresis
STAT3 Signal transducer and activator of transcription 3
T cell T lymphocyte
TCR T cell receptor
TGF- Transforming growth factor
Th T helper cell
Thal- Thalidomide
TILs Tumour infiltrating lymphocytes
TNF- Tumour necrosis factor -
Treg Regulatory T lymphocyte
WM Waldenström macroglobulinaemia
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Abstract
The pathogenesis of monoclonal gammopathies, particularly plasma cell myeloma (MM), is
multifaceted and complex. In recent years, Treg and Th17 cells have emerged as key factors
in the development and progression of malignancies including MM. However, there are still
conflicting reports on whether regulatory T (Treg) cells and Th17 cells are increased or
decreased in the peripheral blood (PB) of patients with MM. This is partly due to technical
difficulties associated with the use of the transcriptional repressor, forkhead box P3 (FoxP3)
to identify Treg cells. Studies have shown FoxP3 results to be dependent on the clones,
fluorochromes attached and fixation/permeabilisation methods used. More recent studies
have defined Treg cells as CD4+CD25hi cells which do not express CD127, an IL-7 receptor.
This methodology was used to determine Treg cell number and develop assays for the
assessment of Treg cell function. The study also extends to exploring Th17 cell number in
plasma cell dyscrasias and the overall effect of the Treg and Th17 cell equilibrium on the
survival of patients with MM.
CD4+CD25hiCD127- expression was used to quantitate Treg cell numbers and an intracellular
IL-17 assay on CD3+CD4+ cells was used for Th17 cell enumeration. Treg cell function was
determined using carboxyfluorescein succinimidyl ester (CFSE) tracking of Treg depleted
lymphocyte preparations stimulated by anti-CD3,CD2,CD28 beads at a 1:1 ratio for 4 days
1:1 fluorescence-activated cell sorted Treg cells. This functional assay was also used to
investigate the effect of recombinant human (rh) TGF- and rhIL-12 on Treg cells.
The mean proportion of Treg cells in the CD4+ compartment of PB of patients with MM
(n=32) was 8.9±0.6% and this was increased compared to the mean of the normal cohort
(n=36) at 6.5±0.4% (p=0.009). However, no significant difference was observed between the
frequency of PB Treg cells in the control group compared to patients with monoclonal
gammopathy of undetermined significance (MGUS) (n=20) (mean=7.5±0.8%; P=0.24) and
patients with Waldenström macroglobulinaemia (WM) (n=13) (mean=6.0±0.5%; P=0.48).
Interestingly, a comparison of the absolute numbers exhibited different results. A
significantly lower number of Treg cells was observed in patients with MM [(3.2±0.4) x107/L;
P<0.01] and WM [(3.0±0.6) x107/L; P<0.01] compared to the control group [(6.4±0.7)
x107/L]. However, no significant difference was observed when comparing patients with
MGUS [(4.3±0.8) x107/L; P= 0.06] to the normal cohort. It was observed that a significantly
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higher proportion of PB Treg cells in patients with MM (85.9±1.8%; P<0.01) and WM
(86.4±2.1%; P=0.02) to be of the CD45RO+ memory phenotype compared to the normal
cohort (76.7±2.5%). However this was not observed in patients with MGUS (73.4±4.0%;
P=0.47). In addition, the study revealed that PB Treg cell proportions were not influenced by
MM stage. Thalidomide treated patients with MM appeared to have an increased PB Treg
cell proportion, however only a small number of thalidomide treated patients were tested
due to the use of thalidomide therapy being phased out and its replacement with
lenalidomide. Treg cells from bone marrow (BM) were compared to matched PB samples
from patients with MM, demonstrating a significantly greater proportion (p=0.02) of Treg
cells in the CD4+ compartment of the BM (9.7±1.2%) compared to PB (6.7±1.4%).
Regarding Th17 cells, a significant decrease (p=0.03) in the mean proportion and absolute
number of Th17 cells was observed in the PB of patients with MM (n=22) compared with the
controls (n=20) (0.7±0.1% and 2.0±0.6% respectively). However, the mean number of Th17
cells in patients with MGUS (2.2±0.6%; n=15) and WM (1.1±0.2%; n=12) was not significantly
different from normal. No correlation was observed between Th17 cell number and MM
staging or therapy.
Additionally, the study explored the Treg/Th17 cell ratio in PB of patients with monoclonal
gammopathies with comparison made to normal subjects. The mean Treg/Th17 cell ratio of
patients with MM (16.1±2.4) was significantly higher (p=0.0002) than the healthy control
group (6.6±1.0). The Treg/Th17 cell ratio of WM and MGUS patients was 7.0±1.0 and
4.9±0.5 respectively, neither of which were statistically different to the ratio of the normal
controls. Most interestingly, patients who have survived with MM for 10 or more years
possessed a Treg/Th17 cell ratio similar to the normal controls (7.04±2.47; p=0.84) and this
was shown to affect overall survival. The data demonstrated that patients with MM
observed to have a high Treg/Th17 cell ratio had an overall shorter survival compared to
those whose Treg/Th17 cell ratio was lower (p<0.025).
The suppressive capability of Treg cells from MM patients (n=15) was variable. The Treg cell
function of patients treated with lenalidomide (n=5) was increased (mean=68%) compared
to patients treated with thalidomide (n=5; mean=23%), Velcade (n=3; mean=12%),
untreated patients (n=5; mean=36%) and normal controls (n=11; mean=31%). The
suppression exerted upon the CD4+ T cell subset in patients treated with bortezomib was
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significantly lower when compared to the normal cohort. However, no significant difference
in CD8+ T cell suppression was found between patients with MM and the normal controls.
rhTGF- increased the suppressive capabilities and rhIL-12 reduced the function of Treg cells
from both MM and normal PB samples.
In conclusion, immune regulation is dysfunctional in patients with MM as the proportion of
PB Treg cells is increased and Th17 cells are reduced. Also, the cytokine microenvironment
and treatment have a major impact on the function of Treg cells. The data clearly delineate
the importance of the PB Treg/Th17 cell equilibrium, revealing a strong association between
the Treg/Th17 cell homeostatic balance and disease progression and survival in MM,
indicating an imbalance may cause either or both the innate and adaptive immune system
to be dormant and incapacitate the anti-tumour response.
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Table of Contents
ACKNOWLEDGEMENTS .................................................................................................................. II
MANUSCRIPTS AND PRESENTATIONS ARISING FROM THE WORK COMPLETED AS PART OF THIS THESIS ........... III
ABBREVIATIONS ......................................................................................................................... IV
ABSTRACT .............................................................................................................................. .. VII
TABLE OF CONTENTS .................................................................................................................... X
LIST OF FIGURES ........................................................................................................................ XV
LIST OF TABLES ......................................................................................................................... XVII
INTRODUCTION................................................................................................... 1
PLASMA CELL MYELOMA................................................................................................................ 2
1.1 INTRODUCTION TO PLASMA CELL MYELOMA: EPIDEMIOLOGY, INCIDENCE AND MORTALITY ............... 2
1.2 CLINICAL PRESENTATION, DIAGNOSIS AND PROGNOSTIC INDICATORS IN MM ................................ 2
1.2.1 Clinical presentation ............................................................................................ 2
1.2.2 Diagnosis and classification of monoclonal gammopathies ................................ 3
1.2.3 Staging and prognosis .......................................................................................... 5
1.3 THERAPY FOR MM ........................................................................................................... 8
1.3.1 Thalidomide ......................................................................................................... 8
1.3.2 Lenalidomide and Pomalidomide ........................................................................ 9
1.3.3 Bortezomib ......................................................................................................... 10
1.3.4 Haematopoietic stem cell transplantation ........................................................ 11
1.3.4.1 Autologous haematopoietic stem cell transplantation ................................. 11
1.3.4.2 Allogeneic haematopoietic stem cell transplantation ................................... 12
IMMUNE REGULATION ................................................................................................................ 12
1.4 THE IMMUNE SYSTEM ...................................................................................................... 12
1.4.1 Lymphocytes ...................................................................................................... 12
1.5 REGULATORY T (TREG) CELLS ............................................................................................ 15
1.5.1 Treg cells in PB ................................................................................................... 15
1.5.2 Classes of Treg cells............................................................................................ 15
1.5.3 Treg cell identification by flow cytometry ......................................................... 16
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1.5.4 Treg cells and cancer .......................................................................................... 17
1.5.5 Treg cells and haematological malignancies ..................................................... 18
1.5.6 Treg cells and GvHD ........................................................................................... 18
1.5.7 Controversy ........................................................................................................ 19
1.6 TH17 CELLS AND THEIR CYTOKINES ..................................................................................... 21
1.6.1 Th17 cell development and differentiation ....................................................... 21
1.6.2 The IL-17 cytokine .............................................................................................. 21
1.6.3 Th17 cells in cancer ............................................................................................ 22
1.7 THE ROLE OF THE CYTOKINES TGF- AND IL-12 IN CANCER ..................................................... 23
1.7.1 TGF- .................................................................................................................. 23
1.7.2 IL-12 .................................................................................................................... 23
1.8 BACKGROUND TO THE PROJECT .......................................................................................... 24
1.9 HYPOTHESIS .................................................................................................................. 24
1.10 AIMS OF THE PROJECT ...................................................................................................... 25
MATERIALS AND METHODS .................................................................................. 26
2.1 PARTICIPANTS ................................................................................................................ 27
2.2 SAMPLE COLLECTIONS ...................................................................................................... 27
2.2.1 Blood sample collection ..................................................................................... 27
2.2.2 BM collection ..................................................................................................... 27
2.3 METHODOLOGY FOR PREPARATION OF COMMON REAGENTS ................................................... 28
2.3.1 Preparation of ammonium chloride lysing reagent ........................................... 28
2.3.2 Preparation of phosphate buffered saline ........................................................ 28
2.3.3 Preparation of Roswell Park Memorial Institute -10 medium........................... 28
2.3.4 Preparation of RPMI cell culture medium ......................................................... 29
2.3.5 Preparation of MACSBeads ................................................................................ 29
2.3.6 Preparation of carboxyfluorescein succinimidyl ester stain .............................. 29
2.4 GENERAL TECHNIQUES ..................................................................................................... 31
2.4.1 Cell wash ............................................................................................................ 31
2.4.2 Isolation of mononuclear cells using Ficoll-Paque density gradient centrifugation ................................................................................................................ ... 31
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2.5 MONOCLONAL ANTIBODIES USED DURING EXPERIMENTATION .................................................. 33
2.6 ASSAY FOR IDENTIFICATION OF TREG CELLS .......................................................................... 34
2.6.1 Cell staining for flow cytometric identification of CD127lo/- Treg cells .............. 34
2.6.2 Preparation of PBMC Treg cell identification using FoxP3 ................................ 34
2.6.3 Preparation of BM Treg cells for flow cytometric analysis ................................ 35
2.7 METHODOLOGY FOR THE IDENTIFICATION OF TH17 CELLS IN PB .............................................. 36
2.7.1 Preparation of Th17 cells for flow cytometric analysis ..................................... 36
2.8 TREG CELL FUNCTIONAL ASSAY USING CFSE ......................................................................... 37
2.8.1 Fluorescence-activated cell sorting of PBMC .................................................... 37
2.8.2 FACS purity test .................................................................................................. 38
2.8.3 CFSE staining of target cells ............................................................................... 38
2.8.4 Cell count ........................................................................................................... 39
2.8.5 Preparation of the MACSbead suspension ........................................................ 39
2.8.6 Cell culture of Treg and CFSE stained target cell ............................................... 39
2.8.7 Analysis of the CFSE assay after culture ............................................................ 41
2.9 EVALUATION OF THE IMPACT OF CYTOKINES (IL-12 AND TGF- ) AND ANTI-TGF- ON TREG CELLS 41
2.9.1 IL-12 preparation ............................................................................................... 41
2.9.2 rhTGF- 1 preparation ........................................................................................ 42
2.9.3 Anti TGF- preparation ...................................................................................... 42
2.9.4 Plating of the cell culture wells with addition of cytokines ............................... 42
2.10 STATISTICS AND ANALYSIS ................................................................................................. 44
RESULTS ......................................................................................................... 45
3.1 OVERVIEW .................................................................................................................... 46
3.2 TREG CELLS IN MONOCLONAL GAMMOPATHIES ..................................................................... 46
3.2.1 Identification of Treg cells using CD127 ............................................................ 46
3.2.2 Identification of Treg cells using FoxP3 ............................................................. 49
3.2.3 Enumeration of Treg cells in PB ......................................................................... 52
3.2.4 Phenotypic analysis of Treg cells ....................................................................... 55
3.2.5 Effect of IMiD treatment on Treg cell proportions ............................................ 58
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3.2.6 MM staging and Treg cell quantitation ............................................................. 60
3.2.7 Enumeration of Treg cells in BM versus PB ....................................................... 60
3.2.8 Treg cells in patients with MM who have survived more than 10 years ........... 63
3.3 TH17 CELLS IN MM AND OTHER MONOCLONAL GAMMOPATHIES ............................................. 66
3.3.1 Identification of Th17 cells in PB........................................................................ 66
3.3.2 Enumeration of Th17 cells in PB ........................................................................ 68
3.3.3 Th17 cells and stage of MM ............................................................................... 70
3.3.4 Th17 cells in MM patients who have survived more than 10 years .................. 71
3.4 TREG AND TH17 CELL EQUILIBRIUM ................................................................................... 73
3.4.1 Treg/Th17 cell ratio in monoclonal gammopathies........................................... 73
3.4.2 Effect of a high Treg/Th17 cell ratio on overall survival in MM ........................ 73
3.5 TREG CELL FUNCTIONAL ASSAY ........................................................................................... 77
3.5.1 Development and optimisation of Treg cell functional assay ........................... 77
3.5.2 Treg cell functional assay results ....................................................................... 79
3.5.3 Suppression of T cell proliferation ..................................................................... 79
3.6 EFFECT OF CYTOKINES ON TREG CELL FUNCTION .................................................................... 84
DISCUSSION ..................................................................................................... 86
4.1 OVERVIEW .................................................................................................................... 87
4.2 THE ROLE OF TREG CELLS IN MONOCLONAL GAMMOPATHIES ................................................... 88
4.2.1 The phenotype and identification of Treg cells ................................................. 88
4.2.2 Enumeration and phenotype of Treg cells in monoclonal gammopathies ....... 89
4.2.3 Naïve and memory Treg cells in monoclonal gammopathies ........................... 91
4.2.4 Effect of MM treatment on Treg cell proportion .............................................. 91
4.2.5 Effect of MM stage on Treg cell proportion ...................................................... 92
4.2.6 Quantification of Treg cells in the PB and BM of MM patients ......................... 93
4.2.7 Treg cell function in MM .................................................................................... 93
4.2.8 Treg cell suppression on the CD4 and CD8 T cell subsets.................................. 95
4.2.9 Modification of Treg cell function ..................................................................... 95
4.3 THE ROLE OF TH17 CELLS IN THE MONOCLONAL GAMMOPATHIES ............................................. 97
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4.3.1 Th17 cell enumeration in MM and other monoclonal gammopathies ............. 97
4.3.2 Association of MM stage and Th17 cell proportion .......................................... 99
4.4 TREG AND TH17 EQUILIBRIUM ........................................................................................ 100
4.4.1 Treg/Th17 cell ratio in monoclonal gammopathies......................................... 100
4.4.2 Treg/Th17 cell ratio and survival ..................................................................... 101
4.5 CONCLUSIONS AND FUTURE DIRECTIONS ............................................................................ 102
4.5.1 Future directions .............................................................................................. 102
4.5.2 Conclusion ........................................................................................................ 103
REFERENCES .................................................................................................. 105
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List of Figures
Figure 1.1: Diagnostic characteristics of MM ............................................................................ 4
Figure 1.2: Gene expression patterns and overall survival in the different molecular
subgroups of MM ............................................................................................................... ........ 7
Figure 1.3: The chemical structure of the IMiDs thalidomide, lenalidomide and
pomalidomide .................................................................................................................. ........ 10
Figure 1.4: Hierarchy of lymphocytes and T cell lineages involved in the innate and adaptive
immune response ............................................................................................................... ..... 14
Figure 2.1: Flow cytometric analysis of a CFSE stained cell population .................................. 30
Figure 2.2: Whole blood before and after centrifugation with Ficoll-Paque .......................... 31
Figure 2.3: Cell culture plate set up for investigation of Treg cell function ............................ 40
Figure 2.4: Cell culture plate set up to evaluate the effect of IL-12, TGF- , and anti-TGF- on
the function of Treg cells .................................................................................................... ..... 43
Figure 3.1: Isotype control for each fluorochrome used in the Treg cell assay ...................... 47
Figure 3.2: Flow cytometry results from a representative normal subject showing the gating
strategy for identification of Treg cells in PB ........................................................................... 48
Figure 3.3: Flow cytometry results from a representative normal subject showing the gating
strategy for identification of PB Treg cells using FoxP3 ........................................................... 50
Figure 3.4: Comparison of FoxP3 expression on sorted CD25hiCD127lo/- Treg cells compared
to the Treg depleted T cells .................................................................................................. ... 51
Figure 3.5: Enumeration of PB Treg cells in patients with monoclonal gammopathies and
normal control individuals .................................................................................................... ... 54
Figure 3.6: Flow cytometry results showing CD45RA and CD45RO expression on Treg cells in
PB of a representative normal subject .................................................................................... 56
Figure 3.7: Expression levels of CD45RA and CD45RO on Treg cells in PB of patients with
monoclonal gammopathies and normal individuals ............................................................... 57
Figure 3.8: Effect of IMiD treatment on PB Treg cell proportions in patients with MM ......... 59
Figure 3.9: Comparison of the percentage of PB Treg cells and the different stages of MM . 61
Figure 3.10: Comparison of Treg cell numbers in the BM and PB of patients with MM......... 62
Figure 3.11: Relative Treg cell numbers in PB of normal subjects, patients with MM for less
than 10 years and MM patients who have survived for 10 or more years since diagnosis .... 64
xvi
Figure 3.12: Absolute number of PB Treg cells in normal subjects, patients with MM for less
than 10 years and patients who have survived 10 or more years with MM ........................... 65
Figure 3.13: Flow cytometric results from a PB sample of a representative normal subject
showing the gating strategy for the identification of Th17 cells ............................................. 67
Figure 3.14: Relative Th17 cells number in the PB of patients with monoclonal
gammopathies and normal controls ........................................................................................ 69
Figure 3.15: Comparison of the percentage of Th17 cells of the CD4+ compartment in PB and
different stages of MM ........................................................................................................ .... 70
Figure 3.16: Enumeration of Th17 cells in PB of patients with MM and normal subjects ...... 72
Figure 3.17: Treg/Th17 cell ratio in patients with monoclonal gammopathies and normal
individuals ................................................................................................................... ............. 74
Figure 3.18: Treg/Th17 cell ratio in 10 year MM survivors ..................................................... 75
Figure 3.19: The effect of Treg/Th17 cell ratio on overall survival of patients with MM ....... 76
Figure 3.20: Optimisation of MACSbead stimulation for the Treg functional assay ............... 78
Figure 3.21: Flow cytometry gating strategy for FACS of Treg cells in PB ............................... 81
Figure 3.22: A representative flow cytometric analysis of CFSE stained CD3+ cells after 4 days
culture ....................................................................................................................... ............... 82
Figure 3.23: Effect of treatment on Treg cells suppressive activity on lymphocytes target
cells ......................................................................................................................... ................. 83
Figure 3.24: Effect of IL-12, TGF- and anti-TGF- cytokines on the suppressive function of
Treg cells .................................................................................................................... .............. 85
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List of Tables
Table 1.1: International Staging System for MM ....................................................................... 5
Table 1.2: Comparison of studies of Treg identification, enumeration and function in MM. 20
Table 2.1: List of monoclonal antibodies (mAb) used during experimentation ...................... 33
Table 2.2: Fluorescent antibodies used for the flow cytometric identification of Treg cells
using CD127 ................................................................................................................... .......... 34
Table 2.3: Fluorescent antibodies used for the flow cytometric identification of Treg cells
using FoxP3 ................................................................................................................... ........... 35
Table 2.4: Fluorescent antibodies used for the flow cytometric identification of BM Treg cells
............................................................................................................................... ................... 36
Table 2.5: Fluorescent antibodies used to identify Th17 cells for analysis by flow cytometry
............................................................................................................................... ................... 37
Table 2.6: Fluorescent antibodies used to identify Treg cells for flow cytometric sorting ..... 38
Table 2.7: Fluorescent antibodies used for analysis of the CFSE assay by flow cytometry .... 41
1
CHAPTER ONE
INTRODUCTION
2
PLASMA CELL MYELOMA
1.1 Introduction to plasma cell myeloma: Epidemiology, incidence and mortality
Plasma cell myeloma (MM), more commonly known as multiple myeloma, is a malignancy of
plasma cells that is characterised morphologically by an excessive number of abnormal
plasma cells in the bone marrow (BM). The Australian Institute of Health and Welfare data
from 2007 indicates that in Australia, MM accounts for approximately 1.2% of all cancers
with approximately 1200 people, most of whom are above the age of 40, diagnosed each
year. The median age of onset is in the early 60s, and it is more common in males than
females, occurring at a ratio of 1.6:1. Overall, MM accounts for approximately 10% of all
haematological malignancies (Welfare, 2010).
In patients with MM, malignant plasma cells (MM cells) produce excessive amounts of a
monoclonal immunoglobulin, called M protein or paraprotein. The type of paraprotein
produced by the plasma cell determines the MM classification. The paraprotein produced by
the malignant plasma cells is Immunoglobulin G (IgG) in 60% of cases, Immunoglobulin A
(IgA) in 20% and Immunoglobulin D (IgD) in 2% of cases. MM characterised by excessive
immunoglobulin M (IgM) is rare. Some patients produce a paraprotein that does not have a
heavy chain and this is referred to as light chain disease (monoclonal kappa or lambda).
There are also a few patients who are non-secretors and have no paraprotein despite the
presence of a large number of malignant plasma cells. MM can be a seriously debilitating
disease with multi-organ involvement. Currently it is incurable, although there are a number
of therapies that improve quality of life and prolong survival.
1.2 Clinical presentation, diagnosis and prognostic indicators in MM
1.2.1 Clinical presentation
The clinical presentation of patients with MM can be quite variable. Twenty percent of
patients are diagnosed by chance without any characteristic symptoms (Sagar, 2010). The
most common symptom of MM is bone pain. Patients usually develop osteolytic lesions in
multiple sites around the body (Figure 1.1A), hence the term “multiple” myeloma. Bone
3
pain may be caused by fractures, spinal compression and/or the formation of lesions by
osteoclasts or osteoblasts proliferating to replace missing bone.
According to the review of Kyle and Rajkumar (2008), the most common clinical findings in
patients with MM at diagnosis are the presence of paraprotein (>90%) and bone lesions
(80%), followed by anaemia (72%), renal failure (19%) and hypercalcaemia (13%).
1.2.2 Diagnosis and classification of monoclonal gammopathies
Physical examination, blood tests, urine tests, BM biopsy and X-ray are all required for the
diagnosis of MM (Marc et al., 2009). At presentation, all patients with a monoclonal
gammopathy are categorised into one of three groups according to the published criteria of
the International Myeloma Working Group (Table 1.1). The original classification of 2005
(Greipp et al., 2005) was revised in 2008 (Kyle and Rajkumar, 2008). The three groups are:
(1) MM, (2) smouldering myeloma (SM) and (3) monoclonal gammopathy of undetermined
significance (MGUS). In addition to the three major groups of monoclonal gammopathies,
there are a number of other, rare, associated conditions that include solitary plasmacytoma,
amyloidosis and osteosclerotic myeloma (POEMS syndrome) (Kyle and Rajkumar, 2008) and
Waldenström macroglobulinaemia (WM), which is now classified as a lymphoplasmacytic
lymphoma (Swerdlow et al., 2008).
While a X-ray (Figure 1.1A), BM biopsy (Figure 1.1B), serum protein electrophoresis (SPE)
(Figure 1.1C) and immunofixation (Figure 1.1D) are the basic tests used for the diagnosis of
MM, a range of laboratory tests are performed to provide prognostic information and to
detect, or monitor, multi-organ failure. A full blood count, biochemistry screen (including
calcium and creatinine), serum 2microglobulin ( 2M), cytogenetics and fluorescent in situ
hybridisation (FISH) are also studied.
4
A B
C D
Figure 1.1: Diagnostic characteristics of MM A. X-rays showing lytic lesions in the skull and bones. B. BM biopsy stained with May-
Grünwald Giemsa showing an increased number of plasma cells. These are large
mononuclear cells with an eccentrically placed nucleus, basophilic cytoplasm and a nuclear
hoff. C. Serum protein electrophoresis showing an abnormal peak in the gamma-globulin
region. D. Immunofixation demonstrating the presence of an IgG paraprotein in a serum
sample from a patient with MM. (Images courtesy of R. Brown, Haematology, RPAH).
5
1.2.3 Staging and prognosis
There are a number of staging systems to classify patients with MM based on pathological
findings. These staging systems are designed to predict the prognosis of each patient. The
Durie-Salmon staging system was originally used as the main staging system for MM (Durie
and Salmon, 1975), however this was replaced in 2005 by the International Staging System
(ISS) (Greipp et al., 2005). The ISS only requires the use of two simple markers, serum
albumin and 2M, yet provides discrimination between each stage, and is superior to other
staging systems.
Table 1.1: International Staging System for MM Serum 2-
microglobulin
Serum albumin Median survival
Stage I <3.5 mg/L 35 g/L 62 months
Stage II Neither stage I or III 44 months
Stage III 5.5 mg/L 29 months
(Greipp et al., 2005)
A range of prognostic factors has been proposed for patients with MM, which may include:
1. Parameters reflecting the inherent proliferative capacity of the malignant clone
2. Parameters reflecting tumour bulk
3. Parameters reflecting renal failure
4. Parameters reflecting host-tumour interactions (Joshua et al., 1994, Joshua, 1996).
Other prognostic tests for MM include plasma cell morphology (Greipp et al., 1998), C-
reactive protein (CRP) levels (Bataille et al., 1992) and plasma cell labelling index (PCLI) to
determine the percentage of plasma cells that are in S-phase of the cell cycle (Pope et al.,
1999, Greipp et al., 2005). A patient with a high percentage of plasma cells in S-phase is
interpreted as having a poor prognosis.
In addition, molecular genetic studies of MM cells, including cytogenetic and FISH analysis,
also provide prognostic indicators. MM is divided into two fairly equally distributed groups
based on karyotypic abnormalities (Dewald et al., 1985, Gould et al., 1988, Lai et al., 1995,
6
Tricot et al., 1995). These comprise the hyperdiploid group, with mostly numerical gains in
chromosomes and few structural changes, and the non-hyperdiploid group, with many
chromosomal rearrangements and occasional numerical loss of chromosomes (Wuilleme et
al., 2004). This cytogenetic classification is of clinical importance as patients with
hyperdiploidy appear to have a better prognosis (Smadja et al., 2001, Debes-Marun et al.,
2003). Genetic aberrations such as chromosome 13 deletion, non-hyperdiploidy, t(4;14) and
t(14;16) translocations confer a poor prognosis while the 11q13 and 6p21 cytogenetic
abnormalities are associated with a better prognosis (Kyle and Rajkumar, 2008, Sagar,
2010).
Although not used in routine clinical practice, a molecular classification of MM, based on the
presence of translocations and hyperdiploidy, has been proposed by Zhan et al. (2006). This
classification consists of seven groups (Figure 1.2A) (Zhan et al., 2006) which have been
defined by two letter names and are characterised as follows:
a) PR – over-expression of genes responsible for cell cycle and cell proliferation
b) MS – over-expression of fibroblast growth factor receptor 3 (FGFR3) and multiple
myeloma SET domain (MMSET) genes
c) HY – hyperdiploid signature
d) CD-1 – over-expression of cyclin D1 and cyclin D3
e) CD-2 – over-expression of cyclin D2
f) MF – over-expression of MAF and MAFB genes
g) LB – low expression of genes involved in bone disease, such as Wnt signalling
antagonists Dickkopf (DKK1) and Frizzled B, and a low number of magnetic resonance
imaging (MRI) defined focal lesions.
With a 36-month median follow-up, the HY, CD-1, CD-2, and LB groups had a higher event-
free survival and overall survival compared with the PR, MS, and MF groups. In fact the high
proliferation group (PR) had the most significantly poor prognosis (Figure 1.2B) (Zhan et al.,
2006).
7
A B
Figure 1.2: Gene expression patterns and overall survival in the different molecular subgroups of MM A. Supervised clustergram of the expression of genes (50 significance analysis of microarray
(SAM)-defined over-expressed and under-expressed genes from each of the 7 defined
molecular subgroups). The vertical axis represents different genes, and the horizontal axis
represents samples. High expression is represented in red and low expression is represented
in blue. B. Kaplan-Meier estimates of overall survival for the 7 molecular subgroups. (Zhan
et al., 2006).
Months from start of therapy
Proportion of patients
8
1.3 Therapy for MM
There is a wide range of treatment options available for patients with MM. Current therapy
for patients under 65 years of age generally involves high dose induction chemotherapy
followed by autologous haematopoietic stem cell transplantation (SCT) (Quach and Prince,
2012). The main therapeutic agents are thalidomide or its analogue, lenalidomide, usually in
combination with dexamethasone. Other agents used are bortezomib and
cyclophosphamide, also in combination with dexamethasone. Patients often have low-dose
chemotherapy for maintenance after transplantation (Marc et al., 2009, Spencer et al.,
2009). Elderly patients may receive a less intensive therapy such as melphalan and
prednisone. Patients with MGUS or smouldering disease are likely not to receive therapy
(Kyle et al., 2007) as it has been shown in two randomised control trials that there is no
clinical benefit (Hjorth et al., 1993, Riccardi et al., 2000). Conversely, a recent study by
Mateos et al. (2013) has shown that early treatment of patients with high-risk smouldering
MM, with lenalidomide and dexamethasone, followed by maintenance therapy with
lenalidomide, would significantly delay the time to progression to symptomatic disease and
improve overall survival.
1.3.1 Thalidomide
Thalidomide ( -N-phthalimido-glutarimide) is a synthetic derivative of glutamic acid that has
been used successfully in the treatment of MM. Thalidomide has a number of different
modes of action that include immunomodulatory, anti-angiogenic, inhibition of the
microenvironment and a direct inhibition of the proliferation of the malignant cells
(D'Amato et al., 1994, Singhal et al., 1999, Teo, 2005). In the early 1960s, thalidomide was
withdrawn from the market as an antiemetic in pregnancy as it was associated with causing
foetal malformations (Lenz et al., 1962, Speirs, 1962). Reports of thalidomide’s efficacy in
graft versus host disease (GvHD) in animal models (Field et al., 1966), and early clinical
studies (Vogelsang et al., 1992), suggested that the drug may modify a T cell response. It is
currently thought that thalidomide initiates immunomodulation through its role as a potent
co-stimulator of human T cells, acting through the T cell receptor complex to increase
interleukin (IL) -2 mediated T cell proliferation and interferon (IFN) - production (Haslett et
al., 1998, Hayashi et al., 2005, Quach et al., 2009). The drug is associated with a range of
9
side effects, including neuropathy, deep vein thrombosis (DVT), fatigue and constipation. In
addition, patients may develop resistance to the drug and eventually relapse. A range of
thalidomide analogues, classified as immunomodulatory drugs (IMiDs), including
lenalidomide and pomalidomide have been developed. These analogues have greater anti-
cancer potency with fewer side effects, however the high cost of these drugs has been a
major factor in their delayed introduction into Australia.
1.3.2 Lenalidomide and Pomalidomide
The thalidomide derivatives lenalidomide (CC-5013; Revlimid) and pomalidomide (CC-4047;
Actimid) (Figure 1.3) are both effective IMiDs in the treatment of MM (Quach et al., 2009).
Compared to thalidomide, these IMiDs have improved potency and reduced toxicity (Quach
et al., 2009).
10
Thalidomide: 2-(2, 6-dioxopiperidin-3-yl)-1H-isoindole-1, 3(2H)-dione
Lenalidomide: 3-(4-amino-1-oxo 1, 3-dihydro-2H-isoindol-2-yl) piperidine-2, 6-dione
Pomalidomide: 4-Amino-2-(2, 6-dioxopiperidin-3-yl) isoindole-1, 3-dione
Figure 1.3: The chemical structure of the IMiDs thalidomide, lenalidomide and pomalidomide An amino group is added to the fourth carbon of the phthaloyl ring of thalidomide to
produce lenalidomide. The chemical structure of pomalidomide is an amalgamation of
thalidomide and lenalidomide (Kotla et al., 2009).
1.3.3 Bortezomib
Another new drug used to treat MM is the proteasome inhibitor bortezomib (Velcade),
which works by inhibiting intracellular protein degradation (Marc et al., 2009). In addition,
bortezomib induces apoptosis and inhibits growth of MM cells (Hideshima et al., 2001,
Mitsiades et al., 2002, Mitsiades et al., 2003). The drug may be beneficial for the treatment
of bone disease, as it increases bone formation by stimulation of osteoblasts and inhibition
of osteoclasts (Giuliani et al., 2007). Due to its different mode of action, bortezomib is a
11
useful agent in patients who are resistant to other therapies, however in Australia it is only
available to patients who meet set criteria. Toxicities associated with bortezomib include
peripheral neuropathy, transient thrombocytopaenia, fatigue, and gastrointestinal disorders
(Marc et al., 2009). A range of next generation protease inhibitors are currently being
trialled, including carfilzomib (Kuhn et al., 2007).
1.3.4 Haematopoietic stem cell transplantation
Haematopoietic SCT is used to facilitate the numerical restoration of cellular elements and
functional recovery of BM cellular interactions (Guillaume et al., 1998). Although autologous
SCT is not curative, it is used to induce long term disease-free survival in MM. In 1996, a
randomised trial by Intergoupe Francophone du Myélome demonstrated a better overall
survival after SCT compared to conventional chemotherapy (Attal et al., 1996).
Haematopoietic SCT can be either autologous, utilising stem cells from the patient’s own
BM or peripheral blood (PB), or allogeneic, utilising stem cells sourced from human
leukocyte antigen (HLA) matched normal donors.
1.3.4.1 Autologous haematopoietic stem cell transplantation
Autologous haematopoietic SCT is preferred in most cases as it is less complex and there is
minimal risk of GvHD (Lennard and Jackson, 2000). It involves high dose induction therapy,
which could involve agents such as high dose dexamethasone and thalidomide, followed by
mobilisation of stem cells to the blood using granulocyte-colony stimulating factor (G-CSF)
and leukapheresis to harvest the patient’s stem cells. The patient then receives high dose
chemotherapy to destroy remaining tumour bulk and the harvested stem cells are reinfused
into the patient. Some patients also undergo tandem autologous SCT that involves infusion
of a second transplant once a patient has recovered from the first. Studies have shown that
this improves event free and overall survival compared to a single autologous transplant
(Attal et al., 2003, Rajkumar and Kyle, 2005).
12
1.3.4.2 Allogeneic haematopoietic stem cell transplantation
Allografts are currently rarely performed. Unfortunately, due to old age, poor organ
function and HLA matched donor availability, only 5-10% of patients with MM are eligible
for allogeneic SCT. While autologous SCT is preferred, allogeneic SCT can be advantageous
as the transplant lacks tumour cell contamination, provides additional immunologic graft-
versus-myeloma effect and is potentially curative (Tricot et al., 1996, Bensinger, 2009,
Koehne and Giralt, 2012). The delay in disease relapse, however, does not offset the effects
of GvHD, which may lead to non-relapse mortality and an overall shortened survival
(Pasquini, 2008). Unless the HLA match is identical, the patient will almost certainly develop
GvHD.
IMMUNE REGULATION
1.4 The immune system
The immune system is composed of many cell types and mediators that interact with one
another. It is divided into two components, the innate and the adaptive immune system
based on antigen specificity and timing of activation (de Visser et al., 2006). The innate
immune system is the first line of defence against pathogens, and comprises macrophages,
natural killer (NK) cells, neutrophils, basophils and eosinophils. The adaptive immune
response has the ability to utilise immunological memory to recognise and retain antigen
specific epitopes. Dendritic cells (DC) are specialised antigen presenting cells (APCs) that
cross the divide between innate and adaptive immunity. Upon subsequent exposure to a
previously encountered antigen, the adaptive immune system is able to mount a more
specific and rapid response. In recent times, it has become apparent that immune cells of
patients with malignancies have impaired function and this may play a critical role in cancer
pathobiology.
1.4.1 Lymphocytes
Lymphocytes are classified into three groups: cells associated with the adaptive immune
response, T (thymus) cells (CD3+) and B (bursa of Fabricius) cells (CD19+) and a key
13
component of the innate immune system, natural killer (NK) cells. T cells are responsible for
cellular immunity, whereas B cells are primarily involved with humoral immunity.
T cells are further subdivided into T helper (Th) cells (CD4+) and cytotoxic T cells (CD8+)
(Figure 1.4). Cytotoxic T cells monitor other cells of the body and are capable of destroying
infected, damaged or dysfunctional cells and micro-organisms (Andersen et al., 2006). T
helper CD4+ cells are an important component of the immune system, that coordinates the
immune response of other cell types (Ji and Zhang, 2010). Upon activation, CD4+ cells are
able to differentiate into different Th subsets. In cases of autoimmunity and immunity
against intracellular pathogens, CD4+ cells are induced to differentiate into the T helper type
1 (Th1) cell type. This subset is distinguished by the expression of the transcription factor T-
bet and production of IFN- and IL-2 (Peck and Mellins, 2010). T helper type 2 (Th2) cell
types are involved with humoral immunity against parasites and allergic reactions and are
characterised by the expression of transcription factor GATA-3 and production of IL-4, IL-5
and IL-13. In recent years, a further two lineages of T helper cells have been identified and
these have been termed T regulatory (Treg) cells (Sakaguchi et al., 1995) and T helper 17
(Th17) cells (Harrington et al., 2005). These cell subsets will be described in greater detail in
the following sections.
In MM, the absolute numbers of T cells, in particular the CD4+ cells, are reduced, especially
in cases of progressive disease (Mills and Cawley, 1983, Pilarski et al., 1989, Kay et al., 2001,
Raitakari et al., 2003). In addition, abnormal T cell function has been observed in MM with
reports of enhanced susceptibility to apoptosis (Massaia et al., 1995) and an impaired CD8+
cell response (Maecker et al., 2003).
14
Figure 1.4: Hierarchy of lymphocytes and T cell lineages involved in the innate and adaptive immune response Depending on cytokine stimulation, T helper cells can differentiate into Th1, Th2, Treg or
Th17 cells.
NK cell CD16/56+
B cell CD19+
T cell CD3+
Th17 cell Inflammation
Treg cell Suppression
Th2 cell Humoral immunity
Th1 cell Cellular immunity
T cytotoxic cell CD8+
T helper cell CD4+
Lymphocyte
15
1.5 Regulatory T (Treg) cells
The concept of Treg cells as a novel CD4+ cell subset was first described in the early 1970s
(Gershon and Kondo, 1971, Gershon et al., 1972), however, there was great scepticism
about the existence of such cells. In 1995, Sakaguchi et al. identified a population of CD4+
cells which constitutively expressed CD25, the IL-2 receptor- chain (Sakaguchi et al., 1995,
Sakaguchi, 2004). It was reported that these cells were involved in maintaining self-
tolerance and eradication of these cells would lead to autoimmunity (Sakaguchi et al., 1995,
Chen and Oppenheim, 2009, Ha, 2009). These cells were termed Treg cells.
1.5.1 Treg cells in PB
Treg cells occupy 5-10% of the CD4+ compartment in PB (Sakaguchi, 2004, Prabhala et al.,
2006, Bronte, 2008, Ha, 2009). They are involved in the maintenance of self-tolerance,
control of autoimmunity, and modulation of the immune response against infections and
tumour cells (Sakaguchi et al., 2001). These cells are crucial in maintaining immunological
homeostasis (Fontenot and Rudensky, 2005, Chen and Oppenheim, 2009) by the
suppression of immune cells. Studies have shown that Treg cells are able to influence the
activation, proliferation and function of a range of immune cells such as T helper cells,
cytotoxic T cells, NK cells, DC, macrophages, osteoblasts, mast cells and B cells (Ha, 2009,
Chen and Oppenheim, 2009). Antigenic stimulation through the T cell receptor (TCR) is
required to induce the suppressive activity of Treg cells, however suppression exerted by
Treg cells appears to be non-specific (Liu et al., 2006, Chen and Oppenheim, 2009). It has
been demonstrated that Treg cells are able to exert their suppressive capabilities using two
mechanisms. Treg cells can inhibit the proliferation of CD4+CD25- cells by cell to cell contact
(Prabhala et al., 2006) or, alternatively, they can secrete immunosuppressive cytokines,
including IL-10 and transforming growth factor (TGF) - , to suppress an immune response
(Chen et al., 2003, Prabhala et al., 2006, Ji and Zhang, 2010).
1.5.2 Classes of Treg cells
There are two classes of Treg cells; the natural Treg (nTreg) cells and the adaptive or
induced Treg (iTreg) cells. nTreg cells are derived from the thymus, then exported into the
16
peripheral circulation to reside in the lymph nodes and spleen (Joshua et al., 2008, Ha,
2009). Naïve T cells can differentiate into iTreg cells in the periphery when induced by TGF-
and IL-10 (Bettelli et al., 2006, Ha, 2009). Moreover, Treg cells can also be further
characterised into at least three subsets: (1) CD4+CD25+FoxP3+, (2) Type 1 Treg cells (T 1)
which secrete IL-10 and (3) Th3 cells which secrete TGF- (Liu et al., 2006, Ha, 2009).
1.5.3 Treg cell identification by flow cytometry
Study in the field of Treg cell immunology has been difficult due to the lack of specific cell
surface biomarkers to identify Treg cells from regulator and effector T cell subsets (Liu et al.,
2006). The earliest studies used CD4 and CD25 as markers to identify the Treg cell
population. In animal models held under pathogen free conditions, CD25 is an adequate
marker for Treg cells. However, the use of CD4 and CD25 in the human setting is insufficient,
as humans are continuously exposed to foreign antigens and therefore constantly possess a
population of activated CD25+ effector T cells (Beyer and Schultze, 2006, Liu et al., 2006).
Currently, the most common phenotype identified and used to define a Treg cell is
CD4+CD25hiFoxP3+. FoxP3 is an X chromosome linked forkhead/winged helix family
transcriptional repressor (Fontenot and Rudensky, 2005, Joshua et al., 2008) that is a crucial
component in the development and function of Treg cells (Liu et al., 2006, Ha, 2009). The
over-expression of FoxP3 is associated with the suppressive function of Treg cells (Prabhala
et al., 2006). However, there are problems associated with the use of FoxP3 as a marker for
Treg cells. Law et al. (2009) demonstrated that the use of different clones of FoxP3, different
fluorochromes attached to the FoxP3 antibody and different fixation/permeabilisation
methods can give different results.
Glucocorticoid-induced tumour necrosis factor (TNF) -receptor-related (GITR) protein
(McHugh et al., 2002) and cytotoxic lymphocyte-associated antigen-4 (CTLA-4 [CD152])
(Takahashi et al., 2000) are reported to be expressed on Treg cells and important for their
development and function (Beyer and Schultze, 2006, Ha, 2009). Other surface antigens that
are purported to be expressed on Treg cells are CD103, CD62L, CD69, CD134, CD71, CD54
and CD45RA (Belkaid and Rouse, 2005, Prabhala et al., 2006).
17
It has been shown by Liu et al. (2006) that the expression of CD127, the IL-7 receptor, is
down-regulated in a subset of CD4+ cells that are also FoxP3+ and that these cells are highly
suppressive. Hence, Treg cells can now be defined as CD4+CD25hiCD127lo/-. This is a
significant advancement in the identification of Treg cells. As FoxP3 is an intracellular
protein, until recently, its use was limited to enumeration of Treg cells and functional
studies, as well as in vitro expansions, had not been possible (Liu et al., 2006). However,
with the use of the surface biomarker CD127 to identify and isolate the Treg cell population,
further studies on Treg cells can be performed.
1.5.4 Treg cells and cancer
Tumours may develop ways to tactically exploit the immune system by evading or
suppressing the immune response. Two principal mechanisms for immune evasion by
tumours have been described. In the first mechanism, the tumour may directly suppress an
immune response by releasing factors like TGF- or by down-regulating major
histocompatibility complex (MHC) class I molecules (Pardoll, 2002). The second mechanism
may be by secreting inhibitory cytokines causing T cell anergy, depletion, or inhibition of the
T cell response (Bourgeois et al., 2002, Joshua et al., 2008).
The role of Treg cells in malignancies is currently an area of intense research interest and
the subject of many reviews. Increasing evidence suggests that high Treg cell levels are
found in the tumour microenvironment, leading to the hypothesis that Treg cells play a
crucial role in tumour immunity (Beyer and Schultze, 2006, Kryczek et al., 2007). A study by
Woo et al. (2001) reported an elevated number of CD4+CD25hi Treg cells in tumour
infiltrating lymphocytes (TILs) in non-small cell lung cancer and ovarian cancer. An increase
in the prevalence of CD4+CD25hi Treg cells in the tumour microenvironment and PB of
patients with breast and pancreatic cancer has also been observed (Liyanage et al., 2002). A
higher proportion of CD4+CD25hi Treg cells has been demonstrated in the PB of patients with
gastrointestinal malignancies (Sasada et al., 2003, Kono et al., 2006), as well as in melanoma
(Javia and Rosenberg, 2003, Viguier et al., 2004). It has also been suggested that poor
prognosis is related to a higher prevalence of Treg cells in patients with gastric carcinoma
(Sasada et al., 2003, Kono et al., 2006) and TILs of patients with advanced disease have a
18
significantly higher percentage of Treg cells compared to early stage disease (Ichihara et al.,
2003, Kono et al., 2006). Treg cells are also purported to be expanded in ovarian cancer
(Curiel et al., 2004), squamous cell carcinoma of the head and neck (Schaefer et al., 2005)
and hepatocellular carcinoma (Ormandy et al., 2005). Overall, it appears that Treg cell
numbers are elevated in the majority of solid tumours investigated and that the increased
percentage of Treg cells infers a poor prognosis.
1.5.5 Treg cells and haematological malignancies
In haematological malignancies, because the malignant cells are often also immune cells,
the interaction between Treg cells and malignant cells may differ compared to solid
tumours. In chronic lymphocytic leukaemia (CLL), an increase in the number of Treg cells in
PB has been reported and this appears to correlate with a poor prognosis (Beyer et al.,
2005, Motta et al., 2005) and treatment with lenalidomide and fludarabine appears to
reduce Treg cell numbers in patients with CLL (Beyer et al., 2005, Idler et al., 2010).
Increased frequency of Treg cells has also been observed in acute myeloid leukaemia (AML)
(Wang et al., 2005, Szczepanski et al., 2009), Hodgkin disease (Marshall et al., 2004) and
non-Hodgkin lymphoma (Yang et al., 2006). In patients with AML, a lower percentage of
circulating Treg cells at diagnosis correlated with better response to induction
chemotherapy (Szczepanski et al., 2009). Conversely, in follicular lymphoma, it has been
demonstrated that higher frequencies of Treg cells correlate with a better prognosis (Álvaro
et al., 2006, Carreras et al., 2006, Lee et al., 2006), possible due to either the direct or
indirect suppression of Treg cells upon B cell proliferation. Karube et al. (2004) report that
Treg cells are down-regulated in adult T-cell leukaemia/lymphoma (ATLL), however, in ATLL,
the tumour cells have been reported to be FoxP3 positive and may function as Treg cells
(Yano et al., 2007).
1.5.6 Treg cells and GvHD
It has been reported that Treg cells suppress GvHD in animal models, however, there are
conflicting reports on the impact of Treg cells on GvHD following SCT. Rezvani et al. (2006)
have reported that there is a greater risk of developing GvHD in patients who receive SCT if
19
they have lower absolute numbers of CD4+FoxP3+ cells. Also, Brunstein et al. (2011) have
suggested that Treg cells inhibit the development of GvHD. Recently, it has been
demonstrated that the infusion of Treg cells at the time of transplantation can preserve the
graft versus tumour effect and at the same time suppress the GvHD incidence and lethality
(Taylor et al., 2002, Edinger, 2009, Colonna et al., 2011). Cohen et al. (2002) have
demonstrated that Treg cells regulate GvHD and removal of these cells will accelerate the
disease. Furthermore, the addition of ex vivo expanded Treg cells at the time of grafting has
been shown to significantly reduce the incidence of GvHD (Cohen et al., 2002). This concept
has resulted in a series of clinical trials, the first of which are now published (Brunstein et al.,
2011, Colonna et al., 2011, Di Ianni et al., 2011), demonstrating the infusion of Treg cells
prevents GvHD in the absence of post transplantation immunosuppression.
Based on current knowledge, it is possible that Treg cells could potentially be used as a
therapeutic agent in preventing GvHD in patients with MM undergoing SCT. The potential
for Treg cells to attenuate GvHD is currently being investigated in both animal models and in
humans (Taylor et al., 2002, Taylor et al., 2004). Treg cells may have the ability to facilitate
engraftment (Shevach, 2002) and reduce the risk of GvHD after allogeneic transplantation
(Sakaguchi et al., 1995, Baecher-Allan et al., 2001, Brunstein et al., 2011).
1.5.7 Controversy
The role of Treg cells in MM remains highly controversial with the existence of conflicting
literature in regards to Treg cell number and function in MM, as shown in Table 1.2. This is
presumably due to the aforementioned problems with Treg cell identification as well as
patient heterogeneity, particularly with treatment.
20
Table 1.2: Comparison of studies of Treg identification, enumeration and function in MM.
*PB: Peripheral blood. BM**: Bone Marrow. Len#: Lenalidomide. Pom^: Pomalidomide.
Reference Treg cell identification
Treg cell frequency in PB*
Suppressive function of Treg cell
Other
Banerjee et al. (2006)
CD4+CD25+FoxP3+ Not studied
Not studied DC injection stimulates Treg cell expansion
Beyer and Schultze (2006)
CD4+CD25+FoxP3+
Foglietta et al. (2006)
CD4+CD25hi Normal Normal
Normal Treg cell number in BM**
Noonan et al. (2006)
CD4+CD25+ Not studied
Not studied Reduced Treg cell in BM** compared to *PB
Prabhala et al. (2006)
CD4+CD25+
Th17 cells increased
Minnema et al. (2007)
CD4+FoxP3+ Not studied
Not studied Len# increased Treg cell
Quach et al. (2008)
CD4+CD25hiCD127lo
FoxP3+ Not studied Len# increases
Treg cell number
Chiarenza et al. (2009)
CD4+CD25+FoxP3+ Not studied Len# increased Treg cell
Feyler et al. (2009)
CD4+CD25+FoxP3+ Normal
Galustian et al. (2009)
CD4+CD25+CTLA4+
FoxP3+ Not
studied Not studied Len# and Pom^
inhibit Treg cell function
Raja et al. (2009)
CD4+CD25hiCD127lo
FoxP3+ Not studied Frequency of
BM** Treg cell proportional to increase severity of disease
Gupta et al. (2011)
CD4+CD25++CD127lo
FoxP3+ Normal Treg cells
increasing after treatment with IMiD
Carter, et al. (2012)
CD4+CD25++FoxP3+ Not studied
Clave et al. (2013)
CD4+CD25++CD127lo Not studied
21
1.6 Th17 cells and their cytokines
The range of effector CD4+ T cell lineages has been expanded with the description of a novel
CD4 sub-population called Th17 cells (Harrington et al., 2005, Kryczek et al., 2007). Th17
cells are characterised by their production of IL-17A, IL-17F, IL-21, IL-22 and IL-26. Th17 cells
also express chemokine receptor CCR6 and its ligand, CCL20 (Fouser et al., 2008, Ji and
Zhang, 2010). They have been observed in both humans and mice and are responsible for
the clearance of extracellular pathogens, including bacteria and fungi, and are pathogenic in
inflammation and autoimmunity (Fouser et al., 2008, Ji and Zhang, 2010, Prabhala et al.,
2010).
1.6.1 Th17 cell development and differentiation
The predominance of Th17 cells in PB and the conditions for Th17 cell development are not
completely understood (Ji and Zhang, 2010). Some groups have reported that IL-6 and TGF-
are responsible for the differentiation of Th17 cells (Bettelli et al., 2006), with contributions
by IL-1, IL-23, TNF- , and other cytokines (Fouser et al., 2008, Noonan et al., 2010).
However, subsequent studies have reported that IL-6, IL-1 and IL-23 were sufficient to
promote Th17 differentiation and that TGF- was not needed (Ji and Zhang, 2010).
Maintenance and expansion of Th17 cells is driven by IL-21 and IL-23. The key
transcriptional regulator for Th17 cytokines is retinoid-related orphan receptor (ROR) - t
(Ivanov et al., 2006, Fouser et al., 2008) and it is the over-expression of ROR- t that
promotes Th17 cell differentiation and up-regulation of IL-17 (Ji and Zhang, 2010). However,
other transcription factors critical in the regulation of Th17 cell development are ROR- and
signal transducer and activator of transcription 3 (STAT3) (Fouser et al., 2008, Ji and Zhang,
2010). Studies have shown that mutation in the STAT3 gene is detrimental to Th17 cell
differentiation and IL-17 production (Fouser et al., 2008, Prabhala et al., 2010) and that IL-2
reduces Th17 cell differentiation (Kryczek et al., 2007).
1.6.2 The IL-17 cytokine
IL-17, initially termed cytotoxic T lymphocyte-associated antigen-8 (CTLA-8), is a T-cell
derived pro-inflammatory cytokine (Rouvier et al., 1993, Nakae et al., 2002). It is a 32-kDa
22
structural homologue of the cystine knot family of proteins with intra-chain disulphide
bonds (Hymowitz et al., 2001, Prabhala et al., 2010). The structural motif of IL-17 is closely
related to TGF- , nerve growth factor, platelet derived growth factor and bone
morphogenetic proteins (Prabhala et al., 2010). The majority of IL-17 is produced by
activated Th17 cells, however, variable amounts of IL-17 are also produced by CD8 cells
(Shin et al., 1999, Ferretti et al., 2003), T cells (Lockhart et al., 2006), NK cells and
neutrophils (Ferretti et al., 2003, Prabhala et al., 2010).
1.6.3 Th17 cells in cancer
The prevalence and function of Th17 cells in cancer is unknown. The role of Th17 cells in
tumour growth and development, particularly in haematological malignancies, is
undoubtedly complex and remains controversial.
Wróbel et al. (2003) report that the concentration of IL-17 in serum is not significantly
elevated in patients with AML. However, a subsequent study by Wu et al. (2009)
demonstrated an increased frequency of Th17 cells in the PB, and a corresponding elevation
in IL-17 levels, in AML. The study also reported a reduction in Th17 levels once a patient had
achieved complete remission after chemotherapy (Wu et al., 2009). In non-Hodgkin
lymphoma, a low frequency of Th17 cells was observed in the tumour microenvironment,
and it was proposed that lymphoma B cells may favour Treg cells and down-regulate the
Th17 cell generation (Yang et al., 2009). In ovarian cancer, a high percentage of Th17 cells
was observed at the tumour site, but a low percentage of Th17 cells was present in PB
(Miyahara et al., 2008). Further, Su et al. (2010) demonstrated elevated Th17 cell frequency
in TILs from melanoma, breast and colon cancer. An increase in Th17 cells, and Th17-related
cytokines, has been reported in PB and tumour draining lymph nodes and this correlated
with clinical stage (Zhang et al., 2008). It has been suggested that Th17 cells may promote
tumour progression and these cells have been proposed as a potential prognostic marker in
hepatocellular carcinoma (Zhang et al., 2009). Studies have also shown that in prostate
cancer, Th17 cell numbers are inversely proportional to results of the Gleason test, a
prostate cancer staging and prognostic test (Sfanos et al., 2008).
23
1.7 The role of the cytokines TGF- and IL-12 in cancer
Cellular homeostasis requires an intricate balance between cells and the cytokine milieu.
The role of cytokines in the tumour microenvironment is an area that is under investigation
and the possibility of utilising cytokines to improve cancer immunotherapy has been
proposed. The effects of TGF- and IL-12 on immunomodulation (Brunda et al., 1993,
Cerwenka et al., 1999, Chen et al., 2003, King et al., 2005, Tahara et al., 1995, Xu et al.,
2010) suggested that these may be two of the most important immunomodulatory
cytokines and thus have been investigated in this study.
1.7.1 TGF-
TGF- is a widely distributed cytokine which has been the subject of many studies involving
cancer. In brief TGF- , a prototypical member of the TGF- superfamily, is a multifunctional
polypeptide that regulates multiple cellular processes including cellular proliferation,
differentiation, survival and adhesion. There are three known isoforms of TGF- called TGF-
1, TGF- 2, and TGF- 3. It has been reported that TGF- , which may be present in the
tumour microenvironment to prevent premalignant progression, may, however, be
eventually exploited by malignant cells (Massagué, 2008). It has been purported that cancer
cells increase the production of TGF- to allow the cells to be more invasive (Blobe et al.,
2000). Matsumoto and Abe (2011) have suggested that TGF- may, in part, suppress BM
formation in MM and inhibition of TGF- signalling may enhance bone formation and
suppress MM cell growth. Growing evidence suggests that TGF- acts as a tumour-derived
immunosuppressor, prompting interest in TGF- as a therapeutic target.
1.7.2 IL-12
The IL-12 family of cytokines, which includes IL-12, IL-23, IL-27 and IL-35, is produced by
APCs, such as DC and macrophages. IL-12 was formerly termed cytotoxic lymphocyte
maturation factor (CLMF) (Stern et al., 1990) or natural killer cell stimulatory factor (NKSF)
(Kobayashi et al., 1989). The cytokine is required for the differentiation to Th1 cells and is a
crucial mediator of inflammatory disease. The critical role of IL-12 in immune regulation has
drawn attention to its potential use for cancer immunotherapy. Studies have investigated
24
the anti-tumour and anti-metastatic effect of IL-12 in a range of murine tumour models such
as melanomas, sarcomas, mammary, colon and renal carcinomas (Brunda et al., 1993,
Colombo and Trinchieri, 2002). IL-12 induces IFN- production by NK cells and T cells, which
is thought to be essential for the anti-tumour effects of IL-12 (Car et al., 1995, Ryffel, 1997,
Wigginton et al., 2001). Administration of IL-12 has been shown to reduce or eradicate
tumour development in tumour bearing mice (Tahara and Lotze, 1995, Tahara et al., 1995).
However, clinical trials have shown limited efficacy of IL-12 therapy, due to systemic toxicity
including splenomegaly, leucopenia and gastrointestinal toxicity (Ryffel, 1997, Car et al.,
1999). Xu et al. (2010) have suggested administering IL-12 with Treg-depleting antibodies to
minimise toxicity and improve therapeutic efficacy.
1.8 Background to the project
The role of Treg and Th17 cells in MM remains highly controversial. As indicated in Table
1.2, the role of Treg cells in MM is not well defined and conflicting literature exists with
respect to Treg cell number and function. In addition, the proportion of Th17 cells in PB of
patients with MM has not been determined although these patients are reported to have a
higher proportion of Th17 cells in their BM compared to BM of patients with the pre-
neoplastic condition MGUS (Dhodapkar et al., 2008). Alexandrakis et al. (2006) have
suggested that elevated serum IL-17 levels may correlate with higher disease stage in MM.
The reciprocal relationship between Treg and Th17 cells has been reported in the literature,
however the Treg/Th17 cell balance has not been described in cancer or in MM in particular.
An imbalance of Treg and Th17 cells may play a crucial role in the dysfunction observed in
MM. Further work in this area of research will aid in the understanding of the aetiology and
pathogenesis of MM and to enhance progress towards the eventual development of a cure
for this disease.
1.9 Hypothesis
The hypothesis of this study is that dysfunction of normal immune control occurs in patients
with malignancies such as MM and that restoration of immune regulation may be beneficial
to overall survival.
25
1.10 Aims of the project
There are conflicting reports about the quantity and function of Treg and Th17 cells in MM.
Thus the overall aim of this study is to clarify any discrepancies in the literature regarding
Treg and Th17 cell number and function in MM. Furthermore, the immunomodulatory
mechanisms utilised by MM cells to cause immune dysfunction were studied.
The overall aim of the project will be achieved through completion of the following specific
aims:
1. Enumeration of Treg and Th17 cell number in the PB of patients with MM, in normal
individuals and in patients with other B cell malignancies.
2. Determination of the importance of the Treg/Th17 cell balance on survival of
patients with MM.
3. Determination the functional status of Treg cells from patients with MM and from
healthy control individuals.
4. Determination of the effect of specific factors derived from tumour cells (e.g. TGF- ,
IL-12) on Treg cell function.
26
CHAPTER TWO
MATERIALS AND METHODS
27
2.1 Participants
Whole blood was collected from patients with MM, MGUS and WM who attend the
haematology department of Royal Prince Alfred Hospital (RPAH) as part of a routine check.
In this study the mean age was 67 ± 10 yrs, 70 ± 12 yrs, and 79 ± 6 yrs for patients with MM,
MGUS and WM respectively. The patients with MM were dichotomised based on 10 year
survival since diagnosis. Patients surviving for greater than 10 years since diagnosis had a
mean age of 73 ± 9 yrs. An age-matched control group was also recruited for the study with
a mean age of 53 ± 21 yrs. Ethics approval was granted by the Sydney South West Area
Health Service Human Research Ethics Committee (RPAH Zone, Protocol X07-0201).
2.2 Sample collections
2.2.1 Blood sample collection
Venepuncture was performed by trained haematology nursing staff in RPAH. PB was
collected in a 4.0mL BD Vacutainer® blood collection tube containing either 5.4mg K2
Ethylenediamine tetra-acetic acid (EDTA) or lithium heparin (BD Biosciences, New Jersey,
USA) as an anticoagulant. The PB was inverted 3 times immediately upon collection. Using
an automated haematology analyser (Cell-Dyn Sapphire; Abbott Diagnostics, Illinois, USA), a
full blood count was performed on each sample on the day of collection. Samples not tested
on the day of collection were stored overnight at 4°C and tested within 48hrs of collection.
For patients on therapy, blood samples were collected immediately prior to the next course
of therapy to minimise the effects of therapy on the blood cells being investigated.
2.2.2 BM collection
BM was aspirated from consenting patients with MM by trained haematology registrars.
The BM was aspirated into a 20mL tube (Sarstedt, Nümbrecht, Germany) containing 1mL of
Hanks Balanced Salt Solution (HBSS) (Thermo Scientific, Massachusetts, USA), supplemented
with foetal calf serum (FCS) (SAFC® Biosciences, Sigma-Aldrich Missouri, USA) and heparin
(Pfizer, New South Wales, Australia). 20mL of sterile RPMI-10 (described in section 2.3.3)
28
was added to the BM aspirate of samples not tested on the day of collection. BM aspirates
were stored at 4°C and tested within 24hrs of collection.
2.3 Methodology for preparation of common reagents
2.3.1 Preparation of ammonium chloride lysing reagent
Ammonium chloride lysing reagent was prepared by dissolving 4.15g ammonium chloride
(Scharlau Chemie, Spain), 0.45g Sodium hydrogen carbonate (VWR, New Jersey, USA) and
0.018g Na2 EDTA.2H2O (Searle, Nebraska, USA) in 500mL Milli-Q™ water. The Milli-Q™ water
was obtained from the Synergy UV filtering system (Millipore, Madison, USA). The pH of the
lysing reagent was determined immediately before use, using a Beckman 44 pH meter
(Beckman, Fullerton, USA). The desired pH range was between 7.25-7.30.
2.3.2 Preparation of phosphate buffered saline
10 phosphate buffered saline (PBS) (Dulbecco A) tablets (Oxoid Ltd., Hampshire, England)
were dissolved in 1L of Milli-Q™ water (Millipore). The manufacturer’s recommended pH
range was 7.30 ± 0.02. pH was optimised by the addition of either 1N HCl or 1N NaOH where
required.
This PBS method was used for all tests unless stated otherwise.
2.3.3 Preparation of Roswell Park Memorial Institute -10 medium
The Roswell Park Memorial Institute (RPMI) -10 medium was prepared under sterile
conditions in an Airpure biological safety cabinet class II (Westinghouse, Australia).
RPMI-1640 cell culture medium with 20mM HEPES, without L-glutamine, sodium
bicarbonate (MP Biomedicals, LLC, Ohio, USA) was supplemented with 10% (v/v) foetal
bovine serum (SAFC Biosciences, Australia).
The RPMI-10 medium was stored at 4°C until required.
29
2.3.4 Preparation of RPMI cell culture medium
The RPMI cell culture medium was prepared under sterile conditions in an Airpure biological
safety cabinet class II (Westinghouse). The following were added to 500mL of RPMI-1640
cell culture medium containing 20mM HEPES, without L-glutamine or sodium bicarbonate
(MP Biomedicals):
50mL heat inactivated, irradiated foetal bovine serum (SAFC Biosciences)
5mL of 1.0mM sodium pyruvate (Invitrogen™, Beijing, China)
5mL of 2mM L-glutamine, 10 l/mL Penicillin/ Streptomycin antibiotics (Invitrogen™,
California, USA)
2mL of 1.5g/L sodium bicarbonate (Invitrogen™, Mulgrave, Australia )
The RPMI cell culture medium was stored at 4°C until required.
2.3.5 Preparation of MACSBeads
Anti-CD2, CD3, CD28 beads were used to stimulate the proliferation of T cells.
For preparation of the MACSbead suspension, a T cell activation/expansion kit containing
anti-biotin MACSiBead (Miltenyi Biotec, Bergisch Gladbach, Germany) was used, in
accordance with the manufacturer’s instructions. 0.4mL CD2-Biotin, 0.4mL CD3-Biotin, and
0.4mL CD28-Biotin, were added to 2mL MACS® anti-biotin MACSiBead™ particles and spun
using a Clements mixer (H.I. Clements Pty Ltd, North Ryde, NSW) for 2hrs at 4°C, yielding a
final concentration of 1x105 beads/ L.
2.3.6 Preparation of carboxyfluorescein succinimidyl ester stain
Carboxyfluorescein succinimidyl ester (CFSE) is a fluorescent cell permeable dye that can be
used to monitor the proliferation of cells. CFSE passively diffuses into cells and binds to
intracellular molecules where it is cleaved by intracellular esterases to yield a fluorescent
dye. As CFSE stained cells divide the daughter cells retain half the original CFSE fluorescence.
30
CFSE
Coun
t
When analysed by flow cytometry (Figure 2.1), each decreasing peak in fluorescence
corresponds to each cell division.
Figure 2.1: Flow cytometric analysis of a CFSE stained cell population The histogram shows the proliferation of a CFSE stained cell population. As each cell divides
the daughter cells retain half the amount of CFSE, seen by the sequential reduction in
fluorescence. Each peak is proportional to the number of cell division. 6 divisions are
displayed in the above flow plot.
The CellTrace™ CFSE Cell Proliferation Kit (Invitrogen™, Mulgrave, Australia) was used to
prepare CFSE. 1 vial of CFSE containing 50 g of lyophilised powder was dissolved in 50 L of
dimethyl sulfoxide (DMSO) (Sigma Aldrich, St Louis, MO, USA). The suspension of CFSE at a
concentration of 5mM was then divided into 2 L aliquots and stored in a Sanyo MDF-U50V
freezer (Sanyo, Japan) at -80°C until required.
Immediately prior to use, the 2 L aliquot was resuspended into 48 L of 37oC RPMI cell
culture medium.
31
2.4 General techniques
2.4.1 Cell wash
Cell washes were generally with 2mL PBS for 2min at 300g, unless otherwise stated.
2.4.2 Isolation of mononuclear cells using Ficoll-Paque density gradient centrifugation
Ficoll-Paque Plus (GE Healthcare, Uppsala, Sweden) was used for the isolation of peripheral
blood mononuclear cells (PBMC) for analysis of Th17 cells and bone marrow mononuclear
cells (BMMC) for identification of BM Treg cells. Ficoll-Paque is a density gradient
centrifugation medium for separation of PB or BM into its constituent components. After
centrifugation of PB or BM with Ficoll-Paque, shown in Figure 2.2B, the bottom layer
contains aggregated erythrocytes and granulocytes; above is the Ficoll-Paque layer; the
lymphocytes, monocytes and platelets sit above the Ficoll-Paque; and the top layer contains
plasma.
Figure 2.2: Whole blood before and after centrifugation with Ficoll-Paque A. Image of diluted PB over a layer of Ficoll-Paque prior to centrifugation. B. After
centrifugation using Ficoll-Paque the PB is separated into its constituent components.
A B
Diluted whole blood
Ficoll-Paque
Peripheral blood mononuclear cells
Plasma
Ficoll-Paque, granulocytes and Red blood cells
32
PB was diluted with PBS (Oxoid, England) at a 1:1 ratio and, using a plastic transfer pipette
(Samco Scientific, California, USA), was gently layered over the Ficoll-Paque in an 8mL
polycarbonate round bottom tube (Sarstedt, South Australia, Australia) at a ratio of 3mL
Ficoll-Paque to 4mL diluted PB. The Ficoll-Paque and diluted PB were then centrifuged at
360g for 15min at 20oC (room temperature; RT) using a Spintron GT10S-V3 centrifuge
(Spintron, Australia). The PBMC layer was collected using a plastic transfer pipette and
transferred into another 8mL polycarbonate tube. The PBMC were then washed in
approximately 7mL PBS and centrifuged at 360g for 10min at RT. The remaining cell pellet
was then resuspended in 1mL RPMI-10.
33
2.5 Monoclonal antibodies used during experimentation
Table 2.1: List of monoclonal antibodies (mAb) used during experimentation mAb name/ specificity
Fluorophore Isotype Clone Company details
CD3 FITC Ms IgG1, SK7 BD, San Jose, CA, USA
CD3 PerCP-Cy5.5 Ms IgG1, SK7 BD
CD4 APC Ms IgG1, SK3 BD
CD4 PE-Cy7 Ms IgG1, SK3 BD
CD4 PerCP-Cy5.5 Ms IgG1, SK3 BD
CD25 APC Ms IgG1, 2A3 BD
CD45RA FITC Ms IgG2b, HI100 BD
CD45RO FITC Ms IgG2a, UCHL1 BD
CD127 PE Ms IgG1, hIL-7R-M21 BD
IL-17 PE Ms IgG1 41802 R&D Systems, Minneapolis, MN, USA
FoxP3 Alexa Fluor® 647 (AF-647)
Ms IgG1, 206D Biolegend, San Diego, CA, USA
FoxP3 PE Ms IgG1 259D/C7 BD
Isotype control APC Ms IgG2a, G155-178 BD
Isotype control FITC Ms IgG1, 1 BD
Isotype control PE Ms IgG1, X40 BD
Isotype control PerCP-Cy™ 5.5 Ms IgG2a, G155-178 BD
FITC: Fluorescein isothiocyanate, PE: Phycoerythrin, PerCP-Cy™ 5.5: Peridinin chlorophyll
protein conjugate with a cyanine-5.5 protein, APC: Allophycocyanin, PE-Cy7: Phycoerythrin
conjugated with cyanine-7 protein
34
2.6 Assay for identification of Treg cells
2.6.1 Cell staining for flow cytometric identification of CD127lo/- Treg cells
100 L of PB from participants was lysed with 2mL lysing reagent (described in section 2.3.1)
for 10min at RT. The lysed blood was then centrifuged for 2min at 300g in an EBA 21
centrifuge (Hettich Zentrifugen, Tuttlingen, Germany) and the supernatant, containing lysed
red cells, was discarded. The cell wash was repeated with PBS to remove any residual lyse
buffer or red cells. The remaining leukocytes were then incubated at RT for 15min with
fluorescent labelled mAb (Table 2.2) in the dark. Following the incubation period, the cells
were washed and the supernatant was discarded. The resulting cell pellet was resuspended
in 0.5mL of PBS. Analysis of the sample was performed on the BD FACSAria II using DIVA
software for acquisition (BD Biosciences, San Jose, CA).
Table 2.2: Fluorescent antibodies used for the flow cytometric identification of Treg cells using CD127
mAb Fluorophore Volume per test
Tube ID
CD45RA CD45RO
CD4 PerCP-Cy5.5 20 L
CD25 APC 5 L
CD127 PE 10 L
CD45RA FITC 20 L
CD45RO FITC 20 L
: indicates mAb in use
2.6.2 Preparation of PBMC Treg cell identification using FoxP3
PBMCs, were fluorescently labelled with the surface antibodies against CD3, CD4, and CD25
(see Table 2.3) for 15min at RT in the dark. The cells were then washed and the supernatant
discarded. 250 L CytoFix/CytoPerm BD™ Fixation/Permeabilisation solution (Becton
Dickinson, SanDiego, CA, USA) was added to the PBMC and incubated for 20min at RT in the
dark. The labelled PBMC were washed once with the Cytofix/Cytoperm washing solution
35
and again with PBS. The suspension of permeabilised cells was incubated with fluorescent-
labelled intracellular antibody against FoxP3 for 30min in the dark at 4°C. The cells were
washed and resuspended in 0.5mL of PBS for acquisition on the BD FACSAria II.
Table 2.3: Fluorescent antibodies used for the flow cytometric identification of Treg cells using FoxP3
mAb Fluorophore Volume per test
Tube ID
FoxP3 AF-647
FoxP3 PE
CD3 PerCP-Cy5.5 20 L
CD4 PE-Cy7 5 L
CD25 FITC 5 L
FoxP3 AlexaFluor647 5 L
FoxP3 PE 10 L
: indicates mAb in use
2.6.3 Preparation of BM Treg cells for flow cytometric analysis
100 L of BMMC suspension was incubated for 15min at RT with mAb in the dark, as per
Table 2.4. The cells were then washed in PBS and the supernatant was discarded. The
resulting cell pellet was resuspended in 0.5mL of PBS. Analysis of the sample was performed
on the BD FACSAria II using DIVA software (BD Bioscience) for acquisition.
36
Table 2.4: Fluorescent antibodies used for the flow cytometric identification of BM Treg cells
mAb Fluorophore Volume per test
CD3 PerCP-Cy5.5 20 L
CD4 PE-Cy7 5 L
CD25 APC 5 L
CD127 PE 10 L
2.7 Methodology for the identification of Th17 cells in PB
2.7.1 Preparation of Th17 cells for flow cytometric analysis
1x106 PBMCs, obtained using the Ficoll-Paque method described in section 2.4.2, was
diluted up to 1mL with RPMI-10. The cell suspension was then incubated with 50ng/mL
phorbol 12-myristate 13-acetate (PMA) (Sigma Aldrich, Missouri, USA) and 750ng/mL
Ionomycin calcium salt, from Streptomyces conglobatus (Sigma Aldrich, Israel) in a Ratek
WB14 water bath (Ratek Instruments, Australia) at 37°C for 2.5hrs. The use of PMA and
Ionomycin stimulates the production of cytokines within cells. The release of cytokines from
the cell was blocked by the addition of 10 L of a 1/10 solution of Brefeldin A diluted with
PBS (Becton Dickinson, USA) followed by a further 2.5hrs incubation in a 37°C water bath.
The cell suspension was then washed in 3mL PBS (Oxoid, England) for 5min at 300g using an
EBA 21 centrifuge (Hettich Zentrifugen). The supernatant was discarded and the resulting
cells were incubated with surface antibodies, as per Table 2.5 for 15min at RT in the dark.
The cells were then washed in 2mL PBS for 3min at 300g. The supernatant was discarded
and the cells were incubated with 250 L CytoFix/CytoPerm BD™ Fixation/Permeabilisation
solution (Becton Dickinson) for 20min at RT in the dark. After washing twice in PBS, the
permeabilised cells were divided into two separate 5mL, 12mm x 75mm, polystyrene round-
bottom tubes (BD Bioscience) and incubated with intracellular antibodies to either human
IL-17 (R&D Systems) or mouse IgG1 (BD Bioscience) for 30min at RT in the dark. The cells
37
were washed and resuspended in 0.5mL PBS. The cell suspension was analysed on the BD
FACSAria II.
Table 2.5: Fluorescent antibodies used to identify Th17 cells for analysis by flow cytometry
mAb Fluorophore Volume Isotype control
Th17 test
Surface mAb
CD3 PerCP-Cy5.5 20 L
CD4 APC 5 L
Intracellular mAb
Mouse IgG1 PE 10 L
IL-17 PE 10 L
: indicates mAb in use
2.8 Treg cell functional assay using CFSE
2.8.1 Fluorescence-activated cell sorting of PBMC
Fluorescence-activated cell sorting (FACS) is a process that allows cells of interest to be
physically separated from a heterogeneous population. All blood samples were prepared
under sterile conditions in an Airpure biological safety cabinet class II (Westinghouse).
PB was diluted at a 1:1 ratio with sterile PBS pH7.4 without calcium chloride and magnesium
chloride (GIBCO Invitrogen, Grand Island, New York, USA). PBMC were obtained by Ficoll-
Paque separation (as previously described in section 2.4.2). Briefly, 30mL of diluted whole
blood was layered over 20mL of Ficoll-Paque in a sterile Blue Max 50mL polypropylene
conical tube (BD Bioscience). The tube was then centrifuged for 25min at 360g, without
brakes, using a Spintron GT10S-V3 centrifuge (Spintron, Australia). The PBMC were
harvested into a separate tube and washed in 45mL sterile PBS (GIBCO Invitrogen) by
centrifugation for 15min at 360g. The supernatant was discarded and the cells were stained
with antibodies, as per Table 2.6, followed by a 30min incubation period, on ice, in the dark.
The PBMC were then washed in sterile PBS (GIBCO Invitrogen) for 5min at 300g, the
supernatant was discarded and the cells were resuspended in 1mL sterile PBS (GIBCO
38
Invitrogen). The suspension was filtered into a 5mL polystyrene round bottom tube with a
cell strainer cap (BD Bioscience) and then sorted using the BD FACSAria II. Both Treg cells
(referred to hereafter as ‘purified Treg’); defined as CD3+CD4+CD25hiCD127lo/-) and
remaining CD3+ cells (referred to hereafter as ‘target’) were sorted into a 5mL polystyrene
round bottom tube (BD Bioscience). Once the sorting process was complete, the cells were
washed for 5min at 300g. The supernatant was discarded and the cells were resuspended in
1mL RPMI cell culture medium.
Table 2.6: Fluorescent antibodies used to identify Treg cells for flow cytometric sorting
Ab Specificity Fluorophore Volume per test
CD3 FITC 40 L
CD4 PE-Cy7 10 L
CD25 APC 10 L
CD127 PE 20 L
2.8.2 FACS purity test
Once the FACS was complete, 10 L of the sorted target cells and purified Treg cell
suspension were each diluted in 200 L of PBS and analysed on the BD FACSAria II. In this
study the criteria for a successful FACS process was to yield a purity of greater than 90%. If
this was not achieved the experiment would be abandoned.
2.8.3 CFSE staining of target cells
2mM CFSE was added to the sorted target cells suspension and incubated at 37°C for 10min.
To quench the reaction, 3mL of cold RPMI cell culture medium was added to the cell
suspension and placed on ice for 5min. The cell suspension was then spun at 300g for 5min
and the supernatant was discarded. The CFSE labelled cells were resuspended in 1mL RPMI
cell culture medium.
39
2.8.4 Cell count
A cell count was performed on both the target and purified Treg cell suspensions. The
sorted cells were counted on a Neubauer Improved Hemocytometer counting chamber
(American Optical Corporation, New York, USA) using a Carl Zeiss light microscope (Carl
Zeiss, New York, USA).
The following formula was used to determine the number of cells in the suspension:
N= number of cells counted in 25 squares of the centre grid
Volume= Volume of cell suspension (mL)
2.8.5 Preparation of the MACSbead suspension
5 L of MACSbeads from stock (equivalent to 5x105 beads) (described in section 2.3.5) was
suspended in 1mL RPMI cell culture medium in a 2mL microtube (Sarstedt, Numbrecht,
Germany) followed by a 5min centrifugation at 300g using an Eppendorf centrifuge 5415D
(Eppendorf AG, Hamburg, Germany) to remove any preservatives. The supernatant was
discarded and the MACSbeads were resuspended in 1mL RPMI cell culture medium.
2.8.6 Cell culture of Treg and CFSE stained target cell
All samples were plated under sterile conditions in an Airpure biological safety cabinet class
II (Westinghouse). The cells were placed in a 96 well U bottom tissue culture plate with low
evaporation lid (Becton Dickinson Labware, Franklin Lakes, NJ, USA) and cultured for four
days at 37oC with 5% CO2 in a NuAire NU-5100E DH Automatic CO2 Direct incubator (Nuaire,
Plymouth, MN, USA).
As displayed in Figure 2.3, to monitor normal proliferation of target cells, a cell culture well
containing CFSE stained target cells was cultured with MACSbeads at a 1:1 ratio. To
determine the suppressive capabilities of Treg cells, a 1:1 ratio of purified Treg cells to
target cells was added to a well containing MACSbeads. As a control, target cells were
Total number of cells/mL = N X 104 X Volume (mL)
40
cultured without MACSbeads and purified Treg cells, as this would demonstrate where the
non-proliferating target cells were positioned on the flow cytometric histogram. Another
control well was set up with MACSbeads and target cells at a 1:2 ratio.
RPMI cell culture medium was added to each well for a final concentration of 25x104
cells/mL.
Figure 2.3: Cell culture plate set up for investigation of Treg cell function
This figure displays the set-up of the 96 well cell culture plates, described in section 2.8.6, to
investigate the suppressive activity of Treg cells. The cell culture wells A and D were used as
a control to monitor proliferation without beads (well A) and with twice the cells (well D).
Cell culture wells B and C were used to evaluate the suppressive activity of Treg cells.
*Please note a 96 well U bottom tissue culture plate was used.
Target cells No beads
Target cells with beads &
Treg cells 1:1:1
Target cells & beads
2:1
Target cells & beads
1:1
A B C D
41
2.8.7 Analysis of the CFSE assay after culture
After 4 days, the cultured cells were transferred from the cell culture plate to a 5mL
polystyrene round-bottom tube (BD Bioscience). The cells were then washed in 2mL PBS at
300g for 3min in an EBA 21 centrifuge (Hettich Zentrifugen). The supernatant was discarded
and the cells were incubated for 15min with the antibodies detailed in Table 2.7. FITC
conjugated antibodies could not be used simultaneously with CFSE due to the similar
excitation and emission properties. The cells were washed and the supernatant discarded.
The remaining cells were resuspended in 0.5mL PBS. Flow cytometric acquisition of the
sample was performed on a BD FACSAria II (BD Bioscience).
Table 2.7: Fluorescent antibodies used for analysis of the CFSE assay by flow cytometry
Ab Specificity Fluorophore Volume per test
CD3 PerCP-Cy5.5 10 L
CD4 PE-Cy7 5 L
CD25 APC 5 L
2.9 Evaluation of the impact of cytokines (IL-12 and TGF- ) and anti-TGF- on Treg cells
To determine the effect of IL-12, TGF- , and anti-TGF- on Treg cells, the same methodology
described in section 2.8.1 to 2.8.5 was followed for FACS, CFSE staining of the target cell
suspension and preparation of MACSbead suspension.
2.9.1 IL-12 preparation
Recombinant human (rh)- IL-12 (R&D Systems, Minneapolis, MN, USA) was stored at -20oC
at a concentration of 10 g/mL. Stock solution was diluted with RPMI cell culture medium to
a final working concentration of 100ng/mL per well.
42
2.9.2 rhTGF- 1 preparation
rhTGF- 1 (R&D Systems, Minneapolis, MN, USA) was stored at -20oC at a concentration of
1 g/mL. Stock solution was diluted with RPMI cell culture medium to a final working
concentration of 100pg/mL per well.
2.9.3 Anti TGF- preparation
Monoclonal anti-human latency associated peptide (LAP) (TGF- 1) antibody (R&D Systems,
Minneapolis, MN, USA) was stored at -20oC at a concentration of 500 g/mL. Stock solution
was diluted with RPMI cell culture medium to a final working concentration of 10ng/mL per
well.
2.9.4 Plating of the cell culture wells with addition of cytokines
All samples were plated under sterile conditions in an Airpure biological safety cabinet class
II (Westinghouse). The cells were placed in a 96 well U bottom tissue culture plate with low
evaporation lid (Becton Dickinson Labware, USA) and cultured for 4 days at 37oC with 5%
CO2 in a NuAire NU-5100E DH Automatic CO2 Direct incubator (Nuaire, USA).
As demonstrated in Figure 2.4, the CFSE stained target cells were cultured with MACSbeads
at a 1:1 ratio. To determine the normal suppressive capabilities of Treg cells, equal numbers
of purified Treg cells were co-cultured with MACSbead stimulated target cells. To determine
the effect of cytokines on Treg cell suppression, either 100ng/mL of IL-12, 100pg/mL TGF-
or 10ng/mL anti-TGF- was added to the cell culture wells with and without purified Treg
cells.
As a proliferation control, target cells were cultured without either MACSbeads or purified
Treg cells. Another control well was set up with beads and target cells at a 1:2 ratio.
43
Figure 2.4: Cell culture plate set up to evaluate the effect of IL-12, TGF- , and anti-TGF-
on the function of Treg cells
This figure displays the set-up of the cell culture plates, described in section 2.9.4, to
determine the effect of IL-12, TGF- , and anti-TGF- on the suppressive activity of Treg cells.
Cell culture wells A and D were used as a control to monitor proliferation without
MACSbeads (well A) and with twice the cells (well D). The cell culture wells in column B and
C were used to evaluate the suppressive activity of Treg cells and the effect of IL-12, TGF- ,
and anti-TGF- on the suppressive activity of Treg cells. ppppppppppppppppppppppppppp
*Please note a 96 well U bottom tissue culture plate was used.
A B C D Target cells No beads
CTarget cells with beads & Treg cells
1:1:1
Target cells & beads
2:1
Target cells & beads
1:1
Target cells & beads
1:1 with rhIL-12
Target cells with beads &
Treg cells 1:1:1
with rhIL-12
Target cells & beads
1:1 with rhTGF-
Target cells with beads &
Treg cells 1:1:1 with rhTGF-
Target cells & beads
1:1 with anti-TGF-
Target cells with beads &
Treg cells 1:1:1 with anti-TGF-
44
2.10 Statistics and analysis
FlowJo software (TreeStar Inc, USA) Version 7.6.4 (PC compatible) was used for analysis of
flow cytometric data.
Statistical analysis of data was performed on GraphPad Prism software versions 5 (GraphPad
Inc, San Diego, California, USA) and calculated using a two-tailed unpaired Students T-test
when of equal variance. For statistical analysis of the Treg cell proportion in BM and PB
comparison a paired Student T-test was performed. The Kaplan-Meier survival curve was
used for statistical comparison between high and normal Treg/Th17 ratio, this was assessed
using a chi-square analysis. P values less than 0.05 were deemed statistically significant. All
experimental data are shown as a mean values ± standard error of mean (SEM) in the text
and the mean is also indicated in the figures.
45
CHAPTER THREE
RESULTS
46
3.1 Overview
The enumeration of Treg and Th17 cells in the PB of patients with MM has been
controversial. Treg and Th17 cells are thought to provide immunological homeostasis and
any imbalance in the number and function of these cells could impact immune control and
potential clinical recovery of patients with MM. The discrepancies that exist in the literature
regarding Treg and Th17 cell number and function in MM, summarised in Table 1.2,
substantiate the need for more research in this field. Therefore, the quantity of Treg and
Th17 cells in the PB of patients with MM, WM, MGUS and the normal control group was
examined using a CD4, CD25 and CD127 staining method for identifying Treg cells (Figure
3.2). Further, a comparison of Treg cell function between normal individuals and patients
with MM was also investigated. In addition, the effect of cytokine treatment on the function
of Treg cells is also detailed. These studies support the proposal that it is the homeostatic
balance between Treg and Th17 cells which is more important than the actual number of
either cell type alone.
3.2 Treg cells in monoclonal gammopathies
3.2.1 Identification of Treg cells using CD127
In order to enumerate Treg cells in the PB of normal subjects and patients with monoclonal
gammopathies, Treg cells needed to be clearly identified amongst other leucocytes. For this
portion of the study, Treg cells were defined as CD4+CD25hiCD127lo/-. The flow cytometric
gating strategy used to obtain Treg cell proportions of lymphocytes is displayed in Figure 3.2
using a representative normal PB sample. Using the size (forward scatter; FSC) and
granularity (side scatter; SSC) parameters, the lymphocyte population was able to be
identified amongst the leucocytes, as depicted in Figure 3.2A. Anti-CD4-PerCP-Cy5.5 was
then used to isolate the T helper cells (Figure 3.2B), of which Treg cells are a subset. To
distinguish the Treg cell population amongst the CD4+ cells, anti-CD25-APC and anti-CD127-
PE were used. The Treg cell population was then identified according to high surface
expression of CD25 and low or negative expression of CD127 (Figure 3.2C). Relevant isotype
controls were performed during the optimisation process, as shown in Figure 3.1, but this
was not required once the assay had been established.
47
SSC
-APC
G1 isotype control for PE G1 isotype control for FITC
G1 isotype control for APC G1 isotype control for PerCP-Cy5.5
Figure 3.1: Isotype control for each fluorochrome used in the Treg cell assay
An anti-mouse IgG1 antibody conjugated to relevant fluorochromes was used as an isotype
control to determine the level of non-specific staining and auto-fluorescence. This was
performed during the optimisation process, but was not required once the assay had been
established.
FSC
Coun
t -FITC -PE
-PerCP-Cy5.5
48
Figure 3.2: Flow cytometry results from a representative normal subject showing the gating strategy for identification of Treg cells in PB
The figure presents the flow cytometric analysis used to identify Treg cells. CD4+CD25hiCD127lo/- expression was used to enumerate Treg cell
numbers in PB. In the Treg assay, cells were analysed after a gating strategy that included a lymphocyte gate on the FSC/SSC scattergram and
the identification of the CD4+ population (Figure 3.2B). Treg cells were then identified from a scattergram which identified a population of CD4+
cells which were CD25hi and CD127lo/- (Figure 3.2C). The results were expressed as a percentage of the CD4+ cells and also as an absolute
number, calculated using the lymphocyte count. CD
127
A B C
CD4 CD25 SSC
FSC
49
3.2.2 Identification of Treg cells using FoxP3
Early research into Treg cells used FoxP3, a transcriptional repressor, to identify Treg cell
populations, defined as CD4+CD25hiFoxP3+. FoxP3 is required in Treg cells as it is associated
with its suppressive capabilities. However, there are problems associated with the use of
FoxP3 as a marker for Treg cells. The use of FoxP3 limited research to only the identification
of Treg cells and functional assays could not be performed, as this required permeabilisation
of the cells, therefore destroying the cells of interest. In addition, Law et al. (2009)
demonstrated that FoxP3 results were dependent on the clones, fluorochromes attached
and fixation/permeabilisation methods used. These difficulties were also encountered
during early optimisation experiments in this project whereby in some cases it was difficult
to achieve a clear separation between FoxP3 positive and FoxP3 negative populations using
flow cytometry (Figure 3.3). Additionally, identifying the CD25hi population was found to be
subjective. Therefore, due to the complications and limitations associated with the use of
FoxP3, the lack of CD127 expression was preferred as the primary marker for identification
of Treg cells, and FoxP3 was omitted from the Treg cell identification panel.
To determine whether Treg cells, defined as CD4+CD25hiCD127lo/- expressed FoxP3, the Treg
cells were sorted from PBMC, using a BD FACSAria II flow cytometric sorter. FoxP3
expression was determined on the purified Treg cells and remaining Treg depleted CD3+ T
cells. As expected, the CD127lo/- Treg cells were found to express intracellular FoxP3 at a
greater level of fluorescence than other CD4+ cells (Figure 3.4).
50
FoxP3 AlexaFluor647
CD25 FITC
CD4
PEcy
7
CD4 PECy7
CD3
Perc
Pcy5
.5
SSC
FSC
FoxP3 PE
Figure 3.3: Flow cytometry results from a representative normal subject showing the gating strategy for identification of PB Treg cells using FoxP3 The figure presents the flow cytometric gating strategy to identify Treg cells defined as
CD3+CD4+CD25hiFoxP3+. Treg cells were analysed after a gating strategy that included a
lymphocyte gate on the FSC/SSC scattergram and the identification of the CD3+CD4+
population. The CD4+CD25hi (Treg) and CD4+CD25- T cells were analysed for their FoxP3
expression. The overlay histogram (bottom row) highlights the difference in FoxP3
expression in Treg cells and other CD4+CD25- T cells, as well as revealing the difference in
expression when using different fluorochrome labelled FoxP3 antibodies.
CD4+CD25- cells
CD4+CD25+ cells
51
Coun
t
Figure 3.4: Comparison of FoxP3 expression on sorted CD25hiCD127lo/- Treg cells compared to the Treg depleted T cells
The figure demonstrates the flow cytometric gating strategy used to determine whether the CD4+CD25hiCD127lo/- Treg cells also expressed
FoxP3. After sorting PBMC for Treg cells, both the isolated Treg cells and the Treg depleted cells were examined for FoxP3 expression. Row A
displays the FoxP3 expression of Treg depleted CD4+ T cells. Row B displays the FoxP3 expression results of the purified Treg cells suspension.
The lymphocyte population was gated based on FSC/SSC characteristics. CD4+ cells were gated based on the constitutive expression of CD3 and
CD4. These CD3+CD4+ cells were then gated and analysed for their FoxP3 expression. The overlay histogram (far right) highlights the difference
in FoxP3 expression in Treg cells and other T cells.
Treg depleted
Purified Treg cells CD
4
FSC
CD3 FoxP3
A
B
SSC
52
3.2.3 Enumeration of Treg cells in PB
There are conflicting results in the literature with regards to PB Treg cell proportions in
patients with MM and in normal subjects. Early studies used CD25hiFoxP3+ cells to identify
Treg cells, and the discrepancies in the literature may be due to the difficulties associated
with FoxP3 staining, discussed in section 3.2.2. Through the use of CD127, the limitations
and difficulties were diminished due to the simplified methodology and reduced processing
required for the identification of Treg cells. Therefore, the use of CD127 provided clearer
indication of Treg cell quantitation in PB.
Flow cytometry was used to enumerate Treg cells in PB of patients with MM (n=32), MGUS
(n=20), WM (n=13) and the normal controls (n=36). After analysis of the flow cytometry
results, Treg cell numbers, as a proportion of CD4+ lymphocytes, were attained. The
lymphocyte count obtained from the Cell-Dyn Sapphire haematology analyser of RPAH, was
used in conjunction with the CD4+ cell percentage obtained by flow cytometry to calculate
the absolute CD4 count. In addition the Treg cell percentage was obtained by flow
cytometry to determine the absolute Treg cell count.
The percentage of Treg cells in the CD4+ compartment (Figure 3.5A) and absolute number
(Figure 3.5B) in PB were statistically compared between the different patient groups and the
normal controls. The mean percentage of Treg cells in the PB of patients with MM was
8.9±0.6% and was significantly elevated (P<0.01) compared to the mean percentage of Treg
cells of the normal controls at 6.5±0.4%. On average, patients with MGUS appear to have a
higher percentage of PB Treg cells compared to normal controls (7.5±0.8%), however this
was not found to be significant (P=0.24). In addition, no significant difference was observed
between the percentage of Treg cells in the control group and patients with WM (6.0±0.5%;
P=0.48). Interestingly, however, the absolute number of Treg cells in PB revealed a different
outcome between the patients with WM and the control group; suggesting that there is a
significant difference in absolute number of Treg cells in patients with WM [(3.0±0.6) x107/L]
compared to the normal control cohort [(6.4±0.7) x107/L; P<0.01]. A significantly lower
absolute number of Treg cells was also observed in patients with MM [(3.2±0.4) x107/L;
Absolute Treg cells = Absolute CD4 count X Per cent Treg cells of CD4+ cells
53
P<0.01] compared to healthy individuals. However, absolute Treg cell numbers in patients
with MGUS [(4.3±0.8) x107/L; P=0.06] did not differ significantly from those of the normal
control cohort.
54
A
B
Normal MM MGUS WM0
5
10
15
20 * *NS
Abso
lute
Tre
g (x
107 /L
)
Figure 3.5: Enumeration of PB Treg cells in patients with monoclonal gammopathies and normal control individuals A. The data are presented as a percentage of Treg cells, as part of the CD4+ cell
compartment, in PB of normal individuals (n=36) and patients with MM (n=32), MGUS
(n=20) and WM (n=13) respectively. B. The data demonstrate the absolute number of Treg
cells in PB of normal individuals (n=39) and patients with MM (n=32), MGUS (n=20) and WM
(n=13) respectively. The mean of each cohort is represented by the horizontal black line. For
analysis, an unpaired two-tailed t-test was performed with a comparison between the
outcomes of patients with monoclonal gammopathies compared to the normal control.
*P<0.05, NS- Not significant.
Normal MM MGUS WM0
5
10
15
20* NS NS
% T
reg
cells
of C
D4+ T
cel
ls
55
3.2.4 Phenotypic analysis of Treg cells
To determine whether the Treg cells were of a naïve or memory cell phenotype, cell surface
expression of CD45RA and CD45RO were determined using anti-CD45RA-FITC and anti-
CD45RO-FITC. Naïve T cells have surface expression of CD45RA whereas CD45RO is
expressed on memory T cells. Displayed in Figure 3.6 is a representative flow cytometric
analysis sequence used to determine the naïve or memory phenotype of PB Treg cells. It
appears that the majority of PB Treg cells were of a memory cell phenotype (Figure 3.7) and
this was consistent amongst both normal individuals and those with monoclonal
gammopathies.
The nature of Treg cells was determined in the PB of the normal cohort (n=26) and
compared to the PB of patients with MM (n=31), MGUS (n=20) and WM (n=13). In
comparison to the normal cohort (16.3±2.1%), the proportion of naïve Treg cells in PB of
patients with MM (12.0±1.9%; P=0.13), MGUS (17±2.4%; P=0.83), and WM (9.8±2.2%;
P=0.06) was not significantly different. Although no significant difference was observed in
CD45RA+ Treg cells proportions in patients with MM they appeared to have a significantly
higher proportion of CD45RO+, memory T cell phenotype, compared to normal subjects
(85.9±1.8; 76.7±2.5 respectively P<0.01). Similarly, Treg cells in patients with WM had a
significantly higher proportion of memory Treg cells compared to the normal cohort
(86.4±2.1%; P=0.02). No significant difference was observed in the CD45RO+ Treg cell
proportion between patients with MGUS and the control group (73.4±4.0%; P=0.47).
56
A
B
Figure 3.6: Flow cytometry results showing CD45RA and CD45RO expression on Treg cells in PB of a representative normal subject PB Treg cells from patients with monoclonal gammopathies and normal individuals was
analysed for their expression of CD45RA+ (naïve phenotype) or CD45RO+ (memory
phenotype). The gating strategy displayed in Figure 3.2 was followed for the identification of
Treg cells. A. Displays a representative result of CD45RA expression on PB Treg cells. B
Displays a representative example of CD45RO expression on PB Treg cells. The majority of
Treg cells appear to be of the memory cell phenotype.
57
CD45RA CD45RO CD45RA CD45RO CD45RA CD45RO CD45RA CD45RO0
20
40
60
80
100
Normal MM MGUS WM
* *%
of t
otal
Tre
g ce
lls
Figure 3.7: Expression levels of CD45RA and CD45RO on Treg cells in PB of patients with monoclonal gammopathies and normal individuals The data are presented as a percentage of CD45RA or CD45RO expression on Treg cells in PB of patients with MM (n=31), MGUS (n=20) and
WM (n=13) compared to the normal cohort. The results of the experiment are presented as a mean ± SEM, shown by the error bars. For
analysis, an unpaired two-tailed t-test was performed with a comparison between the results of patients with monoclonal gammopathies
compared to the normal control. The CD45RO expression on PB Treg cells was found to be significantly higher in patients with MM and WM
compared to normal individuals. *P<0.05
58
3.2.5 Effect of IMiD treatment on Treg cell proportions
In patients with MM, the effect of IMiD therapy on Treg cell proportion was investigated.
Patients undergoing lenalidomide treatment (7.9±0.9%; P=0.89) did not appear to have a
significantly different percentage of Treg cells compared with patients who had not
undergone IMiD therapy. However, a trend for an increase in the proportion of Treg cells
was observed in patients with MM treated with thalidomide (12.7±2.1%) compared to
patients with MM not treated with IMiD therapy (8.1±0.7%; P=0.02), this was found to be
significant as shown in Figure 3.8. For a more conclusive analysis however, additional
patients would need to be tested. Difficulty in testing more patients treated with
thalidomide was encountered, as the use of thalidomide therapy was being phased out and
replaced with lenalidomide. The effect of IMiD therapy on the absolute number of Treg cells
was not analysed due to the limited sample number.
In accordance with previous publications (Chiarenza et al., 2009, Quach et al.,
2008,Minnema et al., 2007)
59
no-IMiD Thalidomide Lenalidomide0
5
10
15
20
NS*
% T
reg
cells
of C
D4+ T
cel
ls
Figure 3.8: Effect of IMiD treatment on PB Treg cell proportions in patients with MM The data are presented as a percentage of Treg cells in the CD4+ compartment of PB in
patients treated with thalidomide (n=4), lenalidomide (n=7) and patients not treated with
IMiDs (n=21). The black horizontal line represents the mean of each cohort. For analysis, an
unpaired two-tailed t-test was performed with a comparison between the percentage of PB
Treg cell in patients with IMiD therapy and those that had not undergone treatment with
IMiDs. The results indicate a significant increase in PB Treg cells of MM patients treated with
thalidomide compared to patients not treated with IMiDs. However, no significant change
was observed in PB Treg cells of patients treated with lenalidomide. *P<0.05, NS- Not
significant.
60
3.2.6 MM staging and Treg cell quantitation
Currently, MM staging is based on the ISS criteria, which uses two biomarkers, serum
albumin and 2microglobulin levels. Patient data were categorised based on the ISS stage to
determine whether there was any correlation between different stages of MM and the
percentage of Treg cells in PB. As evident in Figure 3.9, no correlation between percentage
of Treg cells in PB and MM ISS stage was observed. The percentage of Treg cells in PB of
patients with stage I (8.9±1.0%) MM did not differ significantly from patients with stage II
(9.2±1.2%) or stage III (8.5±1.4%) MM. Further, the absolute number of Treg cells did not
differ between the stages.
3.2.7 Enumeration of Treg cells in BM versus PB
The BM is the site of tumour development in MM, therefore the study aimed to establish
the Treg cell proportion in matched samples of BM compared to PB in patients with MM.
The PB and BM Treg cell proportions were enumerated and statistically compared as shown
in Figure 3.10. BM Treg cells were identified as CD3+CD4+CD25hiCD127lo/-, using the same
gating strategy as shown in Figure 3.21. The CD3+CD4+ cells were distinguished from the
lymphocytes, of which the CD25hiCD127lo/- cells were identified as Treg cells. The BM of
patients with MM comprise 9.7±1.2% of CD4+ T cells and was significantly elevated (P=0.02)
compared to the relative proportion of Treg cells in PB which was observed to be 6.7±1.4%
of CD4+ T cells.
61
Stage I Stage II Stage III0
5
10
15
20NS NS
% T
reg
cells
of C
D4+ T
cel
ls
Figure 3.9: Comparison of the percentage of PB Treg cells and the different stages of MM The data are presented as a percentage of Treg cells as part of the CD4+ cell compartment in
PB of patients with stage I (n=14), stage II (n=9) and stage III (n=9) MM. Staging of patients
with MM was based on the ISS criteria. The results of the experiment are presented as a
mean represented by the black horizontal line. For analysis, an unpaired two-tailed t-test
was performed with a comparison between the outcomes of patients with stage II and stage
III MM compared to patients with stage I MM. *P<0.05, NS- Not significant.
62
Figure 3.10: Comparison of Treg cell numbers in the BM and PB of patients with MM The data are presented as a percentage of Treg cells as part of the CD4+ T cell compartment
in matched BM and PB of patients with MM (n=9). The horizontal black line represents the
mean of each cohort. For analysis, a paired two-tailed t-test was performed with a
comparison between proportions of BM Treg cells to PB Treg cells of the same patients.
*P<0.05, NS- Not significant.
Blood Bone Marrow0
5
10
15
*
% T
reg
of C
D3+ C
D4+ s
ubse
t
63
3.2.8 Treg cells in patients with MM who have survived more than 10 years
To expand our current knowledge of the PB composition of patients with MM and establish
the significance of Treg cell quantity in MM, this study investigated the difference in the
proportion and numbers of PB Treg cells in patients surviving with MM for greater than 10
years since diagnosis. The MM cohort was divided into less than 10 years and greater than
10 years according to the number of years since diagnosis. The data demonstrate, in Figure
3.11, that patients with MM appear to have a significantly higher percentage of Treg cells in
PB compared to normal individuals (8.9±0.6%; 6.5±0.4% respectively; P=0.003). However,
patients who have survived for 10 or more years with MM (5.5±0.8%) were found to have a
significantly lower proportion of Treg cells in PB compared to their MM counterparts who
have survived less than 10 years (P=0.005). The data imply that the proportion of Treg cells
in PB of 10 year survivors appears to normalise to the same proportion as the normal
control group (P=0.21). This same phenomenon was also observed with the absolute PB
Treg cell count of 10 year survivors. Interestingly, substantially lower absolute numbers of
Treg cells were observed in patients with MM for less than 10 years [(3.2±0.4) x107/L]
compared to normal individuals [(6.4±0.7) x107/L; P<0.01]. However, the Treg cell count of
patients who have survived with MM for more than 10 years [(5.1±1.1) x107/L] did not
significantly differ from the normal cohort (P=0.37). Intriguingly, the PB Treg cell count of
MM survivors of greater than 10 years was observed to be significantly higher than those
with MM for less than 10 years (P=0.04).
64
Normal <10Y MM >10Y MM0
5
10
15
20 * *NS
% T
reg
cells
of C
D4+ c
ells
Figure 3.11: Relative Treg cell numbers in PB of normal subjects, patients with MM for less than 10 years and MM patients who have survived for 10 or more years since diagnosis The data are presented as a percentage of Treg cells as part of the CD4+ cell compartment in
PB with a distinction between MM patients who have survived with MM greater than (n=13)
or less than (n=32) 10 years since diagnosis. This was compared to the normal cohort
(n=36). The results of the experiment are presented as a mean, represented by the
horizontal black lines. For analysis, an unpaired two-tailed t-test was performed with a
comparison between the Treg cell proportion of patients with different length of survival
with MM and normal controls. *P<0.05, NS- Not significant.
65
Normal <10Y MM >10Y MM0
5
10
15
20* *
NS
Abso
lute
Tre
g (x
107 /L
)
Figure 3.12: Absolute number of PB Treg cells in normal subjects, patients with MM for less than 10 years and patients who have survived 10 or more years with MM The data are presented as absolute numbers of Treg cells with a distinction between
patients with MM who have survived greater than (n=13) or less than (n=32) 10 years
compared to the normal control cohort (n=36). The horizontal black line represents the
mean of each cohort. For analysis, an unpaired two-tailed t-test was performed with a
comparison between the absolute Treg cells count of patients with different length of
survival with MM compared to the normal cohort. *P<0.05, NS- Not significant.
66
3.3 Th17 cells in MM and other monoclonal gammopathies
Th17 cells are responsible for the clearance of extracellular pathogens and are pathogenic in
inflammation and autoimmunity (Fouser et al., 2008, Ji and Zhang, 2010, Prabhala et al.,
2010). This study examined the quantity of Th17 cells in PB of patients with MM, WM,
MGUS and in normal individuals using a CD3, CD4, and IL-17 phenotype after PMA
stimulation to identify Th17 cells (Figure 3.13). The proportions of PB Th17 cells of the CD4+
compartment were statistically compared to the normal cohort (Figure 3.14). Patients were
categorised based on the type of monoclonal gammopathy, the stage of MM and length of
survival with MM.
3.3.1 Identification of Th17 cells in PB
Th17 cells were identified according to surface expression of CD3, using anti-CD3-FITC, CD4,
using anti-CD4-PE-Cy7 and intracellular expression of IL-17, using anti-IL-17- PE. Figure 3.13
depicts the flow cytometric results from a representative normal PB sample. For each
patient a mouse anti-IgG1-PE isotype control was used. The results for the isotype control
assisted in determining where the negative –PE expressing population was located, and
therefore set the region for the positive IL-17-PE expressing population. In addition, the
isotype control provided an indication of the level of non-specific binding and these results
were considered when determining the IL-17 expression for each patient.
67
CD4
CD3 SSC
FSC
Figure 3.13: Flow cytometric results from a PB sample of a representative normal subject showing the gating strategy for the identification of Th17 cells The figure portrays the flow cytometric gating strategy to identify Th17 cells. CD3+CD4+IL-17+ expression was used to enumerate PB Th17 cell
numbers. In the Th17 assay, PBMC were analysed after a gating strategy that included a lymphocyte gate on the FSC/SSC scattergram and the
identification of the IL-17 expression on the CD3+CD4+ population. An anti-mouse IgG1 isotype control was used to assist with setting the
gating for the PE fluorochrome.
Th17
G1
68
3.3.2 Enumeration of Th17 cells in PB
As illustrated in Figure 3.14, a significant decrease was observed in the mean percentage of
Th17 cells in PB of patients with MM (0.7±0.1%), which includes both treated and untreated
patients, compared to the normal cohort (2.0±0.6%; p=0.03). However, the mean
percentage of Th17 cells in MGUS (2.2±0.6%) and WM (1.1±0.2%) patients was not
significantly different from the control group. Similarly, the absolute number of Th17 cells in
PB was significantly lower in patients with MM [(0.6±0.1) x107/L] compared to the control
group [(2.9±0.7) x107/L] (p=0.004). However, no significant variation was observed in
absolute Th17 cell numbers in patients with WM [(1.1±0.3) x107/L] and MGUS [(2.0±0.5)
x107/L] when compared to the normal cohort.
69
A
B
Normal MM MGUS WM0
5
10
15
20 * NS NS
Abso
lute
Th1
7 (x
107 /L
)
Figure 3.14: Relative Th17 cells number in the PB of patients with monoclonal gammopathies and normal controls A. Data are presented as a percentage of Th17 cells in the CD4+ compartment of PB of
normal individuals (n=20) and patients with MM (n=22), WM (n=12) and MGUS (n=15)
respectively. B. The data demonstrate the absolute number of Th17 cells in PB of normal
individuals (n=23) and patients with MM (n=21), WM (n=12), and MGUS (n=14) respectively.
The results of the experiment are presented as a mean, represented by the horizontal black
lines. For analysis an unpaired two-tailed t-test was performed with a comparison between
the proportions of patients with monoclonal gammopathies compared to the normal
cohort. *P<0.05, NS- Not significant.
Normal MM MGUS WM0
5
10
15 * NS NS
%Th
17 c
ells
of C
D4+ c
ells
70
3.3.3 Th17 cells and stage of MM
To determine whether there was a correlation between the proportion of Th17 cells in PB
and different stages of MM, the tested patients with MM were stratified into different
stages using the ISS criteria. As shown in Figure 3.15, no correlation between the
percentages of Th17 cells in PB and MM stage was observed. The percentage of Th17 cells in
patients with stage I (0.6±0.1%) MM did not differ significantly from patients with stage II
(1.1±0.3%) or stage III (0.6 ±0.2%) MM.
Stage I Stage II Stage III0.0
0.5
1.0
1.5
2.0
%Th
17 c
ells
of C
D4+ c
ells
NS NS
Figure 3.15: Comparison of the percentage of Th17 cells of the CD4+ compartment in PB and different stages of MM The data are presented as a percentage of Th17 cells as part of the CD4+ cell compartment
of PB in patients with stage I (n=10), stage II (n=4) and stage III (n=8) MM. Staging of
patients was based on the international staging system criteria. The horizontal black line
represents the mean of each cohort. For analysis an unpaired two-tailed t-test was
performed with a comparison between patients with stage II and stage III MM compared to
patients with stage I MM. *P<0.05, NS- Not significant.
71
3.3.4 Th17 cells in MM patients who have survived more than 10 years
In an attempt to elucidate the significance of Th17 cells in MM, the relative proportion of
Th17 cells and absolute numbers was investigated in patients with MM. The data depicted
in Figure 3.16 includes patients surviving with MM with minimal disease progression for 10
or more years since diagnosis. The results indicate that patients who have survived greater
than 10 years with MM have a higher proportion of PB Th17 cells compared to their MM
counterparts who have experienced the malignancy for less than 10 years (3.3±0.9% and
0.72±0.1% respectively; P<0.01). Although a significant decrease is observed in Th17 cell
proportions in patients with MM for less than 10 years compared to the normal cohort
(2.0±0.6; P=0.03), this was not the same for the 10-year MM survivors. The data indicates
that 10-year survivors of MM possess similar proportions of PB Th17 cells to that of the
normal subjects (P=0.21). The same trend was also found for the absolute Th17 cell counts
in 10-year survivors of MM. The Th17 cell count in patients surviving greater than 10 years
did not differ significantly (P=0.29) from those of the normal cohort [(1.9±0.5 x107/L) and
(2.9±0.7 x107/L) respectively], although patients with MM who have not yet achieved long
term survival possessed a significantly lower (P<0.01) number of PB Th17 cells (0.58±0.1
x107/L) compared to the normal group. The PB Th17 cell number in 10-year survivors of MM
was also significantly higher than their MM counterparts of less than 10-years survival
(P<0.01).
72
A
B
Figure 3.16: Enumeration of Th17 cells in PB of patients with MM and normal subjects A. The data are presented as a percentage of Th17 cells in the CD4+ compartment of PB of
normal individuals (n=20), and patients with MM who have survived less than (n=22) or
greater than (n=16) 10 years. B. The data demonstrate the absolute number of Th17 cells in
PB of normal individuals (n=23), and patients with MM who have survived less than (n=21)
or greater than (n=16) 10 years. The horizontal black line represents the mean of each
cohort. For analysis an unpaired two-tailed t-test was performed comparing the outcomes
of MM patients with different lengths of survival and to the normal cohort. *P<0.05, NS- Not
significant.
Normal <10Y MM >10Y MM0
5
10
15
20**
NS
Abso
lute
Th1
7 (x
107 /L
)
Normal <10Y MM > 10Y MM0
5
10
15**
NS
%Th
17 c
ells
of C
D4+ c
ells
73
3.4 Treg and Th17 cell equilibrium
As Treg cells and Th17 cells have opposing functions, it is imperative that a balance of the
two cell subsets is maintained in PB. A possible cause for degeneration in haematological
malignancies may be that cell subset proportions may deviate from the homeostatic
equilibrium and cause an imbalance in the cellular environment of PB. To test this, the
Treg/Th17 ratio was determined by dividing the percentage of Treg cells by the percentage
of Th17 cells found in PB for each patient.
3.4.1 Treg/Th17 cell ratio in monoclonal gammopathies
The data, shown in Figure 3.17, suggests that patients with MM have a significantly higher
Treg/Th17 ratio (16.1±2.4) compared to the normal cohort (6.6±1.0; p<0.005). Conversely,
the PB Treg/Th17 cell ratio of patients with WM (7.0±1.0; p=0.79) or MGUS (4.9±0.5;
p=0.23) did not differ significantly from that of the control group. A high Treg/Th17 cell ratio
in patients with MM may contribute to a suppression of the immune control of the
malignancy.
3.4.2 Effect of a high Treg/Th17 cell ratio on overall survival in MM
Interestingly, the data presented in Figure 3.18 indicates that Treg/Th17 ratio of patients
who have survived greater than 10 years with MM (7.04±2.47) was similar to that of the
normal cohort (6.57±1.01; P=0.84), whereas patients who had not reached 10 year survival
with MM had a significant increase in their Treg/Th17 cell ratio (16.1±2.38; p=0.01).
However, a bimodal distribution is observed in the greater than 10 year survivor cohort
(Figure 3.18) particularly, 4 patients exhibiting a higher Treg/Th17 ratio. In addition, the
patients with MM, dichotomised into high and normal Treg/Th17 cell ratio, was further
analysed to assess whether the Treg/Th17 cell ratio influenced the survival time of patients.
As demonstrated in Figure 3.19, the patients with a high Treg/Th17 cell ratio appear to have
Treg/ Th17 cell ratio = % Treg cells % Th17 cells
74
a significantly lower overall survival compared to patients with a normal Treg/Th17 cell ratio
(p=0.025). Thus, taken together, this shows the clinical significance of the Treg/Th17 cell
ratio in MM.
Normal MM MGUS WM0
20
40
60 * NS NS
Treg
to T
h17
cell
ratio
Figure 3.17: Treg/Th17 cell ratio in patients with monoclonal gammopathies and normal individuals The Treg/Th17 cell ratio of patients with MM (n=20), WM (n=12) and MGUS (n=15) was
determined using the percentage values of these cells in PB and compared to the ratio of
the control group (n=28). For analysis, an unpaired two-tailed t-test was performed with a
comparison between the Treg/Th17 cell ratio of patients with monoclonal gammopathies
compared to the normal cohort. *P<0.05, NS- Not significant.
75
Normal <10Y MM >10Y MM0
10
20
30
40 **NS
Treg
to T
h17
cell
ratio
Figure 3.18: Treg/Th17 cell ratio in 10 year MM survivors The Treg/Th17 cell ratio of patients with MM for less than 10 years (<10Y MM; n=20) and
patients with MM for more than 10 years (>10Y MM; n=15) was determined using the
percentage values of these cells in PB and compared to the ratio of the normal control
group (n=28). For analysis, an unpaired two-tailed t-test was performed with a comparison
between the Treg/Th17 cell ratio of patients with MM compared to the normal control
group as well as comparing the different MM cohorts. *P<0.05, NS- Not significant.
76
Figure 3.19: The effect of Treg/Th17 cell ratio on overall survival of patients with MM The Kaplan-Meier curve shows the survival of patients with MM stratified by high Treg/Th17
cell ratio in PB (i.e. +2SD above the mean for patients with MM) and patients with a normal
Treg/Th17 cell ratio in PB. The data demonstrate MM patients with a high Treg/Th17 cell
ratio (dotted line) had a significantly shortened overall survival compared to patients with a
normal Treg/Th17 cell ratio (solid line). For analysis, a chi-square analysis was performed
with comparison between the high Treg/Th17 cell ratio compared to the low Treg/Th17 cell
ratio ( 2=5.1; p<0.025).
0 20 40 600
20
40
60
80
100
Months
Ove
rall
surv
ival
Normal Treg/Th17 cell ratio High Treg/Th17 cell ratio
(%)
77
3.5 Treg cell functional assay
As shown in section 3.2.3, there was a higher proportion of Treg cells in PB of patients with
MM compared to the normal group. However, there is little in the literature about the
functional status of Treg cells in MM. This information could indicate whether Treg cells are
recruited by the tumour to exploit the immune system and inhibit an immune response.
Thus either aberrant or increased numbers of Treg cells may suppress an anti-tumour
immune response. The functional status of PB Treg cells in patients with MM compared to
the normal cohort was investigated using a CFSE suppression assay. Treg cells were
identified, using the gating strategy shown in Figure 3.21, and isolated from PBMC by FACS
using a BD FACSAria II. The Treg cells were then cultured with CFSE stained target cells (Treg
depleted CD3+ T cells) and proliferation of the target T cells was monitored whilst in culture
with and without Treg cells. The percentage of proliferation was obtained by flow
cytometric analysis, and used to calculate the percentage of suppression exerted by the
Treg cells.
The suppression exerted by PB Treg cells on CD3+ target cells was statistically compared
between the Treg cells from patients with MM (n=19) and the normal control group (n=11).
The MM cohort was categorised based on the current treatment the patient was
undergoing, as treatment may have an effect on the activity of Treg cells. The patients
tested were either untreated patients (n=6) or treated with thalidomide (n=5), lenalidomide
(n=5) and bortezomib (n=3).
3.5.1 Development and optimisation of Treg cell functional assay
For optimisation of the Treg functional assay, CD3+ cells were cultured for four days, with
proliferation stimulated by anti-CD3, CD2, CD28 MACSbeads at different concentrations. A
proliferation of approximately 80% was preferred, as this was thought to provide enough
stimulation to the cells without overpowering any potential inhibition by Treg cells. Equally,
if the proliferation of cells was too low the effect of the Treg cell suppression would be
% suppression = % proliferation without Treg - % proliferation with Treg X 100 % proliferation without Treg
78
negligible. As evident in Figure 3.20, a ratio of 1:1 MACSbead to target cell provided enough
stimulation for the target cells.
Figure 3.20: Optimisation of MACSbead stimulation for the Treg functional assay As part of optimisation, different concentrations of beads were used. The figure shows the
proliferation of CD3+ ‘target’ cells using different concentrations of beads. Row A shows
0.06% proliferation with no beads. Row B displays 12.6% proliferation of target cells with
MACSbeads at a ratio of 1 MACSbead to 10 target cells. Row C presents 83.5% proliferation
of target cells with a ratio of 1 MACSbead per target cell.
FSC
CFSE SSC
A
B
C
CD4
CD3
79
3.5.2 Treg cell functional assay results
CD3+CD4+CD25hiCD127lo/- Treg cells were identified by the gating strategy illustrated in
Figure 3.21. The remaining CD3+ cells (‘target cells’) were also collected (Gate A (CD3+CD4-)
and Gate B (CD3+CD4+) of Figure 3.21). The cells were co-cultured with Treg cells for four
days and the suppression exerted upon CD3+ cells was calculated, as described in section
3.5.
Figure 3.22 shows the analysis strategy in which the percentage proliferation of T cells and
their subsets were obtained. As activated lymphocytes are increased in size, they have a
higher FSC value hence, as shown in Figure 3.22; a large gate was created to incorporate
these cells in analysis. Cells without any stimulation (without beads) were used to
determine where the non-proliferating (highest fluorescing) cells were positioned on the
flow cytometric CFSE histogram (Figure 3.22). As the cells divide the daughter cells retain
half the CFSE fluorescence, detected by flow cytometry, and each peak on the CFSE
histogram corresponds to a cell division.
3.5.3 Suppression of T cell proliferation
Untreated patients with MM had a mean suppression of 30.2±10.9% which was similar to
the normal cohort, whose mean Treg cell suppression was 31.4±4.8% (p=0.79), inferring that
Treg cells of patients with MM exhibit normal suppressive activity (Figure 3.23). However,
Treg cells of treated patients with MM exhibited varying degrees of suppression on
lymphocytes which appear to be influenced by treatment. The mean percentage of
suppression of lymphocytes exerted by PB Treg cells in thalidomide treated patients was
17.7±8.0%, which was reduced, however not significantly different from the normal cohort
(p=0.15). Similarly, patients treated with bortezomib had reduced suppressive activity of
12.0±7.7%, however this too was not observed to differ significantly from the normal cohort
(p=0.08). In contrast, patients undergoing combination treatment with lenalidomide and
dexamethasone had a mean suppression exerted by Treg cells of 68.9±6.4%, which is
significantly increased compared to the normal control (P<0.0001) and approximately 3
times more suppressive than observed with thalidomide treatment.
80
The suppression of CD4+ and CD8+ cell proliferation was similar to the suppression exerted
on T cells as a whole. Interestingly, however, Treg cells were significantly more suppressive
on CD4+ cells in the patients treated with bortezomib (p=0.04) compared to the normal
cohort, which was not observed on the CD8+ subset or on T cells as a whole. The
suppression upon CD4+ and CD8+ cells were also statistically compared in each cohort, but
were not found to be significantly different. .
81
Figure 3.21: Flow cytometry gating strategy for FACS of Treg cells in PB The figure demonstrates the flow cytometric analysis used to identify Treg cells for sorting. For the Treg cell sorting assay, cells were analysed
after a gating strategy that included a lymphocyte gate on the FSC/SSC scattergram and the identification of the CD3+CD4+ population. Gate C,
shown in red, were identified as the Treg cells, and cells in gates A and B, shown in black, were combined and identified as target cells.
82
Normal
MM
N
M
Figure 3.22: A representative flow cytometric analysis of CFSE stained CD3+ cells after 4 days culture The figure represents the flow cytometric analysis to determine the suppressive activity of Treg cells on CD3+ target cells. The FSC/SSC
scattergram, shown in the far left, was used to gate on the lymphocytes population. Activated lymphocytes are increased in size and thus have
a high FSC value; therefore a large gate was created to incorporate these cells. The second graph displays CD3 and CD4 for analysis on
individual T cell subsets and T cells as a whole. The histograms demonstrate the proliferation of the cells, whereby each peak is equivalent to
one cell division. The CFSE histograms represent proliferative responses for a patient with MM (top row) and a normal control (bottom row). In
this example the patients with MM has a percent suppression of 35.7%, whereas the normal control has a percent suppression of 22.5%.
83
Figure 3.23: Effect of treatment on Treg cells suppressive activity on lymphocytes target cells The box and whiskers graph presents the percentage of in vitro suppression by PB Treg cells, obtained by FACS, on target T cells in patients
with MM treated with Len + Dex (Lenalidomide in combination with dexamethasone; n=5), Thalidomide (n=5), Bortezomib (n=3) and untreated
patients with MM (n=6) as well as percentage of normal suppression (n=11). The results of the experiment are presented as a mean
represented by the cross, the horizontal line within the box represents the median and the whiskers identify the minimum and maximum
values for each group. For analysis, unpaired two-tailed t-test was performed with a comparison between the suppression of CD3, CD4 and
CD8 cells in patients with MM compared to the normal control. *P<0.05 when compared to the respective normal cohort.
CD3 suppression
CD4 suppression
CD8 suppression
-20
0
20
40
60
80
100
Normal Len + Dex Thalidomide Bortezomib Untreated
* * * *%
sup
pres
sion
84
3.6 Effect of cytokines on Treg cell function
Treg cells play an important role in managing an immune response. The aim of this section
of the study was to investigate whether modification of Treg cell function can be
manipulated to help restore immunological homeostasis. Altering the intensity of Treg cell
suppression may assist the immune system in its anti-tumour response.
Similar methodology to the functional assay, described in Section 3.5, was performed with
the addition of cytokines to target cells with and without Treg cells. As a control, the
cytokine or antibody was added with the target cells without the presence of Treg cells. This
was to determine the direct effect of the cytokine on the target cells. The difference
between the direct effect of the cytokine or antibody on the target and the effect via the
Treg cell was calculated using the formula given below.
This study examined the effect of IL-12, TGF- and an antibody against TGF- on the
suppressive activity of Treg cells from both patients with MM and healthy individuals. rhIL-
12 was observed to decrease the functionality of Treg cells (Figure 3.24). The overall
difference in suppression was -45.6±10.5%. In contrast, rhTGF- increased the suppression
of T cells by 40.8±25%. Anti-TGF- however, was not observed to greatly influence the
suppression of Treg cells (4.2±27%). It should be noted that these suppression assays were
technically difficult to perform, due to the long processing time and low cell numbers, and
this may account for some of the variability observed in the results. Nevertheless, the
results indicate that IL-12 can significantly inhibit (p<0.01) and TGF- can significantly
enhance (p<0.01) the suppression caused by Treg cells.
% change in % proliferation without cytokines - % proliferation with cytokines X 100 suppression % proliferation without cytokines
85
IL12 rhTGF- anti-TGF--200-100
-50
0
50
100200
% c
hang
e in
sup
pres
sion
Figure 3.24: Effect of IL-12, TGF- and anti-TGF- cytokines on the suppressive function of Treg cells The figure demonstrates the change in in vitro suppression by PB Treg cells on target cells
due to the addition of IL-12 (n=10), rhTGF- (n=5) and anti-TGF- (n=8). The mean is
represented by the black horizontal line. The results infer that the addition of IL-12 opposes
the suppression exerted by Treg cell. In contrast, the results indicate rhTGF- to enhance
the suppressive capacity of Treg cells. Anti-TGF- was not shown to greatly influence the
Treg cell suppression. The assay was technically difficult to perform and this may account for
some variability on the results.
86
CHAPTER FOUR
DISCUSSION
87
4.1 Overview
MM is an incurable malignancy characterised by the clonal expansion of abnormal plasma
cells in the BM. Recent developments in treatment, such as the use of IMiDs, proteasome
inhibitors and high dose chemotherapy with autologous SCT, have improved the quality of
life and the length of progression free and overall survival of patients suffering with the
disease. However, despite improvements in both the treatment and management of MM,
most patients eventually relapse. Immune dysfunction is an important characteristic of MM
leading to infections, progression of tumour growth and resistance to different therapies. In
order to further understand the complex malignancy that is MM and develop potential
cures, it is essential to understand the nature of any defects in the immune response in
patients with MM.
Since their first description in the early 1970s, Treg cells have engendered much attention
and in recent years and have become one of the focal points of cancer research. These cells
play a crucial role in immunological homeostasis, autoimmune diseases and possibly in
malignancies. Their role in maintaining self-tolerance leads to question whether these cells
are also responsible for the immune system tolerating tumour cells. Despite the range of
malignancies in which Treg cells are implicated, studies in this field have been highly
controversial. There are discordant findings in the literature which mainly stem from the
difficulty in the identification of these cells, the use of different criteria to identify the cells
and the selection of patients at different stages of disease and treated with different
therapies. There is also still ambiguity regarding enumeration and function of Treg cells in
patients with malignancies, particularly MM.
Another lymphocyte subset of interest in this study was Th17 cells, which are functionally
mutually exclusive to Treg cells. Their predominance and function in PB is still not
completely understood, however studies have proposed Th17 cells as a potential prognostic
indicator in patients with hepatocellular carcinoma (Zhang et al., 2009) and prostate cancer
(Sfanos et al., 2008). Their role in MM and other monoclonal gammopathies, however, still
needs to be investigated and this was addressed in this study.
To facilitate advances in treatment and potential cures for MM, the aims and hypotheses of
the study addressed the role of Treg and Th17 cells in monoclonal gammopathies.
88
Specifically, the study aimed to clarify some discrepancies in the literature with regard to
Treg and Th17 cell proportions in the PB of patients with MM, in normal individuals and in
patients with other monoclonal gammopathies. It also aimed to determine the functional
status of Treg cells in patients with MM and the impact of factors derived from tumour cells
(e.g. TGF- , IL-12) on Treg cell populations and function as well as clinical and prognostic
significance. This chapter discusses the approach, outcome and significant findings for each
aim of the study.
4.2 The role of Treg cells in monoclonal gammopathies
There are inconsistent reports on the role of Treg cells in malignancies. These discordant
findings, which have been outlined in chapter one, are due, in part, to the lack of
standardisation in Treg cell identification across different studies (Law et al., 2009). Previous
attempts to enumerate and understand Treg cell populations in PB have also been
complicated by the lack of surface markers that clearly identify Treg cells. The role of Treg
cells could be of biological and clinical relevance in patients with MM and other monoclonal
gammopathies and therefore their quantification and functional status requires clarification.
The present study was undertaken to elucidate the relative proportion and number of Treg
cells in the PB of patients with MM, WM and MGUS, and to compare with the normal
cohort. The study also aimed to establish whether Treg cell number alterations correlate
with disease severity and/or treatment regime. A further investigation to determine the
proportions of naïve and memory Treg cells was also undertaken, along with a comparison
between the percentage of Treg cells in the PB and the BM. In addition, the current study
explored the suppressive capacity of Treg cells and the effect of exogenous cytokines on
their function.
4.2.1 The phenotype and identification of Treg cells
Due to the complications associated with the use of FoxP3 expression to identify Treg cells,
FoxP3 was not used as the primary marker in the assay. The current study aimed to develop
a simplified cell staining method, defining Treg cells as CD3+CD4+CD25hiCD127lo/-, since this
89
would provide a flexible alternative to FoxP3 (Seddiki et al., 2006) by reducing variables in
identification and eliminating limitations that plagued earlier literature and prevented a
thorough phenotypic and functional assessment of Treg cells. Firstly, it was imperative to
demonstrate that the CD25hiCD127lo/- Treg cell subset was the same subset defined as
CD25hiFoxP3+ in earlier publications. To confirm these populations were the same cell type,
the expression of the FoxP3 transcriptional repressor was determined in the CD25hiCD127lo/-
population. Previous publications have demonstrated an inverse correlation between FoxP3
and CD127 (Liu et al., 2006, Seddiki et al., 2006). The CD25hiCD127lo/- Treg cells identified
herein were found to have a higher expression, and therefore a greater proportion, of FoxP3
compared to the rest of the CD4+ T cell subsets. These results are consistent with the
observation by Liu et al. (2006) that the expression of CD127 is down-regulated in a highly
suppressive subset of CD4+ cells that are also FoxP3+. Thus, it can be concluded that the
CD25hiCD127lo/- cell population possesses the phenotypic characteristics of Treg cells.
Therefore, by virtue of its cell surface expression, the preferred marker for the isolation and
identification of Treg cells in the current study was the lack of CD127.
4.2.2 Enumeration and phenotype of Treg cells in monoclonal gammopathies
Due to the inconsistent findings in previous studies (Table 1.2) regarding Treg cell
proportion and number, it is important to clarify these discrepancies in patients with MM as
well as patients with other monoclonal gammopathies.
The literature indicates that Treg cells constitute 5-10% of the CD4+ lymphocyte population
of healthy individuals (Wolf et al., 2003, Prabhala et al., 2006). This study found the mean
percentage of CD25hiCD127lo/- Treg cells in PB to be 6.5±0.4% for the normal cohort, which is
within the reported mean range. The results obtained from this study demonstrate an
expanded pool of PB Treg cells in patients with MM which corroborate previous studies
(Beyer et al., 2006, Feyler et al., 2009, Brimnes et al., 2010, Muthu Raja et al., 2012). In
terms of absolute number of Treg cells however, there was a reduced number of PB Treg
cells in patients with MM compared to the normal cohort. Albeit it is evident that patients
with MM have lower absolute Treg cell numbers than normal, this could be attributed to the
overall reduction in CD4+ lymphocytes in patients with MM (Mills and Cawley, 1983, Pilarski
90
et al., 1989, Kay et al., 2001, Raitakari et al., 2003). This decrease could also be, at least
partially, a result of treatment, such as chemotherapy, which is known to render patients
lymphopenic (Mackall et al., 1994). Moreover, this study observed an increased frequency
of PB Treg cell in patients with MGUS, however this was not found to be significant and
there was no significant difference in absolute number of Treg cells in patients with MGUS,
compared to the normal cohort. Additionally, no significant difference in Treg cell
proportion was observed in patients with WM when compared to the normal cohort,
however, the reduced absolute number of Treg cells was observed to be significant in these
patients. This too may be a result of treatment such as chemotherapy-induced lymphopenia
(Mackall et al., 1994).
Most interestingly, this study observed that patients who have survived with MM for
greater than 10 years since diagnosis have a normal proportion of PB Treg cells, whereas,
other patients with MM for less than 10 years since diagnosis have a significantly elevated
proportion of PB Treg cells, and, as stated previously, patients with MGUS have an increased
percentage of Treg cells. As most patients with MM have preceding MGUS (Landgren et al.,
2009, Weiss et al., 2009, Korde et al., 2011), the results from this study suggest that an
increase in PB Treg cells in patients with MM may be a result of disease progression, as
opposed to patients with MGUS who have yet to develop significant disease burden. It is
therefore possible that the increased frequencies of Treg cells may abrogate anti-tumour
immunity and that tumour cells may exploit Treg cells to elude immune surveillance and
facilitate tumour progression. This theory is strengthened by the evidence that patients with
MM who have survived greater than 10 years have a normal Treg cell numbers, suggesting
they may have developed an ability to avoid the detrimental increase in PB Treg cells. Thus
the results suggest that the number of PB Treg cells may be of clinical and possible
prognostic value. Similarly, a recent study has shown the relationship between increased
Treg cells in patients with MM and adverse clinical features such as hypercalcaemia,
reduced normal plasma cell count and IgA MM (Muthu Raja et al., 2012). These findings
strengthen the notion of Treg cells as a prognostic indicator in predicting survival and
progression risk of patients with MM.
91
4.2.3 Naïve and memory Treg cells in monoclonal gammopathies
The current study characterised the Treg cells further by categorising them into naïve
(CD45RA+) and memory (CD45RO+) Treg phenotypic groups and comparing the proportions
in the PB of patients with monoclonal gammopathies. Muthu Raja et al. (2012) documented
an increase in naïve Treg cells in patients with MM, however, in sharp contrast, the current
study did not demonstrate any significant difference in the naïve, CD45RA+, Treg cell
proportions amongst the cohorts tested. The study by Muthu Raja et al. (2012) assessed the
naïve Treg cell proportions in 5 patients with MM and this may not be a sufficient number to
accurately represent the disease. The current study has assessed more than 31 patients and
the results may be more of a reflection of the cell proportions in MM. Studies of solid
malignancies, such as lung and breast carcinoma, as well as healthy volunteers, have shown
the majority of Treg cells to be of the memory phenotype (Dieckmann et al., 2001, Jonuleit
et al., 2001, Ng et al., 2001, Liyanage et al., 2002). In accordance with previous publications,
the majority of Treg cells observed in this study were found to constitutively express
CD45RO+, thus resembling a memory T cell phenotype. Interestingly, it was found that of the
total proportion of Treg cells, there was a significant increase in memory Treg cells in the PB
of patients with MM and WM compared to the normal cohort. Memory Treg cell quantity
did not differ between patients with MGUS and individuals within the normal cohort. Lin et
al. (2009) proposed that memory Treg cells may be responsible for the loss of concomitant
tumour immunity, assisting tumour progression. The phenomenon of concomitant tumour
immunity may be utilised in MM, where the memory Treg cells may be repressing the
immune system, possibly cytotoxic T cells and inflammatory Th17 cells from inhibiting
tumour progression.
4.2.4 Effect of MM treatment on Treg cell proportion
The current study also focused on the effect of MM treatments, particularly IMiDs, on PB
Treg cell proportion. Although the exact mechanisms of action are not clear, IMiDs have
been shown to exhibit anti-tumour activities and, in recent years, have been widely adopted
for use in the treatment of MM, with, the previously banned drug, thalidomide, as the first
IMiD utilised in this capacity. Lenalidomide, a second generation analogue of thalidomide,
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has been shown to be more potent and less toxic than thalidomide in the treatment of MM
(Anderson, 2005, Quach et al., 2009). With increasing availability in Australia, more patients
are now treated with lenalidomide. Quach et al. (2009) detailed some of the purported
methods in which IMiDs are proposed to work including both directly against the tumour as
well as through immune related mechanisms. IMiDs have been shown to activate and
induce expansion of both T and NK cells in a number of models, including both mouse
models (Hernandez-Ilizaliturri et al., 2005), normal subjects and patients with MM (Chang et
al., 2006). It has been postulated that IMiDs such as lenalidomide are also active against
MM by their anti Treg cell properties (Kuhn et al., 2007, Galustian et al., 2009). A study by
Galustian et al (2009) showed that lenalidomide inhibits the in vitro expansion and function
of Treg cells. However, thalidomide was not observed to exhibit the same mechanism and
this is almost certainly due to the lack of potency of thalidomide in vitro (Quach et al., 2009).
In the present study, the effect of IMiD treatment on PB Treg cell proportions was examined
in patients with MM. No significant change was observed in the proportion of PB Treg cell in
MM patients receiving lenalidomide treatment compared to untreated patients. Due to the
decreasing number of patients undergoing thalidomide treatment, it was difficult to test a
sufficient number of such patients for a conclusive comparison. The results, however, imply
that thalidomide treated patients have increased PB Treg cell quantity, suggesting that the
mode of action of thalidomide may not be dependent on Treg cell control. Rather, it has
been shown that thalidomide works directly on the tumour by inhibiting vascular
angiogenesis (Quach et al., 2009).
4.2.5 Effect of MM stage on Treg cell proportion
Patients with MM can be categorised into clinical stages based on disease severity using the
ISS. There is currently no consensus as to the association between Treg cell frequency and
MM stage, although a recent study by Muthu Raja et al. (2012) has suggested an association
between the development of adverse clinical features and Treg cell proportion in patients
with MM. The study by Muthu Raja et al. (2012) found a stage dependent increase in Treg
cell frequency, however the observation did not reach statistical significance. Treg cells
have, however, been reported to be associated with disease severity in MM (Feyler et al.,
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2009), B-CLL (Giannopoulos et al., 2008a), cutaneous T cell lymphoma (Gjerdrum et al.,
2007) and papillary thyroid cancer (French et al., 2010). The present study aimed to
elucidate the relationship between the proportion of Treg cells in the PB and clinical stage of
MM. An increase in Treg cell frequency was observed in patients with MM and premalignant
stage MGUS, although the increase was only found to be significant in MM. The Treg cell
frequency, however, was not observed to differ with disease stage, indicating the increase
in Treg cell number may be a tumour induced mechanism aimed to resist the initial immune
response, and the tumour may then progress through other mechanisms. Further work
needs to be performed to clarify these mechanisms.
4.2.6 Quantification of Treg cells in the PB and BM of MM patients
This study aimed to examine Treg cell quantities in the BM of patients with MM and
compare this to Treg cell quantities in their corresponding PB. It has been previously shown
that Treg cells can accumulate at the site of various cancers such as ovarian cancer (Curiel et
al., 2004), follicular lymphoma (Carreras et al., 2006), gastric and oesophageal cancers
(Ichihara et al., 2003) and that this accumulation may hinder the host’s response to the
tumours. It has also been postulated that the BM may be a reservoir for Treg cells in healthy
subjects (Zhan et al., 2006). Given that MM is a cancer of the BM, it is hypothesised that
Treg cells may accumulate in the BM. This notion has been supported by the observation of
increased Treg cell numbers in the BM of patients with MM compared to the corresponding
PB, demonstrated as part of this study. Thus Treg cells may be localised in the tumour
microenvironment in MM.
4.2.7 Treg cell function in MM
There is little in the literature about the function of Treg cells in malignancies. This may be,
at least in part, because the Treg functional assay is technically difficult, requiring sorting (by
FACS) of Treg cells and sufficient purification to perform the assay. Adding to these
complications, it is especially difficult to obtain a sufficient number of cells to perform the
experiment from patients who are often leucopenic. This study has been the first to
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compare the effect of different MM therapies on the function of PB Treg cells using a purely
autologous model. Treg cells were isolated from PB of patients with MM already undergoing
different treatments as well as the normal control subjects. The Treg cells were then co-
cultured with purified CD3+ T cells depleted of Treg cells and the proliferation of the T cells
was observed. Further, to ascertain whether Treg cells preferentially suppress a particular T
cell subset, the effect of Treg cell suppression on the CD4+ and CD8+ T cell subsets was also
investigated.
Lenalidomide has been reported to down-regulate FoxP3 and therefore inhibit the function
and proliferation of Treg cells in vitro (Giannopoulos et al., 2008b, Galustian et al., 2009).
Further, it has been documented that treatment with lenalidomide restores the function of
T cell subsets in CLL (Lee et al., 2011). Both thalidomide and lenalidomide are usually used in
combination with dexamethasone as they have been shown to increase rate of clinical
response (Dimopoulos et al., 2007, Richardson et al., 2007, Hideshima et al., 2008, Galustian
and Dalgleish, 2009, Kastritis et al., 2009, Richardson et al., 2009, Stadtmauer et al., 2009,
Hsu et al., 2011). Patients included in this study had been treated with both an IMiD and
dexamethasone.
The current study observed no significant difference in suppressive activity when comparing
Treg cells from healthy individuals and untreated MM patients, inferring that patients with
MM exhibit normal Treg cell function. The Treg cell function of treated patients with MM,
however, was found to be treatment dependent. A trend was observed for lower
suppressive capabilities of Treg cells from patients treated with thalidomide and bortezomib
compared to those from the normal cohort and untreated patients. Interestingly, however,
it was found that Treg cells of patients treated with lenalidomide in conjunction with
dexamethasone were significantly more suppressive when tested in vitro. In addition, these
suppressive capabilities were effective on both T helper and cytotoxic T cells.
Dexamethasone has been shown to be antagonistic to the immunostimulatory capacity of
lenalidomide (Hsu et al, 2011). Prado et al. (2011) demonstrated dexamethasone’s ability to
increase FoxP3 expression, paradoxically in cells that do not have suppressive activity. On
the contrary, a study by Hu et al. (2012) has shown an improved function of Treg cells in
Graves’ disease patients treated with dexamethasone. Favaloro et al. (2013) have shown
that patients receiving high dose dexamethasone had more suppressive Treg cells compared
95
to patients treated with low dose dexamethasone, suggesting that dexamethasone may be
responsible for the increased Treg cell suppression. Low dose dexamethasone has been
shown to be associated with better outcomes than high dose dexamethasone (Rajkumar et
al., 2010). Aside from increased toxicity, it is possible that high dose dexamethasone may
increase the suppressive capacity of Treg cells and therefore low dose dexamethasone, in
combination with lenalidomide, may be the most effective way to restore Treg cell function.
4.2.8 Treg cell suppression on the CD4 and CD8 T cell subsets
This section investigates the in vitro suppression of the two major subsets of T cells, CD4+
and CD8+ T cells, by Treg cells from treated MM patients. The literature has proposed that
Treg cells substantially suppress memory CD8+ cell responses (Murakami et al., 2002)
abrogating the induction of effector CD8+ T cell-mediated tumour rejection. Also, Dai et al.
(2004) have revealed that the presence of antigen induced Treg cells increases the apoptosis
of memory CD8+ cells.
The current study did not observe Treg cells to preferentially suppress either CD4+ or CD8+ T
cells, despite Treg cells appearing slightly more suppressive on CD4+ cells compared to CD8+
in normal individuals and in thalidomide treated MM patients. Interestingly, untreated
patients were not observed to exhibit the same trend as the normal cohort. Treg cells of
untreated MM patients appear equally as suppressive upon T helper and cytotoxic T cells
and this may be a mechanism utilised by MM cells to facilitate their expansion. Intriguingly,
the Treg cells of patients treated with bortezomib were found to have a significantly lower
suppression upon CD4+ cells compared to the normal cohort, presumably revealing a
mechanism by which bortezomib may exert its anti-MM effect.
4.2.9 Modification of Treg cell function
The aim of this section was to investigate whether the addition of exogenous cytokines,
particularly rhIL-12 and rhTGF- would be able to modify the suppressive activity of Treg
cells in vitro. Further, the effect of anti-TGF- on the suppressive function of Treg cells was
examined. This is of particular interest as the observed increase in Treg cell proportions may
96
be the cause of immune tolerance in MM, with malignant cells exploiting the suppressive
nature of the Treg cells. Utilising cytokines to neutralise Treg cell function could expand
therapeutic approaches for MM and other malignancies (Tang et al., 2004).
Although the exact mechanisms used by Treg cells to exert suppression is unknown, Treg
cells are thought to utilise at least two mechanisms, that of cell to cell contact and cytokine
release, with their function thought to be at least partially mediated by the release of TGF-
and IL-10. TGF- is a widely distributed immunomodulatory cytokine with pleiotropic
functions in T cell development, homeostasis and survival (Cerwenka and Swain, 1999,
Gorelik and Flavell, 2002, Li et al., 2006). Studies have shown that TGF- plays a pivotal role
in the generation of Treg cells from CD4+CD25- T cells (Chen et al., 2003, Fantini et al., 2004,
Tang et al., 2004). Further, Marie et al. (2005) have reported that TGF- 1 is imperative in
the maintenance of FoxP3, regulatory function and Treg cell homeostasis. The results
obtained from this study show that rhTGF- appears to increase the suppressive activity of
Treg cells. Interestingly, anti-TGF- had little effect on the in vitro suppression exerted by
the Treg cells.
On the other hand, IL-12 is purported to be involved in the instigation of the Th1 immune
response (King and Segal, 2005). The cytokine has been shown to induce CD4+ T cell
activation during co-culture with Treg cells (King and Segal, 2005) and is thought to reduce
the frequency of Treg cells by induction of IFN- expression by both conventional T cells and
Treg cells (Zhao et al., 2012). This current study has shown that the addition of exogenous
IL-12 is able to reduce the suppressive capability of Treg cells, and allow effector cells to
proliferate. This may offer a unique therapeutic approach, as IL-12 is found to oppose the
function of Treg cells while simultaneously inducing effector T cell responses.
97
4.3 The role of Th17 cells in the monoclonal gammopathies
In recent years, subsets of the T helper cell lineage have been expanded with the
identification of Th17 cells. Increased numbers of these cells are associated with
autoimmunity and inflammation (Dong et al., 2003, Park et al., 2005, Cooke, 2006, Fouser et
al., 2008, Oukka, 2008, Tesmer et al., 2008, Traves and Donnelly, 2008, Yamada, 2009).
Furthermore, Th17 cells have been implicated in the pathogenesis of solid tumours, and
increased numbers have been observed in the PB of patients with malignancies such as
advanced ovarian cancer, gastric cancer and AML and also in tumour tissues of patients with
pancreatic and renal cell carcinoma (Kryczek et al., 2007, Zhang et al., 2008, Wu et al.,
2009). IL-17 has been demonstrated to promote tumour neovascularisation (Inozume et al.,
2009) and a study conducted by Alexandrakis et al. (2006) suggested that IL-17, as a
mediator of angiogenesis, has been associated with disease progression in MM. Further, IL-
17 production has been shown to correlate with osteoclast mediated lytic bone disease in
MM (Noonan et al., 2010). In sharp contrast, it has also been suggested that Th17 cells have
the ability to eradicate melanoma (Muranski et al., 2008) and may enhance the anti-tumour
effect of a lymphoma vaccine (Alvarez et al., 2010). Other studies have suggested that Th17
cells may possess anti-tumour activities and therefore be beneficial to cancer patients,
particularly those with advanced disease (Kryczek et al., 2007, Kryczek et al., 2009a, Kryczek
et al., 2009b). The role of Th17 cells in cancer progression and development remains
controversial and poorly understood due to the scarce and contradictory reports on Th17
cells. The current study aimed to enumerate Th17 cells in the PB of patients with
monoclonal gammopathies and in a normal cohort to allow a comparison of cell numbers to
be made. Additionally, the study aimed to assess whether factors such as disease stage and
length of survival time had an impact on the predominance of these cells.
4.3.1 Th17 cell enumeration in MM and other monoclonal gammopathies
This study found that patients with MM had a significantly lower proportion of Th17 cells in
their PB compared to healthy volunteers. In addition, the absolute Th17 cell count was also
reduced in patients with MM compared to the normal cohort, albeit this may be a reflection
98
of chemotherapy induced lymphopoenia (Mackall et al., 1994). There was no significant
change in Th17 cell proportions in the PB of patients with WM and MGUS compared to the
normal cohort, inferring that amongst the monoclonal gammopathies studied, the decrease
in Th17 cells is unique to patients with MM. Interestingly, MM patients who had survived 10
or more years since diagnosis possessed PB Th17 cell proportions that were similar to those
of the normal cohort.
Some studies have suggested that Th17 cells are associated with a favourable prognosis and
may be involved in anti-tumour activity (Kryczek et al., 2009b). It has been purported that
this may be mediated through the activation of the innate immune system by IL-17. Kryczek
et al. (2009b) have reported that mice deficient in IL-17 had enhanced tumour growth in
subcutaneous and lung metastasis. This supports the notion that the decrease in Th17 cells
may be evident in malignancies such as MM. In non-Hodgkin lymphoma, a low frequency of
Th17 cells was observed in the tumour microenvironment, and it was proposed that
lymphoma B cells may favour the expansion of Treg cells and down-regulate the generation
of Th17 cells (Yang et al., 2009). This may be similar for patients with MM where malignant
cells may allow for the expansion of Treg cells, simultaneously inhibiting Th17 cell
development. A study of patients with ovarian cancer demonstrated a higher percentage of
Th17 cells at the tumour site, however a low presence of Th17 cells was observed in PB
(Miyahara et al., 2008). While the pathogenesis of solid tumours may be different from that
of haematological malignancies, this still provides a sound basis for the investigation of the
BM of MM patients.
It has been suggested that Th17 cells could generate an immune response against an
established tumour (Chen and Oppenheim, 2009), as studies have proposed exploiting the
autoimmune response of Th17 cells as an immunotherapy (Kottke et al., 2007). In addition,
the adoptive transfer of Th17 cells was potent in inhibiting tumour progression in a study
conducted by Muranski et al. (2008). The study illustrated that, in a B16 melanoma murine
model, animals receiving Th0 or Th1 cells relapsed, whereas animals treated with Th17 cells
remained tumour free. The suggestion that Th17 cells may be potent in inducing an anti-
tumour response and potentially eradicating the tumour provides evidence of possible value
in exploiting the Th17 immune response as an immunotherapy. The results of this study
suggest that Th17 cells may be of clinical and biological importance in MM due to their pro-
99
inflammatory capacity and the decrease in Th17 cells observed may be a result of a tumour
induced mechanism aimed to incapacitate the immune response.
4.3.2 Association of MM stage and Th17 cell proportion
The effect of MM stage and treatment on Th17 cell quantity was also considered in this
study. Although an increase in Th17 cell percentage was observed in patients with stage II
MM, no significant difference was observed amongst the different stages. This shows that
patients with MM have an overall decrease in Th17 cell percentage regardless of their stage
classification, suggesting that the reduction in Th17 cell frequency may be a result of tumour
pathogenesis as opposed to tumour progression. Th17 cells are thought to be potent
activators of the innate immune system and an overall decrease in Th17 cell number may
hinder the process of eradicating the malignant plasma cells. This may possibly be a
mechanism by which the tumour evades an immune response and may be the effect of the
increased Treg cells in the PB of patients with MM. Contrary to these results, an association
between Th17 cells and disease progression in MM has been suggested, proposing the use
of Th17 cells as a possible prognostic predictor in MM (Shen et al., 2012) however, due to
the limited number of patients studied, that particular study also recommended an
additional study with a greater number of MM patients and normal individuals to support
the results. The current study, however, evaluated 22 patients with MM, a much greater
number than that used in the study by Shen et al. and therefore may be more of a reflection
on the effect of MM stage on Th17 cell proportion. However, other factors (eg. therapy,
transfusion etc) being administered to each patient may influence the Th17 cell proportion
in MM and should be considered in any prospective study.
100
4.4 Treg and Th17 equilibrium
The data taken together so far is in accordance with the notion of reciprocal generation of
Treg and Th17 cells. It is thought that there is reciprocal generation of Th17 and Treg cells in
the PB, as these cells have mutually exclusive functions (Bettelli et al., 2006, Joshua et al.,
2008). Presumably, the expanded PB Treg cell pool may be a cause, or effect, of the reduced
PB Th17 cell proportion. Treg cells are known to inhibit the expansion of Th17 cells in the
tumour microenvironment (Chen and Oppenheim, 2009). This decrease in Th17 cell
proportions may enable the expansion of the malignant cells in patients with MM.
4.4.1 Treg/Th17 cell ratio in monoclonal gammopathies
Accumulating evidence suggests that Treg and Th17 cells are mutual antagonists (Afzali et
al., 2007, Joshua et al., 2008). The inverse relationship of Treg and Th17 cells has been
illustrated in a number of studies (Bettelli et al., 2006, Mangan et al., 2006, Veldhoen et al.,
2006). An imbalance in the Treg/Th17 cell ratio can be detrimental to the health of patients
and has been suggested as a factor in the development or progression of various cancers
(Sfanos et al., 2008, Yang et al., 2009, Chi et al., 2010). In the current study, an imbalance in
the ratio of Treg/Th17 cells was observed in patients with MM and such an imbalance was
non-existent in MGUS and WM. This is the first time such an imbalance has been reported
and hence is an original observation in this study. It suggests that measuring Treg cell
numbers alone does not provide sufficient details of the swing of the Treg/Th17 axis. Thus, it
is likely to be more important to evaluate the Treg and Th17 cell homeostatic balance,
rather than PB Treg cell numbers alone, as it appears to be a greater predictor of survival in
patients with MM.
The current study found a clear favouring of PB Treg cells over Th17 cells in patients with
MM compared to the normal cohort. Giannopoulos et al. (2012) reported an association
between increased Treg cell percentage and poor prognosis in patients with MM. However,
they did not determine the number or frequency of Th17 cells. The current study
demonstrates a significant difference in patients with MM, who have a mean Treg/Th17 cell
ratio of 16.1:1, and the normal control cohort, observed to have a Treg/Th17 cell ratio of
6.6:1, indicating a tumour-induced defect in the immune regulation of patients with MM to
101
maintain cellular homeostatic balance in PB. In contrast, the difference in Treg/Th17 cell
ratio was not observed in patients with MGUS or WM, thus suggesting, the imbalance in the
Treg/Th17 cell ratio is dependent on tumour load and disease type. Further, Yang et al.
(2009) reported a similar observation in non-Hodgkin lymphoma. It was reported that
lymphoma B cells may be responsible for the deleterious skewing of the Treg and Th17 cell
balance. Similarly, MM cells may be responsible for the abnormal imbalance between Treg
and Th17 cells by up-regulating Treg cells and down-regulating Th17 cells. Consequently, the
skewed Treg/Th17 cell balance may result in suppression of the immune response, thus
inducing immune tolerance towards the malignant cells.
4.4.2 Treg/Th17 cell ratio and survival
The current study was also able to compare the outcome of patients surviving 10 years or
greater with MM to those with MM for less than 10 years since diagnosis. Most
interestingly, the patients who have survived for 10 or more years with MM possessed a
similar Treg/Th17 cell ratio to the normal cohort, suggesting that survival with MM is
associated with a normal Treg/Th17 cell ratio. This implicates the critical nature of the Treg
and Th17 cell balance on survival with MM. The malignant cells may attempt to alter the
cellular environment for optimisation of their expansion and long term surviving patients
may have the ability to resist the MM cell induced Treg/Th17 cell ratio deviation from
homeostatic equilibrium. Consistent with this idea, the current study is the first to
demonstrate that MM patients with a high Treg/Th17 cell ratio had a significantly lower
survival compared to patients who were able to retain a normal Treg/Th17 cell ratio,
indicating an association between a high Treg/Th17 cell ratio and survival. A bimodal
distribution was observed in patients surviving with MM for more than 10 years (Figure
3.18). 4 patients in particular exhibited a higher Treg/Th17 cell ratio, which may possibly be
associated with relapse or even death. Overall however, the data suggest that the 10 year
survivor cohort had the ability to maintain their Treg and Th17 cell equilibrium and
therefore resistance to the progression of the malignancy. Further, the data emphasise the
importance of preservation of the Treg and Th17 cell homeostatic balance as this may
impact tumour immunity.
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The delicate balance of both TGF- and IL-6 is documented to be important in the
development of either Treg or Th17 cell lineages. TGF- alone skews precursors towards the
development of the Treg cell lineage, whereas a combination of TGF- and IL-6 induces
differentiation of naïve T cells into Th17 cells (Bettelli et al., 2006, Mangan et al., 2006,
Veldhoen et al., 2006). Evidence indicates that IL-6, produced by BM stromal cells and MM
cells, is a major growth and survival factor for malignant plasma cells (Zhang et al., 1992,
Hallek et al., 1998, Zdzisi ska et al., 2008). The expanding malignant clones may possibly
consume the majority of the available IL-6 in the BM, rendering the environment depleted
of IL-6. Furthermore, MM cells secrete large amounts of TGF- (Cook et al., 1999), which
may induce the expansion of Treg cells, hence the increased Treg cell proportion observed
in both the BM and PB of patients with MM. This relative skewing of IL-6 and TGF- may
partly explain the reciprocal Treg/Th17 cell relationship observed in patients with MM, of
which the cytokine milieu in MM may favour the expansion of the immunosuppressive Treg
cell lineage and impede the expansion of the pro-inflammatory Th17 cell lineage.
4.5 Conclusions and future directions
4.5.1 Future directions
There is a potential for either Treg or Th17 cells to be the target of therapies for
malignancies and autoimmunity and this should be investigated in future studies.
Identification of surface markers for the detection of Th17 cells would enable easier
enumeration of this cell type in the BM as well as the development of functional studies for
comparison of their role in MM and other monoclonal gammopathies to healthy individuals.
The current method is timely and far more complicated than a simple surface stain. A
number of novel monoclonal antibodies are currently under investigation but were not
available for these studies (Prof Mark Hogarth, personal communication).
This study reinforces the need to study the Treg/Th17 cell balance in the BM
microenvironment of MM patients with a comparison being made with healthy individuals
to enable a better understanding of the pathogenesis of the malignancies and development
of curative immunotherapies. A prospective study to clarify the prognostic significance of
Treg cells in MM as well as clarification in terms of the Treg/Th17 dynamic, is required to
103
determine whether the high Treg/Th17 ratio is causative of a poor prognosis or a biomarker
of immune dysfunction. Further investigation is warranted to elucidate the factors involved
in the Treg/Th17 dynamic in MM and to study the overall quantitation and interaction
between cytokines and lymphocytes in the PB and BM of patients with MM and other
monoclonal gammopathies. Changing the Treg/Th17 cell ratio may be possible by treatment
with cytokines or by cell therapeutic physical removal of Treg cells. In patients with
autoimmune disease or GvHD, ex vivo expansion and infusion of Treg cells has already been
considered (Brunstein et al., 2011, Colonna et al., 2011, Di Ianni et al., 2011). It is important
that laboratories can provide monitoring support for such clinical activities. The clear bi-
modal distribution of Treg/Th17 cell ratio, evident in patients with MM for greater than 10
years (Figure 3.18), warrants further investigation, and may serve to strengthen the
argument that the ratio, and not the parameters by themselves, is the important factor in
determining the prognostic value of this test.
Considering the complexity of the cytokine network, targeted immunotherapy requires a
delicate balance between increasing the immune response and severe autoimmunity. The
finding that Treg cell function is altered by therapy and by cytokines, elucidates the need to
study the cytokine milieu in the BM and PB of patients with MM and in healthy individuals.
So far studies have suggested the inhibition of TGF- as a new therapeutic approach as it
simultaneously enhances bone formation and assists in the suppression of MM cell growth
(Matsumoto and Abe, 2011). Also, the use of CTLA-4 and PD-1 blockers have emerged as
successful treatment approaches in melanoma, after being explored in phase 1 clinical trials
(Lotem et al., 2012). Thus the results of these studies may facilitate the development of new
immunotherapies, which may assist in alleviating the cancer and may ultimately lead to the
development of a cure through reinstatement of the immunological balance.
4.5.2 Conclusion
The pathogenesis of monoclonal gammopathies is multifaceted and complex. This study
aimed to clarify some aspects of the dysfunctional immunogenic control in these patients.
The results demonstrate a skewed Treg/Th17 cell ratio in the PB of patients with MM
compared to healthy individuals. The study observed an increase in Treg cell percentage,
104
which largely consisted of memory Treg cells, in patients with MM compared to healthy
individuals, as well as a reduced Th17 cell frequency in the PB of patients with MM and this
reciprocal combination was not observed in the other monoclonal gammopathies studied.
Additionally, the BM of patients with MM was found to consist of a higher frequency of Treg
cells compared to the PB of the same patients. The PB Treg and Th17 cell proportions in
patients with MM were not observed to fluctuate based on treatment or disease stage. The
function of Treg cells, however, was observed to differ based on the treatment being
received by the patient and, if required, could be altered using exogenously administered
cytokines. Most interestingly, 10 year survivors of MM possess similar proportions of Treg
and Th17 in their PB compared to healthy individuals, and therefore a similar PB Treg/Th17
cell ratio. Further studies of Treg/Th17 cell ratio in MM demonstrated patients with a high
Treg/Th17 cell ratio had a significantly lower survival than those with a normal Treg/Th17
cell ratio. The results of this study clearly delineate for the first time the importance of the
Treg and Th17 cell equilibrium in the PB of patients with MM. The results of the 10 year
survivors reveal a strong association between the Treg and Th17 cell homeostatic balance
and survival, particularly in MM. Therefore, this indicates that the imbalance favouring
suppressive Treg cells may cause the innate and/or the adaptive immune system to be
quiescent and limited in any anti-tumour response.
105
CHAPTER FIVE
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