Anna Schuh, MD, Ph.D.

• Current position:

Associate Professor and Director of Molecular

Diagnostics in the Department of Oncology University

of Oxford

Honorary Consultant Hematologist at Oxford University

Hospitals Trust, UK

• Focus of work: Genomics, Precision Medicine and

Chronic Lymphocytic Leukaemia

• Specific expertise / current research interest:

Her primary research interest is with the development,

evaluation and implementation of new technologies for

precision diagnostics with a particular focus on

genomics. She leads the Genomics England Clinical

Interpretation Partnership for Haematological

Malignancies on behalf of the NCRN clinical

investigators

Anna Schuh

MD, PhD, FRCP, FRCPath

Associate Professor in Molecular Diagnostics

University of Oxford

Oxford Genome Medicine Centre Clinical Programme Director

Honorary Consultant Haematologist

OUHFT

The role of clinical omics for precision medicine approaches in haematology or:

The 100,000 Genomes Project: where are we now: ….in the non-coding space??

and where will it go…into routine care?

100,000 Genome Project is trying to address the old problem of classification of disease using new technology

From Personalisation to Precision Medicine in CLL?Understand the molecular basis for clinical heterogeneity

• FISH, fluorescence in situ hybridisation; i.v., intravenous;NGS, next-generation sequencing; WGS, whole-genome sequencing.

• 1. Scarfò L, et al. Crit Rev Oncol Hematol 2016; 104:169–182;• 2. Marini BL, et al. J Oncol Pharm Pract 2016 Jun 29. pii: 1078155216656929 (ePub ahead of print).

Morphology Flow FISH Sanger targeted NGS including WES WGS

Pivotal studies/approvals

2014 20151950–2000 2010 2011 2012 2013 2016

Chlorambucil

Fludarabine

Cyclophosphamide

FludarabineCyclophosphamideRituximab

Bendamustine

Alemtuzumab

Ofatumumab Ibrutinib

IdelalisibRituximab

Venetoclax

ObinutuzumabChlorambucil1st line

R/R

OfatumumabChlorambucil

Ibrutinib

Acalabrutinib

Unmet clinical need:Identify the most effective agent for a given patient early on in the disease course with the least toxicity:

To prolong remission durationsTo avoid side-effectsTo ultimately achieve cure

IdelalisibRituximab

Chemoimmunotherapy Remains Standard of Care For Front-Line Treatment of Patients With Standard-Risk CLL

1. Hallek M, et al. Lancet 2010; 376:1164–1174; 2. Fischer K, et al. Blood 2016; 127:208–215.

CLL8 Trial, 1L FCR (N=817): PFS and OS in All Patients1,2

p=0.001 by log-rank test

Months on Study

0

0.2

0.4

0.8

1.0

0.6

Pro

bab

ility

of

Pro

gre

ssio

n-F

ree

Su

rviv

al

9612 24 36 48 60 720 84

Months on Study

0

0.2

0.4

0.8

1.0

0.6

9612 24 36 48 60 720 84

Pro

bab

ility

of

Ove

rall

Surv

ival

p=0.001 by log-rank test

FCR (N=408)FC (N=409)

25% of CLL patients relapse within 2 years from first-line chemoimmunotherapy

N Progression-FreeIGHV mutated 88 49IGHV unmutated 126 12

PFS in According to IGHV mutation status1L FCR: MD Anderson cohort (N=300)

Some Patients are Cured With Chemo-Immunotherapy

Time (Years)

p<0.00010

25

50

75

100

Pro

gre

ssio

n-F

ree

(%

)

162 4 6 8 10 120 14

50% of IGHV mutated patients are “cured”

1L, first line; FC, fludarabine plus cyclophosphamide; FCR, fludarabine, cyclophosphamide and rituximab; mut, mutation; WT, wild typeFischer K et al. Blood 2016;127:208-215.

Tri12Del13qDel11q

None of above

del17p

Long-Term Results after FCR: MD Anderson Experience(Median Follow-Up: 142 Months)

Tam CS, et al. Blood 2014;124(20):3059-64.

TP53wt

TP53mutated

GermanCLL4trial1

Overallsurvival

TP53deleted

Time (months) F

rac

tio

n a

liv

e

Both Deletion and Mutation of TP53 on Chromosome 17p Confer Poor

Prognosis and Resistance to Chemotherapy

1. Zenz T, et al. J Clin Oncol 2010;28:4473–4479; 2. Malcikova J, et al. Blood 2009;114:5307–5317; 3. Zenz T, et al. Blood 2009;114:2589-2598; 4. Dohner et al, NEJM, 2000

At least 50% of patients with FCR-refractory disease do not have TP53 abnormalities

TP53 abnormalities at relapse: 26.6%2

TP53 unmutated

Solely subclonal TP53 MClonal TP53 M

Events Total 5-year OS 95% CI

77 263 75.1% 69.5–80.7%

9 18 46.3% 22.0–70.6%

19 28 34.6% 15.8–53.4%

p<0.0001

- 0.0042 <0.0001

0.0042 - 0.6926

<0.0001 0.6926 -

p from pairwise comparisons

Subclonal TP53 Mutations Have the Same Unfavourable Prognostic Impact as Clonal Defects

CI, confidence interval; OS, overall survival; WT, wild type.1. Rossi D, et al. Blood 2014;123:2139–47; 2. Landau D, et al. Nature 2015;526:525-30.

Targeted NGS1 WES2

samples Gene.refGene ExonicFunc.refGene AAChange.refGene AAChange.refGene2 VAF

TRO-Mic TP53 nonsynonymous SNV TP53:NM_001126115:exon4:c.G443C:p.R148T 0.0541

TRO-Mic TP53 nonsynonymous SNV TP53:NM_001126115:exon4:c.G445A:p.D149N 0.0645

GRUMar TP53 frameshift insertion TP53:NM_001126115:exon1:c.136dupC:p.H46fs 0.0736

Using Diagnostic-Grade NGS,TP53 Mutations Can be Detected to 5% Variant Allele Frequency (VAF)

Clifford et al, Manuscript submitted to Leukemia

Example of TP53 mutations (trend of signal detected by Sanger sequencing)

ARCTIC/ADMIRE

Exonic Predictors of </= 2 year progression free survival after FCR

0 20 40 600

20

40

60

80

100

TP53 Disruption

SAMHD1 Disruption

P<0.0001

Combined Alterations

13q sole

Time (months)

Cu

mu

lativ

e P

FS

, %

ARCTIC/ADMIRE

Clifford et al, manuscript submitted; Clifford et al, Blood 2014Landau et al, Nature 2015

1.0

0.8

0.6

0.4

0.2

2 4 6 8

RPS15mutation

German CLL8

Hierarchical Predictive Models and other candidates(outside of clinical trials)

Rossi et al, Blood, 21 February 2013, volume 121, number 8 Young et al, Leukemia 2017; Parker et al, Leukemia 2016

EGR2 mutations

SETD2 SNVs/deletions

CLL-International Prognostic Index

3472 treatment-naive patientseight international phase 3 clinical trials5 countries

TP53 status deleted/mutated 4

IgHV status unmutated 2

Beta 2 microglobuline >3.5mg/l 2

Clinical Stage Rai 1-IV or Binet B-C 1

Age >65 1

CLLIPI Risk score

incidence Median OD (months)

Low 0-1 28-32% NR

Intermediate 2-3 34-39% 105

High 4-6 25-28% 75

Very high 7-10 5-9% 29

Hallek, Lancet Oncology 2016

SF3B1

TP53ATM

NOTCH1XPO1

SAMHD1MED12

BIRC3MYD88

17p11q

no mutation one gene mutationrecurrent

combinations rare

combinationsn = 22 n = 49 n = 22 n = 21

CLUSTER #1 CLUSTER #2 CLUSTER #3 CLUSTER #4

Multiple-hit CLL

TP53 ATM

SF3B1

Impact of the multiple-hit profile on progression-free survival

114 R/R CLL

patients

ICLL01

CLL201

CLL202

P = 0.003

No multiple-hit profilen = 92

Multiple-hit profile n = 22

19% of relapsed/refractory CLL patients carry multiple recurrent combinations of TP53, ATM and SF3B1. These occur in non-random order (mostly ATM ancestral)

Guièze R et al, Blood. 2015 Aug 27

Ibrutinib Discontinuation and Outcomes in Patients With CLL

Jennifer A. Woyach Hematology 2015;2015:355-360

Maddocks K, et al. JAMA Oncol 2015;1:80-87.

SurvivalOutcomesbyChromosomalAbnormali esDetectedbyFISHinR/RPa ents*

**Nodel17p,del11q,del13q,ortrisomy12;inhierarchicalorderfordel17p,andthendel11qNR,notreached.

Progression-FreeSurvival OverallSurvival

*Only2pa entsintheTNgroupshowedPDordeath.Subgroupanalyses,therefore,focusedontheR/Rpopula on.

MedianOS 5-yearOS

Del17p(n=34) 57mo 32%

Del11q(n=28) NR 61%

Trisomy12(n=5) NR 80%

Del13q(n=13) NR 91%

Noabnormality**(n=16) NR 83%

MedianPFS 5-yearPFS

Del17p(n=34) 26mo 19%

Del11q(n=28) 55mo 33%

Trisomy12(n=5) NR 80%

Del13q(n=13) NR 91%

Noabnormality**(n=16) NR 66%

Courtesy S O’Brien, ASH 2016

Multivariate Analysis* for PFS and OS

Courtesy S O’Brien, ASH 2016

Limitations of these data:

1. at best exome only Non-coding Global signatures Unbiased view

2. often not uniformly treated patients within clinical trials3. Clinical outcome data limited to OS/retrospectively collected4. Laboratory technologies heterogeneous (sensitivity, specificity)

Karyotyping FISH Sanger, TGS, WES Others: fragment analysis, AS-PCR, RT-PCR

5. Statistical issues Cohorts not large enough p-values borderline Subgroup analyses

Targeted NGS vs Whole Exome Sequencing vs Whole Genome Sequencing

1-3% of genome is exome UTRs are not always covered by WESunknown function of non-exonic regions

TP53 locus

Burns et al, submitted to Leukemia

Why WGS? The clinical Significance of Non-Coding Mutations: Patients with NOTCH1 Mutations Do Not Benefit From the Addition of

anti-CD20 Therapy and Have RS Risk

Complement: Chl+O vs Chl1

GCLLSG CLL8: FC vs FCR1

1. Stilgenbauer et al Blood 2013; 2. Puente XS, et al. Nature 2015;526:519-24

3’UTR mutations in NOTCH12

Recurrent Clusters of non-Coding Regions in PAX-5

Puente XS, et al. Nature 2015;526:519-24

Diagnosis and Management of AML in Adults: 2017 ELN Recommendationsfrom an International Expert Panel; Blood Nov 2016

Germline Analysis

Diagnostics Work-Up

100,000 Genomes Project

Annotation Service

Sequencing Centres

Biorepository

Consent

SamplesSamples

SamplesClinicians

Clinical Data

Samples

Commercial Users via Embassy Access

De-anonymisation

Clinician

gVCFs

Commercial Data Service

Patient Data

Genomics England Informatics Service

BAMs

Clinical & Bioinformatic

Research teams via Embassy Access

PatientData

Data Control Service

Patients with haematological malignancy

The Genomics England Haematology Malignancy Programme

1. Chronic lymphocytic leukaemia (CLL) patients who are also being recruited to the FLAIR trial

2. Acute myeloid leukaemia (AML) patients who are also being recruited to AML 18/19 trial

3. Newly diagnosed AML and high-risk MDS outside of clinical trials

4. Myeloma patients who are also being recruited to MUK 9 trial

5. Newly diagnosed Myeloma but only if sufficient CD138+ sorted cells can be obtained from bone marrow for DNA extraction.

6. Newly diagnosed aggressive B and T-cell Non Hodgkin’s Lymphomas including DLBCL, Burkitt Lymphoma, Mediastinal B-cell lymphoma and High Grade lymphoma NOS (ie new WHO grey zone category), but only if sufficient fresh biopsy/resection material can be obtained

7. Patients with an unclassified HM malignancy and unknown diagnosis (for example: MDS/MPD overlap syndromes; uncertain diagnoses where clinical presentation does not fit with pathological diagnosis)

8. Patients with CML who are extreme responders based on RQ-PCR values after 3 months of treatment (<1% and >10%) and/or have experienced disease progression. Only pre-treatment samples should be submitted and the patient has to be consented retrospectively

9. Children with ALL who have not obtained MRD levels of less then 1% at day 28 bone marrow examination.

GEAR 2

• Longitudinal samples

• 1. Relapse

• The value of longitudinal sample collections is generally appreciated across the cancer programme. Overall, more then 50% of patients recruited into GEAR 1 will relapse and eventually succumb to their disease. This is why capturing these patients and re-sequencing samples at relapse represents a unique opportunity. We therefore propose that all patients recruited into GEAR 1 should be eligible for sequencing at relapse.

• 2. High-grade Transformation

• Patients recruited into GEAR 1 might also suffer transformation into a more aggressive phenotype.

• Some patients might present with aggressive disease during GEAR 2 and “legacy” samples of low-grade disease are available for sequencing from their previous presentation. These patients would also be eligible for GEAR 2 (e.g. follicular lymphoma progressing to DLBCL; or MDS progressing to AML; CLL progressing to Richter’s Transformation).

The GEL Haematology Malignancy Programme

Conclusions: Using Genomics to predict clinical response within clinical trials

WE NEED LARGE COHORTS OF GENOMICALLY AND CLINICALLY ANNOTATED PATIENTS

MolecularStra fica on

HypermutatedIgHV

Andsomethingelse:

Isolateddel13q??

chemo-immunotherapy

NOTCH1muta on

Splicesitemuta on??

Omitan -CD20

TargetedNotch1inhibitor?

BCL2promoter

IKZF3promoter

muta ons

BCL2inhibitors?

Del11q

IntronicATM

muta ons?

Needforan -CD20therapy

Ac va ngXPO-1

muta ons

Amp2p

XPO-1inhibitors

Del/muta on>1%TP53

SAMHD1;RPS15,EGR2muta ons

Bi-allelicATMinclBIRC3??

Mul plesubclones;agingsignature??

BCRinhibitor

Combos

Highmuta onburden

Checkpointinhibi on

Richter’s

PDL1andpathwayinhibitorcombos

15% 15% 25%15%10% 5% 5% 10%

Oxford BRC Genomics

Jenny Taylor

Sam Knight

Oxford BRC MolDiag WG

Shirley Henderson

Helene Dreau

Anthony Cutts

Pauline Robbe

Ruth Clifford

Adam Burns

Reem Al-solami

Adele Timbs

HealthEconomics

Sarah Wordworth

James Buchanan

Jilles Fermont

Oxford Haematology

Irene Roberts

Chris Hatton

Doug Higgs

Tim Littlewood

ORB Tissue Banking

Maite Cabes

Research Nurse

Christopher Levett

Cecilia Magallano

UK NCRN CLL Subgroup

Peter Hillmen

Andy Pettitt

Stephen Devereux

LEEDS TRIAL OFFICE

UKCLL BioBANK

Andy Pettitt

Melanie Oates

WTCHG Statistics

Chris Yau

Chris Holmes

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