Anna Schuh, MD, Ph.D.

Transcription

1 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

2 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? 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

3 100,000 Genome Project is trying to address the old problem of classification of disease using new technology

4 From Personalisation to Precision Medicine in CLL? Understand the molecular basis for clinical heterogeneity 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 durations To avoid side-effects To ultimately achieve cure Pivotal studies/approvals st line Chlorambucil Fludarabine Cyclophosphamide Fludarabine Cyclophosphamide Rituximab Bendamustine Obinutuzumab Chlorambucil Ofatumumab Chlorambucil Ibrutinib Idelalisib Rituximab R/R Alemtuzumab Ofatumumab Ibrutinib Idelalisib Rituximab Venetoclax Acalabrutinib Morphology Flow FISH Sanger targeted NGS including WES WGS 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: ; 2. Marini BL, et al. J Oncol Pharm Pract 2016 Jun 29. pii: (epub ahead of print).

5 Probability of Progression-Free Survival Probability of Overall Survival Chemoimmunotherapy Remains Standard of Care For Front-Line Treatment of Patients With Standard-Risk CLL CLL8 Trial, 1L FCR (N=817): PFS and OS in All Patients 1,2 FCR (N=408) FC (N=409) p=0.001 by log-rank test Months on Study 96 0 p=0.001 by log-rank test Months on Study 96 25% of CLL patients relapse within 2 years from first-line chemoimmunotherapy 1. Hallek M, et al. Lancet 2010; 376: ; 2. Fischer K, et al. Blood 2016; 127:

6 Progression-Free (%) Some Patients are Cured With Chemo-Immunotherapy PFS in According to IGHV mutation status 1L FCR: MD Anderson cohort (N=300) 100 N Progression-Free IGHV mutated IGHV unmutated None of above Tri12 Del13q Del11q del17p p< Time (Years) 16 50% of IGHV mutated patients are cured 1L, first line; FC, fludarabine plus cyclophosphamide; FCR, fludarabine, cyclophosphamide and rituximab; mut, mutation; WT, wild type Fischer K et al. Blood 2016;127:

7 Tam CS, et al. Blood 2014;124(20): Long-Term Results after FCR: MD Anderson Experience (Median Follow-Up: 142 Months)

8 Fraction alive Both Deletion and Mutation of TP53 on Chromosome 17p Confer Poor Prognosis and Resistance to Chemotherapy German CLL4 trial 1 Overall survival TP53 wt TP53 mutated TP53 deleted Time (months) At least 50% of patients with FCR-refractory disease do not have TP53 abnormalities TP53 abnormalities at relapse: 26.6% 2 1. Zenz T, et al. J Clin Oncol 2010;28: ; 2. Malcikova J, et al. Blood 2009;114: ; 3. Zenz T, et al. Blood 2009;114: ; 4. Dohner et al, NEJM, 2000

9 Subclonal TP53 Mutations Have the Same Unfavourable Prognostic Impact as Clonal Defects Targeted NGS 1 WES 2 TP53 unmutated Solely subclonal TP53 M Clonal TP53 M p< Events Total 5-year OS 95% CI % % % % % % p from pairwise comparisons < < CI, confidence interval; OS, overall survival; WT, wild type. 1. Rossi D, et al. Blood 2014;123: ; 2. Landau D, et al. Nature 2015;526:

10 Using Diagnostic-Grade NGS,TP53 Mutations Can be Detected to 5% Variant Allele Frequency (VAF) samples Gene.refGene ExonicFunc.refGene AAChange.refGene AAChange.refGene2 VAF TRO-Mic TP53 nonsynonymous SNV TP53:NM_ :exon4:c.G443C:p.R148T TRO-Mic TP53 nonsynonymous SNV TP53:NM_ :exon4:c.G445A:p.D149N GRUMar TP53 frameshift insertion TP53:NM_ :exon1:c.136dupC:p.H46fs Example of TP53 mutations (trend of signal detected by Sanger sequencing) ARCTIC/ADMIRE Clifford et al, Manuscript submitted to Leukemia

11 Cumulative PFS, % Exonic Predictors of </= 2 year progression free survival after FCR 100 ARCTIC/ADMIRE 1.0 German CLL TP53 Disruption SAMHD1 Disruption 20 Combined Alterations P< q sole Time (months) RPS15 mutation Clifford et al, manuscript submitted; Clifford et al, Blood 2014 Landau et al, Nature 2015

12 Hierarchical Predictive Models and other candidates (outside of clinical trials) EGR2 mutations SETD2 SNVs/deletions Rossi et al, Blood, 21 February 2013, volume 121, number 8 Young et al, Leukemia 2017; Parker et al, Leukemia 2016

13 CLL-International Prognostic Index 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 Low % NR Intermediate % 105 High % 75 Very high % 29 Median OD (months) 3472 treatment-naive patients eight international phase 3 clinical trials 5 countries Hallek, Lancet Oncology 2016

14 19% of relapsed/refractory CLL patients carry multiple recurrent combinations of TP53, ATM and SF3B1. These occur in non-random order (mostly ATM ancestral) ICLL01 CLL R/R CLL patient s CLL202 17p 11q TP53 ATM SF3B1 NOTCH1 XPO1 SAMHD1 MED12 BIRC3 MYD88 recurrent combinations rare combinations no mutation one gene mutation n = 22 n = 49 n = 22 n = 21 CLUSTER #1 CLUSTER #2 CLUSTER #3 CLUSTER #4 Impact of the multiple-hit profile on progression-free survival P = Multiple-hit CLL TP53 ATM SF3B1 Multiple-hit profile n = 22 No multiple-hit profile n = 92 Guièze R et al, Blood Aug 27

15 Ibrutinib Discontinuation and Outcomes in Patients With CLL Jennifer A. Woyach Hematology 2015;2015: Maddocks K, et al. JAMA Oncol 2015;1:80-87.

16 Survival Outcomes by Chromosomal Abnormali es Detected by FISH in R/R Pa ents* Progression-Free Survival Overall Survival Median PFS 5-year PFS Del17p (n=34) 26 mo 19% Del11q (n=28) 55 mo 33% Trisomy 12 (n=5) NR 80% Del13q (n=13) NR 91% No abnormality** (n=16) NR 66% *Only 2 pa ents in the TN group showed PD or death. Subgroup analyses, therefore, focused on the R/R popula on. **No del17p, del11q, del13q, or trisomy 12; in hierarchical order for del17p, and then del11q NR, not reached. Median OS 5-year OS Del17p (n=34) 57 mo 32% Del11q (n=28) NR 61% Trisomy 12 (n=5) NR 80% Del13q (n=13) NR 91% No abnormality** (n=16) NR 83% Courtesy S O Brien, ASH 2016

17 Multivariate Analysis* for PFS and OS Courtesy S O Brien, ASH 2016

18 Limitations of these data: 1. at best exome only Non-coding Global signatures Unbiased view 2. often not uniformly treated patients within clinical trials 3. Clinical outcome data limited to OS/retrospectively collected 4. 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

19 Burns et al, submitted to Leukemia Targeted NGS vs Whole Exome Sequencing vs Whole Genome Sequencing TP53 locus unknown function of nonexonic regions 1-3% of genome is exome UTRs are not always covered by WES

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21 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 GCLLSG CLL8: FC vs FCR 1 3 UTR mutations in NOTCH1 2 Complement: Chl+O vs Chl 1 1. Stilgenbauer et al Blood 2013; 2. Puente XS, et al. Nature 2015;526:519-24

22 Recurrent Clusters of non-coding Regions in PAX-5 Puente XS, et al. Nature 2015;526:519-24

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24 Diagnosis and Management of AML in Adults: 2017 ELN Recommendations from an International Expert Panel; Blood Nov 2016 Diagnostics Work-Up Germline Analysis

25 100,000 Genomes Project Clinician Patients with haematological malignancy Consent Clinicians Samples Samples Samples Samples Biorepository Patient Data Clinical Data De-anonymisation Genomics England Informatics Service Sequencing Centres Patient Data Clinical & Bioinformatic Research teams via Embassy Access Data Control Service Annotation Service BAMs Commercial Data Service Commercial Users via Embassy Access gvcfs

26 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 pretreatment 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.

27 GEAR 2 The GEL Haematology Malignancy Programme 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 resequencing 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).

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29 Conclusions: Using Genomics to predict clinical response within clinical trials Molecular Stra fica on Hypermutated IgHV And something else: Isolated del13q?? chemoimmunotherapy NOTCH1 muta on Splice site muta on?? Omit an -CD20 Targeted Notch1 inhibitor? BCL2 promoter IKZF3 promoter muta ons BCL2 inhibitors? Del11q Intronic ATM muta ons? Need for an -CD20 therapy Ac va ng XPO-1 muta ons Amp 2p XPO-1 inhibitors Del/muta on >1% TP53 SAMHD1; RPS15, EGR2 muta ons Bi-allelic ATM incl BIRC3?? Mul ple subclones; aging signature?? High muta on burden Checkpoint inhibi on Richter s PDL1 and pathway inhibitor combos BCR inhibitor Combos 15% 15% 10% 15% 5% 25% 5% 10% WE NEED LARGE COHORTS OF GENOMICALLY AND CLINICALLY ANNOTATED PATIENTS

30 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 Our Patients Genomics England Mark Caulfield Clare Turnbull Deborah Jones Augusto Rendon Matthew Parker WTCHG Statistics Chris Yau Chris Holmes Bio-Informatics Niko Popitsch Kate Ridout Pavlos Anthoniu Dimitris Vavoulis Kate Ridout Basile Stamatopoulos Illumina David Bentley Jennifer Becq Sean Humphray Mark Ross Zora Kingsbury 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