Follicular Lymphoma It s not just the t(14;18) anymore. UK Cytogenetics, Newcastle. Jude Fitzgibbon

Transcription

1 Follicular Lymphoma It s not just the t(14;18) anymore UK Cytogenetics, Newcastle Jude Fitzgibbon Centre for Haemato-Oncology 16 th March 2015

2 Technology has Improved Late 80s: My First PCRs by Water bath. X 3

3 Genome Model = Football Stadium, 25,000

4 Types of NG Sequencing Whole Genome (30x) Whole Exome (100X) Targeted (1000x)

5 Defining Clonality: Variable Allele Frequency Presence or Absence 1000 x : Accurate definition of complexity

6 Personalising Therapy in Cancer One size fits All v Tailored to the Individual

7 Not as simple as Patient, Target, Drug, Cure

8 Precision Medicine Pipeline (Lymphoma UK) Molecular Diagnostic Choice of assay and design Cost Tissue quality Tumour content Analytical validity CLIA Turnaround time Bioinformatics analysis Clinical implementation Tissue acquisition Heterogeneity Expert interpretation Pathway versus tissue of origin Availability of broad panels of drugs Trial design and end points Clinical validity and utility

9 Incidence Small B Cell Lymphoma/NHL EMZL NMZL SMZL 1% 7% 2% MARGINAL ZONE Naive B CELLS MANTLE GERMINAL CENTER PLASMA CELL CLL 11% MEMORY B CELL MCL 8% FL 25% HCL/HCLv LPL/WM 1% 2%

10 Follicular lymphoma (FL) in a nutshell Follicular lymphoma (FL) Germinal centre B cell malignancy Commonest indolent non-hodgkin s lymphoma 2500 new cases in the UK/yr Median age 6 th decade; Relapsing Remitting Widespread disease Treatment consists of Rituximab combination therapies Median survival is approx yrs

11 t(14;18) translocation is insufficient is insufficient for the development for FL development of FL 90% of FL have the t(14;18) Over-expression of anti-apoptotic BCL2 Transgenic mice do not develop FL (McDonnell et al., 1989; McDonnell et al., 1991) Healthy individuals carry the translocation (Limpens et al., 1995, Dolken et al., 1996; Summers et al., 2001; Roulland et al, 2006)

12 FL sequential biopsies Capturing Clinical and Molecular Evolution Andrew Lister

13 Origin Existence of FL? of a existence putative of common a putative founder progenitor cell (CPC) population 1. SHM/Sμ patterns, SNPs in sequential FL/r-FL/t-FL samples (Fitzgibbon et al., 2007; Carlotti et al, 2009; Eide et al, 2010; Ruminy et al, 2008) 2. Donor-derived FL after stem cell transplantation 3yrs later BMT 11 yrs later BMT DLI F F F F Carlotti L et al, Blood L 2009 Weigert et L al, Cancer Discovery L 2012 Pool of FLprogenitor cells CPC Pool Transformation FL-1 FL-2 FL-3 tfl CPC common progenitor cell Adapted from Fitzgibbon and Montoto, JCO, 2011

14 Cancer Research UK - nine high-tech gene Finding genes that put people at a higher risk of developing precancerous growths called polyps and bowel cancer 2. How FOLLICULAR lymphoma transforms into the more aggressive B cell lymphoma 20 WGSs 3. Sequencing the genes in an aggressive form of childhood brain cancer 4. Looking for the genes that affect how pancreatic cancer patients respond to treatment 5. Identifying key genes in skin cancer in people with no family history 6. Studying 1,000 women to find new genes linked to breast cancer 7. Understanding how stem cells in leukaemia pick up new genetic faults 8. The genes that make certain types of skin cancer more aggressive 9. Why kidney cancer has unique genetic defects in different parts of the same tumour.

15 Longitudinal profiling of paired FL-tFL biopsies Mean age at diagnosis: 45.5 yrs Time to transformation: 8.4yrs ( yrs) Number of therapies: 1-6 lines Paired-end sequencing Median: 37 x (WGS); 110 x VARIANT DETECTION

16 Deep sequencing to explore the clonal architecture Methods and Analysis framework -2 Criteria for gene selection: Genes with mutations in > 1 case Biological pathway/function: Epigenetic regulation Immune modulation B-cell development JAK-STAT signalling BCR/NF-ĸB signalling 28 selected genes Average: x 840 depth

17 Current view of FL disease progression First genetic hit: t(14;18) BCL2 over-expression Peripheral blood FLLC? Additional (epi) genetic changes Additional (epi) genetic changes Normal B cell primed malignant cell FLIS? FL tfl Bone marrow Lymph node FLIS follicular lymphoma in situ (Mamessier et al, 2013; Schmidt et al, 2013) FLLC follicular lymphoma like cells (Roulland et al, 2014)

18 How Aims to of tackle the and study why tackle the dilemmas? Define the oncogenic landscape of FL Trace genetic events from FL to relapse to transformation Identify early and late driver mutations and pathways Investigate the clonal architecture of the tumour population Better stratify intrinsic heterogeneity Therapeutic targets Prognostic and predictive biomarkers PRECISION MEDICINE

19 Temporal profiling of paired FL-tFL biopsies Csaba (postdoc), Jessica (Clinical fellow), Alex Wang (informatics) DISCOVERY PATIENT COHORT Mean age at diagnosis: 45.5 yrs Time to transformation: 8.4yrs ( yrs) Number of therapies: 1-6 lines

20 Two patterns of tumour evolution occur in progression to transformation FL t-fl Preceding FL Transformed FL Rich CPC with divergent evolution Okosun et al, Nature Genetics 2014 Sparse CPC with convergent evolution

21 An epigenetic addiction in FL 90% of cases had at least one mutation in an epigenetic regulator Okosun et al, Nature Genetics 2014

22 FL-FL : Activating Mutations in components of the mtor pathway in 20% of FL In conjunction D Sabatini, MIT: Submitted EHA and Lugano New Targeted panel: Agilent 158 genes (Suitable FL and DLBCL)

23 Variant allelic fractions (VAF) clonal vs subclonal 34 variants out of 78 reads VAF = 0.43 or 43% CLONAL 3 variants out of 73 reads VAF = 0.04 or 4% SUB-CLONAL

24 Epigenetic alterations are early and stable N 32 paired FL and tfl patients Okosun et al, Nature Genetics 2014

25 Tumour evolution with FL transformation Progressor genetic events EBF1 and NF-κB regulators

26 Clonal mutations suggest early driver Inferring the timing of mutations from clonality events EARLY Relative timing LATE Okosun et al, Nature Genetics 2014

27 Extent of clonal evolution and intra-tumour heterogeneity A. Patients that haven t B. Spatial profiling transformed FL2 FL3 Skin GL MLL2 CREBBP TNFRSF14 FL5 FL4 Pleural fluid Okosun et al, Unpublished

28 Methods The importance and Analysis of framework clonality -3 N Normal Tumour N N N N Vs. N N N N N Clonal Sub-clonal ABSOLUTE algorithm (Carter et al, 2012) Vs. Clonal Sub-clonal

29 Further Complicated by Non- Tumour Cells Methods and Analysis framework -3 N Normal Tumour Mutation Clonal Clonal Subclonal N N N N N N N N N N N N N

30 Is the diagnostic biopsy sufficient? 90 Minutes Extra Time Penalties Diagnosis 1 st Relapse 2 nd Relapse

31 Can we propose any rationale clinical trials to personalise therapy?

32 Mutation focus on H3K4 and H3K27me3 histone H3 marks Mutation focus on H3K4 and H3K27me3 histone H3 marks EZH2 i HDAC i? MLL2* Me Me Me Ph Me UTX* EZH2* Me Ac Ac Ph Ac Ph Ac Ac Ac Me Ph Me N- A R T K R K S T K R K K R K S K H CREBBP* P300* Ac K 56 Me K 79 * Abbreviations: MTase: methyltransferase, HAT: histone acetyltransferase. +gain- or loss-of function

33 Hypermethylation of PRC2 Targets, EZH2 mutations in FL PRC2/EZH2 H3K27me3 repressive mark FL cases with EZH2 mutations 27% FL EZH2 27 Mutations K634E (n=1) V637A (n=1) Y646N (n=36) Y646F (n=27) Y646S (n=12) Y646H (n=9) Y646C (n=3) Y646 mutations (n=87) V679M (n=1) Mutation load (%) A682G (n=9) A692V (n=7) K63 4 A68 2 A SANT SANT CXC SET domain O Riain et al., Leukemia, 2009; Bodor et al., Leukemia, 2011; Blood 2013

34 Clonality assessment of EZH2 mutations in FL Targeted resequencing (EZH2 VAF range: 3-49%) Comparison of VAFs for EZH2, CREBBP, MLL2, TNFRSF14 and MEF2B (Bodor et al, Blood 2013)

35 Activating EZH2 mutations in B-cell lymphoma GC-DLBCL (Morin et al, Nature Genetics 2010) Targeting codon Y646 (SET domain) Gain of function (Sneeringer et al, PNAS 2010, Yap et al, Blood 2011)

36 Targeting actionable mutations Clinical trials of EZH2 inhibitorsplanned Preferential targeting of mutant cell lines and xenograft models Phase I trials ongoing

37 UK Lymphoma: Biomarker led Trials - Selecting Pt Early EZH2 Trial Opening in UK

38 KDM5i Stabilise the H3k4me3 mark to offset MLL2 Loss? Percentage growth over control (%) Log [KDM5 inhibitor] (M) oci-ly-1 oci-ly-7 oci-ly-18 su-dhl-4 su-dhl-6 su-dhl-8 karpas-422 DOHH-2 HT WSU-DLCL2 Western blots of DMSO (-) Vs 1uM KDM5 inhibitor (+) treated cells for 48hrs H3K4me3 Histone 3 GAPDH OCI-LY SU-DHL SU-DHL OCI-LY Karpas DOHH WSU-DLCL2 - + OCI-LY SU-DHL HT +

39 Precision Medicine Pipeline Aggressive Lymphoma UK Diffuse Large B Cell Lymphoma Barts, Cambridge, Leeds, Oxford, Southampton, York Specialist Programme

40 JAK nuclear membrane BCR NF-kB Mutation Team-Sheet CD79A CD79B CARD11 BCL10 MALT1 Immune escape CD58 CIITA PDL1/2 B2M HLAII TNFRSF14 TNFAIP3 BIRC3 TRAF3 IKBKB MAP3K14 NOTCH NOTCH1 NOTCH2 SPEN JAK-STAT JAK2 SOCS1 TLR MYD88 MAPK RAS BRAF MAP2K1 TARGET GENES Co factors TF Cell cycle CCND1 CCND3 CDKN2A ATM TP53 MYC BCL6 PRDM1 TCF3 ID3 MLL2 EZH2 CREBBP p300 Apoptosis BCL2 Genetic/epigenetic reprogramming

41 SUMMARY Summary EVOLUTION AND TRANSFORMATION: Two modes of tumour evolution: Rich vs Sparse An ancestral CPC population is responsible for the development of successive disease events Early initiating events MLL2 (KMT2D), CREBBP Late acquired events EBF1, MYD88, TNFAIP3 Transformation does not occur via a single genetic event Driver events context dependent Clonality - Upfront screening actionable mutations Precision trials Non coding region still to be explored

42 Roadmap to improve diagnosis, treatment and management 4 integrated projects: 1, Identification and characterization of new cases 2, Capturing the molecular diversity 3, Functional characterisation and disease 4, Improving clinical management modelling Molecular diagnostics, Six predisposition loci Tissue bank, Data collection New genes (NGS), Functional characterisation NOVEL GUIDELINES IMPROVED MANAGEMENT

43 ACKNOWLEDGEMENTS