Link to Hunter Slides

The Genetic Drivers of WM

Zachary Hunter Bing Center for WM Dana-Farber Cancer Institute Harvard Medical School

Bing Center for WM Harvard Research at the Medical Dana-Farber School Cancer Institute  e

Bing Center for WM Research at the Dana-Farber Cancer Institute Understanding Genetics If you only had four letters to work with, what kind of story could you tell? So What is DNA Anyway?

 Deoxyribonucleic Acid (DNA) is made of complex molecules called nucleotides. There are 4 types abbreviated A,T,C,G.  Nucleotide bases form stables pairs: A-T and C-G. Two complimentary strands of these bases form DNA.  DNA is broken into 23 long strands known as chromosomes.  The sections of the DNA that contain instructions on how to build proteins are called genes.  Genes in the DNA are transcribed into a single strand of similar nucleotides called Ribonucleic Acid (RNA) and this “message” is processed by the cell and turned into protein. DNA – RNA – Protein

• Transcribed • Stores Provides from DNA information structure, • Encodes signaling, • Used as a instructions and carries template to make out most for RNA protein cellular work

• Genes are regions of the DNA that are transcribed into RNA • RNA carries the DNA code out into the rest of the cell where it can be used as instructions to make protein Identical Twin Studies

While identical twins share many things in common, they also have very different lives, unique personalities, get different diseases and after a number of years can look quite different from each other. Your DNA is a blueprint for building proteins, NOT a blueprint for who you are You are much more than the sum of your genes If People are Genetically Unique, How do we Make Comparisons? The Human Reference Genome (Print Edition) • There are over 3 billion base pairs in the human genome. We receive a complete copy from each parent. • To create a common basis for comparison, a reference genome was created. This reference is not a single person but a mosaic of 13 different individuals.

CC-BY-SA-3.0; Released under the GNU Free Documentation License. How to make it all fit…

 3 billion base pairs strung end to end is about 40 inches in length.

 This quantity of DNA resides inside the nucleus of every cell in your body

 Needless to say, this is a tightly controlled process. Our apologies, the DNA you are looking for is temporarily unavailable…

Laura, B. (2008) Epigenomics: The new tools in studying complex disease. Nature Education Introducing the “omes”

The Genome The Transcriptome The Proteome

• Transcribed • Stores Provides from DNA information structure, • Encodes signaling, • Used as a instructions and carries template to make out most for RNA protein cellular work

The Epigenome The genome as the cell’s operating system The Environment

The operating system of your Protein computer (Windows/Max OSX/Linux) provides a set of tools to allow programs to be loaded and run. Every laptop may have the same operating system, but no one uses their RNA DNA laptop in exactly the same way Whole Genome Integrative Data Visualization

Hunter et al Blood alet Hunter 2013 f b c a d e The Genomics of WM

Understanding the WM “Operating System” Mutation and Cancer

 Cancer can be caused by accidental changes in the genome known as mutations

 As these accumulate, genes start to gain new functions, or lose old ones

 At the point that the cells start to multiply in an uncontrolled way, we call it cancer MYD88 Signaling

MYD88 InhibitorMYD88

Treon et al NEJM NEJM Treon al et2012

Control mutation the the mutation gene MYD88 in over found is 90% of WM A single base pair pair base single A NFKB Nuclear Translocation in Translocation NFKB Nuclear Cell Line BCWM.1 The

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r t c d g o u e n r N a D P MYD88 L265P in WM/IGM MGUS METHOD TISSUE WM IGM MGUS Treon WGS/Sanger BM CD19+ 91% 10% Xu AS-PCR BM CD19+ 93% 54% Gachard PCR BM 70% Varettoni AS-PCR BM 100% 47% Landgren Sanger BM 54% Jiminez AS-PCR BM 86% 87% Poulain PCR BM CD19+ 80% Argentou PCR-RFLP BM 92% 1/1 MGUS Willenbacher Sanger BM 86% Mori AS-PCR/BSiE1 BM 80% Ondrejka AS-PCR BM 100% Ansell WES/AS-PCR BM 97% Patkar AS-PCR BM 85% Updated from Treon and Hunter. Blood. 2013;121(22):4434-6. 17 MYD88 Signaling

MYD88 InhibitorMYD88

Guang Yang, PhD Yang,Guang Blood al.et Yang 2013

Control mutation the the mutation gene MYD88 in over found is 90% of WM A single base pair pair base single A NFKB Nuclear Translocation in Translocation NFKB Nuclear Cell Line BCWM.1 The

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o u e n r N a D P Ibrutinib MYD88 Mutations in Diffuse Large B-Cell Lymphoma

Ngo et al. Oncogenically active MYD88 mutations in human lymphoma. Nature 2011 Mutations observed in WM • L265P • S219C (subclonal) • M232T • S243N WHIM Syndrome Like Mutations in CXCR4 AFound in 51/177 (28.8%) of WMB Patients MEGISIYTSDNYTEEMGSGDYDSMKEPCFREENANFNKIFLPTI YSIIFLTGIVGNGLVILVMGYQKKLRSMTDKYRLHLSVADLLFVI TLPFWAVDAVANWYFGNFLCKAVHVIYTVNLYSSVLILAFISLD RYLAIVHATNSQRPRKLLAEKVVYVGVWIPALLLTIPDFIFANVS EADDRYICDRFYPNDLWVVVFQFQHIMVGLILPGIVILSCYCIIIS KLSHSKGHQKRKALKTTVILILAFFACWLPYYIGISIDSFILLEIIK QGCEFENTVHKWISITEALAFFHCCLNPILYAFLGAKFKTSAQH ALTSVSRGSSLKILSKGKRGGHSSVSTESESSSFHSS LEGEND A - Germline variant in WHIM syndrome A - Transmembrane helix - Somatic frame shift or nonsense WM variant

C S338 Mutation Types Frame&shift&mutation Wu et al, Science, 2010 Nonsense&mutation Nonsense C/G! 21%!

Nonsense C/A! 54%! 25%! Frame shift!

ACC ACCTCTGTGAGCAGAGGGTCC AAGATCCTCTCCAAAGGAAAGCGAGGTGGACATTCATCTGTTTCCACTGAGTCTGAG T T S V S R G S K I L S K G K R G G H S S V S T E S E 311 318 319 320 321 322 323 324 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 Hunter et al, Blood 2013 Marrow and Serum IgM by Genotype in 174 WM Patients Bone Marrow Involvement Serum IgM Levels 70 6000

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Treon and Hunter et al, Blood 2014 Using Mutation Status to Understand Responses to Ibrutinib

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Treon et al, NEJM 2015 Tumor Clone Evolution: Diversification and Treatment Tracking Mutations in WM through

Ibrutinib Treatment

Mutant Allele Fraction Allele Mutant Genomic Response to Ibrutinib

Therapy: Sensitive Mutations

Mutant Allele Fraction Allele Mutant Genomic Response to Ibrutinib

Therapy: Resistant Mutations

Mutant Allele Fraction Allele Mutant Genomic Response to Ibrutinib

Therapy

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l FOXP1 e g t 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 e e CXCR4 d rml G G E E B D F B B F D E A E F C A C A D H H G H A G D D A H / mu 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 3 5 1 2 4 2 3 5 4 1 i 3 4 5 2 1 1 5 2 3 4 4 3 5 2 2 4 5 1 B n e t 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0

a MYD88 t e 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ARID1A d 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 CXCR4

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 MLL2

0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 CD79B 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 MAP2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 MUC16

0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 TRAF3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 TRAF2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 NOTCH2

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New Findings from the WM transcriptome

RNA from 57 CD19+ selected patient bone Median/Count Range/Percent Gender (Female) 21 / 57 36.8% marrow samples were collected for Age in Years 60 (40 - 78) sequencing. B2 Microglobin at Diagnosis > 3 (mg/L) 19 / 46 41.3% Previous Treatment 20 / 57 35.1% For comparison, paired B-cells Familial B-Cell Disorders 23 / 57 40.4% + - Splenomegaly 13 / 57 22.8% (CD19 CD27 ) and memory B-cells + + Lymphadenopathy 30 / 57 52.6% (CD19 CD27 ) were selected from 9 Bone Marrow Involvement (%) 60 (5 - 95) healthy donor peripheral blood samples. Hematocrit (%) 32.8 (23.4 - 42.2) Serum IgM (mg/dL) 3750 (416 - 8320) Paired end samples were run two per Serum IgG (mg/dL) 517 (82 - 3890) Serum IgA (mg/dL) 40 (6 - 516) lane run for 50 cycles using an Illumina MYD88 Mutations 52 / 57 91.2% HiSeq. Data analyzed using the CXCR4 Mutations 23 / 57 40.0% voom/limma bioconductor package in R. ARID1A Mutations 5 / 51 9.8% Isoform specific expression was estimated CD79B Mutations 4 / 51 7.8% Deletion 6q 24 / 53 45.3% using the cufflinks analysis pipeline. Amplification 6p 6 / 53 11.3% Amplification 3q 11 / 52 19.2% False discovery rate of 10% use to Amplification Chr4 10 / 52 21.1% determine significance. Significant Differentially Expressed Genes by Category

Cytogenetic Changes Healthy Donor Comparisons  Chromosome 6q Deletions: 131 genes  MYD88L265PCXCR4WT vs. Healthy: 12,937 genes

 Chromosome 6p Amplification: 65 genes  MYD88L265PCXCR4WHIM vs. Healthy: 12,178 genes

 Chromosome 4 Amplification: 776 genes  MYD88WTCXCR4WT vs. Healthy: 11,059 genes

 Chromosome 3q Amplification: 11 genes Predisposition  Familial History of WM: 263 genes Affects of Somatic Mutations  MYD88L265PCXCR4WT vs. MYD88L265PCXCR4WHIM: 3,103 genes

 MYD88L265PCXCR4WT vs. MYD88WTCXCR4WT: 1,155 genes

 ARID1A: 16 genes

Expression of BCL2 Family Members in WM

WM versus HD Expression p < 0.0001 BCL2 Expression in HD and WM Samples BCL2L1 Expression in HD and WM Samples BAX Expression in HD and WM Samples

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clinical trial clinical

new Drugs in Drugs new Ibrutinib & Ibrutinib WT MYD88/CXCR4 Interac ons MYD88 Poten al Targets WT • MYD88 and CXCR4 are nega vely CXCR4 • All WM Pa ents correlated and expression levels • Lowest levels of B-cell • CXCR4 (both WT & WHIM) are affected by muta on status. differen a on genes. • CXCL13 • Overall MYD88 expression • Low NFkB Response genes • BCL2 and BCL2L1 nega vely correlates with WM Increased expression of genes • IGF1/IGF1R, par cularly in bone marrow involvement. CXCR4 associated with PIK3 signaling MYD88L265PCXCR4WT has a posi ve correla on. • Increased promoter. • Hypomethyla ng agents in • MYD88 mutant allele expression methyla on of PRDM5 and MYD88WT pa ents is o en reduced versus the wild WNK2. • PIK3 delta inhibitors, par cularly type allele in the mRNA whereas in MYD88WT WM. Addi onal the mutant CXCR4 allele is inhibi on of PIK3 gamma may be preferen ally expressed. All WM necessary for CXCR4WHIM pa ents • Up regulated VDJ Genes: DNTT, RAG1, RAG2 • Role for WT CXCR4: Increased CXCL12, CXCR4, VCAM1 • Decreased BAX expression • High levels of BCL2 MYD88L265P • CXCL13 expression MYD88L265P WT correlates with BM WHIM CXCR4 involvement and CXCR4 • Highest levels of IGF1. Hemoglobin • Silencing of tumor • Highest expression of B-cell suppressors up regulated by differen a on genes. MYD88 muta ons. • Associated with a • High IRAK3 and low TLR4 transcrip onal profile that is Expression. the most dis nct from HD • Decreased G-protein and samples and other WM MAPK signaling nega ve genotypes. regulators. • High levels of PMAIP1. • High PIK3R5 and PIK3CG levels. Acknowledgements

The Bing Center Bing Center for WM Funding and Support Steven P. Treon, Lian Xu, • The Bing Fund for WM Guang Yang, Xia Liu, • International Waldenstrom’s Jorge Castillo, Robert Macroglobulinemia Foundation Manning, Christopher J • Coyote Fund for WM Patterson, Philip Broadsky, • Bailey Family Fund for WM Kirsten Mied, Jie Chen, Nicholas Tsakmaklis, Jiaji • D’Amato Family Fund for Genomic Chen, Maria Demos, Toni Discovery Dubeau, Joshua Gustine, • Orzag Family Fund for WM Genomics Gloria Chan. • Leukemia and Lymphoma Society • NIH Spore Development Award Jerome Lipper Myeloma Center Kenneth Anderson, Nikhil Munshi Yaoyu Wang John Quakenbush And the support of all the WM patients

who made this study possible!