MYD88, CXCR4 and the Genetics of WM Zachary Hunter, PhD Bing Center for WM Research at the Dana-Farber 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 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 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 a Visualization IntegrativeWhole GenomeData b c d e f Hunter et al Blood 2013 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 A single base pair TLR4 IL1R mutation the gene MYD88 is found in over MYD88 Signaling 90% of WM T I R A NFKB Nuclear Translocation in P The BCWM.1 Cell Line MYD88 MYD88 BTK I RA 4 K AK 4 IR I RA 1 K AK 1 IR 2 TA B B TRAF6 A 1 T TAK1 NEMO Control MYD88 Inhibitor IKKα IKKβ Proteasomal IκBα Degrada on p50 p65 Nuclear Transloca on and Signaling Treon et al NEJM 2012 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 A single base pair TLR4 IL1R mutation the gene MYD88 is found in over MYD88 Signaling 90% of WM T I R A NFKB Nuclear Translocation in P The BCWM.1 Cell Line MYD88 MYD88 BTK I RA 4 K AK 4 IR I Ibrutinib RA 1 K AK 1 IR 2 TA B B TRAF6 A 1 T TAK1 NEMO Control MYD88 Inhibitor IKKα IKKβ Proteasomal IκBα Degrada on p50 p65 Nuclear Transloca on and Signaling Guang Yang, PhD Yang et al. Blood 2013 MYD88 Mutations in Diffuse Large B-Cell Lymphoma Ngo et al. Oncogenically active MYD88 mutations in human lymphoma. Nature 2011 Mutations observed in WM vs DLBCL • L265P ABC: 76.4% • S219C (subclonal) ABC: 6.9% • M232T ABC: 4.2% • S243N ABC: 5.6% % Of All MYD88 Mutations in ABC-DLBCL 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 60 5000 t n e 50 m ) l e 4000 d v l / g o v 40 m n ( I C M P 3000 g L I 30 m M u B r t e n S 2000 e r 20 e P 10 1000 0 0 MYD18 8WT MYD828 L265P MYD838 L265P MYD48 8L265P MYD18 8WT MYD828 L265P MYD838 L265P MYD48 8L265P CXCR4WT n=16 CXCR4WT n=105 CXCR4WHIM-FS n=24 CXCR4WHIM-NS n=25 CXCR4WT n=16 CXCR4WT n=105 CXCR4WHIM-FS n=24 CXCR4WHIM-NS n=25 Treon and Hunter et al, Blood 2014 5 5 . 1 A.# 1 e n i l e s a B 0 0 . o 1 1 t d e z i l Using Mutation Statusa to Understand m r Minor Response o N M 5 5 g . I 0 0 Partial Response m u Responses to Ibrutinibr e S Very Good 0 0 . Partial Response 0 0 Serum IgM Response MYD8Hemoglobin8L265PCXCR4WT MYD88L265PCXC RResponse4WHIM MYD88WTCXCR4 WT 5 5 . 1 A.# 1 B.# 8 8 . 1 1 e n e e i l n n i i e l l s e e s s a a a B 6 6 0 0 . B B . 1 1 o 1 1 t o o t t d d d e e e z z z i i i l l l a a a m m m 4 4 r r r Minor Response . o o o 1 1 N N N n n i i M b b 5 5 g o o . I l l g g 0 0 Partial Response o o m 2 2 u m m . r e e 1 1 e H H S 0 0 . Very Good . 1 1 0 0 . Partial Response 0 0 MYD88L265PCXCR4WT MYD88L265PCXCR4WHIM MYD88WTCXCR4WT MYD88L265PCXCR4WT MYD88L265PCXCR4WHIM MYD88WTCXCR4WT B.# 8 8 . 1 1 e e n n i i Treon et al, NEJM 2015 l l e e s s a a 6 6 . B B 1 1 o o t t d d e e z z i i l l a a m m 4 4 r r . o o 1 1 N N n n i i b b o o l l g g o o 2 2 m m . e e 1 1 H H 0 0 . 1 1 MYD88L265PCXCR4WT MYD88L265PCXCR4WHIM MYD88WTCXCR4WT The WM Genome So Far… A B C A 1 1 2 G 2 6 B A 8 8 3 2 1 P H 1 B P 4 4 1 3 2 1 1 1 8 8 2 2 H P B N C 2 2 M 1 9 P F F E A R R 3 C E P K L D D D D D B T L 7 I I G X D C C G A A R 5 E N N V Y K Y L A U E Y O I R R T A X X D R L R R R P O Y Y M P B M L H P A F C M A C M C M M T T N R M T S M T H02 1 1 1 1 1 1 0 1 0 0 H02 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100% 90% D05 1 1 1 1 1 0 1 0 0 0 A01 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 D02 1 1 1 0 0 1 1 1 0 0 D04 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 80% Mutations F08 1 1 1 1 0 1 1 1 0 0 D03 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 H05 1 1 0 1 0 1 1 1 0 0 G01 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 60% D06 0 1 1 1 1 1 1 0 0 0 A02 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 G06 1 1 1 1 1 1 0 1 1 0 H05 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 40% 27% B07 1 1 1 1 1 0 1 0 1 0 G05 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17% B01 1 1 1 1 0 1 1 1 1 0 H03 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20% 7% 7% 7% 7% 3% 3% 3% 3% 3% 3% 3% 3% 3% F02 1 1 1 1 0 1 1 1 1 0 H04 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 B02 1 1 1 0 1 1 1 1 1 0 D02 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0% B03 1 1 1 1 1 1 1 1 1 0 A05 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 4 A B 2 A 3 2 6 3 2 2 2 3 P 1 8 R 1 9 L 1 5 P 1 F F H G 2 A E D C D 7 L P P A C A A C A D R N B06 1 1 1 1 1 1 1 0 1 0 C03 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Y X I D M B T U R R T R E R Y C R C B M T T O T S D07 1 1 1 0 1 1 1 1 1 0 A04 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 M A Y M N M M F06 1 1 1 1 1 1 1 0 1 0 C02 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 H04 1 1 1 0 1 1 1 0 1 0 F03 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 93% B04 1 0 1 0 0 0 0 0 0 1 E04 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 100% 87% Copy Number B08 1 1 1 0 1 0 0 0 0 1 A03 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 77%7 7% B05 1 1 0 1 0 1 0 1 0 1 E02 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 80% 70% D01 1 1 0 1 0 1 0 0 0 1 D05 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 60% Alterations F03 1 0 0 1 0 1 0 0 0 1 F01 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 60% 50% 1 1 1 1 0 1 0 0 0 1 E05 B01 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 37% D04 1 1 1 1 1 1 0 0 0 1 B04 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 40% D03 1 1 1 0 1 0 1 1 0 1 F04 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 F07 1 1 1 1 1 0 1 1 0 1 D01 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 20% D08 1 1 1 1 0 1 1 0 0 1 B05 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 H01 1 1 1 1 0 1 1 0 0 1 E01 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0% F04 1 1 1 1 1 1 1 1 0 1 E05 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 2 1 2 1 1 B 1 H07 1 1 1 1 1 1 1 0 0 1 G04 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 P N 1 P M G E LN G LY X D T V K H ID E01 1 1 1 1 1 0 1 1 1 1 G02 1 1 1 0 0 1 0 0 0 0 1 0 0 0 0 1 R B I K R FO P H M LE A P Somatically deleted/mutated Hunter et al, Blood 2013 Consistent with germline Next Generation RNA Sequencing Studies in WM 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.