Clonal Evolution of saml. Johnnie J. Orozco Hematology Fellows Conference May 11, 2012

Transcription

1 Clonal Evolution of saml Johnnie J. Orozco Hematology Fellows Conference May 11, 2012

2 CML: *bcr-abl and imatinib Melanoma: *braf and vemurafenib CRC: *k-ras and cetuximab Esophageal/Gastric: *Her-2/neu and trastuzumab GIST: *c-kit and imatinib NSCLC / Adeno: *EGFR and erlotinib

3 AML Heterogeneous disease Variable response to 7+3, and even HCT Age variability? (disease severity/genetics?) Cytogenetics: risk stratification Predictive prognostic

4 Three Traditional Cytogenetics Risk Groups Slovak et al., Blood 2000

5 Prognostics of Cytogenetics Medeiros et al., Blood 2010

6 Molecular markers can further risk stratify Dohner et al., Blood 2010

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8 Mardis et al., NEJM 2009

9 Isocitrate DeHydrogenase: -mostly in NK -context dependent *w/ FLT3-ITD: dec relapse *w/o: incr relapse rates Mardis et al., NEJM 2009

10 Candidate Gene Approach Pathogenesis largely undefined AML Genome snapshot in time Prognostic vs therapeutic implications

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12 Study Overview N=seven patients Whole Genome Sequencing of skin, bone marrow with saml to id saml specific somatic mutations Bone marrow sample for each patient from antecedent MDS genotyped Mutations tracked to define clonal architecture

13 Illumina Technology: Generate Fragments Mardis, Annu Rev Genomics Hum. Genet. 2008

14 Bind DNA Fragments Mardis, Annu Rev Genomics Hum. Genet. 2008

15 Bridge Amplification Mardis, Annu Rev Genomics Hum. Genet. 2008

16 DS Intermediate

17 DS Separated Mardis, Annu Rev Genomics Hum. Genet. 2008

18 Colonies of clusters

19 Determine first base Mardis, Annu Rev Genomics Hum. Genet. 2008

20 Capture first cycle Mardis, Annu Rev Genomics Hum. Genet. 2008

21 Prepare for next cycle Mardis, Annu Rev Genomics Hum. Genet. 2008

22 Sequence read over multiple cycles Mardis, Annu Rev Genomics Hum. Genet. 2008

23 Data alignment

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25 Supp Fig 1c: Cell Sorting blasts minimal impact on mutant allele burden

26 Supp Fig 1a,b: BM Asp

27 I. Whole Genome Sequencing >95% coverage for samples

28 II. Recurrent Gene Mutations validated point mutations/ indels per saml genome in 168 genes among 7 samples Most were NOT recurrent mutations many randomly acquired, role in pathogenesis? Two recurrent mutations detected in two samples: loss of Function in myeloid tumor suppressors RUNX1 UMODL1

29 UMODL1 Mutated in patients w/ Multiple Myeloma, ovarian Cancer Expressed in normal CD34+ cells, and saml cells from all 7 patients Two mutations in conserved domains:

30 Compared to 200 de novo AML Identified 10 genes that were mutated in one saml and in at least 3 of 200 AML samples Seven of which are known to have recurrent mutations in AML Four not previously implicated in MDS/AML

31 Recurrent in 2 samples Not previously implicated in AML

32 New Associations CDH23- cadherin 23 Neurosensory epithelium, tip-link filaments at stereocilia SMC3- structural maintenance of chrom3 Hold sister chromatids UMODL1 ZSWIM4

33 U2AF1 Specific codon in multiple samples, may be gain of function Supported by enhanced alternative splicing in vitro

34 STAG2 Predicted protein truncation Reported to be often be deleted in AML and other cancers

35 IIb. Nonrecurrent mutations Nonrecurrent tier 1 mutations implicated at least 11 pathways All pathways altered in seven patients

36 Supp Fig 2

37 Supp Fig 2

38 Supp Fig 2

39 Clonality of MDS and saml Calculated mutant allele frequency for all validated somatic single nucleotide variants (SNVs) Each MDS/sAML contained founding clone of cells (mutation cluster) Mutation cluster with somatic SNVs

40 Supp Fig 1d: Tier 1 validated SNVs

41 Fig 1a: Identification of mutation clusters

42 Fig 1b: ~85% of BM cells were clonal Irrespective of blast count

43 Fig 1c: CNAs recapitulates SNV clusters

44 Fig 1d: Most samples oligoclonal

45 Fig 2a: Clonal Evolution MDS saml Clone 1 (74%): 323 SNVs

46 Fig 2a: Clonal Evolution MDS saml Clone 1 (74%): 323 SNVs Clone 2: becomes dominant saml, with 3 subclones

47 Supp Fig 5 Slow progressor

48 Supp Fig 5 Slow progressor

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50 Supp Fig 5

51 Supp Fig 5 Slow progressor

52 Supp Fig 5 Slow progressor

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54 Supp Fig 5

55 Supp Fig 5

56 Supp Fig 5

57 Supp Fig 5

58 Supp Fig 5

59 Fig 2b: MDS saml dynamic changes in size of mutation clusters

60 Fig 2b: MDS saml dynamic changes in size of mutation clusters

61 saml genomes Contained somatic SNVs Likely not necessary for pathogenesis Slower progression (>20mo) with larger proportion of saml specific mutations 6.7% of mutations specific to saml in rapid progressors vs. 37.8% in slow progression

62 Supp Fig 3b

63 Supp Fig 4: similar spectrum of transition/transversion mutation

64 Supp Fig 4: Treatment effect

65 Conclusions Most bone marrow cells clonally derived Evolution of saml dynamic, variable acquisitions Recurrent mutations in both founding clones and subclones MDS clone persisted, although sometimes outcompeted by daughter subclones

66 Implications MDS and AML distinction currently based on highly interobserver variable manual count; mutation profiling for improved diagnostic accuracy? saml dominant subclone derived from MDS founding close suggests therapies aimed at early mutations maybe worthwhile strategy Dz progression also driven by clone specifics

67 Considerations Causality still not determined Functional data to strengthen hits Discerning random vs. pathogenic mutations

68 Expectations? Godley, NEJM 2012

69 Molecular markers can further risk stratify Patel et al., NEJM 2012

70 Godley, NEJM 2012

71 Other Challenges: Access to technology Turnaround time Most cancers have few candidate molecular targets Most targeted interventions are not permanent, resistance Intratumor and metastasis variation

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