Clonal Evolution of saml Johnnie J. Orozco Hematology Fellows Conference May 11, 2012
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
AML Heterogeneous disease Variable response to 7+3, and even HCT Age variability? (disease severity/genetics?) Cytogenetics: risk stratification Predictive prognostic
Three Traditional Cytogenetics Risk Groups Slovak et al., Blood 2000
Prognostics of Cytogenetics Medeiros et al., Blood 2010
Molecular markers can further risk stratify Dohner et al., Blood 2010
Mardis et al., NEJM 2009
Isocitrate DeHydrogenase: -mostly in NK -context dependent *w/ FLT3-ITD: dec relapse *w/o: incr relapse rates Mardis et al., NEJM 2009
Candidate Gene Approach Pathogenesis largely undefined AML Genome snapshot in time Prognostic vs therapeutic implications
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
Illumina Technology: Generate Fragments Mardis, Annu Rev Genomics Hum. Genet. 2008
Bind DNA Fragments Mardis, Annu Rev Genomics Hum. Genet. 2008
Bridge Amplification Mardis, Annu Rev Genomics Hum. Genet. 2008
DS Intermediate
DS Separated Mardis, Annu Rev Genomics Hum. Genet. 2008
Colonies of clusters
Determine first base Mardis, Annu Rev Genomics Hum. Genet. 2008
Capture first cycle Mardis, Annu Rev Genomics Hum. Genet. 2008
Prepare for next cycle Mardis, Annu Rev Genomics Hum. Genet. 2008
Sequence read over multiple cycles Mardis, Annu Rev Genomics Hum. Genet. 2008
Data alignment
Supp Fig 1c: Cell Sorting blasts minimal impact on mutant allele burden
Supp Fig 1a,b: BM Asp
I. Whole Genome Sequencing >95% coverage for samples
II. Recurrent Gene Mutations 17-32 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
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:
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
Recurrent in 2 samples Not previously implicated in AML
New Associations CDH23- cadherin 23 Neurosensory epithelium, tip-link filaments at stereocilia SMC3- structural maintenance of chrom3 Hold sister chromatids UMODL1 ZSWIM4
U2AF1 Specific codon in multiple samples, may be gain of function Supported by enhanced alternative splicing in vitro
STAG2 Predicted protein truncation Reported to be often be deleted in AML and other cancers
IIb. Nonrecurrent mutations Nonrecurrent tier 1 mutations implicated at least 11 pathways All pathways altered in seven patients
Supp Fig 2
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Supp Fig 2
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 182-660 somatic SNVs
Supp Fig 1d: Tier 1 validated SNVs
Fig 1a: Identification of mutation clusters
Fig 1b: ~85% of BM cells were clonal Irrespective of blast count
Fig 1c: CNAs recapitulates SNV clusters
Fig 1d: Most samples oligoclonal
Fig 2a: Clonal Evolution MDS saml Clone 1 (74%): 323 SNVs
Fig 2a: Clonal Evolution MDS saml Clone 1 (74%): 323 SNVs Clone 2: becomes dominant saml, with 3 subclones
Supp Fig 5 Slow progressor
Supp Fig 5 Slow progressor
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Supp Fig 5 Slow progressor
Supp Fig 5 Slow progressor
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Fig 2b: MDS saml dynamic changes in size of mutation clusters
Fig 2b: MDS saml dynamic changes in size of mutation clusters
saml genomes Contained 304-872 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
Supp Fig 3b
Supp Fig 4: similar spectrum of transition/transversion mutation
Supp Fig 4: Treatment effect
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
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
Considerations Causality still not determined Functional data to strengthen hits Discerning random vs. pathogenic mutations
Expectations? Godley, NEJM 2012
Molecular markers can further risk stratify Patel et al., NEJM 2012
Godley, NEJM 2012
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