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Download Lenalidomide in Relapsed/Refractory Multiple Myeloma
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Genomic Sequencing in Myeloma: Ready for Prime Time? Nikhil C. Munshi, MD Professor of Medicine Harvard Medical School Boston VA Healthcare System Director Basic and Correlative Sciences Dana-Farber Cancer Institute DANA-FARBER CANCER INSTITUTE Multiple Myeloma – Genomic Studies Gene Expression Profile Normal MGUS Myeloma aCGH 55 MM Cell Lines; 73 Patient Samples 192 Newly Dx patients - HDT Cytogenetics/FISH SNP Array Copy Number Alteration Gene Expression Profile-based Response Prediction Microarray gene expression datasets Study IFM 2005# IFM 2005# HOVON 65 MM / GMMG $ APEX / SUMMIT Number of Samples 136 67 282 162 Platform Affymetrix Exon 1.0 ST array Affymetrix Affymetrix Exon 1.0 ST U133 Plus array 2.0 array Affymetrix U133 Plus 2.0 array Treatment Protocol VAD, ASCT Bortezomib, ASCT VAD/PAD, ASCT Bortezomib Response Measurement PostTransplant PostInduction PostTransplant Post-novel agent Relapsed Complete Response 44 (32%) 24 (36 %) 76 (27 %) 73 (43%)∞ #: Unpublished, in preparation $: Broyl A, et al. Blood 2010 ∞: Post-refractory cases from APEX and SUMMIT trials; 13 patients had CR and 60 had PR . Amin et al. Blood 2011 Low Accuracy of Prediction Method Sensitivity Specificity SVM RBF 56 63 SVM Polynomial 52 63 SVM Linear 51 62 Decision Tree 49 70 KNN (n=10) 53 71 LDA 48 66 DLDA 42 69 PAM 54 74 Bayesian 54 64 ANN 49 68 PPV NPV 62 60 64 56 57 60 63 60 65 58 75 68 72 76 64 63 75 70 72 70 Accuracy 64 62 64 61 63 60 64 68 68 60 Amin et al. Blood 2011 High-throughput genomic analysis spanning all regulatory checkpoints WGS aCGH/SNP array Exon arrays GEP array Methylation Array Genome Mutations Copy Number Transcriptional Control RNA transcript RNA splicing RNA level RNA level RNA Processing miRNA arrays miRNA RNA Modification Translation Acytylome Proteamics Phosphome* Protein Functional proteins* Posttranslational Modifications What is the Purpose of Genome Sequencing? • Diagnostic end points • Understand the biology • Prognostication • Therapeutic application Somatic variants in Multiple Myeloma Average n. Validated Substitutions 120 450 400 350 300 80 250 200 150 40 100 50 0 0 n. Nucleotide Change Type of mutation 1704 608 532 2342 522 267 841 283 561 172 C->A/G->T C->G/G->C T->A/A->T Transversions T->G/A->C 1 58.46 C->T/G->A T->C/A->G Transitions MISSENSE SYNONIMOUS NONSENSE 1 STOP_LOST INTRON Heterogeneity of Somatic Variants Total n. of genes found in screen Cancer Census* Genes Non Cancer Census Genes 2462 83 2379 Recurrent ≥2 Unique 396 2066 Non-synonymous variant recurrence Gene n. of cases % recurrent KRAS 16 23.9% BRAF 9 21.4% NRAS 8 11.9% RYR2 8 11.9% FSIP2 7 10.4% TP53 7 10.4% FAT4 5 7.5% HMCN1 5 7.5% DNAH5 5 7.5% ZFHX4 5 7.5% PEG3AS 5 7.5% FLG 4 6.0% PTPRZ1 4 6.0% DNAH9 4 6.0% GPR98 4 6.0% Distribution of genes Recurrent 5-10%, 23 Recurrent 10-15%, 5 Recurrent >20%, 1 Recurrent <5%, 367 Unique, 2066 *Futreal A.P. et al, Nat Rev Cancer (2004).4,177-183 Prevalence of Somatic Mutations Across Human Cancers Alexandrov et al Nature 2013 Mutational Profile in Myeloma Waldenstrom’s macroglobulinemia Mutational Profile in Myeloma Prognostic Implications of Mutations in Myeloma Frequency of Mutation Subclonal Fraction (Bolli et al. Nature Comms, 2014) Immunohistochemical and molecular characterization of BRAF V600E mutation status in multiple myeloma. Andrulis M et al. Cancer Discovery 2013;3:862-869 ©2013 by American Association for Cancer Research Patient With BRAF V600E - Response to Vemurafenib Andrulis M et al. Cancer Discovery 2013;3:862-869 ©2013 by American Association for Cancer Research Only 4/9 of BRAF mutations are activating Patient Gene Protein Patient Gene Protein Kinase Activity* PD4285 PD4286 PD4289 PD4289 PD4292 PD4294 PD4296 PD4301 PD5851a PD5859a PD5861a PD5865a PD5865a PD5869a PD5871a PD5874a PD5875a PD5876a PD5878a PD5878a PD5882a PD5885a PD5886a PD5887a PD5888a PD5889a PD5890a PD5891a PD5892a PD5894a PD5895a PD5901a PD7181 KRAS KRAS KRAS BRAF BRAF BRAF KRAS NRAS NRAS KRAS KRAS KRAS BRAF NRAS BRAF BRAF NRAS KRAS KRAS BRAF BRAF KRAS NRAS KRAS KRAS KRAS KRAS BRAF NRAS KRAS KRAS NRAS NRAS p.G12A p.Q61H p.Q61H p.G466V p.D380Y p.D594G p.G12C p.Q61H p.G12S p.G12A p.A146V p.Q61H p.V600E p.Q61K p.V600E p.E586K p.Q61R p.Q61H p.G12R p.G596V p.V600E p.Q61R p.Q61R p.Q61H p.Q22K p.G12C p.G12V p.G466V p.G13R p.Q61K p.Q61L p.Q61R p.Q61R PD4289 BRAF p.G466V Impaired PD4292 BRAF p.D380Y ? PD4294 BRAF p.D594G Impaired PD5865a BRAF p.V600E High PD5871a BRAF p.V600E High PD5874a BRAF p.E586K High PD5878a BRAF p.G596V Impaired PD5882a BRAF p.V600E High PD5891a BRAF p.G466V Impaired BRAF KINASE ACTIVITY High, 4 Impaired ,4 ?, 1 *Wan et al, Cell 2004 vol. 116 (6) pp. 855-67 Outline • Subclonal diversification in myeloma • Genomic evolution over time RAS-RAF mutations are often late and convergent Clonal Evolution in Myeloma • Whole exome sequencing in 15 patients with serial samples collected at the time of progression at least 4 months apart To evaluate change in clonal composition at progression. • Normal tissue samples • SNP array identified changes compared between early and later samples. Branching evolution Cluster of clonal mutations –in all cells Subclonal fraction late sample Cluster of clonal mutations - Lost in late sample Cluster of clonal mutations - Acquired in late sample Subclonal fraction early sample (Bolli et al. Nature Comms, 2014) Patterns of genomic evolution Driver mutations emerge over time Next-Generation Sequencing Method LymphoSIGHT platform: Sequencing of Immunoglobulin gene Collect marrow and Purify Myeloma cells Extract DNA Multiplex PCR to amplify VDJ Common PCR to prepare for sequencing Sequence ~1M 100bp reads CTGGCCCCAGTAGTCATACCAACTAGCG TTGGCCCCAGAAATCAAGACCATCTAAA ACGGCCCCAGAGATCGAAGTACCAGTGT TTGGCCCCAGACGTCCATATTGTAGTAG CTGGCCCCAGAAGTCAGACCGGCTAACA Myeloma Cells gDNA OR mRNA PCR amplicons Sequencing library • Identification of all “clonotypes” in the sample • Determination of the frequency of each clonotype Sequence data Results Evidence of Oligoclonality • Observed evidence of more than one clone with distinct Ig sequences • Unrelated clones: Clones whose common ancestor is before the pre B cell stage • Related sequences: Clones with a late common ancestor (related clones) 16% One Clone 7% 77% Unrelated Clones Related Clones 2 Related and Unrelated Subclones: Case 4 • Two minor clones are highly similar but unrelated to the major clone Clone 1 (86%) VH3 N DH1 N JH1 Clone 2 (6%) VH1 N DH2 N JH6 Clone 3 (1%) VH1 N DH2 N JH6 A C A Bases indicated are mutations from the germline sequence Clinical implications of subclonal diversification • Evolution is a continuous process • All patients with myeloma have evidence for subclonal diversification • RAS-RAF pathway mutations frequently subclonal, with convergence • Likely to affect response to kinase inhibitors • Different clones likely to have variable treatment response, growth dynamics, Ab production etc Outline • Subclonal diversification in myeloma • Genomic evolution over time • Expression of mutant allele Limited Expression of Mutated Genes What Mutations Are Relevant? 27% (Rashid et al. Blood, 2014 In Press) Not All Mutations are Expressed: Not Even Drivers (Rashid et al. Blood, 2014 In Press) DNA 1.5 Sample 1 Sample 1 25.5 Clone 1 Clone 2 97.1 Sample 2 Sample 3 74.5 Differential Expression of Clone 1 Individual Clones RNA Clone 1 Clone 2 Sample 2 Clone 1 Sample 3 0.3 Clone 1 Clone 1 16.2 Clone 2 Clone 2 68.8 93.5 Sample 4 Sample 4 Clone 1 Clone 1 Sample 5 Sample 5 0 7.9 Clone 1 Clone 2 84.7 Clone 1 Clone 2 IFM/DFCI 2009 Study Newly Diagnosed MM (N=1,000) Randomize CY (3g/m2) MOBILIZATION Goal: 5 x106 cells/kg Induction RVDx3 MRD Collection CY (3g/m2) MOBILIZATION Goal: 5 x106 cells/kg Melphalan 200mg/m2* + ASCT MRD Consolidation RVD x 5 MRD @ CR MRD @ CR RVDx3 Calibration RVD x 2 Revlimid 18 mos Maintenance MRD Revlimid 18 mos SCT at relapse Clinical Implication • • • • • Different patterns of disease evolution over time across patients. Need for repeated genomic analysis Most frequent and not so frequent mutations have been identified – Providing new targets Limited expression of mutant allele – Need to confirm functional impact of gene mutation. Except for MEK/ERK pathway no other mutation is observed in > 10% - Are there number of myeloma sub groups with clonal variability? Sub clonal variants and clonal evolution – Need for multi target therapy and develop clone control mechanisms Is Genome Sequencing Ready for Prime Time? • Yes - For limited POP targeted therapy studies - To understand the biology • No - Diagnostic end points - Prognostication - Wider therapeutic application High-throughput genomic analysis spanning all regulatory checkpoints WGS aCGH/SNP array Exon arrays GEP array Methylation Array Genome Mutations Copy Number Transcriptional Control RNA transcript RNA splicing RNA level RNA level RNA Processing miRNA arrays miRNA RNA Modification Translation Acytylome Proteamics Phosphome* Protein Functional proteins* Posttranslational Modifications DANA-FARBER CANCER INSTITUTE Masood Shammas, PhD Prabhala Rao, Anderson, PhD Kenneth MD Mariateresa Fulciniti, PhD Weihua Song, MD Jagannath Pal, MD, PhD Giovanni Parmigiani, PhD Puru Nanjappa, PhD Cheng Li, PhD Jianhong Lin, MD Yi Li, PhD Maria Gkotzamanidou , MD, PhD Naim Rashid, PhD and Adan Soerling, MD, PhD Mehmet Samur, PhD Weihong Zhang, MD Bioinformatics Group Teresa Calimari, MD ArielDr. Kwart, BS Herve Avet-Lousieu Sophia Adamia, PhD Dr Stephane Miniville, Rajya MS Moreau Dr.Bandi, Philippe YuTzu MD MAGRANGEAS Dr.Tai, Florence Jooeun Bae, PhD Dr. Michel Attal and IFM HAPPY DIWALI Peter Campbell Andy Futreal Graham Bignell Niccolo Boli David Wage
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