Please Silence Your Cell Phones Thank You
Utility of NGS and Comprehensive Genomic Profiling in Hematopathology Practice Maria E. Arcila M.D. Memorial Sloan Kettering Cancer Center New York, NY
Disclosure of Relevant Financial Relationships The USCAP requires that anyone in a position to influence or control the content of all CME activities disclose any relevant relationship(s) which they or their spouse/partner have, or have had within the past 12 months with a commercial interest(s) [or the products or services of a commercial interest] that relate to the content of this educational activity and create a conflict of interest. Complete disclosure information is maintained in the USCAP office and has been reviewed by the CME Advisory Committee. Dr. Maria E. Arcila declares affiliation with Raindance Technologies and InVivoScribe
Overview Mutation profiling in hematologic malignancies Basic concepts of NGS as a genotyping platform Practical applications in the clinical lab (case based) Sequencing in AML / MDS / MPN Sequencing in lymphomas Clonality testing NGS as a discovery tool in clinical care Future directions
Molecular testing in Hematologic Malignancies Integral part of diagnostic work-up for myeloid neoplasms AML, MDS, MPN, MDS/MPN Continuously growing list of mutated genes with clinical utility (diagnostic, prognostic and predictive value) NPM1, FLT3, RAS (KRAS, NRAS), KIT, CEBPA, WT1, IDH1, IDH2, DNMT3A, EZH2, JAK2, MPL, TET2, PHF6. Several altered genes with new associations in lymphoid malignancies BRAF, MYD88, MLL2, NOTCH1, SF3B1
AML (NEJM 366;12, 2012) Mutation Profiling of AML/MDS MDS (NEJM364;26, 2011)
Most frequent somatic genetic mutations Blood Cancer Journal (2013) 3, e127; doi:10.1038/bcj.2013.26
Testing based on single gene and low throughput multiplex assays is a challenge for clinical labs High volume Multiple platforms Complex workflows High DNA requirement Results not available simultaneously for clinical decision making
Molecular Methods SNVs Small duplications, insertions, deletions, indels PCR and Sanger dideoxy seq Variant Types Exon duplications, deletions or gene copy number changes SVs PCR and pyrosequencing +/ 1 PCR and mass Spectrometry +/ 1 Fragment analysis, CE Allele specific PCR Real Time PCR FISH +/ 1 NGS custompanels (amplicon capture) NGS custom panels (hybridization capture) +/ 1 NGS wholeexome +/ 1 NGS whole genome
NGS Applications in clinical practice Susceptibility genes Risk assessment Risk management Patient stratification Prediction of therapeutic response Therapeutic monitoring Molecular profiling Tumor sub typing Somatic/driver mutations Clonality testing Methylation Epigenetic changes Alterations in gene expression Micro RNAs
NGS IN CLINICAL PRACTICE Options Whole genome, whole exome or targeted sequencing Targeted sequencing panels are preferred Disease targeted sequencing aids in therapeutic decision making at adequate time frame Yield much higher coverage of genomic regions of interest Reduces sequencing cost and time. More affordable
Hybridization Capture ~50 20,000 genes Library fragments Custom capture probes B B B B B B B B B B Bind hybrids to streptavidin magnetic beads Wash, elute and amplify Sequence to 500-1000X (HiSeq 2500)
Amplicon Capture ~1 50 genes
Platform chosen based on needs and capabilities of the lab Illumina MiSeq Illumina HiSeq Ion Torrent PGM Ion Torrent Proton All commercially available sequencers have shared attributes: Random fragmentation of starting DNA Ligation with custom linkers = a library Amplification on a solid surface (either bead or glass) Direct step by step detection of incorporated bases during the sequencing reaction
shared attributes (continued) Hundreds of thousands to hundreds of millions of reactions imaged per instrument run = massively parallel sequencing A digital read type that enables direct quantitative comparisons A sequencing mechanism that samples both ends of every fragment sequenced ( paired end reads)
Practical applications through a case based approach AML/MDS/MPN panel amplicon capture (enrichment using pico droplet PCR) Broad based hybridization capture panel Clonality testing and MRD
Patient # 1 74 yo female with newly diagnosed AML Most basic workup CEBPA, NPM1, and FLT3 ITD More extensive profiling can better discriminate patients with AML into various prognostic groups
MSKCC Rapid Myeloid Panel ASXL1 ETV6 IDH2 KIT NRAS SF3B1 TET2 CBL EZH2 JAK1 KRAS PHF6 SH2B3 TP53 CEBPA FLT3 JAK2 MPL PTEN SUZ12 TYK2 DNMT3A IDH1 JAK3 NPM1 RUNX1 TET1 WT1 - MSKCC Thunderstorm myeloid assay - Amplicon capture - 28 genes - 355 target regions, 856 amplicons - 12 samples per run + controls sequenced on Illumina MiSeq
Targeted sequencing using Microdroplet PCR Deep Sequencing Technology Millions of unique single molecule pico droplet PCR reactions Highly uniform single plex PCR products Maximum coverage for the target region of interest and regions not easily targeted by hybridization methods High on target sequence reads PCR primers are synthesized and individually reformatted into droplets with each droplet containing only a single primer pair. Primer library Partitioned DNA sample + master mix
IDH2 mutation Bone marrow Neg control
Patient #1 monitoring 0.8 0.7 0.6 0.5 0.4 0.3 0.2 IDH2 R140Q FLT3 D835Y WT1 K141fs RUNX1 Q262X SUZ12 G11R blast count 0.1 0 Day 28 Screening Date Pretrial Day 3 Cycle 2 Day 1 Cycle 3 Day 1 1 2 3 4 1/13/14 2/24/14 3/28/14 4/24/14 WT1 p.k141fs 0.32 WT1 p.k141fs 0.04 WT1 p.k141fs 0.23 WT1 p.k141fs 0.43 IDH2 p.r140q 0.32 IDH2 p.r140q 0.08 IDH2 p.r140q 0.19 IDH2 p.r140q 0.31 RUNX1 p.q262x 0.24 RUNX1 p.q262x 0.06 RUNX1 p.q262x 0.18 RUNX1 p.q262x 0.12 SUZ12 p.g11r 0.09 SUZ12 p.g11r 0.26 FLT3 p.d835y 0.09 70% blasts 30% blasts 56% blasts 70% blasts
Example #2 Monitoring
Clinical Utility of Test Results Diagnostic and prognostic work up Monitoring of disease Identification of targetable markers Detection of biomarkers not detected in specific settings if broad panel not used Insights into tumor biology
Monitoring and assessment of heterogeneity Digital read out of the allelic fraction of sequencing reads for each mutation in the tumor cell population Prevalence of mutation reflects the history of the tumor evolution Older mutations are present at higher variant allele fraction (VAF) and define founder clones Subclones contain founder plus lower VAF mutations Monitoring of progression and evolutionary forces in response to therapy
Patient #3 59 y/o male with CLL 1995 2008 2009 12 2013 27 Initial diagnosis Disease progression : anemia, weight loss lymphocytosis and lymphadenopathy CD5+ lymphoma colon Started on pentostatin, cyclophosphamide, rituximab Progressive disease with numerous infectious and medical complications, Treated with RCVP bendamustin Infectious complications, Expired at age 77
Genetics FISH: Blood 2008: ATM deletion in 6.2% of the interphase cells, no evidence of trisomy 12, 13q deletion or loss of the p53 BM 2008: Normal for CLL FISH panel Subsequent samples, blood and BM: Normal for CLL FISH panel IGVH gene analysis V3 48; Mutation Frequency: 0% 28
Genetic profiling DNA and RNA NGS sequencing of an extensive panel of all genes known to be recurrently mutated in lymphoid and myeloid malignancies DNA 374 cancer related genes RNA 272 genes frequently rearranged 29
Results of DNA and RNA sequencing: 2005 INITIAL PRESENTATION MUTATIONS (gene name/nucleotide change/aa change/variant allele frequency, read depth) ZMYM3_c1784_1785insA_p.H595fs*9(0.89) FBXW7_c1508_1508delC_p.A503fs*21(0.21), PTPN11_c.1505C>T_p.S502L(0.16) NOTCH1_c7541_7542delCT_p.P2514fs*4(0.07), NSD1_c.6085A>G_p.T2029A(0.20), SPEN_c2591_2592delAA_p.K864fs*28(0.24) SPEN_c.2645_2645delG_p.R882fs*2(0.24) NOTCH1_c.7318C>T_p.Q2440*(0.10) BIRC3_c1282_1283insG_p.E429fs*9(0.07) NOTCH2_c.7021C>T_p.Q2341*(0.06), 2011 MUTATIONS IN PROGRESSION SAMPLE (gene name/nucleotide change/aa change/variant allele frequency, read depth) ZMYM3_c.1784_1785insA_p.H595fs*9(0.87) FBXW7_c.1508_1508delC_p.A503fs*21(0.45) PTPN11_c.1505C>T_p.S502L(0.41) NOTCH1_c.7541_7542delCT_p.P2514fs*4(0.30) BCOR_c.4720_4720delC_p.P1574fs*10(0.09) BRAF_c.1781A>G_p.D594G(0.06) NRAS_c.182A>G_p.Q61R(0.05) NRAS_c.38G>A_p.G13D(0.02) TP53_c.747G>T_p.R249S(0.04) TP53_c.641A>G_p.H214R(0.02) TP53_c.637C>T_p.R213*(0.06) The mutation pattern and allelic frequency is significantly different in two time points suggesting marked subclonal diversity marked biological heterogeneity despite homogeneous morphology.
Interesting features of the case At diagnosis CLL with classic morphology and immunophenotype Unique mutation pattern NOTCH1 Subclonal NOTCH2 mutations At progression Emergence of high risk mutations NRAS and TP53 Likely accounting for the adverse clinical outcome NOTCH1 mutations are seen 10% of newly diagnosed CLL Distinct clinicopathologic subgroup characterized by deregulated cell cycle and short survival Associated with unmutated IGHV and trisomy 12 NOTCH2 regulator of CD23 expression in CLL mutations described in SMZL but not in CLL
Clinical utility Comprehensive, targeted next generation sequencing based genetic analysis Provides unprecedented biological information in CLL Likely to change our approach to diagnosis, monitoring, risk assessment and predicting therapy response. 32
Clonality testing by NGS methods Patient #4 68 yo male Increasing lymphocytosis since 2011 Adult T cell lymphoma / leukemia TCRG
Patient underwent bone marrow transplantation TCRG Diagnostic clone TCRG post transplant
TCRG Diagnostic clone AGAATCAGTAGAGGAAAGTATTTTACTTATGCAAGCATGAGGAGGAGCTGGAAATTGATATTGCAAAATCTAATTGAAAATGATTCTGGATCTATTACTGT
TCRG post transplant
Clinical utility Next generation sequencing based clonality assays Efficiently detect IGH and TCRG gene rearrangements Concurrently identify sequence information required to track clones in subsequent samples Concurrent assessment of somatic hypermutation simple and highly concordant with CE/Sanger assays
NGS in the clinical lab Advantages High throughput Better sensitivity Efficient use of limited tissue Consolidation of platforms Wider range of mutation detection Ability to monitor frequency of a specific mutations at determined time frames Challenges for Clinical Implementation Selection of test platform Establishing bioinformatics infrastructure Evaluation of multi gene panels Establishment of assay characteristics Validation on different sample types Results interpretation and reporting Legal and ethical issues Billing and compliance
Standardized nomenclature Standardized web based signouts Tracking of mutations in multiple samples
Practical Challenges (of medical and legal implications) Reporting of larger scale genomic information Reporting of all versus selected genes Mutations in unordered genes Germline variants Variants of potential significance originating from donors Integration in clinical management Logistics Re engineering of workflow Billing and compliance
Conclusions Next generation sequencing methods are Driving discovery in the research setting Supplanting older technology in clinical laboratories Vastly simplify workflows Consolidates several assays reduction of work load and significant cost savings All testing can be reported at once providing full and more comprehensive molecular diagnosis to be used in a clinically actionable time
Clinical Molecular Diagnostics Laboratory MSKCC
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