The Present and Future of Next-Generation
Sequencing in the Hematology Laboratory
Ahmet Zehir, PhD
Director of Clinical Bioinformatics
Molecular Diagnostics Service,
Department of Pathology
ISLH, 2017
Disclosures
I have nothing to disclose
Molecular Diagnostics
Mission: Identification of molecular alterations that diagnose hematological
malignancies, prognosticate for risk management, help predict outcomes for treatment
modalities, and allow for monitoring of disease across time
Molecular Diagnostics
MacConaill and Garraway, Journal of Clinical Oncology, 2010
Mission: Identification of molecular alterations that diagnose hematological
malignancies, prognosticate for risk management, help predict outcomes for treatment
modalities, and allow for monitoring of disease across time
Molecular Diagnostics
Mission: Identification of molecular alterations that diagnose hematological
malignancies, prognosticate for risk management, help predict outcomes for treatment
modalities, and allow for monitoring of disease across time
BRAF V600E -> Diagnostic marker for hairy cell leukemia
JAK2 V617F -> Diagnostic marker for clonal myeloproliferative neoplasm
Falini et al., Blood, 2016
Molecular Diagnostics
Mission: Identification of molecular alterations that diagnose hematological
malignancies, prognosticate for risk management, help predict outcomes for treatment
modalities, and allow for monitoring of disease across time
Mutations in NPM1 favorable risk factor in AML
Mutations in TP53, RUNX1 poor prognostic markers in AML and MDS
Verhaak et al., Blood, 2005
Molecular Diagnostics
Mission: Identification of molecular alterations that diagnose hematological
malignancies, prognosticate for risk management, help predict outcomes for treatment
modalities, and allow for monitoring of disease across time
BRAF V600E -> Vemurafenib
FLT3 internal tandem duplications (ITDs) -> TK inhibitors
Tiacci, et al., NEJM, 2015
Molecular Diagnostics
Mission: Identification of molecular alterations that diagnose hematological
malignancies, prognosticate for risk management, help predict outcomes for treatment
modalities, and allow for monitoring of disease across time
Examples:
Tracing presence of driver mutations across multiple blood samples
Next Generation Sequencing
Example:
Illumina sequencing by synthesis
Papaemmanuil E, et al., NEJM, 2016
Next Generation Sequencing
Capture based PCR based
Illumina HiSeq 2000, NextSeq, MiniSeq IonTorrent Illumina MiSeq
Data Analysis
Hybridization vs Amplicon Capture
Capture Method
Variant Types
SNVsSmall insertions,
deletions
Large insertions,
deletions
SVs,
fusions
Amplicon Capture ✓ ✓
Hybridization Capture – Gene panels ✓ ✓ ✓ +/-
Hybridization Capture - Whole exome ✓ ✓ ✓ +/-
Hybridization Capture - Whole genome ✓ ✓ ✓ ✓
Amplicon based assaysRaindance thunderbolts
ASXL1 BCOR BCOR1 BRAF CALR CBL CBLB
CEBPA CSF3R DNMT3A ETV6 EZH2 FLT3 GATA1
GATA2 GNAS HRAS IDH1 IDH2 JAK1 JAK2
JAK3 KDM6A KIT KMT2A KRAS MEK1 MPL
MYD88 NOTCH1 NPM1 NRAS PHF6 PML PTEN
PTPN11 RAD21 RUNX1 SETBP1 SF3B1 SMC1A SMC3
SRSF2 STAG2 TET2 TP53 U2AF1 WT1 ZRSR2
At MSK, Over 4,000 patients have been tested with Raindance assay over the last 3 years
Monitoring post treatment
Donor SNP
Host SNPs
Raindance : Post transplant monitoring
Maria Arcila
MSK-IMPACT Heme
MSK-IMPACT Heme : gene listABL1 BCL11B CEBPA ETNK1 HDAC1 JAK1 MLH1 PCBP1 REL SMG1 U2AF2
ACTG1 BCL2 CHEK1 ETV6 HDAC4 JAK2 MOB3B PDCD1 RET SMO UBR5
AKT1 BCL6 CHEK2 EZH2 HDAC7 JAK3 MPEG1 PDGFRA RHOA SOCS1 VAV1
AKT2 BCOR CIC FAM46C HGF JARID2 MPL PDGFRB RICTOR SOX2 VAV2
AKT3 BCORL1 CIITA FANCA HIF1A JUN MRE11A PDPK1 RNF43 SP140 VHL
ALK BCR CRBN FANCC HIST1H1B KDM5A MSH2 PDS5B ROBO1 SPEN WHSC1
ALOX12B BIRC3 CREBBP FANCD2 HIST1H1C KDM5C MSH6 PHF6 ROS1 SPOP WT1
AMER1 BLM CRKL FAS HIST1H1D KDM6A MTOR PIGA RPTOR SRC XBP1
APC BRAF CRLF2 FAT1 HIST1H1E KDR MUTYH PIK3C2G RRAGC SRSF2 XPO1
AR BRCA1 CSF1R FBXO11 HIST1H2AC KEAP1 MYC PIK3C3 RTEL1 STAG1 ZRSR2
ARAF BRCA2 CSF3R FBXW7 HIST1H2AG KIT MYCL1 PIK3CA RUNX1 STAG2
ARHGEF28 BRD4 CTCF FGF19 HIST1H2AL KMT2A MYCN PIK3CG RUNX1T1 STAT3
ARID1A BRIP1 CTNNB1 FGF3 HIST1H2AM KMT2B MYD88 PIK3R1 SAMHD1 STAT5A
ARID1B BTG1 CUX1 FGF4 HIST1H2BC KMT2C NBN PIK3R2 SDHA STAT5B
ARID2 BTK CXCR4 FGFR1 HIST1H2BD KMT2D NCOR1 PIM1 SDHB STAT6
ARID3A CALR CYLD FGFR2 HIST1H2BG KRAS NCOR2 PLCG1 SDHC STK11
ARID3B CARD11 DAXX FGFR3 HIST1H2BJ KSR2 NCSTN PLCG2 SDHD SUFU
ARID3C CASP8 DDR2 FGFR4 HIST1H2BK LCK NF1 PMS2 SETBP1 SUZ12
ARID4A CBFB DDX3X FLCN HIST1H2BO LMO1 NF2 PNRC1 SETD1A SYK
ARID4B CBL DIS3 FLT1 HIST1H3B LTB NFE2 POT1 SETD1B TBL1XR1
ARID5A CCND1 DNMT3A FLT3 HIST1H3G MALT1 NFE2L2 PPP2R1A SETD2 TBX3
ARID5B CCND2 DOT1L FLT4 HLA-A MAP2K1 NKX2-1 PRDM1 SETD3 TERT
ASXL1 CCND3 DTX1 FOXL2 HNF1A MAP2K2 NOTCH1 PRKAR1A SETD4 TET1
ASXL2 CCNE1 DUSP22 FOXO1 HRAS MAP2K4 NOTCH2 PTCH1 SETD5 TET2
ATM CD274 EED FOXP1 ID3 MAP3K1 NOTCH3 PTEN SETD6 TET3
ATP6AP1 CD28 EGFR FURIN IDH1 MAP3K13 NOTCH4 PTPN1 SETD7 TGFBR2
ATP6V1B2 CD58 EGR1 FYN IDH2 MAP3K14 NPM1 PTPN11 SETD8 TNFAIP3
ATR CD79A EP300 GATA1 IGF1 MAPK1 NRAS PTPN2 SETDB1 TNFRSF14
ATRX CD79B EP400 GATA2 IGF1R MAPK3 NSD1 RAD21 SETDB2 TOP1
ATXN2 CDC73 EPHA3 GATA3 IGF2 MCL1 NT5C2 RAD50 SF3B1 TP53
AURKA CDH1 EPHA5 GNA11 IKBKE MDM2 NTRK1 RAD51 SGK1 TP63
AURKB CDK12 EPHA7 GNA12 IKZF1 MDM4 NTRK2 RAD51B SH2B3 TRAF2
AXIN1 CDK4 EPHB1 GNA13 IKZF3 MED12 NTRK3 RAD51C SMAD2 TRAF3
AXL CDK6 ERBB2 GNAQ IL7R MEF2B P2RY8 RAD51D SMAD4 TRAF5
B2M CDK8 ERBB3 GNAS INPP4B MEN1 PAK7 RAD52 SMARCA4 TSC1
BACH2 CDKN1B ERBB4 GNB1 IRF1 MET PALB2 RAD54L SMARCB1 TSC2
BAP1 CDKN2A ERG GRIN2A IRF4 MGA PARP1 RAF1 SMARCD1 TSHR
BARD1 CDKN2B ESCO2 GSK3B IRF8 MGAM PAX5 RARA SMC1A TYK2
BCL10 CDKN2C ESR1 GTF2I IRS2 MITF PBRM1 RB1 SMC3 U2AF1
MSK-IMPACT Heme variant calling strategy
Blood
Saliva
and/or Nail
Variant Call Set
Unmatched variant calling
Variant Call Set with genotypes in normal(s)
Remove variants based on:
• Similar VAF around 50%
• CH characteristics
MSK-IMPACT Heme : example
Maria Arcila
RNAseq : Archer
Ryma Benayed
Archer Pan-Heme PanelABL1 BTK CHD1 EBF1 HOXA10 KLF2 MYBL1 PAX5 PYRY8 SOX11
ABL2 CALR CHIC2 EIF4A1 HOXA9 KMT2A MYC PBX1 RAB29 SRSF2
AICDA CARD11 CIITA ENTPD1 ID4 KRAS MYD88 PDCD1 RAG1 STAT3
AKT3 CBFB CREB3L2 EPOR IDH1 LIMD1 MYH11 PDCD1LG2 RAG2 STAT5B
ALK CBL CREBBP ERG IDH2 LMO1 NEK6 PDGFRA RANBP1 STAT6
ASB13 CCDC50 CRLF2 ETV6 IKZF1 LMO2 NF1 PDGFRB RARA STIL
ASXL1 CCND1 CSF1R EXOC2 IKZF2 LRMP NFKB1 PHF6 RBM15 STRBP
BATF3 CCND2 CSF3R EZH2 IKZF3 LYL1 NFKB2 PICALM RHOA TAL1
BAX CCND3 CTLA4 FAM216A IL16 LZTS1 NME1 PIM1 ROS1 TCF3
BCL11B CD274 CYB5R2 FBXW7 IL7R MAL NOTCH1 PIM2 RUNX1 TFG
BCL2 CD44 DCK FGFR1 IRF4 MALT1 NOTCH2 PLCG1 RUNX1T1 TLX1
BCL2A1 CD79B DEK FGFR2 IRF8 MAML3 NPM1 PLCG2 S1PR2 TLX3
BCL3 CDC25A DENND3 FGFR3 ITPKB MECOM NRAS PML SEMA6A TNFRSF13B
BCL6 CDK6 DLEU1 FLT3 JAK1 MKL1 NT5C2 PPAT SERPINA9 TNFSF4
BCR CDKN2A DNM2 FOXP1 JAK2 MLF1 NTRK3 PRDM16 SETBP1 TP63
BIRC3 CDKN2B DNMT3A FUT8 JAK3 MLLT10 NUP214 PRKAR2B SETD2 TYK2
BLNK CEBPA DNMT3B GATA1 KAT6A MLLT4 NUP98 PTK2B SF3B1 U2AF1
BMF CEBPD DNTT GATA2 KDM6A MME P2RY8 PTPN1 SH2B3 WT1
BMP7 CEBPE DUSP22 GLIS2 KIAA0101 MPL PAG1 PTPN11 SH3BP5 XPO1
BRAF CEBPG E2F2 GNAS KIT MUC1 PAICS PYCR1 SLC29A1 ZCCHC7
Ryma Benayed
Archer Heme : Example
Lymphotrack: Clonality assessment
Replaces conventional assays
Allow identification of the full range of clonal populations
high-resolution picture of the spectrum of immunity found in lymphoid
malignancies.
Determine specific DNA sequence of clonal rearrangements
Detect clonal events hidden in a polyclonal distribution
Track residual disease – low level and MRD
Define initial behaviors of clonal tumor populations, suppression or re-
emergence of these populations following treatment
For B cell processes - Examine Somatic Hypermutation (SHM) as a
prognostic marker
Maria Arcila
CATCTGGATACACCTTCACCAGCTACTATATGCACTGGGTGCGACAGGCCCCTGGACAAGGGCTTGAGTGGATGGGAATAATCAACCCTAGTGGTGGTAGCACAAGCTACGCACAGAAGTTCCAGGGCAGAGTCACCATGACCAGGGACACGTCCACGAGCACAGTCTACATGGAGCTGAGCAGCCTGAGATCTGAGGACACGGCCGTGTATTACTGTGCTAGAGATCAGTGGCTACCTCTCAACTACTTTGACTACTGGGGCCAGGGAACCCT
1 Core biopsy, porta hepatis
Very limited tissue – CLL/SLL
GCCTCAGGATTCTCCTTTAGTAGCTATGGCATGAGCTGGGTCCGCCAGGCTCCAGGGAAGGGGCTGGAGTGAGTGGCACATATCTGGAATGATGGAAGTCAGAAATACTATGCAGACTCTGTGAAGGGCCGATTCACAATCTCCGAGACAATTCTAAGAGCATGCTCTATCTGCAAATGGACAGTCTGAAAGCTAAGGACACGGCCATGTATTACTGTACCCCTTATTATGATTACGTTTGGGGGAGTTATCGTTATACCCACAGCATCACACGGTCCATCAGAAACCCATGCCACAGCCCTCCCCGCAGGGGACCGCCGCGTGCCATGTTACGATTTTGATCGAGGACACAGCGCCATGGGTATGGTGGCTACTGGGACCTACTTTGACTACTGGGGCCAGGGAACCCT
CACTGTCTTTGGTGGCTCCATCAGTACTTACTACTGGAGCTGGATCCGGCAGCCCCCAGGGAAGGGACTGGAGTGGATTGGGTACATCTATGACAGTGGGAGGACCAACTCCAACCCCTCCCTCAGGAGTCGAGTCACCATAATAGGAGACACGTCCAAGAACCAGATCTCCCTGAGGTTGAGCTCTGTGACCGCTGCGGACACGGCCGTTTATTACTGTGCGAGCACCAAGCGTAGAGAAGTTGCTGACGACTACTACTTCTACTACATGGACGTTTGGGGCAAAGGGACCAC
3 2
Future technologies: Molecular Barcoding
Molecular barcoding for detecting very low allele fraction variants
Schmitt et al. PNAS, 2012
Increases sensitivity of mutation calling significantly with reduced background mitation
rates
Data standardization / sharingWhile labs adopt existing or upcoming NGS based technologies, handling the massive
amounts of data generated is one of the biggest challenges to keep in mind
Harmonization of tumor types
Ritika Kundra, Niki Schultz
Data standardization / sharingWhile labs adopt existing or upcoming NGS based technologies, handling the massive
amounts of data generated is one of the biggest challenges to keep in mind
Harmonization of tumor types
Ritika Kundra, Niki Schultz
Needs of the clinical lab
What we needed for manual review of clinical cases?
• Track certain meta-data elements for the sample
• Review mutations at the raw data level (.bam files)
• Review copy number alterations and structural variants
• Track sample failures, repeats, multiple samples from the same patient
• Share data with the institute (clinicians + researchers)
MPath NGS
• MySQL based backend
database
• History tables for tracking
changes in data structures
• SQL Alchemy based data
objects
• Flask based front-end
application
• Interactivity based on
Angular, JQuery, D3
• Authentication for security
MPath
Aijaz Syed, Anoop Balakrishnan, John Ziegler
Ideals of Data Democratization
Genomic
Data
Clinicians Researchers
Decision
Making
Clinical Trial
Accruement
Cohort level
data
Raw data
files
Data sharing with ResearchersCohort level data
MPath
nightly data
update via APIs
de-identified data
cBio Portal
Data sharing with ResearchersCohort level data
MPath
nightly data
update via APIs
de-identified data
cBio Portal
Data sharing with ResearchersCohort level data: cBio Portal
De-identification via DMP ID
P-00001234-T02-IM5
patient id
corresponding to MRN
sample counter
assay identifier
IM3 : MSK-IMPACT v3IM5 : MSK-IMPACT v5AR1 : MSK-Archer v1RD1 : RDTS v1IH1 : MSK-IMPACTHeme v1
Data sharing with ResearchersRaw data sharing
Challenges:
• Allow researchers to run their own algorithms, analyses on the data without
PHI
• Allow researchers to combine clinical with data generated in the research
setting
• Make sure different teams are not working on the same project without realizing
itSolution:
• Create a de-identified .bam file repository, updated nightly
• Require researchers to register their projects with the Data Usage Committee
• Require researchers to register their projects with IRB via data protocols
Acknowledgements
Aijaz
Syed
Mustafa
Syed
Jack
Birnbaum
John
Ziegler
Anoop
Balakrishnan
Shruti
Madur
Raghu
Chandramohan
Liu (Tony)
Zhen
Ryan
PtashkinAbhinita
Mohantya
Ronak
ShahSumit
Middha
Gowtham
Jayakumaran
Hyunjae Ryan
Kim
Meera
Prasad
Clinical Bioinformatics team
Acknowledgements
Clinical BioinformaticsAijaz Syed
Sumit Middha
Raghu Chandramohan
Abhinita Mohanty
Ryan Ptashkin
Meera Prasad
Mustafa Syed
Tony Liu
Jack Birnbaum
John Ziegler
Anoop Balakrishnan
Gowtham Jayakumaran
Aaron Dack
Anita Bowman
Jason Hweei
Mohammad Haque
Shruti Madur
Ronak Shah
Molecular DiagnosticsMarc Ladanyi
Maria Arcila
Ryma Benayed
Khedoudja Nafa
Liying Zhang
Laetitia Borsu
Meera Hameed
Snjezana Dogan
Dara Ross
Jaclyn Hechtman
Diana Mandelker
Lulu Wang
Jinjuan Yao
Deborah DeLair
Talia Mitchell
Angela Yannes
Justyna Sadowska
CMODavid Solit
Michael Berger
Agnes Viale
Barry Taylor
Niki Schultz
Nick Socci
Eder Paraiso
Julia Rudolph
Knowledge SystemsNiki Schultz
JJ Gao
Benjamin Gross
Yichao Sun
Hongxin Zhang
Fred Criscuolo
Dong Li
Ritika Kundra
Annice Chen
Debyani Chakravarty
Sarah Phillips
MSKCCRoss Levine
Jose Baselga
David Hyman
David Klimstra
Craig Thompson
Paul Sabbatini
Melissa Pessin
John Petrini
Chris Sander
Mark Robson
Mike Eubank
Stu Gardos
Roy Cambria
Dalicia Reales
Farmer Family Foundation
Marie Josée and Henry R. Kravis
Cycle for Survival
Geoffrey Beene Cancer Research Center
Justyna Sadowska
Jacklyn Casanova
Anna Plentsova
Iwona Kiecka
Julie Son
Lisa Stewart
Josh Somar
Tamim Malbari
Christine England
George Jour
Navid Sadri
Ken Tian
Keith Killian
Juan Gomez-Gelvez
Deepu Alex
Caleb Ho
Carlos Pagan