Next Generation Sequencing in Haematological Malignancy: A European Perspective. Wolfgang Kern, Munich Leukemia Laboratory
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1 Next Generation Sequencing in Haematological Malignancy: A European Perspective Wolfgang Kern, Munich Leukemia Laboratory
2 Diagnostic Methods Cytomorphology Cytogenetics Immunophenotype Histology FISH Molecular Genetics
3 MDS with isolated 5q-
4 Acute Promyelocytic Leukemia MGG
5 AML:10-color-staining
6 Karyotype: 46,XX,del(5)(q15q32)
7 real time PCR
8 Methods for 2015+? Cytomorphology Cytogenetics Immunophenotype A Histology FISH C Molecular Biology G T
9 Some definitions Genome: complete DNA of a being Intron: non coding region of a gene Exon: coding region of a gene (1.5%)
10 Exon (expressed region) or Intron (intervening region)
11 RUNX1: Exon Structure Transcript ID: ENST E3 270bp E4 157bp E5 105bp E6 192bp E7 162bp E8 476bp 7 amplicons Median: 342 bp Minimum: 341 bp Maximum: 348 bp Bi-directional sequencing
12 TET2: Exon Structure 13 amplicons 6 amplicons E3 E4 E5 E6 E7 E8 E9 E10 E11 3,409bp 91bp 94bp 209bp 151bp 90bp 138bp 355bp 1,472bp. 27 amplicons Median: 343 bp Minimum: 336 bp Maximum: 350 bp Bi-directional sequencing
13 Frequency and location of CALRmut
14 Frequency and location of NOTCH1mut 113 NOTCH1mut in 103/852 patients (12.1%): 67.3% - 12 missense (10.6%) - 18 nonsense (15.9%) - 83 frame-shift (73.5%) 90.3% of mutations located in the C-terminal part
15 Landscape of RUNX1 Mutations in AML 275 RUNX1 mutations observed in 25.9% (211/814) of cases Median clone size: 39% (ranging from 2% to 96%) Mutated cases: 73.9% (156/211): 1 mutation 26.1% (55/211): 2 (n=46) or more (n=9) mutations Recurrent codons: Arg135, Arg139, Asp171, Arg174 missense 34.9% (96/275) nonsense 14.2% (39/275) frame-shift 42.5% (117/275) in-frame 4.0% (11/275) splicing 4.4% (12/275)
16 Molecular workflow for hematology in DNA malignant cells RNA viable cells PCR melting curve Sanger NGS Software tools Report incl. results and recommendations
17 Fluidigm Access Array Sample Prep
18 Droplet-based PCR Process Primer Pair Library Genomic DNA Template Mix PCR Sequencing 2,000,000 Single Template PCR s
19 Myeloid Gene Panel (Dx v2) 31 Gene panel ASXL1 BCOR BRAF CALR CBL CSF3R DNMT3A ETV6 EZH2 FLT3-TKD GATA1 GATA2 IDH1 IDH2 JAK2 KIT KLHL6 KRAS MPL NPM1 NRAS PHF6 PTPN11 SETBP1 SF1 SF3B1 SRSF2 TET2 TP53 U2AF1 WT1 Turn-around time: 6-7 days Input: 2.2 µg DNA 489 amplicons 10 samples per run
20 CLL Gene Panel 13 Gene panel: ATM BIRC3 BRAF (V600) FBXW7 KLHL6 KRAS NOTCH1 (PEST) NRAS MYD88 POT1 SF3B1 (HEAT) TP53 XPO1 Turn-around time: 6-7 days Input: 2.2 µg DNA 323 amplicons 10 samples per run
21 RainDrop System for Panel/MRD
22 RainDrop PCR Process Primer Pair Library Genomic DNA Template Mix PCR Sequencing
23 ThunderBolts Myeloid Panel 53 Gene panel ABL1 ASXL1 BCOR BCORL1 BIRC3 BRAF CALR CBL CBLB CDKN2A CEBPA CSF3R DNMT3A ETV6 EZH2 FBXW7 FLT3-TKD GATA2 GNAS IDH1 IDH2 IKZF1 JAK2 JAK3 KDM6A KIT KRAS MAP2K1 MLL MPL MYD88 NOTCH1 NPM1 NRAS PHF6 PTEN PTPN11 RAD21 RHOA RUNX1 SETBP1 SF3B1 SMC1A SMC3 SRSF2 STAG2 STAT3 TET2 TP53 U2AF1 WT1 XPO1 ZRSR2 Input: <100ng DNA 533 amplicons 8 samples per run As agreed upon by HemOnc Consortium and Raindance 10/2014
24 Read-out: Illumina Miseq A C G T % Bases by cycle Quality by A4RR3:1:1101:15637:1456 1:N:0:1 CAGGAACTCACTGCCTCCCAGCTCTGAAA CATACCATTGTTCAAGTTGAACAGAAAGC TGCACATGTATTTATCATACACTTTCCCT CTTCTGTCAGCTTCATCTTGAGAAATAAT CTAAAAAGAAAGACACAGGAGAAAATTCT TTTGGATAAAGGTGATCAAGCCTGACAGT CAGATCGGAAGAGCACACGTCTGAACTCC AGTCACGAGTGGATCTCGTATGCCGTCTT CTGCTTGAAAAAAAAAAAA + BBBBBFFFFFFFCGGGGGGGGGHHHFB5F FFHHHHFHHHHHHBFGGGHFHHHHHGHFH GBFFHGHHHFGHHHHHHHHHHHHHHHHHH GHHHHHHHHHHHHHFHHHHB5EFBGGHFH HHFHFHFGGGHHHFHHGHH0FHFGHHHHH HHHHGHHHHGHFHHFHHEFHGGHH2GFHH HHHGHGHG/F/<CFHGHHGHHHGEDHHHH FFGFHHGDG<GFHF0DGFEFHHGHGGGHG HHHGGGFF0FFGGGG?=--
25 10 samples per run Myeloid Panel: Turn-around time Sample receipt on Monday Turn-around time: 6 business days
26 MDS
27 MDS: ELN recommondations L. Malcovati et al. for ELN, Blood, 122, , 2013
28 MDS: ELN recommondations L. Malcovati et al. for ELN, Blood, 122, , 2013
29 Molecular/-genetic aberrations in MDS n = 738 patients, 111 genes, 43 genes with mutations mean age: 68 patients with cytogenetic aberrations: 33% patients with molecular oncogenic aberrations: 78% E. Papaemmanuil et al., Blood 122, , 2013
30 Genes mutated in MDS E. Papaemmanuil et al., Blood 122, , 2013
31 Genes mutated in MDS E. Papaemmanuil et al., Blood 122, , 2013
32 Genes mutated in MDS n = 944, 104 genes, 47 genes with mutations median age: 72.8 (range ) patients with cytogenetic aberrations: 31.4% patients with molecular aberrations: 89.5% T. Haferlach et al., Leukemia, 28, , 2014
33 T. Haferlach et al., Leukemia, 28, , 2014 Frequency of Genes being mutated median per patient: 3 range 0-12
34 T. Haferlach et al., Leukemia, 28, , 2014 Prognostic models beyond IPSS-R Model 1: 14 genes + age + WBC, Hb, Plt, % blasts, Cytogenetics according IPSS-R Model 2: 14 genes only (13/14 from Model 1)
35 Comparison of two MDS Cohorts Papaemmanuil et al. Haferlach et al. Demographics Patients (n=) Age (years) 68 (median) 72.8 (mean) Males:females (ratio) 415:323 (1.3) 580:364 (1.6) Median follow-up (in months) MDS subtypes RA 139 (18.8%) 41 (4.3%) RARS 92 (12.5%) 81 (8.6%) RARS-T 17 (2.3%) 28 (3.0%) RCMD 126 (17.1%) 195 (20.7%) RCMD-RS 59 (8.0%) 183 (19.4%) 5q- 20 (2.7%) 37 (3.9%) other 285 (38.6%) 379 (40.1%) Cytogenetics, karyotype Normal:abnormal (ratio) 425:213 (2.0) 648:296 (2.2) Targeted DNA sequencing Genes, analyzed Genes, significantly mutated [1] Number of mutations 2,260 2,764 Affected patients (%) 549 (74.4%) 845 (89.5%) D. Rose et al., BJH, 167, , 2014
36 Comparison of two MDS Cohorts Σ 172 D. Rose et al., BJH, 167, , 2014
37 Comparison of two MDS Cohorts T. Haferlach et al. E. Papaemmanuil et al. p < 10-9 D. Rose et al., BJH, 167, , 2014
38 (adapted from G. Mufti) Mutations in MDS Tyrosin Kinase Pathway Transcription Factors others JAK2 PTPN11 KRAS NRAS BRAF CBL RTK EP300 RUNX1 WT1 ETV6 GATA2 PHF6 TP53 BCOR NPM1 Cohesin GNAS/GNB1 RNA Helicase Epigenetic Regulation Splicing IDH 1 & 2 DNMT3A EZHZ SF3B1 U2AF1 ZRSF2 TET2 ATRX UTX ASXL1 SETBP1 SF1 SRSF2 U2AF2 SF3A1 PRPF40B PRPF8
39 RainDrop System for MRD 1. Screening PCR Droplet Generation Sequencing 2. MRD PCR Droplet Generation Droplet Detection
40 RainDrop System for MRD 1. Screening PCR Droplet Generation Sequencing 2. MRD PCR Droplet Generation Droplet Detection
41 r = 0.75 NPM1mut/ABL: RainDrop vs. Fluidigm EP1
42 RUNX1: RainDrop vs. Roche Run #1 r = 0, Run #2 r = 0,9968
43 Guidelines for NGS?
44 NGS: Standardization of Clinical Testing (Nex-StoCT) Nature Biotechnology; Vol. 30: Issue 11, 2012 A. Gargis et al., Nature Biotechnology; 30: , 2012
45 Rehm et al., Genet Med Sep;15(9):
46 College of American Pathologists on NGS Aziz et al., Arch Pathol Lab Med, epub 25. Aug, 2014
47 College of American Pathologists on NGS Aziz et al., Arch Pathol Lab Med, epub 25. Aug, 2014
48 Bioinformatics
49 Bioinformatics
50 FDA: Questions for Public Comments on NGS (2/2015) Questions: Analytical Performance 1. How are labs currently developing NGS tests and assessing their analytical performance? 2. What are the benefits and risks to public health of having FDA independently evaluate the analytical performance of NGS tests and/or platforms? 3. How should changes or advances in technology be managed utilizing a standardsbased approach? Questions: Clinical Performance 1. What are current practices for clinical interpretation of variant information from NGS tests? 2. Would the use of ClinVar/ClinGen or other curated databases by all test developers provide a more efficient way to establish clinical significance for different variants? 3. Can information about the clinical meaning of variants be of value to physicians and patients when there is uncertainty about the strength of the association between the variant and disease? 4. What controls should be in place for laboratories who wish to implement their own interpretive process, rather than relying on FDA-recognized evidence assessments?
51 ClinVar 1. ClinVar meets several of these criteria and should be considered first choice as of now 2. However, as of 02/2015 only 12 % of overall variants (77,000) were submitted by more than 1 (!) submitter 3. Since ClinVar/ClinGen does not curate the submitted data itself, ~20% of the existing data is already discordant today
52 How to store the DNA?
53 Cell pellets for DNA/RNA
54 Freezer -80 C (n = 35)
55 Cell pellets for DNA/RNA
56 New tubes for Automatic Freezer -80 C
57 New tubes for Automatic Freezer -80 C
58 Automatic Freezer -80 C
59 Automatic Freezer -80 C
60 Automatic Freezer -80 C
61 Automatic Freezer -80 C
62 Automatic Freezer -80 C
63 Automatic Freezer -80 C
64 Automatic Freezer -80 C
65 This is the end?
66 Report (Foundation Medicine, Heme)
67 Report (Foundation Medicine, Heme)
68 Report (Foundation Medicine, Heme)
69 Report (Foundation Medicine, Heme), cont.
70 FoundationOne (pan-cancer test)
71 Foundation Medicine
72 Diagnostic Settings: A new Era with NGS L. Godley, NEJM, 2012, 366(12),
73 Diagnostic Settings: A new Era with NGS L. Godley, NEJM, 2012, 366(12),
74 Diagnostic Settings: A new Era with NGS L. Godley, NEJM, 2012, 366(12),
75
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