INDIVIDUALIZED MEDICINE
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1 CENTER FOR INDIVIDUALIZED MEDICINE George Vasmatzis, Ph.D., Director Biomarker Discovery Program Detecting Structural Variants from NGS Data: Methods Overview 2012 MFMER slide-1
2 Software Methods and Algorithms Johnson, Sarah H. Smadbeck, Jamie Drucker, Travis M. Zenka, Roman M. Gaitatzes, Athanasios Vasmatzis, George Cytogenetics Smoley, Stephanie A. Marcou, Cherisse A., Ph.D. Jenkins, Robert B., M.D., Ph.D.; Sukov, William R., M.D.; Hoppman, Nicole L., Ph.D. Thorland, Erik C., Ph.D.; Kearney, Hutton M., Ph.D. Aypar, Umut, Ph.D. Technologies Molecular Biology Protocols Murphy, Stephen J., Ph.D. Bruce Eckloff Harris, Faye R. Halling Geoffrey C. Pathology Cheville, John C., M.D." Terra, Simone B., M.D." Janaki, Nafiseh, M.D. Molecular Biology Functional Kovtun, Irina V., Ph.D. Kosari, Farhad, Ph.D. Yang, Lin, Ph.D MFMER slide-2
3 Overview Introduction to mate pair sequencing (MPseq) Comprehensive analysis for genomic rearrangements in cancer. Can we use them to inform practice? BCR-ABL and EML4-ALK Why Sequencing vs. Hybridization Almost nucleotide resolution to find junctions Need enough coverage to overcome noise Mate pair is a trick to increase coverage using paired sequences that are far apart. Genome Plot Algorithms to detect structural variants from NGS data MPseq Applications Summary 2012 MFMER slide-3
4 MPseq ($700) Integrated Analysis Junctions CNVs Arrays CNVs cnloh Mutations cnloh Differential Expression Fusions RNAseq ($500) Exome ($1500) 2012 MFMER slide-4
5 Science Oct 28;310(5748): Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Tomlins SA1, Rhodes DR, Perner S, Dhanasekaran SM, Mehra R, Sun XW, Varambally S, Cao X, Tchinda J, Kuefer R, Lee C, Montie JE, Shah RB, Pienta KJ, Rubin MA, Chinnaiyan AM. Recurrent chromosomal rearrangements have not been well characterized in common carcinomas. We used a bioinformatics approach to discover candidate oncogenic chromosomal aberrations on the basis of outlier gene expression. Two ETS transcription factors, ERG and ETV1, were identified as outliers in prostate cancer. We identified recurrent gene fusions of the 5' untranslated region of TMPRSS2 to ERG or ETV1 in prostate cancer tissues with outlier expression. By using fluorescence in situ hybridization, we demonstrated that 23 of 29 prostate cancer samples harbor rearrangements in ERG or ETV1. Cell line experiments suggest that the androgen-responsive promoter elements of TMPRSS2 mediate the overexpression of ETS family members in prostate cancer. These results have implications in the development of carcinomas and the molecular diagnosis and treatment of prostate cancer. ERG Chromosome 21 TMPRSS2 ERG TMPRSS MFMER slide-5
6 2012 MFMER slide-6
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8 2012 MFMER slide-8
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11 chromosome base pairs 2012 MFMER slide-11
12 DB_T_MP WSZ = 3e+05 FOLDER LU UHMK1 DDR2 OBSCN GUK1 RYR2 ALK EIF2AK2 MAP4K3 PKDCC PRKCE AAK1 TGFA EPHA PIGU SRC ZMYND8ZNF217 NCOA3 PTPN1 ZNF ESR TJP2 NTRK2 ROR2 C5 ABL1CACNA1B RXRA X Y MFMER slide-12
13 Chr4 Chr MFMER slide-13
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15 2012 MFMER slide-15
16 NextGen Sequencing by Illumina technology 2.4b for 8 lanes-> 300,000,000/lane For fragment length X lengths for TCL FFPEs that should amount to about 60X/lane. $ MFMER slide-16
17 Overall Process Library Protocol NGS sequencing Mapping to genome Structural Variant (SV) analysis DNA Illumina.config SVs R code no Pass QC Consult MGF yes.fastq reference genome C code BIMA reference genome info chr#.sva SV analysis CNVs Reports, figures, tables.config Metrics BMD Pipeline
18 SVA Bioinformatics Pipeline Binary Index Mapping Algorithm (BIMA V3) Developed in house Strength: Speed and Accuracy Power: Filters / Masks Sequenced ~1300 genomes by Mate Pair Sequenced >30 normal samples Germ line events vary per genome Low numbers of germ line events pass filters (Ave <1) Increasing mask as sequence/validate more events Detects Mutations Potentially Actionable Copy Number Variation 2012 MFMER slide-18
19 Accuracy Comparison of BIMA with others Accuracy CPU Time BIMA3 BWA BWA-MEM Novoalign_V2 Novoalign _V MFMER slide-19
20 Mate Pair Sequencing Quality Samples Per Lane of HiSeq kb Fragments 120,000,000 Bridged Coverage ,000,000 80,000,000 60,000,000 40,000,000 replication (%) fragments not mapped (%) bridged coverage (X) 20 20,000,000 fragments total MFMER slide-20
21 Junction Detection Algorithm 2012 MFMER slide-21
22 False Positive Chr6 Chromosome 1 translocations False Negatives (5.3% uncalled bases) chr7 True Positive chr9 Allele Coverage and clusters (SVs) False Positives Allele Coverage Clusters-all Clusters-filtered True Positives
23 Inversion involving TP63 and B3GALNT1 Chromosome 3 161Mb 189Mb B3GALNT1 P B3GALNT1 TP63 P TP63 B3GALNT1 Beta-1,3-Galactosyltransferase Gene Family Catalyze transfer of sugar moieties Not implicated in Cancer Fusion Junction B3GALNT1/TP63 Fusion Gene TP63 gene driven by B3GALNT1 Promoter Aubry et al Modern Pathology
24 PCR validation PCR Primers: Chr3 Locus 1 Chr3 Locus 2 1. Map Reads to Hu Ref. Genome Lung Tissue Validation: Con an AD1 AD2 1. PCR Primers: spanning breakpoint. Control DNA Adjacent Normal Synchronous Lung Tumors 2. PCR / Agarose Gel 1. Excise DNA bands and Sanger seq. Breakpoint confirmed by Sanger Sequencing B3GALNT1 TP63 2. Validate in patient germ line DNA Germ Line Evaluation: Con B AD1
25 dy CNV Algorithm COUNTS PER WINDOW dx 1020 OC049 WSZ = 6e+05 gender= MFMER slide-25
26 2012 MFMER slide-26
27 2012 MFMER slide-27
28 CNV Detection in MPSeq Or we can color different frequency levels darker or lighter according to deviation from 2N And we can see the results reflected in the read count histogram 2012 MFMER slide-28
29 Cross-Analysis MPseq and ExomeSeq Each green triangle corresponds to a Biallelic -> Monoallelic variant Variants in Exome match with losses in MPSeq Possible LOH area 2012 MFMER slide-29
30 DB_T_MP WSZ = 3e+05 FOLDER LU UHMK1 DDR2 OBSCN GUK1 RYR2 2 ALK EIF2AK2 MAP4K3 PKDCC PRKCE AAK1 TGFA EPHA PIGU SRC ZMYND8ZNF217 NCOA3 PTPN1 ZNF ESR TJP2 NTRK2 ROR2 C5 ABL1CACNA1B RXRA X Y MFMER slide-30
31 DB_T_MP WSZ = 3e+05 FOLDER LU X Y MFMER slide-31
32 2012 MFMER slide-32
33 Sequence Counts for each Exon Sequence Counts for each Exon Inflammatory Myofibroblastic Tumor Fusion validation ALK ALK S1 S2 S5 Sarc Exon Number Exon Number Mansfield, Murphy et al: under review 2012 MFMER slide-33
34 2012 MFMER slide-34
35 Number of mate pairs Number of mate pairs CHROM 21 ( 21q22.2a ), CASE= PR11a_G3_G ERG, 4 _ - - 5KB TMPRSS2 5 4 TMPRSS2, 23 2 _ CHROM 21 ( 21q22.3a ), CASE= PR11a_G3_G7 _ CHROM 21 ( 21q22.2a ), CASE= PR11b_G4_G ERG, 4 _ - _ 5KB TMPRSS2 5 4 TMPRSS2 3, CHROM 21 ( 21q22.3a ), CASE= PR11b_G4_G MFMER slide-35
36 CHROM 21 PR3 PR4 PR5 PR8 PR15 PR46 PR2 PR9 PR14 PR17 PR16 PR18 PR19 PR20 PR29 PR42 PR47 PR53 PR39_G3_LV PR40_G3_LV R36_G3_LV R37_G3_LV PR41_G3_LV PR44_G3_LV PR45_G3_LV PR48_G3_LV PR49_G3_LV PR51_G3_LV PR54_G3_LV R38_G3_LV PR43_G3_LV PR6a PR6b PR1_aN PR10a PR10b PR12a PR12b PR22a PR22b PR25a PR25b PR27a PR27b LNCAP PC3 PR30a PR30b PR32a_G3 PR32b_G4 PR34a_G3 PR34b_G4 PR35_aN PR35b_G4 PR35_PIN PR43_PIN PR7a PR7b PR11a PR11b PR21a PR21b PR13a PR13b PR23a PR23b PR24a PR24b PR26a PR26b PR28a PR28b VCAP PR31a PR31b PR33a_G3 PR33b_G4 PR35a_G3 PR43_aN DSCR10 KCNJ15 KCNJ15 KCNJ15 ERG ERG ERG ERG ERG ERG ERG PR3 PR4 PR5 PR8 PR15 PR46 PR2 PR9 PR14 PR17 PR16 PR18 PR19 PR20 PR29 PR42 PR47 PR53 PR39_G3_LV PR40_G3_LV PR36_G3_LV PR37_G3_LV PR41_G3_LV PR44_G3_LV PR45_G3_LV PR48_G3_LV PR49_G3_LV PR51_G3_LV PR54_G3_LV PR38_G3_LV PR43_G3_LV PR6a PR6b PR1_aN PR10a PR10b PR12a PR12b PR22a PR22b PR25a PR25b PR27a PR27b LNCAP PC3 PR30a PR30b PR32a_G3 PR32b_G4 PR34a_G3 PR34b_G4 PR35_aN PR35b_G4 PR35_PIN PR43_PIN PR7a PR7b PR11a PR11b PR21a PR21b PR13a PR13b PR23a PR23b PR24a PR24b PR26a PR26b PR28a PR28b VCAP PR31a PR31b PR33a_G3 PR33b_G4 PR35a_G3 PR43_aN MFMER slide-36
37 PR25A PR25B PR10a PR10b PR13A PR13B PR7a PR7b PR11a PR11b PR21a PR21b PR24A PR24B PR6a PR6b Height PR23A PR23B PR26A PR26B PR22a PR22b PR28A PR28B PR27B PR27A PR12a PR12b Number of mate pairs Number of mate pairs A. B. CHROM 21 ( 21q22.2a ), CASE= PR11a_G3_G ERG, 4 _ - - 5KB TMPRSS2 5 4 TMPRSS2, 23 2 C. D CHROM 21 ( 21q22.3a ), CASE= PR11a_G3_G7 CHROM 21 ( 21q22.2a ), CASE= PR11b_G4_G C C ERG, 4 _ - _ 5KB TMPRSS2 5 4 TMPRSS2 3, 3 2 G4 G3 shared CHROM 21 ( 21q22.3a ), CASE= PR11b_G4_G7 Scenarios of prostate cancer initiation and progression PR10 PR25 PR13 PR7 PR6 PR24 PR26 PR21 PR11 PR23 PR22 PR12 PR28 PR27 Cluster Dendrogram A GP4 B GP 4 C GP4 GP3 GP3 GP3 N N N GP3 Kovtun IV,et.al..Cancer Res Jun 1;73(11): MFMER slide-37
38 Number of Genomic Breakpoints LU21_AD LU21_BAC LU16_AD LU16_BAC LU15_AD LU15_BAC LU14_AD LU14_BAC LU11_AD LU11_BAC LU18_AD LU18_BAC LU7_AD LU7_BAC LU4_AD LU4_BAC LU6_AD LU6_BAC Height LU20_ADA LU20_ADB LU20_BAC LU8_AD LU8_BAC LU3_AD LU3_BAC LU12_BAC LU5_AD LU5_BAC LU19_AD LU12_AD Number of rearrangements PreLCM PostLCM Unique T1 Unique T2 IS component INV component Shared T1 T2 an gc 1p36.12a to 16q21c Extensive Breakpoint Overlap IN V IS INV alone IS alone INV & IS Shared IN V IS Minimal Breakpoint Overlap PCR Validation: Chr1 Cluster Dendrogram Chr2 Increasing Evidence of Lineage Murphy SJ, et.al. Cancer Res Jun 1;74(11): Center for as.dist(ddgn) INDIVIDUALIZED MEDICINE hclust (*, "complete") 2012 MFMER slide-38
39 Clinical Dilemma Patient presents with Multiple Lung Nodules: ML1 ML3 ML2 How can we tell if independent primary tumors vs metastatic disease? How do we best treat patients with multifocal lung adenocarcinoma? 2012 MFMER slide-39
40 Clinical Significance: Patient presents with multiple lung tumors: How do you treat? RELATED NOT RELATED METASTASIS Advanced Stage Stage IIb, III/IV INDEPENDENT PRIMARIES Stage I/II Adjuvant Tx ±SURGERY Are the Tumors Related? Clinical/Histologic prediction: Genomic prediction: SURGERY ±Adjuvant Tx Informative but not definitive Definitive MFMER slide-40
41 Signature Table SQ3 AD SQ1 SQ2 an AD SQ3 SQ SQ1 Gene 1 Gene 2 Chr 1 Chr 2 mpos1 mpos2 pos 1 pos 2 Locus1 Locus2 10 COL11A1 C11orf ,364,041 66,577,020 1p21.1d 11q13.2a 23 TRIM33 SUCLG ,947,668 67,630,358 1p13.2b 3p14.1b 55 DENND2C DENND2C ,154, ,194,655 1p13.2a 1p13.2a 232 SUCLG2 SUCLG ,514,776 67,564,484 3p14.1b 3p14.1b 8 ROBO1 ZBTB ,061, ,770,443 3p12.3a 3q13.31a 12 TRPM3 TRPM ,190,765 73,512,758 9q21.12a 9q21.12a 12 GRIN3A GRIN3A ,461, ,492,391 9q31.1b 9q31.1b 7 KIAA1958 SUCLG ,393,084 67,630,302 9q32a 3p14.1b 12 ZMIZ1 GAGE10 10 X ,907,165 49,174,579 10q22.3e Xp11.23b 8 CDH22 CDH ,807,178 44,845,921 20q13.12b 20q13.12b 12 LRP1B LRP1B ,019, ,053,596 2q22.1d 2q22.1d 22 C6orf170 MRC1L ,457,292 17,922,180 6q22.31b 10p12.33b 29 SLC35F3 SRGAP ,421, ,612,357 1q42.2c 1q32.1h 10 EBNA1BP2 CACNA1C ,630,010 2,648,203 1p34.2a 12p LYST SLC35F ,934, ,430,917 1q42.3c 1q42.2c 12 FAM110B FAM110B ,930,939 58,965,849 8q12.1c 8q12.1c 19 ADAM5P ADAM5P ,189,078 39,222,660 8p11.22a 8p11.22a 16 CACNA1C CACNA1C ,431,563 2,467,263 12p p PTPRT PTPRT ,703,405 40,748,507 20q12d 20q12d 25 SLC23A2 PRNP ,859,265 4,675,219 20p13 20p13 25 PRNP SLC23A ,674,363 4,860,016 20p13 20p13 65 BRE BRE ,193,006 28,311,842 2p23.2b 2p23.2b 36 RBKS SPDYA ,044,723 29,063,334 2p23.2b 2p23.2a 14 PLB1 GPR ,730,704 26,566,681 2p23.2b 2p23.3b 44 BIRC6 BIRC ,647,787 32,826,595 2p22.3e 2p22.3e 7 GPR113 LOC ,565,370 39,189,131 2p23.3b 2p22.1c 34 LOC BRE ,158,232 28,440,615 2p22.1c 2p23.2b 10 MTA3 BRE ,830,325 28,425,327 2p21e 2p23.2b 37 FOXP1 MYL ,094,315 35,177,418 3p13c 20q11.23a 17 MYL9 FOXP ,177,418 71,094,315 20q11.23a 3p13c 2012 MFMER slide-41
42 Number of Breakpoints Unique Tumor 1 Unique Tumor 2 Shared 2012 MFMER slide-42
43 LU121 LU30 LU124 LU47 LU128 LU40 LU109 LU29SQ1/S LU123 LU39AD/BrM LU130 LU38AD/BrM LU110AD/BrM LU108AD2/ LU27 LU33 AD1/2 LU43 LU108AD LU120 LU32 LU31 LU125 LU111 LU133AD/ LU26 LU129 LU48 LU134 LU46AD/SQ LU49 LU127 LU135 LU123a-c LU122a-b LU29AD/S LU28 LU29AD/S LU124b-c Number of Breakpoints Number of Breakpoints Number of Breakpoints Discrepant Cases: * * * * * = Indeterminate Cases: Pathologies disagree * * = Both Pathologists; Metasstases Both Pathologists: Metastases Both Pathologists: Independent Primaries 350 Unique Tumor Unique Tumor 1 Shared Unique Tumor 2 Unique Tumor 1 Shared MFMER slide-43
44 Liquid biopsy Early-Detection Monitoring Prognosis Screening Watchful-Waiting Recurrence Targeted/chemo-therapy Binary Quantitative (volume) Binary Relative 2012 MFMER slide-46
45 Liquid biopsy monitoring pipeline PCR Primers: Chr4 Chr13 * Case Control 2012 MFMER slide-47
46 OC49 A. PCR Breakpoint validation qpcr result Pre-surg plasma qpcr result:pre-surg serum/ Post-surg plasma Break-point Name Breakpoint 1 1q22 1q22 Control genomic DNA Tumor DNA Blood DNA Genes Affected SLC2A1-AS1 No_gene Tumor DNA diluted 10^3 Tumor DNA diluted 10^4 Tumor DNA diluted 10^5 OC49 pre surg cfplasma Control genomic DNA Control cfplasma Water Tumor DNA diluted 10^3 Tumor DNA diluted 10^4 Tumor DNA diluted 10^5 Tumor DNA diluted 10^6 OC49 post surg cfplasma OC49 pre surg cfserum NC cfplasma NC cfserum Control genomic DNA Water Product Size (bp) 55 Breakpoint 2 1p34.2-1p34.2 SSR2 DAP3 79 Housekeeping GAPDH NA-loading control Beta Actin MFMER slide-48
47 Results presurg ng/ul total cfdna Beta Actin CA125 E1 E2 E3 E4 OC68 presurg OC68 postsurg OC58 presurg OC58 postsurg OC84 presurg OC84 postsurg OC49 presurg (S_P) 0.68_ _ _16 19_18 OC49 postsurg OC67 presurg (S_P) /28/ _22 ND_15 OC67 postsurg / OC63 presurg OC63 postsurg OC24 presurg OC24 postsurg OC101 presurg (S_P) 1.37_ _ _3 12_2 OC101 postsurg MFMER slide-49
48 c(0, 0) (2*j T )/(b tot - d*j T ) UNNORMALIZED OC84 presurg fb tot fj T fj T c(0, e1l) NEED CORRECTION DUE EFFICIENCY ERRORS (2*j T )/(b tot - d*j T ) 2012 MFMER slide-50
49 2012 MFMER slide-51
50 2012 MFMER slide-52
51 Clinical Advances as a Consequence of MPseq NGS for Test Development Constitutional genetics testing HemOnc (AML, etc) MPseq for solid tumors (lung, sarcoma, prostate, ovarian, etc) Junctions (PCR validation), Fusion genes, Rearrangements, CNVs, cnloh 2012 MFMER slide-53
52 Scientific Advances as a Consequence of MPseq NGS for future Test Development Identification of targetable genomic changes in cancer. Monitoring for cancer recurrence Genomic relationship of independent primary cancers compared to primary-metastasis Low level cnloh detection 2012 MFMER slide-54
53 Other Scientific Applications Genomic characterization of Mouse Avatars Genomic Characterization of cell lines Lineage relationships and cancer progression Identification of viral integration cites Genomic changes indicative of indolent and aggressive cancer Prostate cancer TCL 2012 MFMER slide-55
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