Detecting clinically actionable somatic structural aberrations from targeted sequencing data
1
Detecting clinically actionable somatic structural aberrations from targeted sequencing data Ronak H. Shah 1 , Ahmet Zehir 1 , Raghu Chandramohan 1 , Talia Mitchell 3 , Wei Song 1 , Alifya Oultache 1 , Ryma Benayed 1 , Meera Hameed 1 , Khedoudja Nafa 1 , Donavan T. Cheng 1 , Maria E. Arcila 1 , Marc Ladanyi 1,2 , Michael F. Berger 1,2 1 Department of Pathology, 2 Human Oncology and Pathogenesis Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA, 3 The Jackson Laboratory, Farmington, CT 06032, USA Background Results Targeted Sequencing Results Conclusion Overview of the Framework Structural aberrations including deletions, insertions, inversions, tandem duplications, translocations, and more complex rearrangements constitute a frequent type of alteration in human tumors. Here, we sought to explore the potential to discover such events from targeted DNA sequence data in our CLIA-compliant molecular diagnostics laboratory. To detect somatic structural aberrations in individual tumors, we have developed an analytic framework in Perl & Python to detect these events in data generated by a hybridization capture-based, targeted sequencing clinical assay (MSK- IMPACT 1 ), which can reveal structural rearrangements as small as 500bp. Multiple Structural Variant (SV) calling algorithms such as DELLY 2 , PeSV-Fisher 3 , Meerkat 4 , GASV 5 , GASV-Pro 6 & Break-Dancer 7 were tested against a true positive data set generated using MSK-IMPACT, a custom capture-based test involving all coding exons and selected introns of 341 cancer associated genes, for assessment of sensitivity and specificity. MSK-IMPACT includes probes designed to capture 33 introns of 14 recurrently rearranged genes in solid tumors. Algorithms were chosen for their ability to call structural aberrations using a tumor-normal pair approach, where a tumor sample is processed with its matched normal to distinguish somatic structural alterations from germline variants as well as false positive events, such as systematic sequencing and mapping artifacts. We selected DELLY for our final pipeline, which utilizes paired-read & split-read support to nominate rearrangement breakpoints. Candidate structural aberrations were filtered, annotated using in-house tools, and manually reviewed using Integrated Genomics Viewer (IGV). Acknowledgements 1. Won HH, Scott SN, Brannon AR, Shah RH, Berger MF. Detecting somatic genetic alterations in tumor specimens by exon capture and massively parallel sequencing. J Vis Exp 2013:e50710. 2. Rausch T, Zichner T, Schlattl A, Stutz AM, Benes V, Korbel JO. DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics 2012; 28:i333-i9. 3. Escaramis G, Tornador C, Bassaganyas L, Rabionet R, Tubio JM, Martinez-Fundichely A, et al. PeSV-Fisher: identification of somatic and non-somatic structural variants using next generation sequencing data. PLoS One 2013; 8:e63377. 4. Yang L, Luquette LJ, Gehlenborg N, Xi R, Haseley PS, Hsieh CH, et al. Diverse mechanisms of somatic structural variations in human cancer genomes. Cell 2013; 153:919- 29. 5. Sindi S, Helman E, Bashir A, Raphael BJ. A geometric approach for classification and comparison of structural variants. Bioinformatics 2009; 25:i222-30. 6. Sindi SS, Onal S, Peng LC, Wu HT, Raphael BJ. An integrative probabilistic model for Introduction Methods Prepare 24-48 librarie s Probes for 341 cancer genes B B Sequence to 500-1000X (HiSeq 2500) Align to genome & analyze Hybridize & select (NimbleGen SeqCap: IMPACT Assay) 98% of targets at >50% of median 99% of targets at >20% of median References We have developed a framework capable of calling structural aberrations from capture- based targeted sequencing data with high sensitivity and specificity. Some of these structural aberrations represent important targets for personalized cancer therapies. Berger Lab & Diagnostic Molecular Pathology Laboratory Validation Gene Events Partners ALK 14 EML4 RET 4 KIF5B ROS 3 CD74,SLC34A2 FGFR3 2 TACC3 EWSR1 7 FLI1, WT1 EGFR vIII Deletion 14 In total we found 118 functional and non- functional structural aberrations out of 270 unique validation samples. Examples Tumor Normal Image 1: EML4-Alk fusion detected as inversion with 3% of reads supporting the fusion in patient having lung cancer. Image 2: RET-CCDC6 fusion detected as inversion with 10% of reads supporting the fusion in patient having thyroid cancer. Image 3: CD74-ROS1 fusion detected as translocation with 5% of reads supporting the in-frame fusion in patient having lung cancer. Tumor Normal Tumor Normal Image 4: EGFR vIII deletion detected 10% of reads supporting the deletion of exon 2 to exon 8 in- frame in patient having glioblastoma. Tumor Normal Clinical Gene Events Partners ALK 3 EML4 RET 10 CCD6, KIF5B ROS 9 CD74,SLC34A2 FGFR3 2 TACC3 EWSR1 9 FLI1, WT1 TMPRSS2 5 ERG EGFR vIII Deletion 6 In total we have found > 70 functional structural aberrations out of > 1300 clinical samples. Clinical Example • 58/F never smoker • Metastatic cancer involving liver, bone, brain: diagnosed 6/2013 • Treatment 7/2013-12/2013 • carboplatin/pemetrexed/bevacizumab x 4 cycles • pemetrexed/bevacizumab maintenance • Previous molecular testing negative for known drivers • Sequenom negative • Sizing assays for EGFR/ERBB2 negative • Tissue quality inadequate for FISH testing invers ion transloca tion SLC34A 2 ROS1 1 2 3 4 30 29 28 30 31 32 SLC34A2 ROS1 1 2 3 4 30 29 28 27 26 25 SLC34A2 ROS1 transloca tion chr 6 chr 4 ROS1 5’ probe 3’ probe ROS1 break apart Image 5: ROS1-SLC34A2 fusion detected as translocation and ROS1 inversion, with 3% of reads supporting the fusion in patient. Image 6: FISH Confirmation: ROS1 6q22 rearrangement in 54% of interphase cells analyzed 0 weeks 4 weeks Image 7: Minor radiographic response: decreased right lower lobe mass. Clinical Response: Improvement in bone pain and shortness of breath Crizoti nib initiat ed 02/2014 Table 1: Number of known events found in current validation datasets. Table 2: Number of known events found in current clinical datasets. Median Coverage for the target regions Median Normalized Coverage Fraction of Exons
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Structural aberrations including deletions, insertions, inversions, tandem duplications, translocations, and more complex rearrangements constitute a frequent type of alteration in human tumors. Here, we sought to explore the potential to discover such events from targeted DNA sequence data in our CLIA-compliant molecular diagnostics laboratory. To detect somatic structural aberrations in individual tumors, we have developed an analytic framework in Perl & Python to detect these events in data generated by a hybridization capture-based, targeted sequencing clinical assay (MSK-IMPACT), which can reveal structural rearrangements as small as 500bp.
Transcript of Detecting clinically actionable somatic structural aberrations from targeted sequencing data
Detecting clinically actionable somatic structural aberrations from targeted sequencing data
Ronak H. Shah1, Ahmet Zehir1, Raghu Chandramohan1, Talia Mitchell3, Wei Song1, Alifya Oultache1, Ryma Benayed1, Meera Hameed1, Khedoudja Nafa1, Donavan T. Cheng1, Maria E. Arcila1, Marc Ladanyi1,2, Michael F. Berger1,2
1Department of Pathology, 2Human Oncology and Pathogenesis Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA, 3The Jackson Laboratory, Farmington, CT 06032, USA
Background Results
Targeted Sequencing
Results
Conclusion
Overview of the Framework
Structural aberrations including deletions, insertions, inversions, tandem duplications, translocations, and more complex rearrangements constitute a frequent type of alteration in human tumors. Here, we sought to explore the potential to discover such events from targeted DNA sequence data in our CLIA-compliant molecular diagnostics laboratory. To detect somatic structural aberrations in individual tumors, we have developed an analytic framework in Perl & Python to detect these events in data generated by a hybridization capture-based, targeted sequencing clinical assay (MSK-IMPACT1), which can reveal structural rearrangements as small as 500bp.
Multiple Structural Variant (SV) calling algorithms such as DELLY2, PeSV-Fisher3, Meerkat4, GASV5, GASV-Pro6 & Break-Dancer7 were tested against a true positive data set generated using MSK-IMPACT, a custom capture-based test involving all coding exons and selected introns of 341 cancer associated genes, for assessment of sensitivity and specificity. MSK-IMPACT includes probes designed to capture 33 introns of 14 recurrently rearranged genes in solid tumors. Algorithms were chosen for their ability to call structural aberrations using a tumor-normal pair approach, where a tumor sample is processed with its matched normal to distinguish somatic structural alterations from germline variants as well as false positive events, such as systematic sequencing and mapping artifacts. We selected DELLY for our final pipeline, which utilizes paired-read & split-read support to nominate rearrangement breakpoints. Candidate structural aberrations were filtered, annotated using in-house tools, and manually reviewed using Integrated Genomics Viewer (IGV).
Acknowledgements
1. Won HH, Scott SN, Brannon AR, Shah RH, Berger MF. Detecting somatic genetic alterations in tumor specimens by exon capture and massively parallel sequencing. J Vis Exp 2013:e50710.2. Rausch T, Zichner T, Schlattl A, Stutz AM, Benes V, Korbel JO. DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics 2012; 28:i333-i9.3. Escaramis G, Tornador C, Bassaganyas L, Rabionet R, Tubio JM, Martinez-Fundichely A, et al. PeSV-Fisher: identification of somatic and non-somatic structural variants using next generation sequencing data. PLoS One 2013; 8:e63377.4. Yang L, Luquette LJ, Gehlenborg N, Xi R, Haseley PS, Hsieh CH, et al. Diverse mechanisms of somatic structural variations in human cancer genomes. Cell 2013; 153:919-29.5. Sindi S, Helman E, Bashir A, Raphael BJ. A geometric approach for classification and comparison of structural variants. Bioinformatics 2009; 25:i222-30.6. Sindi SS, Onal S, Peng LC, Wu HT, Raphael BJ. An integrative probabilistic model for identification of structural variation in sequencing data. Genome Biol 2012; 13:R22.7. Chen K, Wallis JW, McLellan MD, Larson DE, Kalicki JM, Pohl CS, et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods 2009; 6:677-81.
Introduction
Methods
Prepare 24-48 libraries
Probes for 341 cancer genes
B
B
Sequence to 500-1000X (HiSeq 2500)
Align to genome & analyze
Hybridize & select(NimbleGen SeqCap:
IMPACT Assay)
98% of targets at >50% of median99% of targets at >20% of median
References
We have developed a framework capable of calling structural aberrations from capture-based targeted sequencing data with high sensitivity and specificity. Some of these structural aberrations represent important targets for personalized cancer therapies.
Berger Lab & Diagnostic Molecular Pathology Laboratory
ValidationGene Events Partners
ALK 14 EML4
RET 4 KIF5B
ROS 3 CD74,SLC34A2
FGFR3 2 TACC3
EWSR1 7 FLI1, WT1
EGFR vIII Deletion 14
In total we found 118 functional and non-functional structural aberrations out of 270 unique validation samples.
Examples
Tumor
Normal
Image 1: EML4-Alk fusion detected as inversion with 3% of reads supporting the fusion in patient having lung cancer.
Image 2: RET-CCDC6 fusion detected as inversion with 10% of reads supporting the fusion in patient having thyroid cancer.
Image 3: CD74-ROS1 fusion detected as translocation with 5% of reads supporting the in-frame fusion in patient having lung cancer.
Tumor
Normal
Tumor
Normal
Image 4: EGFR vIII deletion detected 10% of reads supporting the deletion of exon 2 to exon 8 in-frame in patient having glioblastoma.
Tumor
Normal
ClinicalGene Events Partners
ALK 3 EML4RET 10 CCD6, KIF5BROS 9 CD74,SLC34A2
FGFR3 2 TACC3EWSR1 9 FLI1, WT1
TMPRSS2 5 ERGEGFR vIII Deletion 6
In total we have found > 70 functional structural aberrations out of > 1300 clinical samples.Clinical Example• 58/F never smoker• Metastatic cancer involving liver, bone, brain: diagnosed 6/2013• Treatment 7/2013-12/2013
• carboplatin/pemetrexed/bevacizumab x 4 cycles• pemetrexed/bevacizumab maintenance
• Previous molecular testing negative for known drivers• Sequenom negative• Sizing assays for EGFR/ERBB2 negative• Tissue quality inadequate for FISH testing
inversion
translocation
SLC34A2ROS1
1 2 3 4
30 29 28
30 31 32SLC34A2 ROS1
1 2 3 4
30 29 28 27 26 25
SLC34A2 ROS1
translocation
chr 6 chr 4
ROS1 5’ probe 3’ probe ROS1 break apart
Image 5: ROS1-SLC34A2 fusion detected as translocation and ROS1 inversion, with 3% of reads supporting the fusion in patient.
Image 6: FISH Confirmation: ROS1 6q22 rearrangement in 54% of interphase cells analyzed
0 weeks
4 weeks
Image 7: Minor radiographic response: decreased right lower lobe mass. Clinical Response: Improvement in bone pain and shortness of breath
Crizotinib initiated 02/2014
Table 1: Number of known events found in current validation datasets.Table 2: Number of known events found in current clinical datasets.
Median Coverage for the target regions
Median Normalized Coverage
Frac
tion
of E
xons
