Detection of somatic copy number alterations in cancer using targeted exome capture sequencing.
Journal: 2012/April - Neoplasia
ISSN: 1476-5586
PUBMED: 22131877
Abstract:
The research community at large is expending considerable resources to sequence the coding region of the genomes of tumors and other human diseases using targeted exome capture (i.e., "whole exome sequencing"). The primary goal of targeted exome sequencing is to identify nonsynonymous mutations that potentially have functional consequences. Here, we demonstrate that whole-exome sequencing data can also be analyzed for comprehensively monitoring somatic copy number alterations (CNAs) by benchmarking the technique against conventional array CGH. A series of 17 matched tumor and normal tissues from patients with metastatic castrate-resistant prostate cancer was used for this assessment. We show that targeted exome sequencing reliably identifies CNAs that are common in advanced prostate cancer, such as androgen receptor (AR) gain and PTEN loss. Taken together, these data suggest that targeted exome sequencing data can be effectively leveraged for the detection of somatic CNAs in cancer.
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Neoplasia 13(11): 1019-1025

Detection of Somatic Copy Number Alterations in Cancer Using Targeted Exome Capture Sequencing<sup><a href="#FN1" rid="FN1" class=" fn">1</a>,</sup><sup><a href="#FN2" rid="FN2" class=" fn">2</a></sup>

Supplementary Figures and Tables:
Click here to view.(4.7M, pdf)
Michigan Center for Translational Pathology, University of Michigan Medical School, Ann Arbor, MI, USA
Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, MI, USA
Department of Pathology, University of Michigan Medical School, Ann Arbor, MI, USA
Howard Hughes Medical Institute, University of Michigan Medical School, Ann Arbor, MI, USA
Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA
Department of Urology, University of Michigan Medical School, Ann Arbor, MI, USA
Address all correspondence to: Arul M. Chinnaiyan, MD, PhD, Comprehensive Cancer Center, University of Michigan Medical School, 1400 E Medical Center Dr, 5316 CCGC, Ann Arbor, MI 48109-0602. E-mail: ude.hcimu@lura
Dr Chinnaiyan is an investigator for Howard Hughes Medical Institute, an American Cancer Society professor, an S. P. Hicks Endowed Professor of Pathology, and a professor of pathology and urology.
Address all correspondence to: Arul M. Chinnaiyan, MD, PhD, Comprehensive Cancer Center, University of Michigan Medical School, 1400 E Medical Center Dr, 5316 CCGC, Ann Arbor, MI 48109-0602. E-mail: ude.hcimu@lura
Received 2011 Sep 2; Revised 2011 Sep 2; Accepted 2011 Sep 28.

Abstract

The research community at large is expending considerable resources to sequence the coding region of the genomes of tumors and other human diseases using targeted exome capture (i.e., “whole exome sequencing”). The primary goal of targeted exome sequencing is to identify nonsynonymous mutations that potentially have functional consequences. Here, we demonstrate that whole-exome sequencing data can also be analyzed for comprehensively monitoring somatic copy number alterations (CNAs) by benchmarking the technique against conventional array CGH. A series of 17 matched tumor and normal tissues from patients with metastatic castrate-resistant prostate cancer was used for this assessment. We show that targeted exome sequencing reliably identifies CNAs that are common in advanced prostate cancer, such as androgen receptor (AR) gain and PTEN loss. Taken together, these data suggest that targeted exome sequencing data can be effectively leveraged for the detection of somatic CNAs in cancer.

Abstract

Acknowledgments

The authors thank Javed Siddiqui and Rohit Mehra for assisting with sample acquisition, Terrence Barrette for assisting with sequence data generation using the Illumina pipeline, and Jyoti Athanikar for assistance with manuscript preparation.

Acknowledgments

Footnotes

This work was supported in part by the National Institutes of Health (NIH) Specialized Program of Research Excellence (P50 CA69568) and the Early Detection Research Network (U01 {"type":"entrez-nucleotide","attrs":{"text":"CA111275","term_id":"34964582","term_text":"CA111275"}}CA111275). A.M.C. is supported by the Howard Hughes Medical Institute, the Prostate Cancer Foundation, the Taubman Research Institute, the Doris Duke Foundation, and the American Cancer Society as a clinical research professor. K.J.P. is supported by the Prostate Cancer Foundation, the Taubman Research Institute, and the American Cancer Society as a clinical research professor (NIH 1 PO1 {"type":"entrez-nucleotide","attrs":{"text":"CA093900","term_id":"34947207","term_text":"CA093900"}}CA093900 and 1 U01CA143055).

This article refers to supplementary materials, which are designated by Figures W1 to W3 and Tables W1 to W4 and are available online at www.neoplasia.com.

Footnotes

References

  • 1. Pinkel D, Seagraves R, Sudar D, Clark S, Poole I, Kowbel D, Collins C, Kuo WL, Chen C, Zhai Y, et al High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat Genet. 1998;20:207–211.[PubMed][Google Scholar]
  • 2. Sebat J, Lakshmi B, Troge J, Alexander J, Young J, Lundin P, Månér S, Massa H, Walker M, Chi M, et al Large-scale copy number polymorphism in the human genome. Science. 2004;305:525–528.[PubMed][Google Scholar]
  • 3. Sharp AJ, Locke DP, McGrath SD, Cheng Z, Bailey JA, Vallente RU, Pertz LM, Clark RA, Schwartz S, Seagraves R, et al Segmental duplications and copy-number variation in the human genome. Am J Hum Genet. 2005;77:78–88.[Google Scholar]
  • 4. Carter NPMethods and strategies for analyzing copy number variation using DNA microarrays. Nat Genet. 2007;39:S16–S21.[Google Scholar]
  • 5. McCarroll SA, Kuruvilla FG, Korn JM, Cawley S, Nemesh J, Wysoker A, Shapero MH, deBakker PI, Maller JB, Kirby A, et al Integrated detection and population-genetic analysis of SNPs and copy number variation. Nat Genet. 2008;40:1166–1174.[PubMed][Google Scholar]
  • 6. Cooper GM, Zerr T, Kidd JM, Eichler EE, Nickerson DASystematic assessment of copy number variant detection via genome-wide SNP genotyping. Nat Genet. 2008;40:1199–1203.[Google Scholar]
  • 7. Conrad DF, Andrews TD, Carter NP, Hurles ME, Pritchard JKA high-resolution survey of deletion polymorphism in the human genome. Nat Genet. 2006;38:75–81.[PubMed][Google Scholar]
  • 8. Hinds DA, Kloek AP, Jen M, Chen X, Frazer KACommon deletions and SNPs are in linkage disequilibrium in the human genome. Nat Genet. 2006;38:82–85.[PubMed][Google Scholar]
  • 9. McCarroll SA, Hadnott TN, Perry GH, Sabeti PC, Zody MC, Barrett JC, Dallaire S, Gabriel SB, Lee C, Daly MJ, et al Common deletion polymorphisms in the human genome. Nat Genet. 2006;38:86–92.[PubMed][Google Scholar]
  • 10. Campbell PJ, Stephens PJ, Pleasance ED, O'Meara S, Li H, Santarius T, Stebbings LA, Leroy C, Edkins S, Hardy C, et al Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing. Nat Genet. 2008;40:722–729.[Google Scholar]
  • 11. Chiang DY, Getz G, Jaffe DB, O'Kelly MJ, Zhao X, Carter SL, Russ C, Nusbaum C, Meyerson M, Landers ESHigh-resolution mapping of copy-number alterations with massively parallel sequencing. Nat Methods. 2009;6:99–103.[Google Scholar]
  • 12. Nord AS, Lee M, King MC, Walsh TAccurate and exact CNV identification from targeted high-throughput sequence data. BMC Genomics. 2011;12:184.[Google Scholar]
  • 13. Magi A, Benelli M, Yoon S, Roviello F, Torricelli FDetecting common copy number variants in high-throughput sequencing data by using JointSLM algorithm. Nucleic Acids Res. 2011;39:e65.[Google Scholar]
  • 14. Kim TM, Luquette LJ, Xi R, Park PJrSW-seq: algorithm for detection of copy number alterations in deep sequencing data. BMC Bioinformatics. 2010;11:432.[Google Scholar]
  • 15. Medvedev P, Fiume M, Dzamba M, Smith T, Brudno MDetecting copy number variation with mated short reads. Genome Res. 2010;20:1613–1622.[Google Scholar]
  • 16. Boeva V, Zinovyev A, Bleakley K, Vert JP, Janoueix-Lerosey I, Delattre O, Barillot EControl-free calling of copy number alterations in deep-sequencing data using GC-content normalization. Bioinformatics. 2011;27:268–269.[Google Scholar]
  • 17. Alkan C, Kidd JM, Marques-Bonet T, Aksay G, Antonacci F, Hormozdiari F, Kitzman JO, Baker C, Malig M, Mutlu O, et al Personalized copy number and segmental duplication maps using next-generation sequencing. Nat Genet. 2009;41:1061–1067.[Google Scholar]
  • 18. Yan XJ, Xu J, Gu ZH, Pan CM, Lu G, Shen Y, Shi JY, Zhu YM, Tang L, Zhang XW, et al Exome sequencing identifies somatic mutations of DNA methyltransferase gene DNMT3A in acute monocytic leukemia. Nat Genet. 2011;43:309–315.[PubMed][Google Scholar]
  • 19. Varela I, Tarpey P, Raine K, Huang D, Ong CK, Stephens P, Davies H, Jones D, Lin ML, Teague J, et al Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma. Nature. 2011;469:539–542.[Google Scholar]
  • 20. Harbour JW, Onken MD, Roberson ED, Duan S, Cao L, Worley LA, Council ML, Matatall KA, Helms C, Bowcock AMFrequent mutation of BAP1 in metastasizing uveal melanomas. Science. 2010;330:1410–1413.[Google Scholar]
  • 21. Jones S, Wang TL, Shihle M, Mao TL, Nakayama K, Roden R, Glas R, Slamon D, Diaz LA, Jr, Vogelstein B, et al Frequent mutations of chromatin remodeling gene ARID1A in ovarian clear cell carcinoma. Science. 2010;330:228–231.[Google Scholar]
  • 22. The Cancer Genome Atlas Research Network, authorIntegrated genomic analyses of ovarian carcinoma. Nature. 2011;474:609–615.[Google Scholar]
  • 23. Chang H, Jackson DG, Kayne PS, Ross-Macdonald PB, Byseck R, Siemers NOExome sequencing reveals comprehensive genomic alterations across eight cancer cell lines. PLoS One. 2011;6:e21097.[Google Scholar]
  • 24. Taylor BS, Schultz N, Hieronymus H, Gopalan A, Xiao Y, Carver BS, Arora VK, Kaushik P, Cerami E, Reva B, et al Integrative genomic profiling of human prostate cancer. Cancer Cell. 2010;18:11–22.[Google Scholar]
  • 25. Rubin MA, Putzi M, Mucci N, Smith DC, Wojno K, Korenchuk S, Pienta KJRapid (“warm”) autopsy study for procurement of metastatic prostate cancer. Clin Cancer Res. 2000;6:1038–1045.[PubMed][Google Scholar]
  • 26. Langmead B, Trapnell C, Pop M, Salzberg SLUltrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10:R25.[Google Scholar]
  • 27. Olshen AB, Venkatraman ES, Lucito R, Wigler MCircular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics. 2004;5:557–572.[PubMed][Google Scholar]
  • 28. Liu W, Laitinen S, Khan S, Vihinen M, Kowalski J, Yu G, Chen L, Ewing CM, Eisenberg MA, Carducci MA, et al Copy number analysis indicates monoclonal origin of lethal metastatic prostate cancer. Nat Med. 2009;15:559–565.[Google Scholar]
  • 29. Holcomb IN, Young JM, Coleman IM, Salari K, Grove DI, Hsu L, True LD, Roudier MP, Morrissey CM, Higano CS, et al Comparative analyses of chromosome alterations in soft-tissue metastases within and across patients with castration-resistant prostate cancer. Cancer Res. 2009;69:7793–7802.[Google Scholar]
  • 30. Demichelis F, Setlur SR, Beroukhim R, Perner S, Korbel JO, Lafargue CJ, Pflueger D, Pina C, Hofer MD, Sboner A, et al Distinct genomic aberrations associated with ERG rearranged prostate cancer. Genes Chromosomes Cancer. 2009;48:366–380.[Google Scholar]
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