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DESIGN AND ANALYSIS ISSUES IN GENOME-WIDE SOMATIC MUTATION STUDIES OF CANCER

• Giovanni Parmigiani, The Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University & Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
• Simina Boca, Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics
• Jimmy Lin, The Johns Hopkins University, School of Medicine
• Kenneth W. Kinzler, The Johns Hopkins University, School of Medicine, Oncology Center
• Victor E. Velculescu, The Johns Hopkins University, School of Medicine, Oncology Center
• Bert Vogelstein, The Johns Hopkins University, School of Medicine, Oncology Center

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Article comments:

preprint submitted to Elsevier

Abstract:

The availability of the human genome sequence and progress in sequencing and bioinformatic technologies have enabled genome-wide investigation of somatic mu- tations in human cancers. This article briefly reviews challenges arising in the statistical analysis of mutational data of this kind. A first challenge is that of designing studies that efficiently allocate sequencing resources. We show that this can be addressed by two-stage designs, and demonstrate via simulations that even relatively small studies can produce lists of candidate cancer genes that are highly informative for future research efforts. A second challenge is to distinguish mutated genes that are selected for by cancer (drivers) from mutated genes that have no role in the development of cancer and simply happened to mutate (passengers). We suggest that this question is best approached as a classification problem and discuss some of the difficulties of more traditional testing-based approaches. A third challenge is to identify biologic processes affected by the driver genes. This can be achieved by gene set analyses. These can reliably identify functional groups and pathways that are enriched for mutated genes even when the individual genes involved in those pathways or sets are not mutated at sufficient frequencies to provide conclusive evidence as drivers.

Subject Area:

Computational Biology/Bioinformatics

Suggested Citation:

Giovanni Parmigiani, Simina Boca, Jimmy Lin, Kenneth W. Kinzler, Victor E. Velculescu, and Bert Vogelstein, "DESIGN AND ANALYSIS ISSUES IN GENOME-WIDE SOMATIC MUTATION STUDIES OF CANCER" (January 2008). Johns Hopkins University, Dept. of Biostatistics Working Papers. Working Paper 161.
http://www.bepress.com/jhubiostat/paper161