Cancer systems biology of TCGA SKCM: Efficient detection of genomic drivers in melanoma

Jian Guan, Rohit Gupta, Fabian V. Filipp

Research output: Contribution to journalArticlepeer-review

64 Scopus citations

Abstract

We characterized the mutational landscape of human skin cutaneous melanoma (SKCM) using data obtained from The Cancer Genome Atlas (TCGA) project. We analyzed next-generation sequencing data of somatic copy number alterations and somatic mutations in 303 metastatic melanomas. We were able to confirm preeminent drivers of melanoma as well as identify new melanoma genes. The TCGA SKCM study confirmed a dominance of somatic BRAF mutations in 50% of patients. The mutational burden of melanoma patients is an order of magnitude higher than of other TCGA cohorts. A multi-step filter enriched somatic mutations while accounting for recurrence, conservation, and basal rate. Thus, this filter can serve as a paradigm for analysis of genome-wide next-generation sequencing data of large cohorts with a high mutational burden. Analysis of TCGA melanoma data using such a multi-step filter discovered novel and statistically significant potential melanoma driver genes. In the context of the Pan-Cancer study we report a detailed analysis of the mutational landscape of BRAF and other drivers across cancer tissues. Integrated analysis of somatic mutations, somatic copy number alterations, low pass copy numbers, and gene expression of the melanogenesis pathway shows coordination of proliferative events by Gs-protein and cyclin signaling at a systems level.

Original languageEnglish
Article number7857
JournalScientific Reports
Volume5
DOIs
StatePublished - 20 Jan 2015
Externally publishedYes

Fingerprint

Dive into the research topics of 'Cancer systems biology of TCGA SKCM: Efficient detection of genomic drivers in melanoma'. Together they form a unique fingerprint.

Cite this