An integrative somatic mutation analysis to identify pathways linked with survival outcomes across 19 cancer types

Abstract excerpt

Identification of altered pathways that are clinically relevant across human cancers is a key challenge in cancer genomics. We developed a network-based algorithm to integrate somatic mutation data with gene networks and pathways, in order to identify pathways altered by somatic mutations across cancers. We applied our approach to The Cancer Genome Atlas (TCGA) dataset of somatic mutations in 4,790 cancer patients...

Topics

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• Cluster Analysis
• DNA Mutational Analysis
• Gene Regulatory Networks
• Genome, Human
• Genomics
• Mutation
• Neoplasms
• Point Mutation

Identifiers and source

Literature Corpus work

b68e6e29-e463-560c-8411-bc15cffa0487

DOI

10.1101/017582