Cooperative genomic alteration network reveals molecular classification across 12 major cancer types.

摘要: The accumulation of somatic genomic alterations that enables cells to gradually acquire growth advantage contributes tumor development. This has the important implication widespread existence cooperative in process. Here, we proposed a computational method HCOC simultaneously consider genetic context and downstream functional effects on cancer hallmarks uncover events human cancers. Applying our 12 TCGA types, totally identified 1199 with high heterogeneity across cancers, then constructed pan-cancer alteration network. These are associated some high-confident drivers, can trigger dysfunction hallmark pathways co-defect way rather than single alterations. We found these be used produce prognostic classification provide complementary information tissue-of-origin. In further case study glioblastoma, using 23 identified, stratified patients into molecularly relevant subtypes significance independent Glioma-CpG Island Methylator Phenotype (GCIMP). summary, effectively discover cancer-driving valuable clinical markers for patient stratification.