Cancers exhibit extensive mutational heterogeneity and the resulting long tail
phenomenon complicates the discovery of the genes and pathways that are significantly
mutated in cancer. We perform a Pan-Cancer analysis of mutated networks in 3281 samples
from 12 cancer types from The Cancer Genome Atlas (TCGA) using HotNet2, a novel algorithm
to find mutated subnetworks that overcomes limitations of existing single gene and
pathway/network approaches.. We identify 14 significantly mutated subnetworks that include
well-known cancer signaling pathways as well as subnetworks with less characterized roles
in cancer including cohesin, condensin, and others. Many of these subnetworks exhibit
co-occurring mutations across samples. These subnetworks contain dozens of genes with rare
somatic mutations across multiple cancers; many of these genes have additional evidence
supporting a role in cancer. By illuminating these rare combinations of mutations,
Pan-Cancer network analyses provide a roadmap to investigate new diagnostic and
therapeutic opportunities across cancer types.
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