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Label propagation defines signaling networks associated with recurrently mutated cancer genes.

ABSTRACT: Human tumors have distinct profiles of genomic alterations, and each of these alterations has the potential to cause unique changes to cellular homeostasis. Detailed analyses of these changes could reveal downstream effects of genomic alterations, contributing to our understanding of their roles in tumor development and progression. Across a range of tumor types, including bladder, lung, and endometrial carcinoma, we determined genes that are frequently altered in The Cancer Genome Atlas patient populations, then examined the effects of these alterations on signaling and regulatory pathways. To achieve this, we used a label propagation-based methodology to generate networks from gene expression signatures associated with defined mutations. Individual networks offered a large-scale view of signaling changes represented by gene signatures, which in turn reflected the scope of molecular events that are perturbed in the presence of a given genomic alteration. Comparing different networks to one another revealed common biological pathways impacted by distinct genomic alterations, highlighting the concept that tumors can dysregulate key pathways through multiple, seemingly unrelated mechanisms. Finally, altered genes inducing common changes to the signaling network were used to search for genomic markers of drug response, connecting shared perturbations to differential drug sensitivity.

SUBMITTER: Cakir M

PROVIDER: S-EPMC6599034 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Label propagation defines signaling networks associated with recurrently mutated cancer genes.

Cakir Merve M Mukherjee Sayan S Wood Kris C KC

Scientific reports 20190628 1

Human tumors have distinct profiles of genomic alterations, and each of these alterations has the potential to cause unique changes to cellular homeostasis. Detailed analyses of these changes could reveal downstream effects of genomic alterations, contributing to our understanding of their roles in tumor development and progression. Across a range of tumor types, including bladder, lung, and endometrial carcinoma, we determined genes that are frequently altered in The Cancer Genome Atlas patient ...[more]

PMID: 31253832

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Project description:BACKGROUND:Cancer genes tend to be highly mutated under positive selection. Better understanding the recurrently mutated genes (RMGs) in cancer is critical for explicating the mechanisms of tumorigenesis and providing vital clues for therapy. Although some studies have investigated functional impacts of RMGs in specific cancer types, a comprehensive analysis of RMGs and their mutational impacts across cancers is still needed. METHODS:We obtained data from The Cancer Genome Atlas (TCGA) and calculated mutation rate of each gene in 31 cancer types. Functional analysis was performed to identify the important signaling pathways and enriched protein types of RMGs. In order to evaluate functional impacts of RMGs, differential expression, survival, and pairwise mutation patterns analyses were performed. RESULTS:Totally, we identified 897 RMGs and 624 of them were specifically mutant in only a single cancer type. Functional analysis demonstrated that these RMGs were enriched in hydrolases, cytoskeletal protein, and pathways like MAPK, cell cycle, PI3K-Akt, ECM receptor interaction, and energy metabolism. The differentially expressed genes potentially affected by the same common RMG showed a relatively low overlap across different cancer types. For the 19 Mucin (MUC) family genes, nine of them were RMGs and four of them (MUC17, MUC5B, MUC4, and MUC16) were common RMGs shared in 8 to 17 cancer types. The results showed that recurrent mutations in MUC genes were significantly associated with better survival prognosis. Only a small part of RMGs was differentially expressed due to their own mutations and most of them were downregulated. In addition, pairwise mutation pattern analysis revealed the high frequency of co-occurred mutations among RMGs in STAD. CONCLUSION:Through the functional analysis of RMGs, we found that six signaling pathways were disrupted in most cancer types and that energy metabolism was abnormal in tumors. The results also revealed a strong correlation between recurrently mutated genes from MUC family and human survival. In addition, gene expression and survival prognosis were associated with different mutation types of RMGs.

Dataset Information

Label propagation defines signaling networks associated with recurrently mutated cancer genes.

Publications

Label propagation defines signaling networks associated with recurrently mutated cancer genes.

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