Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers.

ABSTRACT: Combining omics data from different layers using integrative methods provides a better understanding of the biology of a complex disease such as cancer. The discovery of biomarkers related to cancer development or prognosis helps to find more effective treatment options. This study integrates multi-omics data of different cancer types with a network-based approach to explore common gene modules among different tumors by running community detection methods on the integrated network. The common modules were evaluated by several biological metrics adapted to cancer. Then, a new prognostic scoring method was developed by weighting mRNA expression, methylation, and mutation status of genes. The survival analysis pointed out statistically significant results for GNG11, CBX2, CDK

SUBMITTER: Demir Karaman E 

PROVIDER: S-EPMC10366886 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature