Combining multi-dimensional data to identify key genes and pathways in gastric cancer.

ABSTRACT: Gastric cancer is an aggressive cancer that is often diagnosed late. Early detection and treatment require a better understanding of the molecular pathology of the disease. The present study combined data on gene expression and regulatory levels (microRNA, methylation, copy number) with the aim of identifying key genes and pathways for gastric cancer. Data used in this study was retrieved from The Cancer Genomic Atlas. Differential analyses between gastric cancer and normal tissues were carried out using Limma. Copy number alterations were identified for tumor samples. Bimodal filtering of differentially expressed genes (DEGs) based on regulatory changes was performed to identify candidate genes. Protein-protein interaction networks for candidate genes were generated by Cytoscape software.

SUBMITTER: Ren W 

PROVIDER: S-EPMC5463969 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature