Identification of key modules and genes associated with breast cancer prognosis using WGCNA and ceRNA network analysis.

ABSTRACT: Breast cancer is one of the leading causes of cancer-associated mortality in women worldwide and has become a major public health problem. Although the definitive cause of breast cancer is not known, many genes sensitive to breast cancer have been detected using advanced technologies. Our study identified 3301 differentially expressed lncRNAs and mRNAs between tumor and normal samples from The Cancer Genome Atlas database. Based on the gene expression analysis and clinical traits as well as weighted gene co-expression network analysis, the co-expression Brown module was found to be key for breast cancer prognosis. A total of 453 genes in the Brown module were used for functional enrichment, protein-protein interaction analysis, lncRNA-miRNA-mRNA ceRNA network, and lncRNA-RNA binding protei

SUBMITTER: Yin X 

PROVIDER: S-EPMC7880379 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature