Identifying breast cancer subtypes associated modules and biomarkers by integrated bioinformatics analysis.

ABSTRACT: Breast cancer is the most common form of cancer afflicting women worldwide. Patients with breast cancer of different molecular classifications need varied treatments. Since it is known that the development of breast cancer involves multiple genes and functions, identification of functional gene modules (clusters of the functionally related genes) is indispensable as opposed to isolated genes, in order to investigate their relationship derived from the gene co-expression analysis. In total, 6315 differentially expressed genes (DEGs) were recognized and subjected to the co-expression analysis. Seven modules were screened out. The blue and turquoise modules have been selected from the module trait association analysis since the genes in these two modules are significantly correlated with the

SUBMITTER: Wang Y 

PROVIDER: S-EPMC7796196 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature