In silico analysis of differentially expressed genesets in metastatic breast cancer identifies potential prognostic biomarkers.

ABSTRACT:

Background

Identification of specific biological functions, pathways, and appropriate prognostic biomarkers is essential to accurately predict the clinical outcomes of and apply efficient treatment for breast cancer patients.

Methods

To search for metastatic breast cancer-specific biological functions, pathways, and novel biomarkers in breast cancer, gene expression datasets of metastatic breast cancer were obtained from Oncomine, an online data mining platform. Over- and under-expressed genesets were collected and the differentially expressed genes were screened from four datasets with large sample sizes (N > 200). They were analyzed for gene ontology (GO), KEGG pathway, protein-protein interaction, and hub gene analyses using online bioinformatic tools (Enrichr, STRING, an

SUBMITTER: Kim J 

PROVIDER: S-EPMC8235641 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature