Prognostic biomarkers related to breast cancer recurrence identified based on Logit model analysis.

ABSTRACT:

Background

This study intended to determine important genes related to the prognosis and recurrence of breast cancer.

Methods

Gene expression data of breast cancer patients were downloaded from TCGA database. Breast cancer samples with recurrence and death were defined as poor disease-free survival (DFS) group, while samples without recurrence and survival beyond 5 years were defined as better DFS group. Another gene expression profile dataset (GSE45725) of breast cancer was downloaded as the validation data. Differentially expressed genes (DEGs) were screened between better and poor DFS groups, which were then performed function enrichment analysis. The DEGs that were enriched in the GO function and KEGG signaling pathway were selected for cox regression analysis and Logit

SUBMITTER: Zhou X 

PROVIDER: S-EPMC7519567 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature