Identification of differentially expressed genes-related prognostic risk model for survival prediction in breast carcinoma patients.

ABSTRACT: Since the imbalance of gene expression has been demonstrated to tightly related to breast cancer (BRCA) genesis and growth, common genes expressed of BRCA were screened to explore the essence in-between. In current work, most common differentially expressed genes (DEGs) in various subtypes of BRCA were identified. Functional enrichment analysis illustrated the driving factor of deactivation of the cell cycle and the oocyte meiosis, which critically triggers the development of BRCA. Herein, we constructed a 12-gene prognostic risk model relative to differential gene expression. Subsequently, the K-M curves, analysis on time-ROC curve and Cox regression were performed to assess this risk model by determining the respective prognostic value, and the prediction performance were ascertained for

SUBMITTER: Li J 

PROVIDER: S-EPMC8266316 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature