Identification of novel cell glycolysis related gene signature predicting survival in patients with breast cancer.

ABSTRACT: One of the most frequently identified tumors and a contributing cause of death in women is breast cancer (BC). Many biomarkers associated with survival and prognosis were identified in previous studies through database mining. Nevertheless, the predictive capabilities of single-gene biomarkers are not accurate enough. Genetic signatures can be an enhanced prediction method. This research analyzed data from The Cancer Genome Atlas (TCGA) for the detection of a new genetic signature to predict BC prognosis. Profiling of mRNA expression was carried out in samples of patients with TCGA BC (n = 1222). Gene set enrichment research has been undertaken to classify gene sets that vary greatly between BC tissues and normal tissues. Cox models for additive hazards regression were used to classify gen

SUBMITTER: Jiang F 

PROVIDER: S-EPMC7889867 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature