A Novel Risk Factor Model Based on Glycolysis-Associated Genes for Predicting the Prognosis of Patients With Prostate Cancer.

ABSTRACT:

Background

Prostate cancer (PCa) is one of the most prevalent cancers among males, and its mortality rate is increasing due to biochemical recurrence (BCR). Glycolysis has been proven to play an important regulatory role in tumorigenesis. Although several key regulators or predictors involved in PCa progression have been found, the relationship between glycolysis and PCa is unclear; we aimed to develop a novel glycolysis-associated multifactor prediction model for better predicting the prognosis of PCa.

Methods

Differential mRNA expression profiles derived from the Cancer Genome Atlas (TCGA) PCa cohort were generated through the "edgeR" package. Glycolysis-related genes were obtained from the GSEA database. Univariate Cox and LASSO regression analyses were used to identify g

SUBMITTER: Guo K 

PROVIDER: S-EPMC8476926 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature