Identification of diagnostic biomarkers in prostate cancer-related fatigue by construction of predictive models and experimental validation.

ABSTRACT:

Background

Cancer-related fatigue (CRF) is a prominent cancer-related complication occurring in Prostate cancer (PCa) patients, profoundly affecting prognosis. The lack of diagnostic criteria and biomarkers hampers the management of CRF.

Methods

The CRF-related data and PCa single-cell data were retrieved from the GEO database and clinical data was downloaded from the TCGA database. The univariate logistic/Cox regression analysis were used to construct the prediction models. The predictive value of models was analyzed using the ROC curve and Kaplan-Meier survival. The hub genes were screened by an intersection analysis of DEGs. The mice model of PCa and PCa-related fatigue were established, and fatigue-like behaviors of mice were detected. The expression of selected hub gene

SUBMITTER: Chen M 

PROVIDER: S-EPMC11791036 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature