Identification and validation of immune-related hub genes based on machine learning in prostate cancer and AOX1 is an oxidative stress-related biomarker.

ABSTRACT: To investigate potential diagnostic and prognostic biomarkers associated with prostate cancer (PCa), we obtained gene expression data from six datasets in the Gene Expression Omnibus (GEO) database. The datasets included 127 PCa cases and 52 normal controls. We filtered for differentially expressed genes (DEGs) and identified candidate PCa biomarkers using a least absolute shrinkage and selector operation (LASSO) regression model and support vector machine recursive feature elimination (SVM-RFE) analyses. A difference analysis was conducted on these genes in the test group. The discriminating ability of the train group was determined using the area under the receiver operating characteristic curve (AUC) value, with hub genes defined as those having an AUC greater than 85%. The expression l

SUBMITTER: Mo X 

PROVIDER: S-EPMC10423936 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature