A Prognostic Signature for Treatment Planning and Evaluation in Prostate Cancer

Researchers constructed an effective signature to predict the prognosis of prostate cancer (PCa) and identify the biofunctions of signature-related genes. The results were published in Frontiers in Cell and Development Biology.

To conduct this study, researchers screened differentially expressed genes (DEGs) between PCa and normal control tissues in The Cancer Genome Atlas (TCGA) and GSE46602 datasets. Subsequently, they performed weighted gene co-expression network analysis (WGCNA) to discern gene modules linked with tumors. In total, they analyzed 124 differentially co-expressed genes. Additionally, they noted, five genes (ARHGEF38, NETO2, PRSS21, GOLM1, and SAPCD2) were identified to develop the prognostic signature based on TCGA data. This five-gene risk score was verified using multivariate Cox regression analyses.

According to the findings, the expression of the five genes involved in the signature was detected in the Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA), and Oncomine databases. Moreover, the use of DiseaseMeth 2.0 and MEXPRESS analysis demonstrated that abnormal methylation patterns may be a potential mechanism for these five DEGs in PCa. Overall, they observed that these genes, except PRSS21, were highly expressed in tumor samples and PCa cells.

The researchers concluded that “this prognostic signature had significant clinical significance for treatment planning and prognostic evaluation of patients with PCa. Thus, ARHGEF38, NETO2, GOLM1, and SAPCD2 may serve as oncogenes in PCa.”