A four-gene signature associated with clinical features can better predict prognosis in prostate cancer.

ABSTRACT: Prostate cancer (PCa) is one of the most deadly urinary tumors in men globally, and the 5-year over survival is poor due to metastasis of tumor. It is significant to explore potential biomarkers for early diagnosis and personalized therapy of PCa. In the present study, we performed an integrated analysis based on multiple microarrays in the Gene Expression Omnibus (GEO) dataset and obtained differentially expressed genes (DEGs) between 510 PCa and 259 benign issues. The weighted correlation network analysis indicated that prognostic profile was the most relevant to DEGs. Then, univariate and multivariate COX regression analyses were conducted and four prognostic genes were obtained to establish a four-gene prognostic model. And the predictive effect and expression profiles of the four gene

SUBMITTER: Yuan P 

PROVIDER: S-EPMC7643642 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature