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Identification of ARHGEF38, NETO2, GOLM1, and SAPCD2 Associated With Prostate Cancer Progression by Bioinformatic Analysis and Experimental Validation

1 Sept 2021

Abstract excerpt

Prostate cancer (PCa) represents one of the most prevalent types of cancers and is a large health burden for men. The pathogenic mechanisms of PCa still need further investigation. The aim of this study was to construct an effective signature to predict the prognosis of PCa patients and identify the biofunctions of signature-related genes. First, we screened differentially expressed genes (DEGs) between PCa and...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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PMID: 34540835
DOI: 10.3389/fcell.2021.718638

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