Four Novel Prognostic Genes Related to Prostate Cancer Identified Using Co-expression Structure Network Analysis - Feng, Tao; Wei, Dechao; Li, Qiankun; Yang, Xiaobing; Han, Yili; Luo, Yong; Jiang, Yongguang (Frontiers in Genetics, 2021)
Prostate cancer (PCa) is one of most common malignancies for male, but little is known about their pathogenesis. The aim of our study was to identify novel biomarkers associated with PCa prognosis and elucidating the underlying molecular mechanism. Firstly, we utilized The Cancer Genome Atlas (TCGA) RNA-sequencing (RNA-seq) data to identify differentially expressed genes (DEGs) between tumor and normal samples. Then DEGs were applied to construct a co-expression network by weighted gene co-expression network analysis (WGCNA). We screened the magenta module, which was highly related to the gleason score (r = 0.46, p = 3e-26) and tumor stage (r = 0.38, p = 2e-17). Subsequently, all genes of magenta module were performed to function annotation. From the key module, we chose CCNA2, CKAP2L, NCAPG, NUSAP1 as our candidate genes. Finally, we combined internal datasets (TCGA) and external datasets (GSE32571, GSE70770, GSE141551) to validate predict value of real hub genes. We found that above genes were up-regulated in PCa samples, and higher expression levels were significantly associated with higher gleason scores and tumor T stage. Moreover, receive operating characteristic (ROC) and survival analysis validated that hub genes exhibited excellent value for PCa progression and prognosis. In addition, the protein level of these 4 genes were also higher in tumor tissues compare with normal tissues. Gene set Enrichment analysis (GSEA) and Gene set variation analysis (GSVA) for single gene unveiled that they were closely related with cell proliferation. Meanwhile, we also screened out some small molecular drugs that have the potential to treat PCa. In conclusion, our research identified 4 potential prognostic genes and several candidate molecular drugs for PCa treatment.