Feng Tao, Wei Dechao, Li Qiankun, Yang Xiaobing, Han Yili, Luo Yong, Jiang Yongguang
Department of Urology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
Front Genet. 2021 Apr 1;12:584164. doi: 10.3389/fgene.2021.584164. eCollection 2021.
Prostate cancer (PCa) is one of the most common malignancies for males, but very little is known about its pathogenesis. This study aimed to identify novel biomarkers associated with PCa prognosis and elucidate the underlying molecular mechanism. First, The Cancer Genome Atlas (TCGA) RNA-sequencing data were utilized to identify differentially expressed genes (DEGs) between tumor and normal samples. The DEGs were then applied to construct a co-expression and mined using structure network analysis. The magenta module that was highly related to the Gleason score ( = 0.46, = 3e-26) and tumor stage ( = 0.38, = 2e-17) was screened. Subsequently, all genes of the magenta module underwent function annotation. From the key module, CCNA2, CKAP2L, NCAPG, and NUSAP1 were chosen as the four candidate genes. Finally, internal (TCGA) and external data sets (GSE32571, GSE70770, and GSE141551) were combined to validate and predict the value of real hub genes. The results show that the above genes are up-regulated in PCa samples, and higher expression levels show significant association with higher Gleason scores and tumor T stage. Moreover, receiver operating characteristic curve and survival analysis validate the excellent value of hub genes in PCa progression and prognosis. In addition, the protein levels of these four genes also remain higher in tumor tissues when compared with normal tissues. Gene set enrichment analysis and gene set variation analysis for a single gene reveal the close relation with cell proliferation. Meanwhile, 11 small molecular drugs that have the potential to treat PCa were also screened. In conclusion, our research identified four potential prognostic genes and several candidate molecular drugs for treating PCa.
前列腺癌（PCa）是男性最常见的恶性肿瘤之一，但其发病机制却鲜为人知。本研究旨在识别与PCa预后相关的新型生物标志物，并阐明其潜在的分子机制。首先，利用癌症基因组图谱（TCGA）的RNA测序数据来识别肿瘤样本与正常样本之间的差异表达基因（DEG）。然后将这些DEG用于构建共表达，并通过结构网络分析进行挖掘。筛选出与Gleason评分（= 0.46，= 3e - 26）和肿瘤分期（= 0.38，= 2e - 17）高度相关的品红色模块。随后，对品红色模块的所有基因进行功能注释。从关键模块中，选择CCNA2、CKAP2L、NCAPG和NUSAP1作为四个候选基因。最后，合并内部（TCGA）和外部数据集（GSE32571、GSE70770和GSE141551）来验证和预测真正的核心基因的价值。结果表明，上述基因在PCa样本中上调，较高的表达水平与较高的Gleason评分和肿瘤T分期显著相关。此外，受试者工作特征曲线和生存分析验证了核心基因在PCa进展和预后中的优异价值。此外，与正常组织相比，这四个基因的蛋白质水平在肿瘤组织中也仍然较高。对单个基因的基因集富集分析和基因集变异分析揭示了其与细胞增殖的密切关系。同时，还筛选出了11种具有治疗PCa潜力的小分子药物。总之，我们的研究确定了四个潜在的预后基因和几种治疗PCa的候选分子药物。
