Chen Xi, Ma Junjie, Xu Chengdang, Wang Licheng, Yao Yicong, Wang Xinan, Zi Tong, Bian Cuidong, Wu Denglong, Wu Gang
Department of Urology, Tongji Hospital, School of Medicine, Tongji University, 389 Xincun Road, Shanghai, 200065, China.
Discov Oncol. 2022 Jun 30;13(1):54. doi: 10.1007/s12672-022-00508-y.
Prostate cancer (PCa) and benign prostate hyperplasia (BPH) are commonly encountered diseases in males. Studies showed that genetic factors are responsible for the occurrences of both diseases. However, the genetic association between them is still unclear. Gene Expression Omnibus (GEO) database can help determine the differentially expressed genes (DEGs) between BPH and PCa. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were utilized to find pathways DEGs enriched. The STRING database can provide a protein-protein interaction (PPI) network, and find hub genes in PPI network. R software was used to analyze the clinical value of hub genes in PCa. Finally, the function of these hub genes was tested in different databases, clinical samples, and PCa cells. Fifteen up-regulated and forty-five down-regulated genes were found from GEO database. Seven hub genes were found in PPI network. The expression and clinical value of hub genes were analyzed by The Cancer Genome Atlas (TCGA) data. Except CXCR4, all hub genes expressed differently between tumor and normal samples. Exclude CXCR4, other hub genes have diagnostic value in predicting PCa and their mutations can cause PCa. The expression of CSRP1, MYL9 and SNAI2 changed in different tumor stage. CSRP1 and MYH11 could affect disease-free survival (DFS). Same results reflected in different databases. The expression and function of MYC, MYL9, and SNAI2, were validated in clinical samples and PCa cells. In conclusion, seven hub genes among sixty DEGs may be achievable targets for predicting which BPH patients may later develop PCa and they can influence the progression of PCa.
前列腺癌（PCa）和良性前列腺增生（BPH）是男性常见疾病。研究表明，遗传因素是这两种疾病发生的原因。然而，它们之间的遗传关联仍不清楚。基因表达综合数据库（GEO）有助于确定BPH和PCa之间的差异表达基因（DEGs）。利用基因本体论（GO）和京都基因与基因组百科全书（KEGG）分析来寻找DEGs富集的通路。STRING数据库可以提供蛋白质-蛋白质相互作用（PPI）网络，并在PPI网络中找到枢纽基因。使用R软件分析枢纽基因在PCa中的临床价值。最后，在不同数据库、临床样本和PCa细胞中测试这些枢纽基因的功能。从GEO数据库中发现了15个上调基因和45个下调基因。在PPI网络中发现了7个枢纽基因。通过癌症基因组图谱（TCGA）数据对枢纽基因的表达和临床价值进行了分析。除CXCR4外，所有枢纽基因在肿瘤和正常样本之间的表达均有差异。排除CXCR4，其他枢纽基因在预测PCa方面具有诊断价值，且它们的突变可导致PCa。CSRP1、MYL9和SNAI2的表达在不同肿瘤分期发生变化。CSRP1和MYH11可影响无病生存期（DFS）。不同数据库中反映出相同结果。在临床样本和PCa细胞中验证了MYC、MYL9和SNAI2的表达及功能。总之，60个DEGs中的7个枢纽基因可能是预测哪些BPH患者日后可能发展为PCa的可实现靶点，并且它们可以影响PCa的进展。
