Department of TCM, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, People's Republic of China.
Institute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, People's Republic of China.
J Biochem Mol Toxicol. 2022 Sep;36(9):e23137. doi: 10.1002/jbt.23137. Epub 2022 Jun 9.
Prostate cancer (PCa) is a common urinary malignancy. The lack of specific and sensitive biomarkers for the early diagnosis and prognosis of PCa makes it important to seek alternatives. R software was used to analyze the PCa expression profile from data sets in Gene Expression Omnibus. Core differential genes were identified by String and Cytoscape and further validated by Gene Expression Profiling Interactive Analysis (GEPIA) and The Human Protein Atlas (HPA). Gene Ontology analysis was done in the DIVID database and visualization analysis was conducted by Hiplot. Pathway enrichment was analyzed by IPA. To identify potential competitive endogenous RNAs (ceRNA) networks, the experimentally validated microRNA-target interactions database (miRTarBase), The Encyclopedia of RNA Interactomes (StarBase), lncBase, and GEPIA were used. The lncLocator was utilized to perform subcellular localization of long noncoding RNAs (lncRNAs). Both miRTarBase and StarBase were used to find the binding site of mRNAs-miRNAs and miRNAs-lncRNAs. Visualization of the ceRNA network was performed with Cytoscape. Nine genes closely related to the diagnosis and prognosis of PCa were obtained, including four identified biomarkers by HPA, CENPF, TPX2, TK1, and CCNB1, and five novel PCa biomarkers, RRM2, UBE2C, TOP2A, BIRC5, and ZWINT. Pathway analysis indicated that PCa carcinogenesis was highly correlated with liver fibrosis pathways, ILK signaling, and NRF2-mediated oxidative stress response. Two sets of ceRNA networks, BIRC5/hsa-miR-218-5p/NEAT1 and UBE2C/hsa-miR-483-3p/NEAT1 were found to be novel biomarkers for the identification of PCa. The quantitative real-time polymerase chain reaction results verified that UBE2C, BIRC5, and NEAT1 were upregulated and hsa-miR-218-5p and hsa-miR-483-3p were downregulated in human PCa cells compared with normal prostate epithelial cells. The novel identified biomarkers in this study would be valuable for the diagnosis and prognosis of PCa.
前列腺癌（PCa）是一种常见的泌尿系统恶性肿瘤。由于缺乏用于 PCa 早期诊断和预后的特异性和敏感生物标志物，因此寻找替代方法很重要。使用 R 软件分析了来自基因表达综合数据库（GEO）中数据集的 PCa 表达谱。通过 String 和 Cytoscape 鉴定核心差异基因，并通过基因表达谱分析交互分析（GEPIA）和人类蛋白质图谱（HPA）进一步验证。在 DIVID 数据库中进行基因本体论（GO）分析，并通过 Hiplot 进行可视化分析。通过 IPA 进行通路富集分析。为了鉴定潜在的竞争性内源 RNA（ceRNA）网络，使用了经过实验验证的 microRNA 靶标相互作用数据库（miRTarBase）、RNA 相互作用组百科全书（StarBase）、lncBase 和 GEPIA。使用 lncLocator 进行长非编码 RNA（lncRNA）的亚细胞定位。miRTarBase 和 StarBase 均用于查找 mRNAs-miRNAs 和 miRNAs-lncRNAs 的结合位点。使用 Cytoscape 可视化 ceRNA 网络。获得了与 PCa 诊断和预后密切相关的 9 个基因，包括 HPA 鉴定的 4 个生物标志物，CENPF、TPX2、TK1 和 CCNB1，以及 5 个新的 PCa 生物标志物，RRM2、UBE2C、TOP2A、BIRC5 和 ZWINT。通路分析表明，PCa 发生与肝纤维化途径、ILK 信号和 NRF2 介导的氧化应激反应高度相关。发现了两组 ceRNA 网络，BIRC5/hsa-miR-218-5p/NEAT1 和 UBE2C/hsa-miR-483-3p/NEAT1，这是鉴定 PCa 的新型生物标志物。实时定量聚合酶链反应（qPCR）结果验证了与正常前列腺上皮细胞相比，人 PCa 细胞中 UBE2C、BIRC5 和 NEAT1 上调，hsa-miR-218-5p 和 hsa-miR-483-3p 下调。本研究中鉴定的新型生物标志物对 PCa 的诊断和预后具有重要价值。
