Chen Zhao, Yan Xin, Du Guo-Wei, Tuoheti Kurerban, Bai Xiao-Jie, Wu Hua-Hui, Zhang Ren-Jie, Xiao Guan-Fa, Liu Tong-Zu
Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Front Oncol. 2020 Aug 25;10:1532. doi: 10.3389/fonc.2020.01532. eCollection 2020.
Prostate cancer (PC) is the second most frequent tumor in men, which has a high recurrence rate and poor prognosis. Therefore, this study aimed to identify novel prognostic biomarkers and therapeutic targets for immunotherapy and small molecule drugs for PC treatment. The Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm was applied to calculate immune scores and stromal scores of TCGA-PRAD data. Differentially expressed genes (DEGs) were identified using R package "limma." GO, KEGG, and DO analyses were performed to analyze DEGs. Overall survival and disease-free survival analyses were conducted for hub gene identification. To validate the hub gene at the mRNA and protein expression levels, genetic alterations were measured, and CCLE and Cox regression analyses were performed. Connectivity map (CMap) analysis and GSEA were performed for drug exploration and function analysis, respectively. Immune scores ranged from -1795.98 to 2339.39, and stomal scores ranged from -1877.60 to 1659.96. In total, 45 tumor microenvironment (TME)-related DEGs were identified, of which Complement C7 (C7) was selected and validated as a hub gene. CMap analysis identified six small molecule drugs as potential agents for PC treatment. Further analysis demonstrated that C7 expression was significantly correlated with clinical T, pathological N, and immune infiltration level. In conclusion, of the 45 TME-related DEGs, C7 was shown to correlate with PC prognosis in patients, indicating it as a novel prognostic biomarker and immunotherapy target in PC. Additionally, six small molecule drugs showed strong therapeutic potential for PC treatment.
前列腺癌（PC）是男性中第二常见的肿瘤，具有高复发率和不良预后。因此，本研究旨在识别用于PC治疗的免疫疗法和小分子药物的新型预后生物标志物和治疗靶点。使用表达数据估计恶性肿瘤组织中的基质和免疫细胞（ESTIMATE）算法来计算TCGA-PRAD数据的免疫评分和基质评分。使用R包“limma”识别差异表达基因（DEG）。进行基因本体论（GO）、京都基因与基因组百科全书（KEGG）和疾病本体（DO）分析以分析DEG。进行总生存和无病生存分析以鉴定枢纽基因。为了在mRNA和蛋白质表达水平验证枢纽基因，测量了基因改变，并进行了癌症细胞系百科全书（CCLE）和Cox回归分析。分别进行连通图（CMap）分析和基因集富集分析（GSEA）用于药物探索和功能分析。免疫评分范围为-1795.98至2339.39，基质评分范围为-1877.60至1659.96。总共鉴定出45个肿瘤微环境（TME）相关的DEG，其中补体C7（C7）被选为枢纽基因并进行了验证。CMap分析确定了六种小分子药物作为PC治疗的潜在药物。进一步分析表明，C7表达与临床分期T、病理分期N和免疫浸润水平显著相关。总之，在45个TME相关的DEG中，C7与PC患者的预后相关，表明它是PC中的一种新型预后生物标志物和免疫治疗靶点。此外，六种小分子药物对PC治疗显示出强大的治疗潜力。
