Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China.
Department of Urology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Biomed Res Int. 2020 May 18;2020:5019793. doi: 10.1155/2020/5019793. eCollection 2020.
Prostate adenocarcinoma (PRAD) is a common malignant tumor in elderly men. Our research uses The Cancer Gene Atlas (TCGA) database to find potential related genes for predicting the prognosis of patients with PRAD.
We downloaded gene expression profiles and clinical sample information from TCGA for 490 patients with PRAD (patient age: 41-78 years). We calculated stromal and immune scores using the ESTIMATE algorithm to predict the level of stromal and immune cell infiltration. We categorized patients with PRAD in TCGA into high and low score arrays according to their median immune/stromal scores and identified differentially expressed genes (DEGs) that were significantly correlated with the prognosis of PRAD. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. The association between DEGs and overall survival was investigated by weighted Kaplan-Meier survival analysis and multivariate analysis. Furthermore, the protein-protein interaction network (PPI) of DEGs was constructed using the STRING tool. Finally, the hub genes were identified by analyzing the degree of association of PPI networks.
We found that 8 individual DEGs, C6, S100A12, MLC1, PAX5, C7, FAM162B, CAMK1G, and TCEAL5, were significantly predictive of favorable overall survival and one DEG, EPYC, was associated with poor overall survival. GO and KEGG pathway analyses revealed that the DEGs were associated with immune responses. Moreover, 30 hub genes were obtained using the PPI network of DEGs: ITGAM, CD4, CD3E, IL-10, LCP2, ITGB2, ZAP-70, C3, CCL19, CXCL13, CXCL9, BTK, CCL21, CD247, CD28, CD3D, FCER1G, PTPRC, TYROBP, CCR5, ITK, CCL13, CCR1, CCR2, CD79B, CYBB, IL2RG, JAK3, PLCG2, and CD19. These prominent nodes had the most associations with other genes, indicating that they might play crucial roles in the prognosis of PRAD.
We extracted a list of genes associated with the prostate adenocarcinoma microenvironment, which might contribute to the prediction and interpretation of PRAD prognosis.
前列腺腺癌（PRAD）是老年男性常见的恶性肿瘤。我们的研究使用癌症基因图谱（TCGA）数据库来寻找预测 PRAD 患者预后的潜在相关基因。
我们从 TCGA 下载了 490 名 PRAD 患者（患者年龄：41-78 岁）的基因表达谱和临床样本信息。我们使用 ESTIMATE 算法计算了基质和免疫评分，以预测基质和免疫细胞浸润的水平。我们根据 TCGA 中患者的中位数免疫/基质评分将其分为高和低评分数组，并确定与 PRAD 预后显著相关的差异表达基因（DEGs）。然后进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路分析。通过加权 Kaplan-Meier 生存分析和多变量分析研究 DEGs 与总生存的相关性。此外，使用 STRING 工具构建了 DEGs 的蛋白质-蛋白质相互作用网络（PPI）。最后，通过分析 PPI 网络的关联度来确定枢纽基因。
我们发现 8 个个体 DEGs（C6、S100A12、MLC1、PAX5、C7、FAM162B、CAMK1G 和 TCEAL5）显著预测总生存良好，一个 DEG（EPYC）与总生存不良相关。GO 和 KEGG 通路分析表明，DEGs 与免疫反应有关。此外，通过 DEGs 的 PPI 网络获得了 30 个枢纽基因：ITGAM、CD4、CD3E、IL-10、LCP2、ITGB2、ZAP-70、C3、CCL19、CXCL13、CXCL9、BTK、CCL21、CD247、CD28、CD3D、FCER1G、PTPRC、TYROBP、CCR5、ITK、CCL13、CCR1、CCR2、CD79B、CYBB、IL2RG、JAK3、PLCG2 和 CD19。这些突出节点与其他基因的关联最多，表明它们可能在 PRAD 的预后中发挥关键作用。
我们提取了一组与前列腺腺癌微环境相关的基因，这可能有助于预测和解释 PRAD 的预后。
