Department of Oncology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China (mainland).
Department of Oncology, Jinshan Hospital of The First Affiliated Hospital of Chongqing Medical University, Chongqing, China (mainland).
Med Sci Monit. 2020 Feb 8;26:e919953. doi: 10.12659/MSM.919953.
BACKGROUND With the development of research on cancer genomics and microenvironment, a new era of oncology focusing on the complicated gene regulation of pan-cancer research and cancer immunotherapy is emerging. This study aimed to identify the common gene expression characteristics of multiple cancers - lung cancer, liver cancer, kidney cancer, cervical cancer, and breast cancer - and the potential therapeutic targets in public databases. MATERIAL AND METHODS Gene expression analysis of GSE42568, GSE19188, GSE121248, GSE63514, and GSE66272 in the GEO database of multitype cancers revealed differentially expressed genes (DEGs). Then, GO analysis, KEGG function, and path enrichment analyses were performed. Hub-genes were identified by using the degree of association of protein interaction networks. Moreover, the expression of hub-genes in cancers was verified, and hub-gene-related survival analysis was conducted. Finally, infiltration levels of tumor immune cells with related genes were explored. RESULTS We found 12 cross DEGs in the 5 databases (screening conditions: "adj p<0.05" and "logFC>2 or logFC<-2"). The biological processes of DEGs were mainly concentrated in cell division, regulation of chromosome segregation, nuclear division, cell cycle checkpoint, and mitotic nuclear division. Furthermore, 10 hub-genes were obtained using Cytoscape: TOP2A, ECT2, RRM2, ANLN, NEK2, ASPM, BUB1B, CDK1, DTL, and PRC1. The high expression levels of the 10 genes were associated with the poor survival of these multiple cancers, as well as ASPM, may be associated with immune cell infiltration. CONCLUSIONS Analysis of the common DEGs of multiple cancers showed that 10 hub-genes, especially ASPM and CDK1, can become potential therapeutic targets. This study can serve as a reference to understand the characteristics of different cancers, design basket clinical trials, and create personalized treatments.
随着癌症基因组学和微环境研究的发展,一个专注于泛癌研究和癌症免疫治疗中复杂基因调控的肿瘤学新时代正在出现。本研究旨在从公共数据库中确定多种癌症(肺癌、肝癌、肾癌、宫颈癌和乳腺癌)的共同基因表达特征和潜在的治疗靶点。
从 GEO 数据库中分析 GSE42568、GSE19188、GSE121248、GSE63514 和 GSE66272 这 5 个多类型癌症数据集的基因表达数据,找到差异表达基因(DEGs)。然后,进行 GO 分析、KEGG 功能和通路富集分析。利用蛋白质相互作用网络的关联度确定枢纽基因。此外,还验证了枢纽基因在癌症中的表达情况,并进行了与枢纽基因相关的生存分析。最后,探讨了与相关基因相关的肿瘤免疫细胞的浸润水平。
在 5 个数据库中发现了 12 个交叉 DEGs(筛选条件:“adj p<0.05”和“logFC>2 或 logFC<-2”)。DEGs 的生物过程主要集中在细胞分裂、染色体分离调节、核分裂、细胞周期检查点和有丝分裂核分裂。此外,使用 Cytoscape 获得了 10 个枢纽基因:TOP2A、ECT2、RRM2、ANLN、NEK2、ASPM、BUB1B、CDK1、DTL 和 PRC1。这 10 个基因的高表达水平与这些多种癌症的不良生存有关,而 ASPM 可能与免疫细胞浸润有关。
对多种癌症的共同 DEGs 进行分析表明,10 个枢纽基因,特别是 ASPM 和 CDK1,可能成为潜在的治疗靶点。本研究可为了解不同癌症的特征、设计篮子临床试验和制定个性化治疗方案提供参考。