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挖掘TCGA数据库以筛选和鉴定肾透明细胞癌微环境中的枢纽基因。

Mining TCGA database for screening and identification of hub genes in kidney renal clear cell carcinoma microenvironment.

作者信息

Li Song, Xu Weibo

机构信息

Department of Urology, Huaihe Hospital of Henan University, Kaifeng, China.

出版信息

J Cell Biochem. 2020 Aug;121(8-9):3952-3960. doi: 10.1002/jcb.29511. Epub 2019 Nov 7.

DOI:10.1002/jcb.29511
PMID:31697440
Abstract

To evaluate the diagnosis and prognosis of the tumor microenvironment (immunization and stromal cells) in kidney renal clear cell carcinoma (KIRC), KIRC cases selected from The Cancer Genome Atlas database were divided into two groups according to the ESTIMATE algorithm-derived immune scores. Our data suggested that the Von Hippel-Lindau mutations and pathologic grades are associated with immune scores. Importat ntly, we identified 173 differential expression genes (DEGs) associated with prognosis in patients with KIRC. Consequently, Gene Ontology functional enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed on these DEGs, which included immune response, defense response, intrinsic to the plasma membrane, positive regulation of immune system process, and cytokine binding. Next, the protein-protein interaction network of DEGs and the most significant module was constructed. Five hub genes were identified and analyzed using biological analysis. The survival analysis of the hub genes showed that KIRC patients with high gene expression of C2, MXRA8, TNFSF13B, and X-linked inhibitor of apoptosis protein-associated factor 1 (XAF1) had worse overall survival, and MXRA8, TNFSF13B, and XAF1 alteration were significantly associated with disease-free survival (DFS). In addition, high gene expression of XAF1 alteration showed better DFS. Conclusion: we identified a list of microenvironment-related genes that are useful for understanding the molecular mechanisms and prognosis of KIRC.

摘要

为了评估肾透明细胞癌(KIRC)中肿瘤微环境(免疫细胞和基质细胞)的诊断和预后,根据ESTIMATE算法得出的免疫评分,将从癌症基因组图谱数据库中选取的KIRC病例分为两组。我们的数据表明,冯·希佩尔-林道突变和病理分级与免疫评分相关。重要的是,我们鉴定出了173个与KIRC患者预后相关的差异表达基因(DEG)。因此,对这些DEG进行了基因本体功能富集分析和京都基因与基因组百科全书通路分析,其中包括免疫反应、防御反应、质膜内在成分、免疫系统过程的正调控以及细胞因子结合。接下来,构建了DEG的蛋白质-蛋白质相互作用网络和最显著的模块。鉴定出五个枢纽基因并进行生物学分析。枢纽基因的生存分析表明,C2、MXRA8、肿瘤坏死因子配体超家族成员13B(TNFSF13B)以及X连锁凋亡抑制蛋白相关因子1(XAF1)基因高表达的KIRC患者总生存期较差,并且MXRA8、TNFSF13B和XAF1的改变与无病生存期(DFS)显著相关。此外,XAF1改变的高基因表达显示出更好的DFS。结论:我们鉴定出了一系列与微环境相关的基因,这些基因有助于理解KIRC的分子机制和预后。

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