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目的:利用生物信息学分析肾嫌色细胞癌基因表达谱芯片，寻找肾嫌色细胞癌发生的关键基因。方法:从GEO数据库下载肾嫌色细胞癌基因芯片数据GSE15641和GSE11151，利用R软件中的“affy”、“limma”等R软件包进行差异表达基因筛选，结合DAVID和STRING在线生物信息学工具对差异表达基因进行调控网络分析并构建蛋白质-蛋白质相互作用(PPI)网络，通过Cytoscape软件中的Cytohubba插件筛选Hub基因。结果:共筛选出肾嫌色细胞癌差异表达基因261个，包括194个表达下调基因，67个表达上调基因。对差异表达基因进行基因富集(GO)分析和京都基因与基因组百科全书(KEGG)通路富集分析以挖掘其生物学功能，其中GO富集分析中的生物学过程(BP)主要富集于细胞分泌、糖异生和细胞增殖调控；在细胞组成(CC)主要富集于细胞外泌体、细胞质膜及其组成部分；在分子功能(MF)主要富集于肝素结合，在KEGG通路分析中主要富集于代谢通路、抗体的生物合成、蛋白质消化吸收、肾素-血管紧张素系统等。利用在线生物信息学工具构建PPI网络，通过Cytoscape软件中的Cytohubba插件筛选前10位Hub基因，分别是胡椒酸和肌氨酸氧化酶(PIPOX)、羟基酸氧化酶2(HAO2)、犬尿氨酸-3-单加氧酶(KMO)、溶质转运家族2成员2(SLC2A2)、甲酰亚胺基转移酶环脱氨酶(FTCD)、血管生成素(ANG)、催化多肽-1(APOBEC1)互补因子(A1CF)、重组表达醛脱氢酶8A1(ALDH8A1)、维生素D结合蛋白(GC)、血浆富含组氨酸糖蛋白(HRG)。结论:利用生物信息学方法分析肾嫌色细胞癌的差异表达基因，可有效发掘这些差异表达基因的相互作用信息，为肾嫌色细胞癌的治疗提供新的思路。“,”Objective:Bioinformatics was used to analyze the gene expression profile of renal chromophobe cell carcinoma (RCCC) to find out the key genes of RCCC.Methods:Chromophobe renal cell carcinoma gene chip data GSE15641 and GSE11151 were downloaded from the GEO database. Using R software packages such as “ Affy” and “ limma” in R software to screen differentially expressed genes, combining with David and STRING online bioinformatics tools to analyze the regulatory network of differentially expressed genes and construct protein-protein interaction (PPI) network, the Hub gene was screened through the Cytohubba plug-in of Cytoscape software.Results:A total of 261 differentially expressed genes were screened, including 194 down-regulated genes and 67 up-regulated genes. Gene enrichment (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to explore their biological functions. In GO enrichment analysis, biological processes were mainly enriched in cell secretion, gluconeogenesis and cell proliferation regulation; in cell composition, they were mainly enriched in exosomes, plasma membranes and their components; in molecular function, they were mainly enriched in heparin binding; in KEGG pathway analysis, they were mainly enriched in metabolic pathway, antibody biosynthesis pathway and renin angiotensin system pathway. PPI network was constructed by using online bioinformatics tools. The top 10 Hub genes were screened by using cytohubba plug-in in Cytoscape software, which were pipecolic acid and sarcosine oxidase (PIPOX), hydroxyacid oxidase 2 (HAO2), kynurenine 3-monooxygenase (KMO), solute carrier family 2 member 2 (SLC2A2), formimidoyltransferase cyclodeaminase (FTCD), angiogenin (ANG), APOBEC1 complementation factor (A1CF), aldehyde dehydrogenase 8 family member A1 (ALDH8A1), vitamin D binding protein (GC), histidine rich glycoprotein (HRG).Conclusions:Bioinformatics analysis of differentially expressed genes in renal chromophobe cell carcinoma can effectively explore the interaction information of these differentially expressed genes, and provide new ideas for the treatment of renal chromophobe cell carcinoma.