Co-expression network analysis identified FCER1G in association with progression and prognosis in human clear cell renal cell carcinoma.
Co-expression network analysis identified FCER1G in association with progression and prognosis in human clear cell renal cell carcinoma.
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DOI：
10.7150/ijbs.21657
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发表时间：
2017
影响因子：
9.2
通讯作者：
Wang X
中科院分区：
文献类型：
--
作者：
Chen L;Yuan L;Wang Y;Wang G;Zhu Y;Cao R;Qian G;Xie C;Liu X;Xiao Y;Wang X
透明细胞肾细胞癌（ccRCC）是肾脏内最常见的实体病变，其预后受复杂的基因相互作用网络的影响。本研究通过分析含有ccRCC和邻近正常组织的微阵列数据GSE66272，鉴定出4042个差异表达基因，并对其进行加权基因共表达网络分析。然后鉴定出12个共表达基因模块。Pearson相关分析发现，蓝色模块与病理分期相关性最高（r = -0.77）。功能富集分析显示，蓝色模组的生物学过程主要集中在炎症反应、免疫反应和趋化性（p < 1e-10）。在显著模块中，共鉴定出38个网络枢纽基因，其中FCER1G与ccRCC进展的相关性最高（r = 0.95）。此外，FCER1G也是蓝色模块中基因蛋白-蛋白相互作用网络中的枢纽节点。因此，随后选择FCER1G进行验证。在测试集GSE53757和rna测序数据中，FCER1G的表达也与ccRCC的四个阶段进展呈正相关（p < 0.001）。受试者工作特征（ROC）曲线显示，FCER1G能够区分局限性（病理期I、II）和非局限性（病理期III、IV） ccRCC （AUC=0.74, p < 0.001）。此外，基于rna测序数据的生存分析显示，FCER1G在临床中也可能是一种预后基因（p < 0.05）。综上所述，通过加权基因共表达分析，FCER1G与ccRCC的进展和预后相关，并可能通过影响免疫相关通路改善预后。
Clear cell renal cell carcinoma (ccRCC) is the most common solid lesion within kidney, and its prognostic is influenced by the progression covering a complex network of gene interactions. In current study, the microarray data GSE66272 containing ccRCC and adjacent normal tissues was analyzed to identify 4042 differentially expressed genes, on which weighted gene co-expression network analysis was performed. Then 12 co-expressed gene modules were identified. The highest association was found between blue module and pathological stage (r = -0.77) by Pearson's correlation analysis. Functional enrichment analysis revealed that biological processes of blue module focused on inflammatory response, immune response, chemotaxis (all p < 1e-10). In the significant module, a total of 38 network hub genes were identified, FCER1G exhibited the highest correlation (r = 0.95) with ccRCC progression. In addition, FCER1G was hub node in the protein-protein interaction network of the genes in blue module as well. Thus, FCER1G was subsequently selected for validation. In the test set GSE53757 and RNA-sequencing data, FCER1G expression was also positively correlated with four stages of ccRCC progression (p < 0.001). Receiver operating characteristic (ROC) curve indicated that FCER1G could distinguish localized (pathological stage I, II) from non-localized (pathological stage III, IV) ccRCC (AUC=0.74, p < 0.001). Besides, FCER1G could be a prognostic gene in clinical practice as well, revealed by survival analysis based on RNA-sequencing data (p < 0.05). In conclusion, using weighted gene co-expression analysis, FCER1G was identified and validated in association with ccRCC progression and prognosis, which might improve the prognosis by influencing immune-related pathways.
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