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Co-expression network analysis identified FCER1G in association with progression and prognosis in human clear cell renal cell carcinoma

机译:共表达网络分析确定了FCER1G与人类透明细胞肾细胞癌的进展和预后相关

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摘要

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 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 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.
机译:透明细胞肾细胞癌(ccRCC)是肾脏内最常见的实体病变,其预后受覆盖基因相互作用的复杂网络的进展的影响。在当前的研究中,分析了包含ccRCC和邻近正常组织的微阵列数据,以鉴定4042个差异表达的基因,并对其进行了加权基因共表达网络分析。然后鉴定了12个共表达的基因模块。通过Pearson相关分析,发现蓝色模块与病理阶段之间的最高关联(r = -0.77)。功能富集分析表明,蓝色模块的生物学过程集中于炎症反应,免疫反应,趋化性(所有p <1e-10)。在重要模块中,总共鉴定出38个网络中心基因,FCER1G与ccRCC进程显示最高相关性(r = 0.95)。此外,FCER1G也是蓝色模块中基因的蛋白质-蛋白质相互作用网络中的枢纽节点。因此,随后选择了FCER1G进行验证。在测试集和RNA测序数据中,FCER1G表达也与ccRCC进展的四个阶段呈正相关(p <0.001)。接收器工作特性(ROC)曲线表明FCER1G可以区分局部(病理I,II期)和非局部(RC,III期)ccRCC(AUC = 0.74,p <0.001)。此外,通过基于RNA测序数据的生存分析显示,FCER1G在临床实践中也可能是预后基因(p <0.05)。总之,使用加权基因共表达分析,与ccRCC进展和预后相关的FCER1G已得到鉴定和验证,这可能通过影响免疫相关途径来改善预后。

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