m5C methylation⁃related genes predict prognosis in renal clear cell carcinoma
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摘要:
目的：利用肿瘤基因组图谱(the Cancer Genome Atlas，TCGA)数据库中的数据，构建m5C甲基化相关基因组成的生存预后模型，分析与肾透明细胞癌生存有关的独立预后影响因素以预测肾透明细胞癌患者的预后。方法：从TCGA数据库下载肾透明细胞癌患者资料，从已发表的文献中获取m5C甲基化相关基因并分析其在肿瘤组和对照组间的表达差异。对这些基因进行共识聚类分析以揭示m5C甲基化相关基因与肾透明细胞癌预后之间的关系。通过单变量Cox分析和Lasso⁃Cox回归分析构建出生存预后模型并分析与肾透明细胞癌相关的预后影响因素，GO和KEGG富集分析进一步探索生物功能和潜在的信号通路。通过qRT⁃PCR验证m5C甲基化相关基因在肾透明细胞癌细胞系及组织和正常肾细胞系及组织之间的差异表达。 结果：m5C甲基化相关基因在肾透明细胞癌肿瘤组和正常组之间存在差异性表达。共识聚类分析结果显示亚群1的肾透明细胞癌患者预后优于亚群2。构建的生存预后模型将肾透明细胞癌分为高风险组和低风险组，单变量和多变量Cox分析显示分级和分期可能是肾透明细胞癌的独立预后因素，而GO和KEGG分析显示m5C⁃RNA甲基化修饰可影响肾透明细胞癌的进展。 此外，qRT⁃PCR实验也证实m5C甲基化相关基因在肾透明细胞癌肿瘤组和正常组之间表达存在差异。结论：本文构建的m5C 甲基化相关基因的生存预后模型可以预测肾透明细胞癌患者的预后。
Abstract:
Objective：This study aims to use the data from the Cancer Genome Atlas(TCGA)database to construct a survival prognostic model composed of m5C methylation⁃related genes，and to analyze the independent prognostic factors related to the survival of patients with renal clear cell carcinoma(RCCC)to predict the prognosis of RCCC. Methods：The data of patients with RCCC were downloaded from the TCGA database，m5C methylation⁃related genes were obtained from the published literature，and their differential expression between the tumor group and the control group was analyzed. Consensus clustering analysis was then performed to reveal the relationship between m5C methylation ⁃ related genes and prognosis of RCCC. A survival prognostic model was constructed by univariate Cox analysis and Lasso ⁃Cox regression analysis to analyze the prognostic factors associated with RCCC. Finally，GO and KEGG enrichment analysis was performed to further explore biological functions and potential signaling pathways. In addition，we also performed qRT ⁃PCR experiments to measure the differential expression of m5C methylation ⁃ related genes between cancer cells and normal cell lines or between RCCC and adjacent normal tissue. Results：We found that m5C methylation ⁃ related genes were differentially expressed between the tumor group and the normal group in RCCC. The results of consensus clustering analysis showed that the prognosis of patients with RCCC in cluster 1 was better than that in cluster 2.The constructed survival prognostic model divided RCCC into high⁃risk group and low⁃risk group. Univariate and multivariate Cox analysis showed that grade and stage may be independent prognostic factors for RCCC. GO and KEGG analysis showed that m5C ⁃ RNA modification helps to regulate the progression of RCCC. In addition，qRT ⁃ PCR experiments also confirmed that m5C methylation ⁃ related genes are differentially expressed between the tumor group and the normal group in RCCC. Conclusion：The survival prognostic model of m5C methylation⁃related genes constructed by this research can predict the prognosis of patients with RCCC.
