乳头状肾细胞癌诊断和预后相关miRNA的生物信息学研究

Bioinformatics Study of miRNA Related to Diagnosis and Prognosis of Papillary Renal Cell Carcinoma

目的 挖掘乳头状肾细胞癌(PRCC)诊断和预后相关miRNA,探索其临床意义。方法 通过癌症基因组图谱(TCGA)数据库获取PRCC miRNA表达谱数据,包含miRNA-seq和临床数据。利用R语言筛选PRCC组织和正常组织差异表达miRNAs。通过单因素Cox、LASSO及多因素Cox回归分析筛选与预后相关的miRNAs,并绘制受试者工作特征(ROC)曲线评价与预后相关miRNAs诊断PRCC的准确度和敏感度。借助TransmiR和Genecards数据库预测miRNAs的转录因子。通过miRDB、TargetScan、miRTarBase数据库预测miRNAs靶基因,并借助DAVID数据库进行GO及KEGG富集分析。利用TIMER数据库分析靶基因表达与免疫细胞浸润水平的相关性。结果 PRCC组织与正常组织的差异表达miRNAs共163个,其中hsa-miR-34a及hsa-miR-551b与PRCC预后相关,随着肿瘤进展,其表达下调,其高表达则PRCC患者总生存率更高。ROC曲线提示hsa-miR-34a诊断PRCC的曲线下面积(AUC)>0.7,准确度更高。hsa-miR-34a的表达受TP53等44个转录因子的调控。功能富集分析显示hsa-miR-34a的靶基因参与细胞因子负调控、miRNAs与癌症通路等,且参与细胞因子负调控的靶基因PPP1R11及LGR4表达和PRCC多种免疫细胞的浸润水平相关。结论 hsa-miR-34a与PRCC诊断和预后相关,可作为PRCC诊断和预后评估的生物标志物。

Objective To explore the clinical significance of miRNA related to the diagnosis and prognosis of papillary renal cell carcinoma(PRCC).Methods The expression profile data of PRCC miRNA,including miRNA-seq and clinical data,were obtained from the cancer genome map(TCGA)database.R language was used to screen differentially expressed miRNAs between PRCC tissue and normal tissue.The prognostic miRNAs were screened by univariate Cox,LASSO and multivariate Cox regression,and the receiver operating characteristic(ROC)curve was drawn to evaluate the accuracy and sensitivity of prognostic miRNAs in diagnosing PRCC.Prediction of transcription factors of miRNAs with the help of TransmiR and Genecards databases.miRNAs target genes were predicted by miRDB,TargetScan and miRTarBase databases,and GO and KEGG enrichment analysis were carried out by DAVID database.The correlation between target gene expression and immune cell infiltration level was analyzed by TIMER database.Results There were 163 differentially expressed miRNAs in PRCC tissues and normal tissues,among which hsa-miR-34a and hsa-miR-551b were related to the prognosis of PRCC,with the progress of tumor,their expression was down-regulated,and the overall survival rate of PRCC patients was higher with high expression.The ROC curve indicated that the area under the curve(AUC)of hsa-miR-34a in diagnosing PRCC>0.7,the accuracy was higher.The expression of hsa-miR-34a was regulated by 44 transcription factors such as TP53.Functional enrichment analysis showed that the target genes of hsa-miR-34a were involved in the negative regulation of cytokines,miRNAs and cancer pathways,and the expression of target genes PPP1R11 and LGR4 involved in the negative regulation of cytokines was related to the infiltration level of various immune cells in PRCC.Conclusion hsa-miR-34a is related to the diagnosis and prognosis of PRCC,and can be used as a biomarker for the diagnosis and prognosis evaluation of PRCC.