肝细胞癌RNA结合蛋白功能和预后价值系统分析

目的 基于癌症基因组图谱(TCGA)数据库，对肝细胞癌(HCC)组织异常表达的RNA结合蛋白(RBPs)进行系统生物信息学分析，筛选预后标志物和潜在的治疗靶点。方法 从TCGA中下载HCC组织RNA测序数据，测定HCC组织和正常组织差异表达的RBPs,进行功能富集分析和相互作用关系的可视化分析。应用单因素和多因素Cox回归分析筛选与预后显著相关的RBPs并构建预后模型。通过生存分析和ROC曲线分析对预后模型的预测性能进行评估，并在验证队列中进行验证。应用人类蛋白质图谱(HPA)在线数据库对预后模型中RBPs水平进行验证。结果 鉴定出82个差异表达的RBPs,其中55个上调，27个下调；进一步功能富集分析和相互作用研究发现主要与mRNA代谢调控、RNA和mRNA分解代谢、高分子甲基化等有关；LIN28B、SMG5、PPARGC1A、LARP1B和ANG5个RBPs被鉴定为与预后相关的基因，被用于构建预后模型；在验证序列中验证了该预后模型的预测能力，经ROC曲线分析显示该预后模型具有较好的敏感性和特异性；独立预后分析显示，风险得分可作为HCC独立的预后因素。结论 本研究通过对HCC差异表达...

Systematic analysis of functions of RNA-binding proteins in hepatocellular carcinoma

Objective Based on the cancer genome atlas (TCGA) database, we conducted a systematic bioinformatics analysis of abnormal cancerous RNA binding proteins (RBPs) in patients with hepatocellular carcinoma (HCC), with the aim of identifying the prognostic markers and potential therapeutic targets. Methods The cancerous and adjacent liver tissue HCC RNA sequencing data was downloaded from TCGA database, and the functional enrichment analysis and visualization of interaction relationships among them were performed. The univariate and multivariate Cox regression analyses were subsequently applied to identify RBPs that were significantly related to the prognosis and a prognostic model was constructed. The predictive performance of the prognostic model was evaluated by survival analysis and receiver operating characteristic (ROC) curve and was verified in the test cohort. The human protein atlas online database was applied to verify the RBP levels in the prognostic model. Results A total of 82 differentially expressed RBPs were identified, including 55 up-regulated and 27 down-regulated (FDR< 0.05 and |log2 FC|>1); the further functional enrichment and interaction analyses showed that the differentially expressed RBPs were mainly related to regulation of mRNA metabolic process, RNA catabolic, mRNA catabolic process, and macromolecule methylation; five RBP genes, e.g., the LIN28B, SMG5, PPARGC1A, LARP1B, and ANG were identified as prognostic-related genes and were used to construct the prognostic model; the predictive ability of the prognostic model was verified in the test cohort; the ROC curve analysis showed that the prognostic model had good sensitivity and specificity; the independent prognostic analysis showed that the risk score could be an independent prognostic factor for patients with HCC. Conclusion The constructed prognostic prediction model by analyzing the differentially expressed RBPs in cancerous tissues in patients with HCC is reliable, which might be served as a prognostic biomarkers and therapeutic targets.