Biological functions and prognostic value of RNA Binding Proteins in clear cell Renal Cell Carcinoma.

Biological functions and prognostic value of RNA Binding Proteins in clear cell Renal Cell Carcinoma.
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RNA结合蛋白在透明细胞肾细胞癌中的生物学功能和预后价值

DOI:
10.7150/jca.49175
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发表时间:
2020
期刊:
影响因子:
3.9
通讯作者:
Lin J
Lin J
中科院分区:
医学3区
文献类型:
--
作者:
Zhu Z;He A;Lin L;Xu C;Cai T;Lin J

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早期发现和准确评估是改善肾透明细胞癌(ccRCC)患者预后的关键。更重要的是,RNA结合蛋白(RBP)在许多癌症的发生和发展中起着至关重要的作用。然而,限制性商业惯例与ccRCC之间的关系仍不清楚。探索RBP在ccRCC中的潜在生物学功能并建立预测生存概率的预后特征仍然有意义。本研究从TCGA数据库、GEO数据库和ICGC数据库中获得转录组分析和相应的临床信息。利用“edgeR”R软件包,共检测到200个DERBPs,其中上调的128个,下调的72个。基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析表明,DERBPs主要参与调控转录过程和代谢。此外,在PPI网络中还发现了4个中枢基因(RPS 2、RPS 14、RPS 20和RPLP 0),它们可能在这些DERBPs中发挥重要的生物学作用。然后,我们使用LASSO回归来构建预后特征,并在GEO和ICGC队列中验证该特征。时间依赖的受试者工作特征(ROC)曲线显示,该特征可以准确地预测ccRCC患者的预后。然后我们建立了诺模图,校准曲线和ROC曲线表明诺模图可以准确预测ccRCC患者的1年、3年和5年总生存期(AUC值:0.871、0.829和0.816)。总之,我们构建了一个基于10-RBP的预后特征,整合了临床参数来预测ccRCC患者的预后。基于差异表达的RBP(DERBPs)的预后特征可能作为ccRCC中有前途的诊断和预后生物标志物。
Early detection and accurate evaluation were both critical to improving the prognosis of clear cell Renal Cell Carcinoma (ccRCC) patients. More importantly, RNA Binding Proteins (RBPs) play a vital role in the tumorigenesis and progression of numerous cancers. However, the relationship between RBPs and ccRCC is still unclear. Exploring the potential biological functions of RBPs in ccRCC and establishing a prognostic signature to predict the survival probability remains meaningful. In this study, transcriptome profiling and the corresponding clinical information were obtained from the TCGA database, GEO database, and ICGC database. By using the "edgeR" R package, 200 DERBPs were found, including 128 up-regulated and 72 down-regulated RBPs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that DERBPs were mainly involved in regulating transcriptional processes and metabolism. Furthermore, there were 4 hub genes (RPS2, RPS14, RPS20, and RPLP0) were found in the PPI network, which may play vital biological roles among those DERBPs. Then we used LASSO regression to construct a prognostic signature and validated the signature in the GEO and ICGC cohort. The time-dependent receiver operating characteristic (ROC) curve showed that the signature could accurately predict the prognosis of ccRCC patients. Then we established a nomogram, and the calibration curve and ROC curve showed that the nomogram could accurately predict 1-year, 3-year, and 5-year overall survival (OS) of ccRCC patients (The AUC value: 0.871, 0.829, and 0.816). In conclusion, we constructed a 10-RBPs-based prognostic signature integrating clinical parameters to predict the prognosis of ccRCC patients. The prognostic signature based on the differentially expressed RBPs (DERBPs) might serve as promising diagnostic and prognostic biomarkers in ccRCC.
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