Department of Clinical Medicine, Qingdao University, Qingdao, Shandong, 266000, China.
Department of Urology, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China.
BMC Nephrol. 2022 May 5;23(1):172. doi: 10.1186/s12882-022-02801-y.
The dysfunction of RNA binding proteins (RBPs) is associated with various inflammation and cancer. The occurrence and progression of tumors are closely related to the abnormal expression of RBPs. There are few studies on RBPs in clear cell renal carcinoma (ccRCC), which allows us to explore the role of RBPs in ccRCC.
We obtained the gene expression data and clinical data of ccRCC from the Cancer Genome Atlas (TCGA) database and extracted all the information of RBPs. We performed differential expression analysis of RBPs. Risk model were constructed based on the differentially expressed RBPs (DERBPs). The expression levels of model markers were examined by reverse transcription-quantitative PCR (RT-qPCR) and analyzed for model-clinical relevance. Finally, we mapped the model's nomograms to predict the 1, 3 and 5-year survival rates for ccRCC patients.
The results showed that the five-year survival rate for the high-risk group was 40.2% (95% CI = 0.313 ~ 0.518), while the five-year survival rate for the low-risk group was 84.3% (95% CI = 0.767 ~ 0.926). The ROC curves (AUC = 0.748) also showed that our model had stable predictive power. Further RT-qPCR results were in accordance with our analysis (p < 0.05). The results of the independent prognostic analysis showed that the model could be an independent prognostic factor for ccRCC. The results of the correlation analysis also demonstrated the good predictive ability of the model.
In summary, the 4-RBPs (EZH2, RPL22L1, RNASE2, U2AF1L4) risk model could be used as a prognostic indicator of ccRCC. Our study provides a possibility for predicting the survival of ccRCC.
RNA 结合蛋白（RBPs）的功能障碍与各种炎症和癌症有关。肿瘤的发生和发展与 RBPs 的异常表达密切相关。在透明细胞肾细胞癌（ccRCC）中，关于 RBPs 的研究较少，这使得我们能够探索 RBPs 在 ccRCC 中的作用。
我们从癌症基因组图谱（TCGA）数据库中获得了 ccRCC 的基因表达数据和临床数据，并提取了所有 RBP 信息。我们对 RBPs 进行了差异表达分析。基于差异表达 RBPs（DERBPs）构建风险模型。通过逆转录定量 PCR（RT-qPCR）检测模型标志物的表达水平，并分析模型与临床的相关性。最后，我们将模型的列线图映射到预测 ccRCC 患者的 1、3 和 5 年生存率。
结果表明，高危组的 5 年生存率为 40.2%（95%CI=0.3130.518），而低危组的 5 年生存率为 84.3%（95%CI=0.7670.926）。ROC 曲线（AUC=0.748）也表明我们的模型具有稳定的预测能力。进一步的 RT-qPCR 结果与我们的分析一致（p<0.05）。独立预后分析的结果表明，该模型可以作为 ccRCC 的独立预后因素。相关性分析的结果也证明了该模型的良好预测能力。
综上所述，4-RBPs（EZH2、RPL22L1、RNASE2、U2AF1L4）风险模型可作为 ccRCC 的预后指标。我们的研究为预测 ccRCC 的生存提供了一种可能性。
