Fan Zongyao, Xu Hewei, Ge Qingyu, Li Weilong, Zhang Junjie, Pu Yannan, Chen Zhengsen, Zhang Sicong, Xue Jun, Shen Baixin, Ding Liucheng, Wei Zhongqing
Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Department of Urology, The Second Clinical Medical College of Nanjing Medical University, Nanjing, China.
Front Oncol. 2023 Mar 22;13:1067987. doi: 10.3389/fonc.2023.1067987. eCollection 2023.
There is growing evidence that immune cells are strongly associated with the prognosis and treatment of clear cell renal cell carcinoma (ccRCC). Our aim is to construct an immune subtype-related model to predict the prognosis of ccRCC patients and to provide guidance for finding appropriate treatment strategies.
Based on single-cell analysis of the GSE152938 dataset from the GEO database, we defined the immune subtype-related genes in ccRCC. Immediately afterwards, we used Cox regression and Lasso regression to build a prognostic model based on TCGA database. Then, we carried out a series of evaluation analyses around the model. Finally, we proved the role of VMP1 in ccRCC by cellular assays.
Initially, based on TCGA ccRCC patient data and GEO ccRCC single-cell data, we successfully constructed a prognostic model consisting of five genes. Survival analysis showed that the higher the risk score, the worse the prognosis. We also found that the model had high predictive accuracy for patient prognosis through ROC analysis. In addition, we found that patients in the high-risk group had stronger immune cell infiltration and higher levels of immune checkpoint gene expression. Finally, cellular experiments demonstrated that when the VMP1 gene was knocked down, 786-O cells showed reduced proliferation, migration, and invasion ability and increased levels of apoptosis.
Our study can provide a reference for the diagnosis and treatment of patients with ccRCC.
越来越多的证据表明免疫细胞与透明细胞肾细胞癌（ccRCC）的预后和治疗密切相关。我们的目的是构建一个与免疫亚型相关的模型，以预测ccRCC患者的预后，并为寻找合适的治疗策略提供指导。
基于来自GEO数据库的GSE152938数据集的单细胞分析，我们定义了ccRCC中与免疫亚型相关的基因。随后，我们使用Cox回归和Lasso回归基于TCGA数据库构建了一个预后模型。然后，我们围绕该模型进行了一系列评估分析。最后，我们通过细胞实验证明了VMP1在ccRCC中的作用。
最初，基于TCGA ccRCC患者数据和GEO ccRCC单细胞数据，我们成功构建了一个由五个基因组成的预后模型。生存分析表明，风险评分越高，预后越差。我们还通过ROC分析发现该模型对患者预后具有较高的预测准确性。此外，我们发现高危组患者的免疫细胞浸润更强，免疫检查点基因表达水平更高。最后，细胞实验表明，当VMP1基因被敲低时，786-O细胞的增殖、迁移和侵袭能力降低，凋亡水平升高。
我们的研究可为ccRCC患者的诊断和治疗提供参考。
