Department of Urology, The First Affiliated Hospital of Ningbo University, Ningbo, 315000, China.
Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
Sci Rep. 2024 Oct 27;14(1):25651. doi: 10.1038/s41598-024-75948-3.
Increasing evidence highlights the important role of ubiquitination in cancer. The objective of our study is to establish a reliable marker for predicting clinical outcomes and treatment responses in patients with clear cell renal cell carcinoma (ccRCC) using genes related to ubiquitination (URGs). The URGs subtypes were identified using consensus clustering based on TCGA-KIRC, and a signature containing the prognostic differentially expressed genes of the subtypes was determined using LASSO and Cox regression analysis. To demonstrate the strength of the signature, verification analyses were performed on both E-MTAB-1980 and TCGA-KIRC test datasets. We developed a nomogram to enhance the effectiveness of our predictive tool. Risk genes expression was determined through RT-qPCR. Six genes were combined to create the URGs signature, which had a highly correlated with patient prognosis in patients with ccRCC. A nomogram was developed based on the URGs signature and clinicopathological characteristics. We found that the predictive power was substantially greater than the other individual predictors. Moreover, the study on the immune microenvironment revealed significant variations in the levels of immune cells and the expression of immune checkpoint genes among the groups categorized as high-risk and low-risk. Furthermore, it was found that immunotherapy yielded better outcomes in cohorts with low risk. The URGs signature might serve as a novel and powerful prognosis biomarker and offer a momentous reference for individualized treatment for patients in ccRCC.
越来越多的证据强调了泛素化在癌症中的重要作用。我们的研究目的是利用与泛素化相关的基因(URGs),为透明细胞肾细胞癌(ccRCC)患者建立一个可靠的预测临床结局和治疗反应的标志物。根据 TCGA-KIRC 数据,使用共识聚类方法确定了 URGs 亚型,并使用 LASSO 和 Cox 回归分析确定了包含亚型预后差异表达基因的特征。为了证明该特征的优势,在 E-MTAB-1980 和 TCGA-KIRC 测试数据集上都进行了验证分析。我们开发了一个列线图来增强预测工具的有效性。通过 RT-qPCR 确定风险基因的表达。将六个基因组合在一起,构建了一个与 ccRCC 患者预后高度相关的 URGs 特征。基于 URGs 特征和临床病理特征,建立了一个列线图。我们发现,与其他单个预测因子相比,该预测模型的预测能力显著提高。此外,对免疫微环境的研究表明,在高风险和低风险组之间,免疫细胞水平和免疫检查点基因的表达存在显著差异。此外,还发现免疫治疗在低风险组中效果更好。URGs 特征可能成为一种新的强大预后生物标志物,为 ccRCC 患者的个体化治疗提供重要参考。