Table_4_Cuproptosis-related modification patterns depict the tumor microenvironment, precision immunotherapy, and prognosis of kidney renal clear cell carcinoma.xlsx

BackgroundDue to the different infiltration abundance of immune cells in tumor, the efficacy of immunotherapy varies widely among individuals. Recently, growing evidence suggested that cuproptosis has impact on cancer immunity profoundly. However, the comprehensive roles of cuproptosis-related genes in tumor microenvironment (TME) and in response to immunotherapy are still unclear.
MethodsBased on 43 cuproptosis-related genes, we employed unsupervised clustering to identify cuproptosis-related patterns and single-sample gene set enrichment analysis algorithm to build a cuproptosis signature for individual patient’s immune cell infiltration and efficacy of immune checkpoint blockade (ICB) evaluation. Then, the cuproptosis-related genes were narrowed down using univariate Cox regression model and least absolute shrinkage and selection operator algorithm. Finally, a cuproptosis risk score was built by random survival forest based on these narrowed-down genes.
ResultsTwo distinct cuproptosis-related patterns were developed, with cuproptosis cluster 1 showing better prognosis and higher enrichment of immune-related pathways and infiltration of immune cells. For individual evaluation, the cuproptosis signature that we built could be used not only for predicting immune cell infiltration in TME but also for evaluating an individual’s sensitivity to ICBs. Patients with higher cuproptosis signature scores exhibited more activated cancer immune processes, higher immune cell infiltration, and better curative efficacy of ICBs. Furthermore, a robust cuproptosis risk score indicated that patients with higher risk scores showed worse survival outcomes, which could be validated in internal and external validation cohorts. Ultimately, a nomogram which combined the risk score with the prognostic clinical factors was developed, and it showed excellent prediction accuracy for survival outcomes.
ConclusionDistinct cuproptosis-related patterns have significant differences on prognosis and immune cell infiltration in kidney renal clear cell carcinoma (KIRC). Cuproptosis signature and risk score are able to provide guidance for precision therapy and accurate prognosis prediction for patients with KIRC.

研究背景：由于肿瘤组织中免疫细胞浸润丰度存在差异，免疫治疗的疗效在个体间呈现显著异质性。近年来，越来越多的研究证据表明铜死亡（Cuproptosis）对癌症免疫具有深远影响。然而，铜死亡相关基因在肿瘤微环境（TME）以及免疫治疗应答中的全面作用仍未明确。
研究方法：本研究基于43个铜死亡相关基因，采用无监督聚类方法识别铜死亡相关亚型，并通过单样本基因集富集分析算法构建铜死亡评分模型，用于评估个体患者的免疫细胞浸润情况与免疫检查点阻断（ICB）治疗疗效。随后，通过单因素Cox回归模型与最小绝对收缩和选择算子算法筛选核心铜死亡相关基因。最终，基于上述筛选得到的基因，利用随机生存森林构建铜死亡风险评分模型。
研究结果：本研究确立了两种不同的铜死亡相关亚型，其中铜死亡聚类1型表现出更优的预后结局，且免疫相关通路富集程度与免疫细胞浸润水平更高。针对个体患者评估而言，本研究构建的铜死亡评分模型不仅可用于预测肿瘤微环境中的免疫细胞浸润情况，还可评估个体对免疫检查点阻断治疗的敏感性。铜死亡评分较高的患者呈现出更活化的癌症免疫进程、更高的免疫细胞浸润水平以及更佳的免疫检查点阻断治疗疗效。此外，稳健的铜死亡风险评分显示，风险评分较高的患者生存结局更差，该结果可在内部及外部验证队列中得到验证。最后，本研究构建了整合风险评分与预后临床因素的列线图，该列线图对患者生存结局具有出色的预测准确性。
研究结论：肾透明细胞癌（KIRC）中不同的铜死亡相关亚型在预后与免疫细胞浸润方面存在显著差异。铜死亡评分模型与风险评分可为肾透明细胞癌患者的精准治疗与精准预后预测提供指导。