Department of Central Laboratory, the Fifth Hospital of Xiamen, Xiamen, China.
Department of Pharmacy, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Front Immunol. 2022 Aug 11;13:877076. doi: 10.3389/fimmu.2022.877076. eCollection 2022.
Aging is a complex biological process and a major risk factor for cancer development. This study was conducted to develop a novel aging-based molecular classification and score system in clear cell renal cell carcinoma (ccRCC).
Integrative analysis of aging-associated genes was performed among ccRCC patients in the TCGA and E-MTAB-1980 cohorts. In accordance with the transcriptional expression matrix of 173 prognostic aging-associated genes, aging phenotypes were clustered with the consensus clustering approach. The agingScore was generated to quantify aging phenotypes with principal component analysis. Tumor-infiltrating immune cells and the cancer immunity cycle were quantified with the ssGSEA approach. Immunotherapy response was estimated through the TIDE algorithm, and a series of tumor immunogenicity indicators were computed. Drug sensitivity analysis was separately conducted based on the GDSC, CTRP, and PRISM analyses.
Three aging phenotypes were established for ccRCC, with diverse prognosis, clinical features, immune cell infiltration, tumor immunogenicity, immunotherapeutic response, and sensitivity to targeted drugs. The agingScore was developed, which enabled to reliably and independently predict ccRCC prognosis. Low agingScore patients presented more undesirable survival outcomes. Several small molecular compounds and three therapeutic targets, namely, , , and , were determined for the low agingScore patients. Additionally, the high agingScore patients were more likely to respond to immunotherapy.
Overall, our findings introduced an aging-based molecular classification and agingScore system into the risk stratification and treatment decision-making in ccRCC.
衰老属于一种复杂的生物学过程，也是癌症发展的主要风险因素。本研究旨在建立一种基于衰老的新型分子分类和评分系统，用于透明细胞肾细胞癌（ccRCC）。
对 TCGA 和 E-MTAB-1980 队列中的 ccRCC 患者进行衰老相关基因的综合分析。根据 173 个预后相关衰老基因的转录表达矩阵，采用共识聚类方法对衰老表型进行聚类。利用主成分分析生成衰老评分，以量化衰老表型。采用 ssGSEA 方法量化肿瘤浸润免疫细胞和癌症免疫周期。利用 TIDE 算法估计免疫治疗反应，并计算一系列肿瘤免疫原性指标。分别基于 GDSC、CTRP 和 PRISM 分析进行药物敏感性分析。
为 ccRCC 建立了三种衰老表型，具有不同的预后、临床特征、免疫细胞浸润、肿瘤免疫原性、免疫治疗反应和靶向药物敏感性。开发了衰老评分，可用于可靠且独立地预测 ccRCC 的预后。低衰老评分患者的生存结局更差。确定了几种小分子化合物和三个治疗靶点，即、、和、，用于低衰老评分患者。此外，高衰老评分患者更有可能对免疫治疗有反应。
总之，我们的研究结果为 ccRCC 的风险分层和治疗决策引入了一种基于衰老的分子分类和评分系统。
