Department of Urology Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, China.
Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Int Immunopharmacol. 2024 Dec 5;142(Pt B):113106. doi: 10.1016/j.intimp.2024.113106. Epub 2024 Sep 16.
Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignancy of the urinary system. Despite the integration of immune checkpoint inhibitors (ICIs) into the treatment paradigm for advanced RCC, resistance to immunotherapy has emerged as a pivotal determinant impacting the clinical outlook of ccRCC. Accumulating evidence underscores the pivotal role of immune evasion-related genes and pathways in enabling tumor escape from host immune surveillance, consequently influencing patients' responsiveness to immunotherapy. Nonetheless, the clinical relevance of immune evasion-related genes in ccRCC patients undergoing immunotherapy remains inadequately understood. In this study, we aggregated RNA sequencing and clinical data from ccRCC patients across three cohorts: the Cancer Genome Atlas (TCGA), CheckMate cohorts, and the JAVELIN Renal 101 trial. Leveraging a curated immune evasion-related gene set from Lawson et al., we employed the LASSO algorithm and Cox regression analysis to identify eight genes (LPAR6, RGS5, NFYC, PCDH17, CENPW, CNOT8, FOXO3, SNRPB) significantly associated with immune therapy prognosis (HR, 3.57; 95 % CI, 2.38-5.35; P<0.001). A predictive algorithm developed utilizing these genes exhibited notable accuracy in forecasting patients' progression-free survival in the training set (AUC, 0.835). Furthermore, stratification of patients by risk score revealed discernible differences in immunotherapy response and tumor microenvironment. In summary, we present a prognostic model intricately linked with immune status and treatment response. For ccRCC patients undergoing immunotherapy, this approach holds promise in aiding clinical decision-making by providing more precise and tailored treatment recommendations.
透明细胞肾细胞癌（ccRCC）是一种常见的泌尿系统恶性肿瘤。尽管免疫检查点抑制剂（ICIs）已被纳入晚期 RCC 的治疗模式，但免疫疗法的耐药性已成为影响 ccRCC 临床前景的关键决定因素。越来越多的证据强调了免疫逃逸相关基因和途径在肿瘤逃避宿主免疫监视中的关键作用，从而影响患者对免疫治疗的反应性。然而，免疫逃逸相关基因在接受免疫治疗的 ccRCC 患者中的临床相关性仍未得到充分理解。在这项研究中，我们汇集了来自三个队列的 ccRCC 患者的 RNA 测序和临床数据：癌症基因组图谱（TCGA）、CheckMate 队列和 JAVELIN Renal 101 试验。利用 Lawson 等人精心筛选的免疫逃逸相关基因集，我们采用 LASSO 算法和 Cox 回归分析，确定了 8 个与免疫治疗预后显著相关的基因（LPAR6、RGS5、NFYC、PCDH17、CENPW、CNOT8、FOXO3、SNRPB）（HR，3.57；95%CI，2.38-5.35；P<0.001）。利用这些基因开发的预测算法在训练集中对患者无进展生存期的预测具有显著的准确性（AUC，0.835）。此外，按风险评分对患者进行分层，发现免疫治疗反应和肿瘤微环境存在明显差异。总之，我们提出了一个与免疫状态和治疗反应密切相关的预后模型。对于接受免疫治疗的 ccRCC 患者，这种方法有望通过提供更精确和定制的治疗建议来帮助临床决策。
