Department of Urology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
Comput Biol Med. 2024 Nov;182:109210. doi: 10.1016/j.compbiomed.2024.109210. Epub 2024 Sep 27.
Over the past decade, the realm of immunotherapy-based combination therapy has witnessed rapid growth for renal cell carcinoma (RCC), however, success has been constrained thus far. This limitation primarily stems from the absence of biomarkers essential for identifying patients likely to derive benefits from such treatments.
In this study, the immunotherapy-based combination associated score (IBCS) was established using single-sample gene set enrichment analysis (ssGSEA) based on the genes identified in the key modules extracted by weighted correlation network analysis (WGCNA) in the IMmotion151 dataset, a randomized, global phase III trial.
High IBCS patients showed better responses to immunotherapy-based combinations and had longer progression-free survival (PFS). Further transcriptomic analysis revealed that IBCS was negatively correlated to TIDE score, identifying a subset of RCC patients characterized by enrichment of T-effector and moderate cell-cycle/angiogenesis gene expression. Our analysis of hub genes unveiled a novel molecule that could potentially serve as a target antigen in RCC. Validation through multiplex immunofluorescence assays on tissue microarrays (TMAs) containing 180 samples confirmed the pivotal role of this hub gene in immunoregulation. Furthermore, we developed an independent risk score model, which is significant for prognostic evaluation and patient stratification. Notably, we devised a forecasting nomogram using this risk score model, surpassing the IMDC score (a widely accepted risk score for predicting survival in patients undergoing VEGF-targeted therapy) in prognostic accuracy for patients treated with immunotherapy-based combinations.
This study has collectively developed an immunotherapy-based combination associated score, pinpointed effective biomarkers for prognostic and responsiveness of kidney cancer patients to immunotherapy-based combinations, and delved into their potential biological mechanisms, offering promising targets for further exploration.
在过去的十年中，基于免疫疗法的联合治疗在肾细胞癌（RCC）领域取得了快速发展，但迄今为止，这种治疗方法的疗效受到了限制。这种局限性主要源于缺乏识别可能从这些治疗中获益的患者的生物标志物。
本研究采用单样本基因集富集分析（ssGSEA），基于加权相关网络分析（WGCNA）提取的关键模块中鉴定的基因，建立了基于免疫疗法的联合相关评分（IBCS）。该研究使用了 IMmotion151 数据集，这是一项随机、全球性的 III 期临床试验。
高 IBCS 患者对基于免疫疗法的联合治疗反应更好，且无进展生存期（PFS）更长。进一步的转录组分析表明，IBCS 与 TIDE 评分呈负相关，确定了 RCC 患者的一个亚组，其特征是 T 效应细胞富集和中等细胞周期/血管生成基因表达。我们对枢纽基因的分析揭示了一种可能作为 RCC 靶抗原的新型分子。通过对包含 180 个样本的组织微阵列（TMA）进行多重免疫荧光检测验证了该枢纽基因在免疫调节中的关键作用。此外，我们建立了一个独立的风险评分模型，该模型对预后评估和患者分层具有重要意义。值得注意的是，我们使用该风险评分模型开发了一个预测列线图，在预测接受基于免疫疗法的联合治疗的患者的预后方面，其准确性超过了 IMDC 评分（一种广泛用于预测接受 VEGF 靶向治疗的患者生存的风险评分）。
本研究共同开发了一种基于免疫疗法的联合相关评分，确定了有效的生物标志物，用于预测肾细胞癌患者对基于免疫疗法的联合治疗的反应和预后，并探讨了其潜在的生物学机制，为进一步探索提供了有前景的靶点。
