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.
Computers in biology and medicine. 2024 Sep 27 [Epub ahead of print]
Zhengfang Liu, Maolin Zang, Kaiyue Li, Wenqiang Qi, Huiyang Yuan, Lipeng Chen, Yan Zhang
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., Medical Integration and Practice Center, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China; Shenzhen Research Institute, Shandong University, Shenzhen, Guangdong, 518057, China. Electronic address: .