Department of Pathology, Second Clinical Medical College of ShanXi Medical University, Tai Yuan City, ShanXi Province, China.
Department of Anesthesiology, Second Hospital of ShanXi Medical University, Tai Yuan, ShanXi Province, China.
BMC Cancer. 2023 Jul 12;23(1):649. doi: 10.1186/s12885-023-11150-4.
Clear cell renal cell carcinoma (ccRCC) is the most common renal malignancy, although newly developing targeted therapy and immunotherapy have been showing promising effects in clinical treatment, the effective biomarkers for immune response prediction are still lacking. The study is to construct a gene signature according to ccRCC immune cells infiltration landscape, thus aiding clinical prediction of patients response to immunotherapy.
Firstly, ccRCC transcriptome expression profiles from Gene Expression Omnibus (GEO) database as well as immune related genes information from IMMPORT database were combine applied to identify the differently expressed meanwhile immune related candidate genes in ccRCC comparing to normal control samples. Then, based on protein-protein interaction network (PPI) and following module analysis of the candidate genes, a hub gene cluster was further identified for survival analysis. Further, LASSO analysis was applied to construct a signature which was in succession assessed with Kaplan-Meier survival, Cox regression and ROC curve analysis. Moreover, ccRCC patients were divided as high and low-risk groups based on the gene signature followed by the difference estimation of immune treatment response and exploration of related immune cells infiltration by TIDE and Cibersort analysis respectively among the two groups of patients.
Based on GEO and IMMPORT databases, a total of 269 differently expressed meanwhile immune related genes in ccRCC were identified, further PPI network and module analysis of the 269 genes highlighted a 46 genes cluster. Next step, Kaplan-Meier and Cox regression analysis of the 46 genes identified 4 genes that were supported to be independent prognosis indicators, and a gene signature was constructed based on the 4 genes. Furthermore, after assessing its prognosis indicating ability by both Kaplan-Meier and Cox regression analysis, immune relation of the signature was evaluated including its association with environment immune score, Immune checkpoint inhibitors expression as well as immune cells infiltration. Together, immune predicting ability of the signature was preliminary explored.
Based on ccRCC genes expression profiles and multiple bioinformatic analysis, a 4 genes containing signature was constructed and the immune regulation of the signature was preliminary explored. Although more detailed experiments and clinical trials are needed before potential clinical use of the signature, the results shall provide meaningful insight into further ccRCC immune researches.
透明细胞肾细胞癌（ccRCC）是最常见的肾恶性肿瘤，尽管新的靶向治疗和免疫疗法在临床治疗中显示出了有希望的效果，但仍然缺乏用于预测免疫反应的有效生物标志物。本研究根据 ccRCC 免疫细胞浸润景观构建基因特征，从而辅助临床预测患者对免疫治疗的反应。
首先，我们将 ccRCC 转录组表达谱从基因表达综合数据库（GEO）和免疫相关基因信息从免疫相互作用数据库（IMMPORT）中合并，以鉴定 ccRCC 与正常对照样本相比差异表达且与免疫相关的候选基因。然后，基于蛋白质-蛋白质相互作用网络（PPI）和候选基因的后续模块分析，进一步鉴定出一个用于生存分析的核心基因簇。进一步应用 LASSO 分析构建一个特征，然后通过 Kaplan-Meier 生存分析、Cox 回归和 ROC 曲线分析对该特征进行评估。此外，根据基因特征将 ccRCC 患者分为高风险组和低风险组，然后通过 TIDE 和 Cibersort 分析分别估计两组患者的免疫治疗反应差异和探索相关免疫细胞浸润。
基于 GEO 和 IMMPORT 数据库，我们共鉴定出 269 个在 ccRCC 中差异表达且与免疫相关的候选基因，进一步的 PPI 网络和候选基因模块分析突出了一个 46 个基因簇。下一步，对 46 个基因进行 Kaplan-Meier 和 Cox 回归分析，确定了 4 个被支持为独立预后指标的基因，并基于这 4 个基因构建了一个基因特征。此外，通过 Kaplan-Meier 和 Cox 回归分析评估其预后指示能力后，评估了特征的免疫相关性，包括与环境免疫评分、免疫检查点抑制剂表达以及免疫细胞浸润的相关性。综上所述，初步探索了特征的免疫预测能力。
基于 ccRCC 基因表达谱和多种生物信息学分析，构建了一个包含 4 个基因的特征，并初步探讨了特征的免疫调节作用。虽然在该特征的潜在临床应用之前需要进行更详细的实验和临床试验，但这些结果将为进一步的 ccRCC 免疫研究提供有意义的见解。
