Suppr超能文献

鉴定免疫原性细胞死亡相关基因特征可预测透明细胞肾细胞癌的生存和免疫治疗敏感性。

Identification of an immunogenic cell death-related gene signature predicts survival and sensitivity to immunotherapy in clear cell renal carcinoma.

机构信息

Department of Urology, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.

出版信息

Sci Rep. 2023 Mar 17;13(1):4449. doi: 10.1038/s41598-023-31493-z.

Abstract

Immunogenic cell death (ICD) is the trigger of adaptive immune responses. However, the role of ICD-related genes in clear cell renal carcinoma (ccRCC) remains unclear. We aimed to identify biomarkers associated with ICD and develop an ICD-related predictive model that predicts the immune microenvironment, prognosis, and response to immunotherapy in ccRCC. Our study included 739 patients (603 in the training set and 136 in the validation set) with clinicopathologic information and transcriptome sequencing data. Consensus clustering, principal component analysis (PCA), weighted gene co-expression network analysis (WGCNA), univariate COX analysis, multivariate COX analysis, and the Lasso-Cox algorithm were applied to shrink predictors and construct a predictive signature of overall survival (OS). We used CIBERSORT, ESTIMATE, and TIMER in the R package IOBR to evaluate the tumor microenvironment and immune infiltration pattern of each sample. Finally, the single cell sequencing results of immune cells in ccRCC were used to verify the results of immune infiltration analysis, and the performance of the prognostic model was evaluated by calibration curves and c-index. This study revealed that inability of the initial immune response and primary immunodeficiency were significantly enriched in the ICD subgroup with poor prognosis. We found that the ten candidate ICD genes (CALR, ENTPD1, FOXP3, HSP90AA1, IFNB1, IFNG, IL6, LY96, PIK3CA, and TLR4) could affect the prognosis of ccRCC (p < 0.05). The prediction model (PRE) we constructed can not only predict the long-term survival probability but also evaluate the landscape of immune infiltration in ccRCC. Our study demonstrated that low infiltration of dendritic cells in ccRCC implies a poor prognosis, whereas the degree of CTL infiltration is less important. An individualized prediction model was created to predict the 1-, 2-, 3-, and 5-year survival and responsiveness of ccRCC patients to immunotherapy, which may serve as a potent tool for clinicians to make better treatment decisions and thus improve the overall survival (OS) of ccRCC patients in the future.

摘要

免疫原性细胞死亡(ICD)是适应性免疫反应的触发因素。然而,ICD 相关基因在透明细胞肾细胞癌(ccRCC)中的作用尚不清楚。我们旨在鉴定与 ICD 相关的生物标志物,并开发一个 ICD 相关的预测模型,以预测 ccRCC 的免疫微环境、预后和对免疫治疗的反应。我们的研究包括 739 名患者(训练集 603 名,验证集 136 名)的临床病理信息和转录组测序数据。采用共识聚类、主成分分析(PCA)、加权基因共表达网络分析(WGCNA)、单变量 COX 分析、多变量 COX 分析和 Lasso-Cox 算法对预测因子进行收缩,并构建总生存期(OS)的预测特征。我们使用 R 包 IOBR 中的 CIBERSORT、ESTIMATE 和 TIMER 评估每个样本的肿瘤微环境和免疫浸润模式。最后,使用 ccRCC 免疫细胞的单细胞测序结果验证免疫浸润分析结果,并通过校准曲线和 c 指数评估预后模型的性能。本研究表明,初始免疫反应无能和原发性免疫缺陷在预后不良的 ICD 亚组中显著富集。我们发现,十个候选 ICD 基因(CALR、ENTPD1、FOXP3、HSP90AA1、IFNB1、IFNG、IL6、LY96、PIK3CA 和 TLR4)可以影响 ccRCC 的预后(p<0.05)。我们构建的预测模型(PRE)不仅可以预测长期生存概率,还可以评估 ccRCC 中的免疫浸润景观。我们的研究表明,ccRCC 中树突状细胞浸润程度低预示着预后不良,而 CTL 浸润程度则不太重要。建立了个体化预测模型来预测 ccRCC 患者 1、2、3 和 5 年的生存和对免疫治疗的反应性,这可能为临床医生提供一种有力的工具,以便做出更好的治疗决策,从而提高未来 ccRCC 患者的总体生存率(OS)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aead/10023707/30a3ff156e8e/41598_2023_31493_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验