Wei Dong, Liu Ying, Yuan Ying, Li Yishuai, Zhao Fangchao, Qin Xuebo
Department of Urology, Hebei General Hospital, Shijiazhuang 050000, China.
Department of Neurology, Xingtai Third Hospital, Xingtai 054000, China.
Aging (Albany NY). 2024 Jan 17;16(2):1516-1535. doi: 10.18632/aging.205442.
The cGAS-STING pathway emerges as a pivotal innate immune pathway with the potential to profoundly influence all facets of tumor initiation and progression. The prognostic significance and immunological role of cGAS-STING pathway-related genes (CRGs) in individuals diagnosed with bladder cancer (BLCA) have not yet been fully elucidated.
Performed unsupervised cluster analysis to identify distinct clusters. Utilizing LASSO and multivariate Cox regression analysis to construct a prognostic risk model. The IMvigor210, GSE13507 and GSE78220 cohorts were utilized to explore the potential value of risk score in immune therapy response and survival prediction.
A risk model was developed utilizing four CRGs in order to forecast the overall survival (OS) of BLCA patients. The risk score to be a standalone risk factor, which was further corroborated by the external validation set obtained from the GEO database (GSE13507). We established an integrated nomogram that combined risk scoring and clinical information, exhibiting commendable clinical practicality in predicting the overall survival period of BLCA patients. It is noteworthy that risk score could differentiate tumor microenvironments among different risk groups and individuals who were more responsive to immunotherapy in IMvigor210 and GSE13507 cohorts. experiments, we noted an up-regulation of IRF3 and IKBKB upon the activation of the cGAS-STING pathway. Conversely, the activation of the cGAS-STING pathway resulted in a down-regulation of POLR3G and CTNNB1.
CRG risk model shows promise as a potential stratification approach for bladder cancer patients.
cGAS-STING通路已成为一条关键的固有免疫通路，有可能对肿瘤发生和进展的各个方面产生深远影响。cGAS-STING通路相关基因（CRGs）在膀胱癌（BLCA）患者中的预后意义和免疫作用尚未完全阐明。
进行无监督聚类分析以识别不同的聚类。利用LASSO和多变量Cox回归分析构建预后风险模型。使用IMvigor210、GSE13507和GSE78220队列来探索风险评分在免疫治疗反应和生存预测中的潜在价值。
利用四个CRGs开发了一个风险模型，以预测BLCA患者的总生存期（OS）。风险评分是一个独立的风险因素，来自GEO数据库（GSE13507）的外部验证集进一步证实了这一点。我们建立了一个综合列线图，将风险评分与临床信息相结合，在预测BLCA患者的总生存期方面表现出良好的临床实用性。值得注意的是，风险评分可以区分不同风险组之间的肿瘤微环境，以及在IMvigor210和GSE13507队列中对免疫治疗反应更强的个体。在实验中，我们注意到cGAS-STING通路激活后IRF3和IKBKB上调。相反，cGAS-STING通路的激活导致POLR3G和CTNNB1下调。
CRG风险模型有望成为膀胱癌患者的一种潜在分层方法。
