Zheng Haoxiang, Luo Weihan, Li Yuqing, Peng Guoyu, Zhou Dewang, Tang Dongdong, Cheng Jiwen, Wu Song
Luohu Clinical Medicine School, Shantou University Medical College, Shantou University, Shantou, China.
Institute of Urology, The Third Affiliated Hospital of Shenzhen University (Luohu Hospital Group), Shenzhen University, Shenzhen, China.
Front Cell Dev Biol. 2022 Mar 3;10:837849. doi: 10.3389/fcell.2022.837849. eCollection 2022.
Bladder urothelial carcinoma (BLCA) is one of the most common malignant tumors with high morbidity and recurrence rate. The study aims to establish a prediction model to elaborate the relation between inflammatory response and prognosis of BLCA and thus to evaluate the potential prognostic value of inflammatory response-related genes (IRGs) in therapeutic choices. The study utilized the gene expression profiles from the The Cancer Genome Atlas and Gene Expression Omnibus (GSE32894) datasets. Differentially expressed IRGs between normal and tumor tissues were identified, and 10 of them were correlated with overall survival (OS) ( < 0.05). Then, the LASSO-Cox regression analysis was applied to optimize the signature. RNA sequencing data of patients with BLCA from GSE32894 were applied as a validation set. Cox regression analyses of the seven-gene signature were performed to examine the efficiency of signature in predicting prognosis. Receiver operating characteristic curve analysis was applied to measure the predictive performance of the risk score for OS. Analysis of independent prognostic factors, downstream functional enrichment, drug sensitivity, and immune features were included in this study. The IRG signature (LDLR, ROS1, MMP14, TNFAIP6, MYC, PTGER4, and RIPK2) was used to divide patients into high- and low-risk groups. Cox regression analyses revealed that the risk score was an independent predictive factor. Functional enrichment analysis revealed that genes were enriched in prognosis-related molecular functions and immune-related biological processes. Drug sensitivity and tumor microenvironment correlation analysis indicated that the signature was related to immunotherapy effect. The study defined a new prognostic signature consisting of seven IRGs, which could effectively predict the prognosis of patients with BLCA and reveal relationship of immune features in BLCA with different risk scores. The study also provided a possible indicator for targeted therapy.
膀胱尿路上皮癌（BLCA）是最常见的恶性肿瘤之一，发病率和复发率都很高。本研究旨在建立一个预测模型，以阐明炎症反应与BLCA预后之间的关系，从而评估炎症反应相关基因（IRGs）在治疗选择中的潜在预后价值。该研究利用了来自癌症基因组图谱和基因表达综合数据库（GSE32894）的数据集中的基因表达谱。确定了正常组织和肿瘤组织之间差异表达的IRGs，其中10个与总生存期（OS）相关（<0.05）。然后，应用LASSO-Cox回归分析来优化特征。将来自GSE32894的BLCA患者的RNA测序数据作为验证集。对七基因特征进行Cox回归分析，以检验该特征在预测预后方面的效率。应用受试者工作特征曲线分析来衡量风险评分对OS的预测性能。本研究还包括独立预后因素分析、下游功能富集分析、药物敏感性分析和免疫特征分析。IRG特征（低密度脂蛋白受体、ROS1、基质金属蛋白酶14、肿瘤坏死因子α诱导蛋白6、MYC、前列腺素E受体4和受体相互作用丝氨酸/苏氨酸蛋白激酶2）用于将患者分为高风险组和低风险组。Cox回归分析显示，风险评分是一个独立的预测因素。功能富集分析表明，基因富集于与预后相关的分子功能和与免疫相关的生物学过程。药物敏感性和肿瘤微环境相关性分析表明，该特征与免疫治疗效果相关。该研究定义了一个由七个IRGs组成的新的预后特征，该特征可以有效地预测BLCA患者的预后，并揭示不同风险评分的BLCA患者的免疫特征之间的关系。该研究还为靶向治疗提供了一个可能的指标。
