Zhang Ganghua, Yang Jingxin, Fang Jianing, Yu Rui, Yin Zhijing, Chen Guanjun, Tai Panpan, He Dong, Cao Ke, Jiang Jiaode
Department of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Staff Hospital of Central South University, Central South University, Changsha, China.
J Cancer. 2024 Aug 13;15(16):5204-5217. doi: 10.7150/jca.99483. eCollection 2024.
Bladder cancer (BLCA) is a highly heterogeneous tumor. We aim to construct a classifier from the perspective of N6-methyladenosine methylation (m6A) to identify patients with different prognostic risks and treatment responsiveness for precision therapy. Data on gene expression profile, mutation, and clinical characteristics were mainly obtained from the TCGA-BLCA cohort. Unsupervised clustering was performed to construct m6A subtypes. The tumor microenvironment (TME) landscapes were explored by using ssGSEA, ESTIMATE, and MCPcounter algorithms. K-M survival curves and Cox regression analysis were used to demonstrate the significance of m6A subtypes in predicting prognosis. pRRophetic, oncoPredict, and TIDE algorithms were used to evaluate responsiveness to antitumor therapy. A classifier of m6a subtypes was finally developed based on random forest and artificial neural network (ANN). The two m6A subtypes have significantly different m6A-related gene expression profiles and mutational landscapes. TME analysis showed a higher level of stromal and Inhibitory immune components in subtype B compared with subtype A. The m6A subtype is a clinically independent prognostic predictor of BLCA, subtype B has a poorer prognosis. Drug sensitivity analysis showed that subtype B has lower IC50 values and AUC values for cisplatin and docetaxel. Efficacy assessment showed significantly poorer radiotherapy efficacy and lower immunotherapy responsiveness in subtype B. We finally constructed an ANN classifier to accurately classify BLCA patients into two m6A subtypes. Our study developed a classifier for identifying subtypes with different m6A characteristics, and BLCA patients with different m6A subtypes have significantly different prognosis and responsiveness to antitumor therapy.
膀胱癌（BLCA）是一种高度异质性肿瘤。我们旨在从N6-甲基腺嘌呤甲基化（m6A）的角度构建一个分类器，以识别具有不同预后风险和治疗反应性的患者，从而实现精准治疗。基因表达谱、突变和临床特征数据主要来自TCGA-BLCA队列。进行无监督聚类以构建m6A亚型。使用ssGSEA、ESTIMATE和MCPcounter算法探索肿瘤微环境（TME）景观。采用K-M生存曲线和Cox回归分析来证明m6A亚型在预测预后中的意义。使用pRRophetic、oncoPredict和TIDE算法评估对抗肿瘤治疗的反应性。最终基于随机森林和人工神经网络（ANN）开发了一个m6A亚型分类器。两种m6A亚型具有显著不同的m6A相关基因表达谱和突变景观。TME分析显示，与A亚型相比，B亚型的基质和抑制性免疫成分水平更高。m6A亚型是BLCA的临床独立预后预测指标，B亚型预后较差。药物敏感性分析表明，B亚型对顺铂和多西他赛的IC50值和AUC值较低。疗效评估显示，B亚型的放射治疗疗效显著较差，免疫治疗反应性较低。我们最终构建了一个ANN分类器，以准确地将BLCA患者分为两种m6A亚型。我们的研究开发了一种用于识别具有不同m6A特征亚型的分类器，不同m6A亚型的BLCA患者在预后和对抗肿瘤治疗的反应性方面存在显著差异。
