Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China.
Translational Medicine Research and Cooperation Center of Northern China, Heilongjiang Academy of Medical Sciences, Harbin 150081, China.
Brief Bioinform. 2021 Sep 2;22(5). doi: 10.1093/bib/bbab013.
m6A RNA methylation is an emerging epigenetic modification, and its potential role in immunity and stemness remains unknown. Based on 17 widely recognized m6A regulators, the m6A modification patterns and corresponding characteristics of immune infiltration and stemness of 1152 low-grade glioma samples were comprehensively analyzed. Machine-learning strategies for constructing m6AScores were trained to quantify the m6A modification patterns of individual samples. Here, we reveal a significant correlation between the multi-omics data of regulators and clinicopathological parameters. We identified two distinct m6A modification patterns (an immune-activated differentiation pattern and an immune-desert dedifferentiation pattern) and four regulatory patterns of m6A methylation on immunity and stemness. We show that the m6AScores can predict the molecular subtype of low-grade glioma, the abundance of immune infiltration, the enrichment of signaling pathways, gene variation and prognosis. The concentration of high immunogenicity and clinical benefits in the low-m6AScore group confirmed the sensitive response to radio-chemotherapy and immunotherapy in patients with high-m6AScore. The results of the pan-cancer analyses illustrate the significant correlation between m6AScore and clinical outcome, the burden of neoepitope, immune infiltration and stemness. The assessment of individual tumor m6A modification patterns will guide us in improving treatment strategies and developing objective diagnostic tools.
m6A RNA 甲基化是一种新兴的表观遗传修饰，其在免疫和干性中的潜在作用尚不清楚。基于 17 种广泛认可的 m6A 调节剂，全面分析了 1152 例低级别胶质瘤样本的免疫浸润和干性的 m6A 修饰模式及其相应特征。构建 m6AScores 的机器学习策略用于量化单个样本的 m6A 修饰模式。在这里，我们揭示了调节剂的多组学数据与临床病理参数之间存在显著相关性。我们确定了两种不同的 m6A 修饰模式（免疫激活分化模式和免疫荒漠去分化模式）和四种免疫和干性的 m6A 甲基化调控模式。我们表明，m6AScores 可以预测低级别胶质瘤的分子亚型、免疫浸润的丰度、信号通路的富集、基因变异和预后。低 m6AScore 组中高免疫原性和临床获益的浓度证实了高 m6AScore 患者对放化疗和免疫治疗的敏感反应。泛癌分析的结果说明了 m6AScore 与临床结局、新抗原负荷、免疫浸润和干性之间存在显著相关性。评估个体肿瘤的 m6A 修饰模式将指导我们改进治疗策略和开发客观的诊断工具。
