The Hypoxic Landscape Stratifies Gastric Cancer Into 3 Subtypes With Distinct M6a Methylation and Tumor Microenvironment Infiltration Characteristics.
The Hypoxic Landscape Stratifies Gastric Cancer Into 3 Subtypes With Distinct M6a Methylation and Tumor Microenvironment Infiltration Characteristics.
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缺氧环境将胃癌分为具有不同 M6a 甲基化和肿瘤微环境浸润特征的 3 个亚型
DOI：
10.3389/fimmu.2022.860041
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发表时间：
2022
影响因子：
7.3
通讯作者：
中科院分区：
文献类型：
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缺氧与RNA N6-甲基腺苷（m6 A）之间的相互作用是一个新兴的研究热点。然而，在胃癌（GC）中，不同缺氧水平下m6 A修饰的变化仍然未知。进行无监督层次聚类以将样本分层到不同的聚类中。差异表达基因分析、单变量考克斯比例风险回归分析和风险比计算用于建立m6 A评分以量化m6 A调节因子修饰模式。在使用最小绝对收缩和选择算子（LASSO）和自举的算法，我们确定了最佳的候选预测基因。因此，我们建立了一个m6 A相关的缺氧通路基因预后标志，并建立了诺模图来评估其预测能力。该图的曲线下面积（AUC）值为0.811，高于风险评分（AUC=0.695）和分期（AUC=0.779），表明该图具有较高的可信度。此外，抗PD-1/CTLA-4免疫治疗的临床反应在高风险和低风险患者之间显示出显著差异。我们的研究成功地探索了一个全新的GC病理分类的基础上缺氧通路基因和m6 A修饰模式的定量。全面的免疫分析和验证表明，缺氧簇是可靠的，我们的签名可以为GC患者的临床决策和免疫策略提供新的方法。
The interaction between hypoxia and RNA N6-methyladenosine (m6A) is an emerging focus of investigation. However, alterations in m6A modifications at distinct hypoxia levels remain uncharacterized in gastric cancer (GC). Unsupervised hierarchical clustering was performed to stratify samples into different clusters. Differentially expressed gene analysis, univariate Cox proportional hazards regression analysis, and hazard ratio calculations were used to establish an m6A score to quantify m6A regulator modification patterns. After using an algorithm integrating Least absolute shrinkage and selection operator (LASSO) and bootstrapping, we identified the best candidate predictive genes. Thence, we established an m6A-related hypoxia pathway gene prognostic signature and built a nomogram to evaluate its predictive ability. The area under the curve (AUC) value of the nomogram was 0.811, which was higher than that of the risk score (AUC=0.695) and stage (AUC=0.779), suggesting a high credibility of the nomogram. Furthermore, the clinical response of anti-PD-1/CTLA-4 immunotherapy between high- and low-risk patients showed a significant difference. Our study successfully explored a brand-new GC pathological classification based on hypoxia pathway genes and the quantification of m6A modification patterns. Comprehensive immune analysis and validation demonstrated that hypoxia clusters were reliable, and our signature could provide a new approach for clinical decision-making and immunotherapeutic strategies for GC patients.