标题： 跨平台的Group 3 & 4髓母细胞瘤八种分子亚型的DNA甲基化分类器 显示英文标题

标题： Cross-Platform DNA Methylation Classifier for the Eight Molecular Subtypes of Group 3 & 4 Medulloblastoma

摘要： 髓母细胞瘤是一种恶性儿童脑癌，分子亚组的发现正在推动个性化治疗策略的发展。 2019年，一项共识在组3和组4中确定了八个新的亚型，每个亚型都表现出异质性特征。 分类器对于将这些发现转化为临床实践至关重要，它们支持临床试验、个性化治疗的开发和应用以及患者监测。 本研究提出了一种基于DNA甲基化的跨平台机器学习分类器，能够在HM450和EPIC甲基化芯片样本上区分这些亚型。 在两个独立测试集中，该模型实现了加权F1 = 0.95和平衡准确率= 0.957，并且在不同平台上保持一致。 作为首个跨平台解决方案，它提供了向后兼容性，同时扩展到新平台的应用范围，也提高了可及性。 一旦通过网络应用程序部署，它有望成为这些亚型的第一个公开可用的分类器，这将在未来计划实现。 总体而言，这项工作在推进精准医学和改善大多数流行亚组髓母细胞瘤患者临床结果的方向上迈出了重要一步，即组3和组4。 显示英文摘要

摘要： Medulloblastoma is a malignant pediatric brain cancer, and the discovery of molecular subgroups is enabling personalized treatment strategies. In 2019, a consensus identified eight novel subtypes within Groups 3 and 4, each displaying heterogeneous characteristics. Classifiers are essential for translating these findings into clinical practice by supporting clinical trials, personalized therapy development and application, and patient monitoring. This study presents a DNA methylation-based, cross-platform machine learning classifier capable of distinguishing these subtypes on both HM450 and EPIC methylation array samples. Across two independent test sets, the model achieved weighted F1 = 0.95 and balanced accuracy = 0.957, consistent across platforms. As the first cross-platform solution, it provides backward compatibility while extending applicability to a newer platform, also enhancing accessibility. It also has the potential to become the first publicly available classifier for these subtypes once deployed through a web application, as planned in the future. This work overall takes steps in the direction of advancing precision medicine and improving clinical outcomes for patients within the majority prevalence medulloblastoma subgroups, groups 3 and 4.