Gliomas are currently classified through integration of histology and mutation information, with new developments in DNA methylation classification. However, discrepancies exist amongst the major classification methods. This study sought to compare transcriptome-based classification to the established methods. RNAseq and microarray data were obtained for 1032 gliomas from the TCGA and 395 gliomas from REMBRANDT. Data were analyzed using unsupervised and supervised learning and other statistical methods. Global transcriptomic profiles defined four transcriptomic glioma subgroups with 91.4% concordance with the WHO-defined mutation subtypes. Using these subgroups, 168 genes were selected for the development of 1000 linear support vector classifiers (LSVC). Based on plurality voting of 1000 LSVC, the final ensemble classifier confidently classified all but 17 TCGA gliomas to one of the four transcriptomic profile (TP) groups. The classifier was validated using a gene expression microarray dataset. TP1 cases include IDHwt, glioblastoma high immune infiltration and cellular proliferation and poor survival prognosis. TP2a is characterized as IDHmut-codel, oligodendrogliomas with high tumor purity. TP2b tissue is mostly composed of neurons and few infiltrating malignant cells. TP3 exhibit increased NOTCH signaling, are astrocytoma and IDHmut-non-codel. TP groups are highly concordant with both WHO integrated histology and mutation classification as well as methylation-based classification of gliomas. Transcriptomic profiling provides a robust and objective method to classify gliomas with high agreement to the current WHO guidelines and may provide additional survival prediction to the current methods.

目前胶质瘤的分类是通过组织学和突变信息的整合，DNA甲基化分类有了新的进展。然而，主要分类方法之间存在差异。本研究试图将基于转录组的分类与已建立的方法进行比较。从 TCGA 获得了 1032 个神经胶质瘤，从 REMBRANDT 获得了 395 个神经胶质瘤的 RNAseq 和微阵列数据。使用无监督和监督学习以及其他统计方法来分析数据。全球转录组学概况定义了四个转录组神经胶质瘤亚组，与 WHO 定义的突变亚型的一致性为 91.4%。使用这些亚组，选择了 168 个基因来开发 1000 个线性支持向量分类器 (LSVC)。基于 1000 个 LSVC 的多数投票，最终的集成分类器自信地将除 17 个 TCGA 神经胶质瘤之外的所有肿瘤分类到四个转录组谱 (TP) 组之一。使用基因表达微阵列数据集验证分类器。 TP1病例包括IDHwt、胶质母细胞瘤高免疫浸润和细胞增殖以及生存预后差。 TP2a 的特征是 IDHmut-codel，具有高肿瘤纯度的少突胶质细胞瘤。 TP2b组织主要由神经元和少量浸润的恶性细胞组成。 TP3 表现出增加的 NOTCH 信号传导，属于星形细胞瘤和 IDHmut-non-codel。 TP 组与 WHO 综合组织学和突变分类以及基于甲基化的神经胶质瘤分类高度一致。转录组学分析提供了一种稳健而客观的方法来对神经胶质瘤进行分类，与当前的世界卫生组织指南高度一致，并且可以为当前的方法提供额外的生存预测。