DNA methylation signatures for 2016 WHO classification subtypes of diffuse gliomas.
DNA methylation signatures for 2016 WHO classification subtypes of diffuse gliomas.
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DOI：
10.1186/s13148-017-0331-9
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发表时间：
2017
影响因子：
5.7
通讯作者：
Somasundaram K
中科院分区：
文献类型：
--
作者：
Paul Y;Mondal B;Patil V;Somasundaram K
胶质瘤是所有原发性脑肿瘤中最常见的，预后差，死亡率高。 2016年世界卫生组织对中枢神经系统肿瘤的分类除了组织学之外还使用分子参数重新定义了许多肿瘤实体。新的分类方案根据组织学将弥漫性胶质瘤分为低级别胶质瘤（LGG）和胶质母细胞瘤（GBM）。 LGG 进一步分为异柠檬酸脱氢酶 (IDH) 野生型或突变型，后者进一步分为具有 1p/19q 共缺失的少突胶质细胞瘤或具有完整 1p/19q 位点但富含 ATRX 丢失和 TP53 突变的弥漫性星形细胞瘤。 GBM 分为对应于原发性或新生 GBM 的 IDH 野生型和对应于继发性或进行性 GBM 的 IDH 突变体。为了使 2016 年 WHO 弥漫性胶质瘤亚型更加可靠，我们进行了微阵列预测分析 (PAM)，以开发这些亚型的 DNA 甲基化特征。在本研究中，我们将 PAM 应用于源自癌症基因组图谱 (TCGA) 的一组弥漫性神经胶质瘤训练集，并鉴定了 DNA 甲基化特征，以将 LGG IDH 野生型与 LGG IDH 突变体、具有 1p/19q 共缺失的 LGG IDH 突变体与完整 1p/19q 位点的 LGG IDH 突变体进行分类，将 GBM IDH 野生型与 GBM IDH 突变体进行分类，准确度为 99–100%。使用源自 TCGA 的弥漫性神经胶质瘤样本测试集对特征进行了验证，准确度为 96% 至 99%。此外，我们还使用独立的 LGG 和 GBM 队列对所有三个签名进行了额外验证。此外，甲基化特征识别出一部分样本不一致，这些样本被发现具有甲基化特征识别的亚型的典型分子和临床特征。因此，我们确定了能够准确分类弥漫性胶质瘤不同亚型的甲基化特征，并提出这些特征可以补充2016年世界卫生组织弥漫性胶质瘤分类方案。本文的在线版本 (doi:10.1186/s13148-017-0331-9) 包含补充材料，可供授权用户使用。
Glioma is the most common of all primary brain tumors with poor prognosis and high mortality. The 2016 World Health Organization classification of the tumors of central nervous system uses molecular parameters in addition to histology to redefine many tumor entities. The new classification scheme divides diffuse gliomas into low-grade glioma (LGG) and glioblastoma (GBM) as per histology. LGGs are further divided into isocitrate dehydrogenase (IDH) wild type or mutant, which is further classified into either oligodendroglioma that harbors 1p/19q codeletion or diffuse astrocytoma that has an intact 1p/19q loci but enriched for ATRX loss and TP53 mutation. GBMs are divided into IDH wild type that corresponds to primary or de novo GBMs and IDH mutant that corresponds to secondary or progressive GBMs. To make the 2016 WHO subtypes of diffuse gliomas more robust, we carried out Prediction Analysis of Microarrays (PAM) to develop DNA methylation signatures for these subtypes. In this study, we applied PAM on a training set of diffuse gliomas derived from The Cancer Genome Atlas (TCGA) and identified DNA methylation signatures to classify LGG IDH wild type from LGG IDH mutant, LGG IDH mutant with 1p/19q codeletion from LGG IDH mutant with intact 1p/19q loci and GBM IDH wild type from GBM IDH mutant with an accuracy of 99–100%. The signatures were validated using the test set of diffuse glioma samples derived from TCGA with an accuracy of 96 to 99%. In addition, we also carried out additional validation of all three signatures using independent LGG and GBM cohorts. Further, the methylation signatures identified a fraction of samples as discordant, which were found to have molecular and clinical features typical of the subtype as identified by methylation signatures. Thus, we identified methylation signatures that classified different subtypes of diffuse glioma accurately and propose that these signatures could complement 2016 WHO classification scheme of diffuse glioma. The online version of this article (doi:10.1186/s13148-017-0331-9) contains supplementary material, which is available to authorized users.