Suppr超能文献

弥漫性胶质瘤的多维尺度分析:在具有预后相关分子亚型发现的 2016 年世界卫生组织分类系统中的应用。

Multidimensional scaling of diffuse gliomas: application to the 2016 World Health Organization classification system with prognostically relevant molecular subtype discovery.

机构信息

Department of Pathology, Division of Neuropathology, University of Washington School of Medicine, 325 9th Avenue, Box 359791, Seattle, WA, 98104, USA.

Division of Human Biology, and Seattle Tumor and Translational Research, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., Mailstop C3-168, Seattle, WA, 98109, USA.

出版信息

Acta Neuropathol Commun. 2017 May 22;5(1):39. doi: 10.1186/s40478-017-0443-7.

Abstract

Recent updating of the World Health Organization (WHO) classification of central nervous system (CNS) tumors in 2016 demonstrates the first organized effort to restructure brain tumor classification by incorporating histomorphologic features with recurrent molecular alterations. Revised CNS tumor diagnostic criteria also attempt to reduce interobserver variability of histological interpretation and provide more accurate stratification related to clinical outcome. As an example, diffuse gliomas (WHO grades II-IV) are now molecularly stratified based upon isocitrate dehydrogenase 1 or 2 (IDH) mutational status, with gliomas of WHO grades II and III being substratified according to 1p/19q codeletion status. For now, grading of diffuse gliomas is still dependent upon histological parameters. Independent of WHO classification criteria, multidimensional scaling analysis of molecular signatures for diffuse gliomas from The Cancer Genome Atlas (TCGA) has identified distinct molecular subgroups, and allows for their visualization in 2-dimensional (2D) space. Using the web-based platform Oncoscape as a tool, we applied multidimensional scaling-derived molecular groups to the 2D visualization of the 2016 WHO classification of diffuse gliomas. Here we show that molecular multidimensional scaling of TCGA data provides 2D clustering that represents the 2016 WHO classification of diffuse gliomas. Additionally, we used this platform to successfully identify and define novel copy-number alteration-based molecular subtypes, which are independent of WHO grading, as well as predictive of clinical outcome. The prognostic utility of these molecular subtypes was further validated using an independent data set of the German Glioma Network prospective glioblastoma patient cohort.

摘要

2016 年,世界卫生组织(WHO)中枢神经系统(CNS)肿瘤分类的最新更新显示,首次通过整合组织形态学特征和反复出现的分子改变来重组脑肿瘤分类。修订后的 CNS 肿瘤诊断标准还试图减少组织学解释的观察者间变异性,并提供与临床结果更相关的更准确分层。例如,弥漫性神经胶质瘤(WHO 分级 II-IV)现在根据异柠檬酸脱氢酶 1 或 2(IDH)突变状态进行分子分层,WHO 分级 II 和 III 的神经胶质瘤根据 1p/19q 缺失状态进行亚分层。目前,弥漫性神经胶质瘤的分级仍然依赖于组织学参数。独立于 WHO 分类标准,癌症基因组图谱(TCGA)弥漫性神经胶质瘤的分子特征多维标度分析已确定了不同的分子亚群,并允许在二维(2D)空间中对其进行可视化。我们使用基于网络的平台 Oncoscape 作为工具,将多维标度衍生的分子群应用于 2016 年 WHO 弥漫性神经胶质瘤分类的 2D 可视化。在这里,我们表明 TCGA 数据的分子多维标度提供了代表 2016 年 WHO 弥漫性神经胶质瘤分类的 2D 聚类。此外,我们还使用该平台成功识别和定义了基于新型拷贝数改变的分子亚型,这些亚型独立于 WHO 分级,并且可以预测临床结果。这些分子亚型的预后效用在德国神经胶质瘤网络前瞻性胶质母细胞瘤患者队列的独立数据集上进一步得到验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef71/5439117/c795314c1ff3/40478_2017_443_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验