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将大型下一代测序面板整合到胶质细胞瘤的临床诊断中,为从 FFPE 组织或涂片制备物进行分类提供了一个全面的平台。

Integrating a Large Next-Generation Sequencing Panel into the Clinical Diagnosis of Gliomas Provides a Comprehensive Platform for Classification from FFPE Tissue or Smear Preparations.

机构信息

Department of Pathology, The University of Chicago, Chicago, Illinois.

Department of Radiology, The University of Chicago, Chicago, Illinois.

出版信息

J Neuropathol Exp Neurol. 2019 Mar 1;78(3):257-267. doi: 10.1093/jnen/nly130.

Abstract

The 2016 WHO classification of brain tumors represents a major step towards the integration of molecular data into pathologic diagnoses. Our institution has included massively parallel sequencing technology in the diagnostic work-up of all gliomas since January 2016. The utilized platform successfully identifies copy number variations, individual gene mutations, small insertions and deletions, and selected gene fusions. Herein, we retrospectively review the first 51 glial tumor samples run for clinical purposes using the UCM-OncoPlus platform, a 1213 gene targeted hybrid-capture next generation sequencing (NGS) panel. NGS paired with histomorphology and clinical data allowed for reliable, comprehensive, and cost-effective classification of all the analyzed gliomas (51/51) with minimal tissue required and without the need for additional testing. In addition to detecting all diagnostically relevant mutations according to the 2016 WHO system, our data suggest a large NGS-based platform may improve the accuracy of classifying gliomas beyond the 2016 WHO system, to provide truly personalized diagnostics. Furthermore, this methodology assists in classifying histologically challenging or clinically unusual cases. And, finally, the versatile nature of this testing methodology allows for near effortless expansion as new therapeutic targets and prognostic markers are discovered.

摘要

2016 年世界卫生组织(WHO)脑肿瘤分类代表着将分子数据纳入病理诊断的重要一步。自 2016 年 1 月以来,我们机构已将大规模平行测序技术纳入所有胶质瘤的诊断工作中。该平台成功地识别了拷贝数变异、个别基因突变、小插入和缺失以及特定的基因融合。在此,我们回顾了使用 UCM-OncoPlus 平台进行临床目的的前 51 例胶质肿瘤样本,该平台是一个针对 1213 个基因的靶向杂交捕获下一代测序(NGS)面板。NGS 与组织形态学和临床数据相结合,仅用最小量的组织且无需额外检测,即可可靠、全面且具有成本效益地对所有分析的胶质瘤(51/51)进行分类。除了根据 2016 年 WHO 系统检测到所有具有诊断意义的突变外,我们的数据还表明,大型 NGS 平台可能会提高 2016 年 WHO 系统以外的胶质瘤分类准确性,从而提供真正的个性化诊断。此外,这种方法有助于对组织学上具有挑战性或临床上不常见的病例进行分类。最后,这种测试方法的多功能性允许在发现新的治疗靶点和预后标志物时,几乎毫不费力地进行扩展。

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