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. 2017 Mar;19(2):328-337.
doi: 10.1016/j.jmoldx.2016.10.010. Epub 2016 Dec 30.

Targeted Next-Generation Sequencing in Molecular Subtyping of Lower-Grade Diffuse Gliomas: Application of the World Health Organization's 2016 Revised Criteria for Central Nervous System Tumors

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Targeted Next-Generation Sequencing in Molecular Subtyping of Lower-Grade Diffuse Gliomas: Application of the World Health Organization's 2016 Revised Criteria for Central Nervous System Tumors

Jamal H Carter et al. J Mol Diagn. 2017 Mar.
Free article

Abstract

The 2007 World Health Organization Classification of Tumours of the Central Nervous System classifies lower-grade gliomas [LGGs (grades II to III diffuse gliomas)] morphologically as astrocytomas or oligodendrogliomas, and tumors with unclear ambiguous morphology as oligoastrocytomas. The World Health Organization's newly released (2016) classification incorporates molecular data. A single, targeted next-generation sequencing (NGS) panel was used for detecting single-nucleotide variation and copy number variation in 50 LGG cases originally classified using the 2007 criteria, including 36 oligoastrocytomas, 11 oligodendrogliomas, 2 astrocytomas, and 1 LGG not otherwise specified. NGS results were compared with those from IHC analysis and fluorescence in situ hybridization to assess concordance and to categorize the tumors according to the 2016 criteria. NGS results were concordant with those from IHC analysis in all cases. In 3 cases, NGS was superior to fluorescence in situ hybridization in distinguishing segmental chromosomal losses from whole-arm deletions. The NGS approach was effective in reclassifying 36 oligoastrocytomas as 30 astrocytomas (20 IDH1/2 mutant and 10 IDH1/2 wild type) and 6 oligodendrogliomas, and 1 oligodendroglioma as an astrocytoma (IDH1/2 mutant). Here we show that a single, targeted NGS assay can serve as the sole testing modality for categorizing LGG according to the World Health Organization's 2016 diagnostic scheme. This modality affords greater accuracy and efficiency while reducing specimen tissue requirements compared with multimodal approaches.

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