纳米孔测序作为髓母细胞瘤分类的前沿技术。

IF 16.4 1区 医学 Q1 CLINICAL NEUROLOGY
Mathilde Filser, Jacob Torrejon, Kevin Merchadou, Christelle Dufour, Elodie Girard, Christine Bourneix, Elisa Lemaître, Tarek Gharsalli, Riwan Brillet, Jennifer Wong, David Gentien, Audrey Rapinat, Nicolas Servant, Alexandre Vasiljevic, Anne Isabelle Bertozzi, Sandra Raimbault, Arnault Tauziede Espariat, Benoit Lhermitte, Cécile Faure-Conter, Céline Icher, Claire Berger, Claude Alain Maurage, Damien Bodet, David Meyronet, Emmanuelle Uro-Coste, Emilie De Carli, Fabien Forest, Gilles Palenzuela, Guillaume Chotard, Guillaume Gauchotte, Helene Sudour, Ludovic Mansuy, Marianna Deparis, Matthias Tallegas, Maxime Faisant, Natacha Entz-Werle, Pascale Varlet, Pierre Leblond, Sophie Michalak-Provost, Stéphanie Proust Houdemont, Valérie Rigau, François Doz, Olivier Delattre, Franck Bourdeaut, Olivier Ayrault, Julien Masliah-Planchon
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引用次数: 0

摘要

背景:髓母细胞瘤(Medulloblastoma, MB)是最常见的胚胎恶性脑肿瘤之一。目前的分类将这些肿瘤分为四个分子亚群(WNT, SHH, Group 3和Group 4mb)。最近,建立了一个全面的分类,确定了许多亚型,其中一些表现出预后不良。建立有效的分型方法对准确诊断和患者管理至关重要,在改善预后和减少合并症风险之间取得微妙的平衡。方法:我们评估了纳米孔测序提供临床相关的MB甲基化和拷贝数谱的能力。纳米孔测序应用于44个冷冻MB的EPIC队列,以金标准EPIC阵列为基准,并进一步评估了116 MB的综合诊断队列。95.5%和106/116;91.4%),通过纳米孔测序准确亚组。使用Flongle流动池进行18mb的分析,可以实现更快速、更经济的分析,正确分类率为94.4%(17/18)。纳米孔测序使我们能够准确地对28/30 (93.3%)MB进行亚型分析。结论:这项研究是迄今为止使用纳米孔测序分析的最大MB队列,建立了这种现代创新技术非常适合MB分类的概念证明。纳米孔测序显示了MB精确分型的强大能力,这是一项重要的进步,在未来的临床试验中具有增强患者分层的巨大潜力。它能够提供快速和具有成本效益的结果,牢固地确立了它在MB分类领域的游戏规则改变者地位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nanopore sequencing as a cutting-edge technology for medulloblastoma classification.

Background: Medulloblastoma (MB) is one of the most prevalent embryonal malignant brain tumors. Current classification organizes these tumors into 4 molecular subgroups (WNT, SHH, Group 3, and Group 4 MB). Recently, a comprehensive classification has been established, identifying numerous subtypes, some of which exhibit a poor prognosis. It is critical to establish effective subtyping methods for accurate diagnosis and patient's management that strikes a delicate balance between improving outcomes and minimizing the risk of comorbidities.

Methods: We evaluated the ability of Nanopore sequencing to provide clinically relevant methylation and copy number profiles of MB. Nanopore sequencing was applied to an EPIC cohort of 44 frozen MB, benchmarked against the gold standard EPIC array, and further evaluated on an integrated diagnosis cohort of 116 MB.

Results: Most MB of both cohorts (42/44; 95.5% and 106/116; 91.4%, respectively) were accurately subgrouped by Nanopore sequencing. Employing Flongle flow cells for 18 MB allowed a more rapid and cost-effective analysis, with 94.4% (17/18) being correctly classified. Nanopore sequencing enabled us to accurately subtype 28/30 (93.3%) MB.

Conclusion: This study, conducted on the largest cohort of MB analyzed with Nanopore sequencing to date, establishes the proof of concept that this modern and innovative technology is well-suited for MB classification. Nanopore sequencing demonstrates a robust capacity for precise subtyping of MB, a critical advancement that holds significant potential for enhancing patient stratification in future clinical trials. Its ability to deliver quick and cost-effective results firmly establishes it as a game-changer in the field of MB classification.

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来源期刊
Neuro-oncology
Neuro-oncology 医学-临床神经学
CiteScore
27.20
自引率
6.30%
发文量
1434
审稿时长
3-8 weeks
期刊介绍: Neuro-Oncology, the official journal of the Society for Neuro-Oncology, has been published monthly since January 2010. Affiliated with the Japan Society for Neuro-Oncology and the European Association of Neuro-Oncology, it is a global leader in the field. The journal is committed to swiftly disseminating high-quality information across all areas of neuro-oncology. It features peer-reviewed articles, reviews, symposia on various topics, abstracts from annual meetings, and updates from neuro-oncology societies worldwide.
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