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使用基于 DNA 甲基化的分类器进行脑肿瘤诊断作为诊断支持工具。

Brain tumour diagnostics using a DNA methylation-based classifier as a diagnostic support tool.

机构信息

Department of Pathology, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands.

Department of Pathology, Odense University Hospital, Odense, Denmark.

出版信息

Neuropathol Appl Neurobiol. 2020 Aug;46(5):478-492. doi: 10.1111/nan.12610. Epub 2020 Apr 7.

Abstract

AIMS

Methylation profiling (MP) is increasingly incorporated in the diagnostic process of central nervous system (CNS) tumours at our centres in The Netherlands and Scandinavia. We aimed to identify the benefits and challenges of MP as a support tool for CNS tumour diagnostics.

METHODS

About 502 CNS tumour samples were analysed using (850 k) MP. Profiles were matched with the DKFZ/Heidelberg CNS Tumour Classifier. For each case, the final pathological diagnosis was compared to the diagnosis before MP.

RESULTS

In 54.4% (273/502) of all analysed cases, the suggested methylation class (calibrated score ≥0.9) corresponded with the initial pathological diagnosis. The diagnosis of 24.5% of these cases (67/273) was more refined after incorporation of the MP result. In 9.8% of cases (49/502), the MP result led to a new diagnosis, resulting in an altered WHO grade in 71.4% of these cases (35/49). In 1% of cases (5/502), the suggested class based on MP was initially disregarded/interpreted as misleading, but in retrospect, the MP result predicted the right diagnosis for three of these cases. In six cases, the suggested class was interpreted as 'discrepant but noncontributory'. The remaining 33.7% of cases (169/502) had a calibrated score <0.9, including 7.8% (39/502) for which no class indication was given at all (calibrated score <0.3).

CONCLUSIONS

MP is a powerful tool to confirm and fine-tune the pathological diagnosis of CNS tumours, and to avoid misdiagnoses. However, it is crucial to interpret the results in the context of clinical, radiological, histopathological and other molecular information.

摘要

目的

甲基化分析(MP)在荷兰和斯堪的纳维亚的中心正越来越多地被纳入中枢神经系统(CNS)肿瘤的诊断过程中。我们旨在确定 MP 作为 CNS 肿瘤诊断支持工具的优势和挑战。

方法

大约 502 个 CNS 肿瘤样本使用(850k)MP 进行分析。将图谱与 DKFZ/海德堡 CNS 肿瘤分类器相匹配。对于每个病例,将最终病理诊断与 MP 前的诊断进行比较。

结果

在所有分析病例的 54.4%(273/502)中,提示的甲基化类别(校准评分≥0.9)与初始病理诊断相符。在这些病例的 24.5%(67/273)中,纳入 MP 结果后诊断更加细化。在 9.8%的病例(49/502)中,MP 结果导致新的诊断,导致这些病例中的 71.4%(35/49)的 WHO 分级发生改变。在 1%的病例(5/502)中,基于 MP 的提示类别最初被忽视/解释为误导,但事后回顾,MP 结果预测了其中三个病例的正确诊断。在六个病例中,提示类别被解释为“不一致但无贡献”。其余 33.7%的病例(169/502)的校准评分<0.9,包括 7.8%(39/502)根本没有类别指示(校准评分<0.3)。

结论

MP 是确认和微调 CNS 肿瘤病理诊断以及避免误诊的有力工具。但是,在解释结果时,必须结合临床、放射学、组织病理学和其他分子信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bfb/7496466/04dd970abee9/NAN-46-478-g001.jpg

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