Multiple approaches converge on three biological subtypes of meningioma and extract new insights from published studies
Multiple approaches converge on three biological subtypes of meningioma and extract new insights from published studies
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DOI：
10.1126/sciadv.abm6247
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发表时间：
2022-02-01
期刊：
影响因子：
13.6
通讯作者：
Patel, Akash J.
中科院分区：
文献类型：
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作者：
Bayley, James C.;Hadley, Caroline C.;Patel, Akash J.
世界卫生组织（WHO）组织病理学分级分类为良性的脑膜瘤中有五分之一会表现为恶性。为了更好地诊断这些肿瘤，几个小组转向DNA甲基化，而我们结合了RNA测序（RNA-seq）和细胞遗传学。这两种方法在识别侵袭性肿瘤方面都比组织病理学更准确，但它们是否揭示了相似的肿瘤类型尚不清楚。因此，我们对110例原发性脑膜瘤（WHO I级和II级）进行了无偏倚的DNA甲基化、RNA-seq和细胞遗传学分析。每种技术都区分了与我们之前的分子分类相同的三个组（两个良性和一个恶性）;将这些方法集成到一个分类器中进一步提高了准确性。计算模型揭示了恶性肿瘤中转录和细胞遗传学变化，特别是染色体1 p丢失之间的强相关性。将我们的分类器应用于以前研究的数据，也解决了按WHO分级对肿瘤进行分组所带来的某些异常。因此，准确的分类将阐明脑膜瘤的生物学，以及改善诊断和预后。
One-fifth of meningiomas classified as benign by World Health Organization (WHO) histopathological grading will behave malignantly. To better diagnose these tumors, several groups turned to DNA methylation, whereas we combined RNA-sequencing (RNA-seq) and cytogenetics. Both approaches were more accurate than histopathology in identifying aggressive tumors, but whether they revealed similar tumor types was unclear. We therefore performed unbiased DNA methylation, RNA-seq, and cytogenetic profiling on 110 primary meningiomas WHO grade I and II). Each technique distinguished the same three groups (two benign and one malignant) as our previous molecular classification; integrating these methods into one classifier further improved accuracy. Computational modeling revealed strong correlations between transcription and cytogenetic changes, particularly loss of chromosome 1p, in malignant tumors. Applying our classifier to data from previous studies also resolved certain anomalies entailed by grouping tumors by WHO grade. Accurate classification will therefore elucidate meningioma biology as well as improve diagnosis and prognosis.