Toward improved grading of malignancy in oligodendrogliomas using metabolomics
Toward improved grading of malignancy in oligodendrogliomas using metabolomics
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DOI：
10.1002/mrm.21486
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发表时间：
2008-05-01
影响因子：
3.3
通讯作者：
Namer, I. J.
中科院分区：
文献类型：
--
作者：
Erb, G.;Elbayed, K.;Namer, I. J.
尽管少突胶质细胞瘤的组织病理学分级一直备受关注，但仍存在争议。确定能够改善恶性肿瘤分级的可靠生物标志物仍然是朝着更好的患者治疗管理努力的重要步骤。因此，使用高分辨率魔角旋转核磁共振光谱（HRMAS）研究了34例人脑活检组织的代谢组，组织病理学分类为低级（LGO，N = 10）和高级（HGO，N = 24）少突胶质细胞。核磁共振光谱（HRMAS）和多元统计分析。获得的分类模型提供了一个明确的区别Leptin和Heptin，并提供了一些有用的见解不同的代谢途径，恶性肿瘤分级。对模型中最具鉴别力的代谢物的分析揭示了在Hyndrome中存在肿瘤缺氧。然后使用统计模型研究通过组织病理学分类为中间型少突胶质细胞瘤（N = 6）和胶质母细胞瘤（GBM）（N = 30）的活检样品。结果显示，肿瘤缺氧的梯度在以下方向上增加：Leptin、中间型少突胶质细胞瘤、Heptin和GBM。此外，在分析患者的临床演变时，代谢分类似乎比组织病理学分析提供与实际患者演变更密切的相关性。
In spite of having been the object of considerable attention, the histopathological grading of oligodendrogliomas is still controversial. The determination of reliable biomarkers capable of improving the malignancy grading remains an essential step in working toward better therapeutic management of patients. Therefore the metabolome of 34 human brain biopsies, histopathologically classified as low-grade (LGO, N = 10) and high-grade (HGO, N = 24) oligodendroglioms, was studied using high-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HRMAS NMR) and multivariate statistical analysis. The classification model obtained afforded a clear distinction between LGOs and HGOs and provided some useful insights into the different metabolic pathways that underlie malignancy grading. The analysis of the most discriminant metabolites in the model revealed the presence of tumoral hypoxia in HGOs. The statistical model was then used to study biopsy samples that were classified as intermediate oligodendrogliomas (N = 6) and glioblastomas (GBMs) (N = 30) by histopathology. The results revealed a gradient of tumoral hypoxia increasing in the following direction: LGOs, intermediate oligodendrogliomas, HGOs, and GBMs. Moreover upon analysis of the clinical evolution of the patients, the metabolic classification seems to provide a closer correlation with the actual patient evolution than the histopathological analysis.