Malignancy-associated metabolic profiling of human glioma cell lines using 1H NMR spectroscopy.
Malignancy-associated metabolic profiling of human glioma cell lines using 1H NMR spectroscopy.
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使用 H-1 NMR 光谱对人神经胶质瘤细胞系进行恶性肿瘤相关代谢分析
DOI：
10.1186/1476-4598-13-197
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发表时间：
2014-08-27
期刊：
影响因子：
37.3
通讯作者：
Ji T
中科院分区：
文献类型：
--
作者：
Shao W;Gu J;Huang C;Liu D;Huang H;Huang Z;Lin Z;Yang W;Liu K;Lin D;Ji T
胶质瘤恶变的不明确性使得预后诊断非常具有挑战性。肿瘤恶性转化与代谢谱的特异性改变密切相关。因此，探索不同恶性程度胶质瘤细胞中潜在的代谢改变对于开发用于预后监测的代谢生物标志物至关重要。我们对从不同恶性等级（WHO II和WHO IV）的胶质瘤中产生的细胞系（CHG 5、SHG 44、U87、U118、U251）进行了基于1H核磁共振（NMR）的代谢分析。采用主成分分析（PCA）、偏最小二乘判别分析（PLS-DA）、模糊c-均值聚类（FCM）和正交投影潜在结构判别分析（OPLS-DA）等方法对细胞极性提取物的1H-NMR谱数据进行分析，并对特征代谢物进行鉴定。胶质细胞酸性蛋白（GFAP）和基质金属蛋白酶（MMP-9）的表达分析用于评估细胞系的恶性行为。GeneGo通路分析用于将特征性代谢物与恶性行为蛋白标志物GFAP和MMP-9相关联。获得了五种细胞系的稳定和不同的代谢谱。低恶性级别组（CHG 5，SHG 44）的代谢谱与高恶性级别组（U87，U118，U251）的代谢谱明显不同。鉴定了17种特征代谢物，可以区分两组的代谢谱，其中9种被映射到与GFAP和MMP-9相关的过程。定量比较和代谢相关性分析结果表明，代谢产物的显著改变主要涉及三羧酸（TCA）循环回补通量、氨基酸代谢、抗氧化机制和胆碱代谢等代谢途径的紊乱，可能与胶质瘤细胞恶性行为的改变相关。我们的研究结果揭示了不同恶性程度的胶质瘤细胞系的代谢异质性。所获得的代谢谱和特征性代谢产物与胶质瘤细胞的恶性特征密切相关，这为进一步研究胶质瘤恶性转化的分子机制和开发无创性生物标志物用于预后监测奠定了基础。本文的在线版本（doi：10.1186/1476-4598-13-197）包含补充材料，可供授权用户使用。
Ambiguity in malignant transformation of glioma has made prognostic diagnosis very challenging. Tumor malignant transformation is closely correlated with specific alterations of the metabolic profile. Exploration of the underlying metabolic alterations in glioma cells of different malignant degree is therefore vital to develop metabolic biomarkers for prognosis monitoring. We conducted 1H nuclear magnetic resonance (NMR)-based metabolic analysis on cell lines (CHG5, SHG44, U87, U118, U251) developed from gliomas of different malignant grades (WHO II and WHO IV). Several methods were applied to analyze the 1H-NMR spectral data of polar extracts of cell lines and to identify characteristic metabolites, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), fuzzy c-means clustering (FCM) analysis and orthogonal projection to latent structure with discriminant analysis (OPLS-DA). The expression analyses of glial fibrillary acidic protein (GFAP) and matrix metal proteinases (MMP-9) were used to assess malignant behaviors of cell lines. GeneGo pathway analysis was used to associate characteristic metabolites with malignant behavior protein markers GFAP and MMP-9. Stable and distinct metabolic profiles of the five cell lines were obtained. The metabolic profiles of the low malignancy grade group (CHG5, SHG44) were clearly distinguished from those of the high malignancy grade group (U87, U118, U251). Seventeen characteristic metabolites were identified that could distinguish the metabolic profiles of the two groups, nine of which were mapped to processes related to GFAP and MMP-9. Furthermore, the results from both quantitative comparison and metabolic correlation analysis indicated that the significantly altered metabolites were primarily involved in perturbation of metabolic pathways of tricarboxylic acid (TCA) cycle anaplerotic flux, amino acid metabolism, anti-oxidant mechanism and choline metabolism, which could be correlated with the changes in the glioma cells’ malignant behaviors. Our results reveal the metabolic heterogeneity of glioma cell lines with different degrees of malignancy. The obtained metabolic profiles and characteristic metabolites are closely associated with the malignant features of glioma cells, which may lay the basis for both determining the molecular mechanisms underlying glioma malignant transformation and exploiting non-invasive biomarkers for prognosis monitoring. The online version of this article (doi:10.1186/1476-4598-13-197) contains supplementary material, which is available to authorized users.
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DOI：
10.1016/0360-3016(92)90653-y
发表时间：
1992-01-01
影响因子：
7
作者：
BAUMANN, M;DUBOIS, W;SUIT, HD
通讯作者：
SUIT, HD
影响因子：
4.3
作者：
Dang, Chi V.
通讯作者：
Dang, Chi V.
影响因子：
2.9
作者：
Harley W;Floyd C;Dunn T;Zhang XD;Chen TY;Hegde M;Palandoken H;Nantz MH;Leon L;Carraway KL 3rd;Lyeth B;Gorin FA
通讯作者：
Gorin FA
影响因子：
6.4
作者：
Badie, B;Goh, CS;Boothman, DA
通讯作者：
Boothman, DA
影响因子：
2.5
作者：
Isobe, T;Matsumura, A;Nose, T
通讯作者：
Nose, T