Malignancy-associated metabolic profiling of human glioma cell lines using 1H NMR spectroscopy

Molecular Cancer

Research

Zhen Lin¹  Kun Liu¹  Wei Shao¹  Donghai Lin¹  Jinping Gu¹  Dan Liu¹  Wensheng Yang¹  Tianhai Ji¹  Zicheng Huang¹  Caihua Huang²  Huiying Huang³ 

[1] Chenggong Hospital and College of Chemistry and Chemical Engineering, Xiamen University, 361005, Xiamen, China;Research Institute of Exercise and Rehabilitation, Fujian Medical University, 351009, Fuzhou, China;School of Life Sciences, Xiamen University, 361005, Xiamen, China;

关键词: Glioma cell line;    Malignancy;    Metabolic profiling;    H-NMR;    Spectroscopy;   

DOI  :  10.1186/1476-4598-13-197

 received in 2014-03-30, accepted in 2014-08-21,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundAmbiguity 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.MethodsWe 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.ResultsStable 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.ConclusionsOur 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.

【 授权许可】

Unknown   
© Shao et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.