This work was supported by grants from The National Natural Science Foundation of China(10234070, 20573132 and 20575074) and The Chinese Academy of Sciences (100T programme: T12508-06S138).
Metabolic characteristics of 39 human brain tumor tissues, including 15 astrocytomas, 13 fibroblastic meningiomas and 11 transitional meningiomas from 39 individual patients, have been studied using high resolution magic-angle spinning (HRMAS) 1H NMR spectroscopy in conjunction with principal component analysis (PCA). With rich metabolite information, 1H NMR spectra showed that the tumor-tissue metabonome was dominated by lipids, lactate, myo-inositol, creatine, choline metabolites such as choline, phosphocholine and glycerophosphocholine, amino acids such as alanine, glutamate, glutamine, taurine, N-acetyl-aspartate and glutathione. PCA of the tumor NMR spectra clearly showed metabonomic differences between low-grade astrocytomas and meningiomas whereas such differences were more moderate between fibroblastic and transitional meningiomas. Compared with meningiomas, the low-grade astrocytomas had higher levels of glycerophosphocholine, phosphocholine, myo-inositol and creatine but lower levels of alanine, glutamate, glutamine, glutathione and taurine. The N-acetyl-aspartate level was low but detectable in low-grade astrocytomas whereas it was not detectable in meningiomas. It is concluded that tissue metabonomics technology consisting of HRMAS 1H NMR spectroscopy and multivariate data analysis (MVDA) offers a useful tool (1) for distinguishing different types of brain tumors, (2) for providing the metabolic information for human brain tumors, which are potentially useful for understanding biochemistry of tumor progression.
CHEN Wen-Xue, LOU Hai-Yan, ZHANG Hong-Ping, NIE Xiu, XIANG Yun, YANG Yong-Xia, WU Guang-Yao, QI Jian-Ping, YUE Yong, LEI Hao, TANG Hui-Ru, DENG Feng. Metabonomic Characterization of The Low-grade Human Astrocytomas and Meningiomas Using Magic-angle Spinning 1H Nuclear Magnetic Resonance Spectroscopy and Principal Component Analysis[J]. Progress in Biochemistry and Biophysics,2008,35(10):1142-1153
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