Metabolic Profiling of Human Lung Cancer Tissue by H-1 High Resolution Magic Angle Spinning (HRMAS) NMR Spectroscopy
authors Rocha, CM; Barros, AS; Gil, AM; Goodfellow, BJ; Humpfer, E; Spraul, M; Carreira, IM; Melo, JB; Bernardo, J; Gomes, A; Sousa, V; Carvalho, L; Duarte, IF
nationality International
journal JOURNAL OF PROTEOME RESEARCH
author keywords lung cancer; NMR spectroscopy; HRMAS; metabolic composition; multivariate analysis
keywords MAGNETIC-RESONANCE-SPECTROSCOPY; PERCHLORIC-ACID EXTRACTS; HR-MAS SPECTROSCOPY; INVASIVE CERVICAL-CANCER; BREAST-CANCER; IN-VIVO; H-1-NMR SPECTROSCOPY; PATTERN-RECOGNITION; PROSTATE-CANCER; BRAIN-TUMORS
abstract This work aims at characterizing the metabolic profile of human lung cancer, to gain new insights into tumor metabolism and to identify possible biomarkers with potential diagnostic value in the future. Paired samples of tumor and noninvolved adjacent tissues from 12 lung tumors have been directly analyzed by H-1 HRMAS NMR (500/600 MHz) enabling, for the first time to our knowledge, the identification of over 50 compounds. The effect of temperature on tissue stability during acquisition time has also been investigated, demonstrating that analysis should be performed within less than two hours at low temperature (277 K), to minimize glycerophosphocholine (GPC) and phosphocholine (PC) conversion to choline and reduce variations in some amino acids. The application of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) to the standard 1D H-1 spectra resulted in good separation between tumor and control samples, showing that inherently different metabolic signatures characterize the two tissue types. On the basis of spectral integration measurements, lactate, PC, and GPC were found to be elevated in tumors, while glucose, myo-inositol, inosine/adenosine, and acetate were reduced. These results show the valuable potential of HRMAS NMR-metabonomics for investigating the metabolic phenotype of lung cancer.
publisher AMER CHEMICAL SOC
issn 1535-3893
year published 2010
volume 9
issue 1
beginning page 319
ending page 332
digital object identifier (doi) 10.1021/pr9006574
web of science category Biochemical Research Methods
subject category Biochemistry & Molecular Biology
unique article identifier WOS:000273267900030
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journal impact factor 3.950
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