title: Classification of human cancer cells by means of capillary gas chromatography and pattern recognition analysis.
abstract: The metabolic profiles of brain biopsies obtained at surgery were recorded using capillary gas chromatography (GC). About 160 peaks were seen, of which 105 were used for data analysis. Three classes of brain tissue were examined: normal cerebral cortex, pituitary tumours and " brain" tumours. Pattern recognition analyses of the GC profiles using the SIMCA multivariate programme clearly resolved normal brain tissue from the tumours. Subclassification of the different tumours was more difficult, probable because the number of samples in each tumour class was too small. High-resolution two-dimensional electrophoresis separated the brain biopsies into several hundred different proteins. The combined use of the latter technique and capillary GC-mass spectrometry and pattern recognition analyses gives the possibility of the classification of diseased cells based solely on differences in their biochemical compositions.
mesh_terms: D001932:Brain Neoplasms / Q000145:classification / Q000378:metabolism*; D002849:Chromatography, Gas / Q000379:methods; D003937:Diagnosis, Differential; D004591:Electrophoresis, Polyacrylamide Gel; D008401:Gas Chromatography-Mass Spectrometry; D006801:Humans; D007525:Isoelectric Focusing; D009363:Neoplasm Proteins / Q000032:analysis*; D010363:Pattern Recognition, Automated; D010911:Pituitary Neoplasms / Q000378:metabolism
chemical_list: D009363:Neoplasm Proteins