Metabolic differences among melanoma and two prostate cancer cell lines by electrospray ion mobility mass spectrometry

Abstract

Detecting early stages of cancer has been a challenge for analytical methods. Even with the advances in mammography and prostate specific antigen (PSA) testing the number of false positives and negatives is still significant. Cancer cell lines provide realistic simulations to assess detection technologies for different stages and types of cancer. Metabolomics, the measure of end products of all biological processes, is a recent addition to the field of systems biology and can be targeted towards early disease detection. For this study, the metabolomes of three cancer cell lines, two prostate (DU145 and PC3) and one melanoma (A375), were investigated by an ion mobility mass spectrometer (IMMS) for both positive and negative ion detection mode. IMMS produced multidimensional data that includes m/z, mobility and intensity for each ion detected in the sample. In order to see differences between the cancer cell lines, principal components analysis (PCA), a multi-variant technique used to pull patterns out of the data, was used in conjunction with the IMMS data. The sample patterns from the PCA were observed in the score plot and the individual metabolites that contributed the most to the model were shown in the loadings plot. For positive mode 127 metabolite ions were statistically analyzed and in the negative mode 115 metabolite ions were analyzed. PCA score plots were able to model 98% and 87% of the original data for positive and negative mode, respectively. The metabolite ions from the loadings plot were tentatively identified based on m/z.