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Pokemon, a transcriptional repressor, inhibits the transcription of tumor suppressor genes and promotes tumor formation by affecting chromatin recombination or binding directly to the tumor suppressor genes. In this study, the mechanism behind the Pokemon regulation of liver cancer cell metabolism was evaluated using liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. Pokemon-overexpressing HL7702 cells were obtained by lipofection. The cells were collected at different time points after transfection and their intracellular metabolites were analyzed using an LC-MS-based metabolomic method. Based on the results of a multivariate statistical analysis, candidate metabolites with significant differences were selected, and 36 of them were confirmed by database and MS/MS analysis. These metabolites were primarily involved in lipid synthesis by KEGG database searches. Further analysis indicated that both the acetyl-coenzyme carboxylase and the fatty acid synthase were activated in the lipid synthesis pathway. The results show that Pokemon can affect cell metabolism by activating the lipid synthesis pathways in cells.

Intracellular metabolites can reflect the physiological state of cells. Ultra performance liquid chromatography/time of flight mass spectrometry (UPLC-TOF MS) is a relatively new technique for the separation of complex samples. The aim of this work is to assess the feasibility of metabonomics in cell line sorting. In the work, a total of 5 cell line samples were analyzed by using UPLC-TOF MS and small molecules metabolite profiles from the extraction of intracellular metabolites were obtained. Principal component analysis (PCA) models were used to extract meaningful information from the complex biological samples. The cell line discrimination was highly improved by PCA. These preliminary results suggested that UPLC/MS coupled with pattern recognition show promise for metabonomics. It is a potential and very promising technology for the classification of the cell lines.