Serum metabolite profiling of cutaneous T-cell lymphoma based on a multiplatform approach.

Cutaneous T-cell lymphoma (CTCL) is a class of non-Hodgkin lymphoma with a difficult early diagnosis. The overall annual age-adjusted incidence of CTCL had consistently increased to around 10.2 cases per million persons. However, our knowledge regarding its mechanism of disease origin and progression remains unclear. In this study, serum samples from 31 CTCL patients and 31 matched healthy volunteers were analyzed in depth to screen metabolites capable of differentiating CTCL from controls. To obtain a higher coverage of metabolome with various hydrophilicity, a multiplatform approach with GC-MS and UHPLC-QTOF-MS has been employed. Data were analyzed by multivariate statistical analysis and CTCL group was separated from control group successfully using supervised OPLS-DA model. A total of 51 CTCL-regulated metabolites were identified, among which 15 differential metabolites have an AUC > 0.9 in receiver operating characteristic (ROC) curve analysis. Glycerophospholipid metabolism, tryptophan metabolism and purine metabolism were highlighted as 3 major altered pathways in CTCL serum. These alterations revealed impacts to membrane stability and weakened immune as well as ATP depletion associated with CTCL. Overall, these results aid in improving understanding of the mechanism related to CTCL, and demonstrate this multiplatform approach is suitable for serum metabolomics researches.

Cross-platform metabolomics investigating the intracellular metabolic alterations of HaCaT cells exposed to phenanthrene.

Phenanthrene (Phe) is one of the most abundant Polycyclic aromatic hydrocarbons (PAHs) contamination from various ambient sources, which has a tremendous impact on public health. However, our knowledge regarding its effects on skin remains limited. In this study, we investigated the metabolite profiling of the human keratinocytes HaCaT cells after Phe exposure to understand the toxic effects of Phe exposure on skin. To obtain a broad picture of metabolome with various hydrophilicity, a cross-platform approach with GC-MS and UHPLC-QTOF-MS has been employed. Data were analyzed by multivariate statistical analysis and samples were separated successfully using supervised PLS-DA models. It was shown that the impacts of Phe exposure on HaCaT cells were both dose-related and time-related. A total of 48 Phe-regulated metabolites were identified and among which 19 were confirmed by reference standards. By pathway analysis, amino acid metabolism, glutathione metabolism and glycerophospholipid metabolism were highlighted as the major metabolic pathways disturbed by Phe. Furthermore, it was found that the mechanisms included a reduced amino pool and a reduced antioxidant status. Overall, these results aid in improving understanding of the dermal toxicology related to Phe, and demonstrate this cross-platform approach is suitable for metabolomics researches on HaCaT cells.