@article{2981022,
    title = "Human melanoma‐cell metabolic profiling: Identification of novel biomarkers indicating metastasis",
    author = "Kosmopoulou, M. and Giannopoulou, A.F. and Iliou, A. and Benaki, D. and Panagiotakis, A. and Velentzas, A.D. and Konstantakou, E.G. and Papassideri, I.S. and Mikros, E. and Stravopodis, D.J. and Gikas, E.",
    journal = "International Journal of Molecular Sciences",
    year = "2020",
    volume = "21",
    number = "7",
    publisher = "MDPI AG",
    issn = "1422-0067",
    doi = "10.3390/ijms21072436",
    keywords = "acylcarnitine;  alanine;  alanine aminotransferase;  asparagine;  aspartic acid;  choline;  glutamic acid;  glutamine;  glycerol;  guanosine;  inosine;  isoleucine;  lactic acid;  leucine;  limonene;  monophenol monooxygenase;  phenylalanine;  phosphorylcholine;  polyketide;  proline;  saturated fatty acid;  threonine;  tryptophan;  tyrosine;  valine;  biological marker;  purine;  purine derivative, Article;  carcinogenesis;  cell metabolism;  cell viability;  citric acid cycle;  controlled study;  discriminant analysis;  electrospray;  glycolysis;  high performance liquid chromatography;  human;  human cell;  liquid chromatography-mass spectrometry;  mass fragmentography;  melanogenesis;  melanoma;  metabolite;  metabolomics;  metastasis;  multiple reaction monitoring;  multiple sclerosis;  oxidative phosphorylation;  protein protein interaction;  proton nuclear magnetic resonance;  receiver operating characteristic;  sensitivity and specificity;  Th17 cell;  THP-1 cell line;  tumor growth;  female;  least square analysis;  liquid chromatography;  melanoma;  metabolism;  metabolome;  middle aged;  multivariate analysis;  nuclear magnetic resonance spectroscopy;  principal component analysis;  procedures;  tumor cell line, Biomarkers;  Cell Line, Tumor;  Chromatography, Liquid;  Discriminant Analysis;  Female;  Humans;  Least-Squares Analysis;  Magnetic Resonance Spectroscopy;  Melanoma;  Metabolome;  Metabolomics;  Middle Aged;  Multivariate Analysis;  Neoplasm Metastasis;  Principal Component Analysis;  Purines;  ROC Curve",
    abstract = "Melanoma is the most aggressive type of skin cancer, leading to metabolic rewiring and enhancement of metastatic transformation. Efforts to improve its early and accurate diagnosis are largely based on preclinical models and especially cell lines. Hence, we herein present a combinational Nuclear Magnetic Resonance (NMR)‐ and Ultra High Performance Liquid Chromatography‐High‐Resolution Tandem Mass Spectrometry (UHPLC‐HRMS/MS)‐mediated untargeted metabolomic profiling of melanoma cells, to landscape metabolic alterations likely controlling metastasis. The cell lines WM115 and WM2664, which belong to the same patient, were examined, with WM115 being derived from a primary, pre‐metastatic, tumor and WM2664 clonally expanded from lymph‐node metastases. Metabolite samples were analyzed using NMR and UHPLC‐HRMS. Multivariate statistical analysis of high resolution NMR and MS (positive and negative ionization) results was performed by Principal Component Analysis (PCA), Partial Least Squares‐Discriminant Analysis (PLS‐DA) and Orthogonal Partial Least Squares‐Discriminant Analysis (OPLS‐DA), while metastasis‐related biomarkers were determined on the basis of VIP lists, S‐plots and Student’s t‐tests. Receiver Operating Characteristic (ROC) curves of NMR and MS data revealed significantly differentiated metabolite profiles for each cell line, with WM115 being mainly characterized by upregulated levels of phosphocholine, choline, guanosine and inosine. Interestingly, WM2664 showed notably increased contents of hypoxanthine, myo‐inositol, glutamic acid, organic acids, purines, pyrimidines, AMP, ADP, ATP and UDP(s), thus indicating the critical roles of purine, pyrimidine and amino acid metabolism during human melanoma metastasis. © 2020 by the authors. Licensee MDPI, Basel, Switzerland."
}