Chinese Journal of Dermatology ›› 2024, Vol. 57 ›› Issue (7): 601-609.doi: 10.35541/cjd.20230452

• Original Articles • Previous Articles     Next Articles

Untargeted metabolomics analysis-based metabolic characterization of hemangioma-derived endothelial cells

Yang Kaiying, Tian Bowen, Lan Chaoting   

  1. Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, National Children's Medical Center for South Central Region, Guangzhou Medical University, Guangzhou 510623, China
  • Received:2023-08-07 Revised:2024-04-29 Online:2024-07-15 Published:2024-07-02
  • Contact: Yang Kaiying E-mail:yangkaiying1123@126.com
  • Supported by:
    The Guangdong Basic and Applied Basic Research Foundation (2023A1515012751); the Guangzhou Basic and Applied Basic Research Foundation (2024A04J3857); the China Postdoctoral Science Foundation (2023M730793, 2023M730793); the Research Foundation of Guangzhou Women and Children′s Medical Center for Clinical Doctor (2023BS014, 2023BS015)

Abstract: 【Abstract】 Objective To investigate the metabolic profiles of hemangioma-derived endothelial cells (HemECs) based on untargeted metabolomics analysis. Methods Primary human umbilical vein endothelial cells (HUVECs) served as the control group, and HemECs as the experimental group. Cellular metabolites were extracted and analyzed using ultra-performance liquid chromatography-mass spectrometry (UPLC‐MS) for untargeted metabolomics analysis of HUVECs and HemECs. Bioinformatics analysis was employed to screen differentially expressed metabolites, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and metabolic pathway analysis. Univariate analysis including t test and fold change analysis, as well as multivariate analysis including unsupervised principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were carried out. Results A total of 542 and 241 differential metabolites were identified between HemECs and HUVECs by using the positive and negative ion modes of UPLC-MS, respectively. In the positive ion mode, the differential metabolites were mainly lipids and lipid-like molecules (35.142%) as well as organic acids and derivatives (24.537%), while in the negative ion mode the differential metabolites were organic acids and derivatives (31.466%) as well as lipids and lipid-like molecules (28.879%) . Annotation analysis of differential metabolites indicated that differential metabolites were mainly clustered and enriched in amino acid metabolic pathways in both positive and negative ion modes. KEGG metabolic pathway analysis revealed that 3 significantly differential metabolic pathways were screened out in the positive ion mode (P < 0.05), including "arginine and proline metabolism","glutamic acid and glutamine metabolism" and "sphingolipid metabolism"; in the negative ion mode, 12 significantly differential metabolic pathways were screened out (P < 0.05), including "arginine and proline metabolism", "tricarboxylic acid cycle", "glycine, serine and threonine metabolism", etc. Conclusion There were significant differences in metabolic profiles between HemECs and HUVECs, and amino acid metabolism, especially arginine and proline metabolism, was an important metabolic pathway involved in the regulation of HemEC metabolism.

Key words: Hemangioma, Child, Hemangioma-derived endothelial cell, Human umbilical vein endothelial cells, Untargeted metabolomics, Amino acid metabolism