Understanding metabolic characteristics and molecular mechanisms of large to giant congenital melanocytic nevi: implications for melanoma risk and therapeutic targets
Large to giant congenital melanocytic nevi (LGCMN) present clinical challenges due to their complex phenotypic heterogeneity and increased melanoma risk. Molecular-level research is essential for understanding the pathogenic mechanisms of LGCMN and identifying potential therapeutic targets. Tissue samples from 67 LGCMN lesions and 49 matched controls were analyzed using metabolomics and transcriptomics to identify metabolic characteristics and gene expression differences. A protein-protein interaction network and a multi-layer network of key metabolites-genes-pathways were established to explore the metabolic characteristics and gene associations with LGCMN. Metabolic analysis revealed a consistent dysregulation in amino acid metabolisms, including arginine, alanine, aspartate, glutamate, phenylalanine, and tyrosine, across LGCMN lesions and subtypes. Compared to controls, 18 upregulated metabolites and 7 downregulated metabolites were identified in LGCMN lesions. Metabolic profiles varied among LGCMN subtypes, with the trunks subtype exhibiting significant alterations in branched-chain amino acids. Network analysis identified 23 genes related to melanogenesis and amino acid metabolism, including TYR, SOX10, and MITF, which showed strong correlation with tyrosine, phenylalanine, and branched-chain amino acids (<i>r</i> > 0.6). High centrality values for genes (<i>e.g.</i>, EDNRB, TYR, MITF, SOX10, and MAPK3 > 0.300) and amino acids (<i>e.g.</i>, tyrosine at 0.397 and phenylalanine at 0.374) emphasize their pivotal roles in melanogenesis. This study reveals significant metabolic and molecular differences between LGCMN lesions, normal skin, and across LGCMN subtypes, highlighting the deregulation of amino acid metabolism and key genes involved in melanogenesis. These insights enhance our understanding of LGCMN's biological heterogeneity and provide novel avenues for therapeutic intervention.
Authors
- Guiping Shen (ORCID: https://orcid.org/0000-0002-0779-1859)
- Jianghua Feng (ORCID: https://orcid.org/0000-0001-8899-2750)
- Yongqiang Ren (ORCID: https://orcid.org/0009-0007-2137-2646)
- Zhaohui Wang (ORCID: https://orcid.org/0000-0002-9035-3867)
- Ge Song (ORCID: https://orcid.org/0000-0003-2178-3086)
- Pengfei Guo (ORCID: https://orcid.org/0009-0009-1989-2508)
- Yajie Chang (ORCID: https://orcid.org/0009-0002-2138-2717)
- Tao Dai (ORCID: https://orcid.org/0000-0002-6462-124X)
Institutions
- Tongji University (CN)
- Xiamen University (CN)
- First Affiliated Hospital of Henan University of Science and Technology (CN)
- Tongji Hospital (CN)
- Xiamen University of Technology (CN)
Publication Details
- Journal
- Analytical Methods
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5ay00122f
- Citations
- 2
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 2.09
Funders
- National Natural Science Foundation of China
- Henan University of Science and Technology
- Natural Science Foundation of Fujian Province
- Henan University
- Xiamen University