Abstract
BACKGROUND: Cutaneous malignant melanoma (CMM) ranks among the deadliest forms of cancer. Abnormalities in lipid metabolism may have a connection with the risk of CMM progression. METHODS: Lipid metabolism-related genes were selected in MSigDB. A lipid metabolism-related predictive model was constructed in The Cancer Genome Atlas-skin cutaneous melanoma (TCGA-SKCM) using univariate Cox regression analysis, non-negative matrix factorization (NMF) clustering analysis, Weighted correlation network analysis (WGCNA), least absolute shrinkage and selection operator regression (LASSO) analysis, and outcomes-related genes were identified. The roles of candidate genes in CMM were determined using in vivo and in vitro experiments, and the pathway mechanism of the candidate gene was studied using transcriptomics, proteomics, lipid metabolomics, and other molecular biological methods. RESULTS: A predictive model was established, Risk Score = -0.009 * UBE2L6 + 0.033 * PLEKHA5 + 0.024 * LHB + 0.036 * CARM1 + 0.016 * PRXL2B + 0.131 * PLA2G4D. The pleckstrin homology domain-containing A5 (PLEKHA5) was identified as an essential gene and positively correlated with poor outcomes in CMM. Fc receptor-like A (FCRLA) is the downstream gene of PLEKHA5, upregulated in CMM, and tumor necrosis factor alpha (TNFα) is also an essential cytokine that promotes CMM proliferation and metastasis. Lipid metabolomics showed that PLEKHA5 knockdown increased ceramide and sphingosine levels while decreasing cholesterol ester and triglyceride levels in CMM cells, possibly related to disease progression. CONCLUSION: The predictive model of CMM related to lipid metabolism was constructed. TNFα activates the PLEKHA5-FCRLA axis to enhance neutral lipid storage and energy metabolism in CMM cells, promoting malignant behavior.