Serum metabolomic signatures of cutaneous malignancies identified by untargeted profiling.

Background and aims: Skin cancers are among the most common malignancies worldwide, and improved non-invasive diagnostic tools are needed to support clinical decision making. Metabolomics offers a promising approach by capturing systemic biochemical alterations associated with tumor presence. Methods: In this study, we performed untargeted serum metabolomic profiling based on high-performance liquid chromatography coupled with mass spectrometry in 85 individuals, including 49 with basal cell carcinoma, 19 with squamous cell carcinoma, 8 with melanoma and 9 with benign lesions. Results: The analysis yielded 98 polar metabolites and 53 lipophilic metabolites that passed quality filtering. Thirteen metabolites showed significant differences between the cancer and benign groups, including lysophosphatidylcholine (20:3), N-palmitoyl tryptophan, serotonin, and fumaric acid. Principal component analysis demonstrated clear separation between malignant and benign groups, while cancer samples displayed wider metabolic variability consistent with tumor heterogeneity. Integrating principal component scores into a linear discriminant model yielded an area under the ROC curve of 0.98 corresponding to a sensitivity of 96% and a specificity of 67%. Pathway enrichment analysis revealed consistent alterations in mitochondrial electron transport, amino acid metabolism, the urea cycle, and the Warburg effect, indicating that common metabolic pathways are perturbed across cutaneous malignancies. Conclusions: These findings show that serum metabolomics can distinguish cancer from benign skin lesions and highlight metabolic signatures that may serve as potential biomarkers for non-invasive assessment of skin cancer.