Proteomic and metabolomic profiles of plasma-derived Extracellular Vesicles differentiate melanoma patients from healthy controls

• Published in: Translational oncology Vol. 50; p. 102152
• Main Authors: Bollard, SM, Howard, J, Casalou, C, Kelly, BS, O'Donnell, K, Fenn, G, O'Reilly, J, Milling, R, Shields, M, Wilson, M, Ajaykumar, A, Triana, K, Wynne, K, Tobin, DJ, Kelly, PA, McCann, A, Potter, SM
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01-12-2024; Elsevier
• Subjects: Biomarkers; Extracellular Vesicle; Melanoma; Metabolomics; Proteomics; Biomarkers; Metabolomics; Melanoma; Extracellular Vesicle; Proteomics
• ISSN: 1936-5233; 1936-5233
• DOI: 10.1016/j.tranon.2024.102152

•Plasma-derived Extracellular Vesicles (EVs) from patients with melanoma have similar size and concentration compared to those from healthy controls.•Proteins linked to melanoma development (PRG4, APOC4, SERPIND1, VWF, TNC and PLG) were identified in the plasma-derived EVs of patients with melanoma.•Metabolomic analysis revealed alterations in phosphatidylcholines in the plasma-derived EVs of patients with melanoma, although their definitive role is unclear.
Plasma-derived Extracellular Vesicles (EVs) have been suggested as novel biomarkers in melanoma, due to their ability to reflect the cell of origin and ease of collection. This study aimed to identify novel EV biomarkers that can discriminate between disease stages. This was achieved by characterising the plasma-derived EVs of patients with melanoma, and comparing their proteomic and metabolomic profile to those from healthy controls.
EVs were isolated from the plasma of 36 patients with melanoma and 13 healthy controls using Size Exclusion Chromatography. Proteomic and Metabolomic Analyses were performed, and machine learning algorithms were used to identify potential proteins and metabolites to differentiate the plasma-derived EVs from melanoma patients of different disease stages.
The concentration and size of the EV population isolated was similar between groups. Proteins (APOC4, PRG4, PLG, TNC, VWF and SERPIND1) and metabolites (lyso PC a C18:2, PC ae C44:3) previously associated with melanoma pathogenesis were identified as relevant in differentiating between disease stages.
The results further support the continued investigation of circulating plasma-derived EVs as biomarkers in melanoma. Furthermore, the potential of combined proteo-metabolomic signatures for differentiation between disease stages may provide valuable insights into early detection, prognosis, and personalised treatment strategies.