Bollard S M, Howard J, Casalou C, Kelly B S, O'Donnell K, Fenn G, O'Reilly J, Milling R, Shields M, Wilson M, Ajaykumar A, Triana K, Wynne K, Tobin D J, Kelly P A, McCann A, Potter S M
Department of Plastic & Reconstructive Surgery, Mater Misericordiae University Hospital, Dublin 7, Ireland; School of Medicine, University College Dublin, Dublin 4, Ireland; Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin 4, Ireland.
School of Medicine, University College Dublin, Dublin 4, Ireland; Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin 4, Ireland.
Transl Oncol. 2024 Dec;50:102152. doi: 10.1016/j.tranon.2024.102152. Epub 2024 Oct 13.
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.
血浆来源的细胞外囊泡（EVs）因其能够反映细胞来源且易于收集，已被认为是黑色素瘤的新型生物标志物。本研究旨在鉴定能够区分疾病阶段的新型EV生物标志物。这是通过对黑色素瘤患者的血浆来源的EVs进行表征，并将其蛋白质组学和代谢组学特征与健康对照者的进行比较来实现的。
使用尺寸排阻色谱法从36例黑色素瘤患者和13例健康对照者的血浆中分离出EVs。进行了蛋白质组学和代谢组学分析，并使用机器学习算法来识别潜在的蛋白质和代谢物，以区分不同疾病阶段的黑色素瘤患者的血浆来源的EVs。
各组分离出的EV群体的浓度和大小相似。先前与黑色素瘤发病机制相关的蛋白质（载脂蛋白C4、润滑蛋白、纤溶酶原、肌腱蛋白C、血管性血友病因子和丝氨酸蛋白酶抑制剂D1）和代谢物（溶血磷脂酰胆碱a C18:2、磷脂酰胆碱ae C44:3）被确定为在区分疾病阶段方面具有相关性。
结果进一步支持继续研究循环血浆来源的EVs作为黑色素瘤的生物标志物。此外，联合蛋白质组-代谢组特征在区分疾病阶段方面的潜力可能为早期检测、预后和个性化治疗策略提供有价值的见解。
