晚期高级别浆液性癌 (HGSC) 患者的五年预后仍然不佳，这凸显了识别早期生物标志物的迫切需要。这项研究探索了血液中循环的细胞外囊泡 (EV) 的潜力，据信这些细胞外囊泡含有反映 HGSC 微环境的蛋白质组货物，作为生物标志物发现的来源。我们对从血浆、腹水、和患者的细胞系，采用数据依赖型 (DDA) 和数据独立型采集 (DIA) 方法构建针对目标蛋白质组学定制的谱库。我们的研究旨在通过比较患有 HGSC 的女性与患有良性妇科疾病的女性的 EV 的蛋白质组学特征，发现用于早期检测 HGSC 的新生物标志物。最初的队列由 19 名捐赠者组成，利用 DDA 蛋白质组学进行光谱库开发。随后的队列涉及 30 名 HGSC 患者和 30 名对照受试者，出于类似目的采用 DIA 蛋白质组学。支持向量机（SVM）分类应用于两个队列，以识别具有高特异性和敏感性的组合生物标志物（ROC-AUC > 0.90）。值得注意的是，当与其他生物标志物结合使用时，MUC1 在两个队列中都成为重要的生物标志物。通过对良性 (n = 18)、I 期 (n = 9) 和 II 期 (n = 9) 血浆样本子集进行 ELISA 测定验证，证实了 MUC1 在 HGSC 早期检测中的诊断效用。研究强调了基于 EV 的蛋白质组学分析在发现早期卵巢癌检测组合生物标志物方面的价值。© 2024。作者。

The five-year prognosis for patients with late-stage high-grade serous carcinoma (HGSC) remains dismal, underscoring the critical need for identifying early-stage biomarkers. This study explores the potential of extracellular vesicles (EVs) circulating in blood, which are believed to harbor proteomic cargo reflective of the HGSC microenvironment, as a source for biomarker discovery.We conducted a comprehensive proteomic profiling of EVs isolated from blood plasma, ascites, and cell lines of patients, employing both data-dependent (DDA) and data-independent acquisition (DIA) methods to construct a spectral library tailored for targeted proteomics. Our investigation aimed at uncovering novel biomarkers for the early detection of HGSC by comparing the proteomic signatures of EVs from women with HGSC to those with benign gynecological conditions. The initial cohort, comprising 19 donors, utilized DDA proteomics for spectral library development. The subsequent cohort, involving 30 HGSC patients and 30 control subjects, employed DIA proteomics for a similar purpose. Support vector machine (SVM) classification was applied in both cohorts to identify combinatorial biomarkers with high specificity and sensitivity (ROC-AUC > 0.90). Notably, MUC1 emerged as a significant biomarker in both cohorts when used in combination with additional biomarkers. Validation through an ELISA assay on a subset of benign (n = 18), Stage I (n = 9), and stage II (n = 9) plasma samples corroborated the diagnostic utility of MUC1 in the early-stage detection of HGSC.This study highlights the value of EV-based proteomic analysis in the discovery of combinatorial biomarkers for early ovarian cancer detection.© 2024. The Author(s).