# Targeted proteomics of plasma extracellular vesicles uncovers MUC1 as combinatorial biomarker for the early detection of high-grade serous ovarian cancer

## TL;DR

This study identifies MUC1 as a promising biomarker for early detection of high-grade serous ovarian cancer using proteomics of blood-based extracellular vesicles.

## Contribution

The study introduces MUC1 as a combinatorial biomarker for early-stage high-grade serous ovarian cancer detection using EV proteomics.

## Key findings

- MUC1 was identified as a significant biomarker in two cohorts using proteomic analysis of extracellular vesicles.
- Combination of MUC1 with other biomarkers achieved high specificity and sensitivity (ROC-AUC > 0.90) for early-stage detection.
- ELISA validation confirmed MUC1's diagnostic utility in early-stage high-grade serous ovarian cancer.

## Abstract

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.

The online version contains supplementary material available at 10.1186/s13048-024-01471-8.