Proteomic analysis of ascitic extracellular vesicles describes tumour microenvironment and predicts patient survival in ovarian cancer

J Extracell Vesicles. 2024 Mar;13(3):e12420. doi: 10.1002/jev2.12420.


High-grade serous carcinoma of the ovary, fallopian tube and peritoneum (HGSC), the most common type of ovarian cancer, ranks among the deadliest malignancies. Many HGSC patients have excess fluid in the peritoneum called ascites. Ascites is a tumour microenvironment (TME) containing various cells, proteins and extracellular vesicles (EVs). We isolated EVs from patients' ascites by orthogonal methods and analyzed them by mass spectrometry. We identified not only a set of 'core ascitic EV-associated proteins' but also defined their subset unique to HGSC ascites. Using single-cell RNA sequencing data, we mapped the origin of HGSC-specific EVs to different types of cells present in ascites. Surprisingly, EVs did not come predominantly from tumour cells but from non-malignant cell types such as macrophages and fibroblasts. Flow cytometry of ascitic cells in combination with analysis of EV protein composition in matched samples showed that analysis of cell type-specific EV markers in HGSC has more substantial prognostic potential than analysis of ascitic cells. To conclude, we provide evidence that proteomic analysis of EVs can define the cellular composition of HGSC TME. This finding opens numerous avenues both for a better understanding of EV's role in tumour promotion/prevention and for improved HGSC diagnostics.

Keywords: ascites; extracellular vesicles (EV); fallopian tube and peritoneum (HGSC); high-grade serous carcinoma of the ovary; macrophage; ovarian cancer (OC); tandem mass spectrometry (MS/MS); tumour microenvironment (TME).

MeSH terms

  • Ascites / metabolism
  • Ascites / pathology
  • Cystadenocarcinoma, Serous* / diagnosis
  • Cystadenocarcinoma, Serous* / genetics
  • Cystadenocarcinoma, Serous* / metabolism
  • Extracellular Vesicles* / metabolism
  • Female
  • Humans
  • Ovarian Neoplasms* / diagnosis
  • Proteomics
  • Tumor Microenvironment