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

Autor: Anna Vyhlídalová Kotrbová, Kristína Gömöryová, Antónia Mikulová, Hana Plešingerová, Stanislava Sladeček, Marek Kravec, Šárka Hrachovinová, David Potěšil, Garett Dunsmore, Camille Blériot, Mathilde Bied, Jan Kotouček, Markéta Bednaříková, Jitka Hausnerová, Luboš Minář, Igor Crha, Michal Felsinger, Zbyněk Zdráhal, Florent Ginhoux, Vít Weinberger, Vitězslav Bryja, Vendula Pospíchalová
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Journal of Extracellular Vesicles, Vol 13, Iss 3, Pp n/a-n/a (2024)
Druh dokumentu: article
ISSN: 2001-3078
DOI: 10.1002/jev2.12420
Popis: Abstract 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.
Databáze: Directory of Open Access Journals
Nepřihlášeným uživatelům se plný text nezobrazuje