# Neutrophil- and Endothelial Cell-Derived Extracellular Microvesicles Are Promising Putative Biomarkers for Breast Cancer Diagnosis

**Authors:** Thayse Batista Moreira, Marina Malheiros Araújo Silvestrini, Ana Luiza de Freitas Magalhães Gomes, Kerstin Kapp Rangel, Álvaro Percínio Costa, Matheus Souza Gomes, Laurence Rodrigues do Amaral, Olindo Assis Martins-Filho, Paulo Guilherme de Oliveira Salles, Letícia Conceição Braga, Andréa Teixeira-Carvalho

PMC · DOI: 10.3390/biomedicines13030587 · Biomedicines · 2025-02-27

## TL;DR

This study explores how microvesicles from neutrophils and endothelial cells could serve as non-invasive biomarkers for diagnosing and monitoring breast cancer.

## Contribution

The study introduces a novel diagnostic panel using neutrophil- and endothelial cell-derived microvesicles for breast cancer screening and monitoring.

## Key findings

- Breast cancer patients had higher levels of neutrophil- and endothelial cell-derived microvesicles compared to healthy controls.
- Machine learning identified neutrophil- and endothelial cell-derived microvesicles as top candidates for diagnostic biomarkers.
- Microvesicle levels changed over time following treatment, suggesting potential for monitoring cancer progression.

## Abstract

Introduction: Breast cancer (BC) is a disease that affects about 2.2 million people worldwide. The prognosis and treatment of these patients depend on clinical and histopathologic staging, in which more aggressive cancers need a less conservative therapeutic approach. Previous studies showed that patients with BC have an increased frequency of systemic microvesicles (MVs) that are associated with invasion, progression, and metastasis, which can be used in liquid biopsy to predict the therapeutic response in individualized treatment. Objective: This study proposes the development of a minimally invasive BC diagnostic panel and follow-up biomarkers as a complementary method to screen patients. Methods: The quantification of circulating MVs in 48 healthy women and 100 BC patients who attended the Mário Penna Institute between 2019 and 2022 was performed by flow cytometry. In addition, the MVs of BC patients were analyzed before treatment and 6, 12, and 24 months post-treatment. Machine learning approaches were employed to determine the performance of MVs to identify BC and to propose BC classifier algorithms. Results: Patients with BC had more neutrophil- and endothelial cell-derived MVs than controls before treatment. After treatment, all MV populations were decreased compared to pre-treatment, but leukocyte- and erythrocyte-derived MVs were increased at 12 months after treatment, before decreasing again at 24 months. Conclusions: Performance analyses and machine learning approaches pointed out that MVs from neutrophils and endothelial cells are the best candidates for BC diagnostic biomarkers. Neutrophil- and endothelial cell-derived MVs are putative candidates for BC biomarkers to be employed as screening tests for BC diagnosis.

## Linked entities

- **Diseases:** breast cancer (MONDO:0004989)

## Full-text entities

- **Diseases:** cancers (MESH:D009369), BC (MESH:D001943), metastasis (MESH:D009362)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC11940338/full.md

## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11940338/full.md

## References

41 references — full list in the complete paper: https://tomesphere.com/paper/PMC11940338/full.md

---
Source: https://tomesphere.com/paper/PMC11940338