Extracellular vesicles

Bispecific Antibodies, Nanobodies and Extracellular Vesicles: Present and Future to Cancer Target Therapy

Cancer remains one of the leading causes of mortality worldwide, with a growing need for precise and effective treatments. Traditional therapies such as chemotherapy and radiotherapy have limitations, including off-target effects and drug resistance. In recent years, targeted therapies have emerged as promising alternatives, aiming to improve treatment specificity and reduce systemic toxicity. Among the most innovative approaches, bispecific antibodies, nanobodies, and extracellular vesicles offer distinct and complementary mechanisms for cancer therapy. Bispecific antibodies enhance immune responses and enable dual-targeting of cancer cells, nanobodies provide superior tumor penetration due to their small size, and extracellular vesicles present a novel platform for drug and RNA delivery. This work aims to review and analyze these three approaches, assessing their current applications, advantages, challenges, and future perspectives.

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

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.