Breast cancer is the most common cancer in women worldwide and development of distant metastases is a main reason for cancer mortality. The median survival after diagnosis of metastatic breast cancer is 2 year (with a broad spreading from a few months till several years). To increase median survival times the effectiveness of cancer treatments should be optimized and associated morbidity should be reduced. Treatment response in terms of efficacy and toxicity should be detected before clinical manifestation. Unfortunately, in current clinical practice, the most common diagnostic tools to analyze therapy efficiency are based on clinical data and imaging modalities. Most of these analyses require long-term treatment and often fail to correctly assess therapy response.

Extracellular Vesicles (EVs) are nanosized membrane vesicles which contain bioactive proteins, lipids, and nucleic acids, and emerge as indicators and functional agents of cancer. EVs are released by all cells, including cancer cells and circulate in the blood stream. EVs provide unique opportunities for the development of novel biomarkers in the context of therapeutic efficacy because their molecular content is a fingerprint of the releasing cells and their status; and because they are enriched for highly selected biomarkers which otherwise would constitute only a very small proportion (less than 0.01%) of the total molecular content of blood.

Pioneer studies suggest that quantification and characterization of EVs can be implemented to refine patient prognosisand predict therapy response. The final objective of this project is to monitor treatment efficiency based on an EV-derived biomarker.

To achieve this we will make use of three complementary work packages:

• Workpackage 1: Isolation and proteomic characterization of EVs from plasma
• Workpackage 2: Evaluation of EV signatures in metastatic mouse models under treatment
• Workpackage 3: Evalutation of EV signatures in longitudinal plasma samples from treatment responsive and treatment unresponsive metastatic breast cancer patients

This project is multidisciplinary, and attempts to consider the staggering costs of therapy, the selection of patients based on response-resistance markers will be key to the economic sustainability of cancer management strategies. Most importantly, EV biomarker monitoring may prevent unnecessary exposure of unresponsive patients to ineffective therapy.