Extracellular Vesicles and Artificial Intelligence: Unique Weapons against Breast Cancer

Abstract

Breast cancer (BC) caused 685,000 deaths globally in 2020, earning the title of the most common type of tumor among females. With a multifactorial genesis, BC is influenced by several factors such as age, genetic and epigenetic predisposition, and an individual’s exposome, and its classification is based on morphological/histological, invasiveness, and molecular futures. Extracellular vesicles (EVs) are cell-derived lipid-bilayer-delimited nanoparticles, which are distinguishable by size, genesis, and the markers expressed in exosomes (40 to 150 nm), microvesicles (40 to 10,000 nm), and apoptotic bodies (100–5000 nm). Produced in physiological and pathological cellular contexts, EVs are shuttles of biological material and are implicated in cell-to-cell communications, thus attracting significant interest in diagnostic and drug delivery research. We report and discuss the latest evidence regarding the important role of EVs in BC, deepening their implication in tumorigenesis and metastatic mechanisms. On the other hand, the use of BC-derived EVs as prognostic biomarkers and therapeutic approaches is undergoing investigation. Hence, EVs have become new weapons in precision medicine; however, only with the support of advanced algorithms such as artificial intelligence (AI) can we develop a wide range of information. Looking ahead, it is possible to see the application of AI in the prognosis and diagnosis of different pathologies.

Keywords

• hormonal receptors
• extracellular vesicles
• machine learning
• prevention
• precision medicine
• drug resistance