<p>The search for reliable cancer biomarkers is increasingly driven by the need for non-invasive tools that can monitor tumor dynamics in real time. Extracellular vesicles (EVs) are a heterogeneous family of nanoparticles secreted by almost all cell types under physiological and pathological conditions. By carrying proteins, nucleic acids, lipids and metabolites that reflect the molecular state of their cells of origin, EVs act as dynamic messengers of tumor biology. Their stability and abundance in easily accessible body fluids make them ideal candidates for liquid biopsy, offering a unique opportunity to investigate the molecular mechanisms underlying cancer initiation, progression and therapy resistance. Advances in high-throughput omics technologies, including proteomics, metabolomics, lipidomics and transcriptomics, have enabled comprehensive profiling of EV cargo. These approaches have already identified promising biomarkers now entering clinical application, creating opportunities for earlier detection and more personalized interventions. However, relying on a single omics layer captures only a fraction of the molecular complexity underlying malignant disease. Integrative multi-omics strategies might uncover the regulatory networks and signaling pathways that drive tumor heterogeneity and evolution. Bioinformatics multi-omics integration focuses on developing tools that combine data from multiple omics experiments, revealing how their components interact and how these interactions change in disease. This review summarizes recent advances in EV-based multi-omics research for cancer diagnosis and clinical management, emphasizing how integrative approaches not only enhance biomarker discovery but also provide a systems-level understanding of disease mechanisms, paving the way toward precision and personalized medicine.</p>