Exosomal biomarkers in cancer: Insights from Multi-OMIC approaches

Extracellular vesicles, particularly exosomes, are emerging as powerful tools in cancer research due to their role in intercellular communication and their capacity to reflect the molecular composition of their originating cells. Multi-omic approaches, including proteomics, transcriptomics, metabolomics, and lipidomics, have revolutionized exosome research, enabling the discovery of novel biomarkers for early cancer detection, prognosis, and therapeutic monitoring. This review highlights the clinical applications of omics-driven exosomal biomarkers, emphasizing their roles in immunotherapy, cancer progression, and metastasis. It also examines how artificial intelligence (AI) facilitates biomarker discovery by enabling the analysis of complex multi-omic datasets. Recent clinical trials discussed here further illustrate the potential of exosomes in non-invasive cancer diagnostics and treatment. Tumor-specific proteins, RNAs, metabolic, and lipid profiles associated with malignancy underscore the utility of exosomes in precision oncology. The continued integration of AI and omics technologies will accelerate their clinical translation in cancer research and personalized medicine.