Article Impact Level: HIGH Data Quality: STRONG Summary of Clinica Chimica Acta, 579, 120606. https://doi.org/10.1016/j.cca.2025.120606 Dr. Fatima M. Al-Daffaie et al.
Points
- Researchers conducted a narrative review of over one hundred studies to evaluate the diagnostic potential of exosomes found in bodily fluids like blood and urine.
- The analysis utilized a multi-omics approach to decode the molecular cargo of extracellular vesicles including proteins and genetic material released by tumor cells.
- Artificial intelligence was identified as a crucial tool for scanning complex molecular datasets to uncover biomarkers that human observation might miss.
- The study found that tumor-derived exosomes reflect the internal state of cancer cells and provide a detailed map of disease progression and immune evasion.
- Findings suggest that liquid biopsies using exosomal analysis could eventually replace invasive tissue sampling for early detection and monitoring of patient response to therapy.
Summary
This narrative review published in Clinica Chimica Acta synthesized findings from over 100 studies conducted between 2018 and 2025 to evaluate the diagnostic utility of exosomes in oncology. The authors aimed to assess the viability of liquid biopsies utilizing extracellular vesicles derived from body fluids such as blood and urine. By focusing on the molecular cargo of exosomes—specifically proteins, genetic material, lipids, and metabolites—the review sought to determine their efficacy as noninvasive biomarkers for early detection, prognosis, and therapeutic monitoring compared to traditional tissue sampling.
The analysis identified four major associations by employing a multi-omics approach that integrated proteomics, transcriptomics, metabolomics, and lipidomics. The review highlighted that tumor-derived exosomes undergo distinct compositional changes that mirror the intracellular environment of the malignancy, effectively mapping mechanisms of cancer communication and immune evasion. Furthermore, the integration of artificial intelligence (AI) was identified as a critical accelerator, enabling the processing of complex molecular datasets to uncover patterns invisible to standard observation and identify reliable biomarkers with greater precision.
The synthesized data supports the potential of exosomal analysis to serve as a cornerstone for precision oncology and immunotherapy monitoring. The authors conclude that decoding exosomal cargo allows for the prediction of tumor aggressiveness and patient response to therapy. While the review confirms the theoretical and experimental validity of this noninvasive approach, it emphasizes that continued integration of AI and multi-omics technologies is essential to translate these findings from clinical trials into routine diagnostic practice.
Link to the article: https://www.sciencedirect.com/science/article/abs/pii/S0009898125004851?via%3Dihub
References
Al-Daffaie, F. M., Al-Daffaie, M. M., Abuhelwa, A. Y., Alqudah, M. A. Y., Aleidi, S. M., El-Huneidi, W., Abu-Gharbieh, E., Alzoubi, K. H., Bustanji, Y., & Semreen, M. H. (2026). Exosomal biomarkers in cancer: Insights from Multi-OMIC approaches. Clinica Chimica Acta, 579, 120606. https://doi.org/10.1016/j.cca.2025.120606
