Extracellular vesicles as diagnostic and prognostic biomarkers in non-small cell lung cancer

作者
Shayista Akbar,Queenie Fernandes,Zeenath Safira K. M. Yoosuf,Reem Elasad,Laila Assami,Karama Makni‐Maalej,Varghese Philipose Inchakalody,Mariam Al-Muftah,Shahab Uddin,Maysaloun Merhi,A R Ahmad,Said Dermime
出处
期刊:Expert Review of Molecular Diagnostics [Taylor & Francis]
卷期号:26 (8): 667-679
标识
DOI:10.1080/14737159.2026.2693700
摘要

INTRODUCTION: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis and limited availability of reliable biomarkers. Extracellular vesicles (EVs) are membrane-bound nanoparticles released by cells that carry nucleic acids, proteins, and lipids reflective of their cellular origin. Their stability and accessibility through minimally invasive sampling make them promising liquid biopsy biomarkers. AREAS COVERED: This review summarizes current evidence supporting EVs as diagnostic and prognostic biomarkers in NSCLC. We discuss the clinical relevance of EV-associated molecular signatures, including miRNAs, other non-coding RNAs, and proteins, in early detection, disease stratification, and outcome prediction. Recent advances in EV isolation and characterization technologies, particularly microfluidic and high-throughput platforms, are highlighted. We also examine key barriers to clinical translation, including biological heterogeneity, methodological variability, and the lack of standardized protocols. EXPERT OPINION: EVs have the potential to transform NSCLC management by enabling minimally invasive diagnosis, real-time disease monitoring, and personalized treatment strategies. However, widespread clinical implementation requires standardized methodologies, improved tumor-specific EV enrichment, and large-scale validation studies. Future integration of multi-omics, artificial intelligence, and advanced detection technologies is expected to enhance biomarker performance and facilitate the incorporation of EV-based liquid biopsy approaches into precision oncology.

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