Advances in the role of extracellular vesicles in circulating microRNA biomarker discovery for lung cancer

TL;DR

This paper explores how tiny cell particles called extracellular vesicles can carry microRNAs that may help detect and monitor lung cancer non-invasively.

Contribution

The paper highlights the novel use of EV-derived miRNAs as stable and tumor-specific biomarkers for early diagnosis and treatment monitoring in lung cancer.

Findings

EV-associated miRNAs show distinct expression patterns in lung cancer patients, correlating with tumor progression and survival.

Dynamic changes in EV-miRNA profiles during treatment can predict responses to immunotherapy and targeted therapy.

EV-derived miRNAs are stable in bodily fluids and exhibit tumor specificity, making them promising for liquid biopsy applications.

Abstract

Lung cancer remains a leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis and the limited efficacy of current therapeutic approaches. Recent advancements highlight the potential of extracellular vesicles (EVs), particularly those carrying microRNA (miRNA) molecules, as promising non-invasive biomarkers for early detection, prognosis, and therapy monitoring. EVs are nanoscale vesicles secreted by tumour cells, capable of transporting various bioactive molecules including miRNAs while preserving their structural stability in circulation. These miRNAs mirror the molecular state of the tumour and often exhibit distinct expression signatures depending on cancer subtype and stage. Studies have shown that specific EV-associated miRNAs are significantly dysregulated in lung cancer patients and correlate with tumour progression, metastatic potential, and overall survival. Moreover, tracking dynamic changes in EV-miRNA profiles during treatment may provide predictive insights into responsiveness to immunotherapy and targeted therapy. This review emphasizes the diagnostic and prognostic utility of EV-derived miRNAs, highlighting their tumour specificity and stability in bodily fluids. In addition, we summarise key challenges such as the lack of standardisation, EV heterogeneity, and technical variability, while also outlining future directions including single-EV detection, multi-omics integration, AI-driven diagnostics, and therapeutic applications. By integrating these biomarkers into clinical workflows via liquid biopsy, it may become possible to detect lung cancer earlier and adapt therapeutic strategies more effectively ultimately improving patient outcomes and offering new directions in precision oncology.

Figures