ArticleFrontiers in immunology2026
Extracellular vesicles as prognostic biomarkers: results of a neoadjuvant chemoimmunotherapy clinical trial in stage IIIA (N2) non-small-cell lung cancer (SAKK 16/14).
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The introduction of immune checkpoint inhibitors has transformed cancer therapy. In non-small-cell lung cancer (NSCLC), immune-checkpoint blockade targeting programmed cell death 1 (PD-1) and its ligand PD-L1 has demonstrated substantial therapeutic efficacy and survival benefit. Recent evidence indicates that small extracellular vesicles (EVs), including exosomes, play a crucial role in modulating the tumor microenvironment and immune responses, potentially influencing immunotherapy efficacy. This study investigates longitudinal EV dynamics in patients with resectable stage IIIA (N2) NSCLC undergoing multimodal therapy, including sequential neoadjuvant chemotherapy (cisplatin and docetaxel) combined with anti-PD-L1 antibody (durvalumab) immunotherapy, followed by surgery, and adjuvant durvalumab. Serum samples from the SAKK 16/14 trial were analyzed using a galectin-based EV isolation technique. EV marker expression (PD-L1, PanEV, PanCK, EpCAM, and CD45) was assessed by flow cytometry at five predefined treatment time points. Nanoparticle tracking analysis and electron microscopy confirmed successful EV isolation. Results indicated a trend toward decreasing EV-MFI values following initial therapy. In current smokers, EV-associated markers levels correlated significantly with disease progression. Importantly, elevated post-therapeutic PanEV/PanCK double-positive EV levels were significantly associated with reduced event-free survival and overall survival (p = 0.001 and p = 0.003, respectively). This study demonstrates the feasibility of longitudinal EV biomarker assessment in NSCLC and suggests that EV-based liquid biopsies may provide complementary prognostic information in the context of cancer therapy. Such approaches may be particularly informative in heterogeneous cancer stages, supporting future efforts toward personalized treatment strategies.
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