Extracellular vesicle-derived lncRNA-GC1 serves as a novel biomarker for predicting and monitoring the immunotherapeutic outcomes of patients with gastric cancer

Background Efforts to predict the outcomes of patients with gastric cancer (GC) following immune checkpoint inhibitor (ICI) treatments remain limited, owing to a lack of reliable biomarkers. Studies have found that extracellular vesicle (EV)-derived lncRNA-GC1 may serve as a GC-specific biomarker. This study was designed to expand on these previous results by estimating the usefulness of EV-derived lncRNA-GC1 as a predictive indicator for patients with GC who undergo ICI treatments. Methods EV-derived lncRNA-GC1 levels were measured using quantitative polymerase chain reaction (qPCR) in patients with unresectable or metastatic GC who were receiving ICI treatments. Correlations between this biomarker and ICI treatment outcomes were analyzed in a training cohort (n = 136), three external validation cohorts (n = 188, n = 214, and n = 30), and one prospective cohort (n = 192). Results Circulating EVs exhibited a lncRNA-GC1 expression profile that was distinct from that of tissues or circulating cells. EV-derived lncRNA-GC1 levels were found to be independent of PD-L1 expression status or the density of CD8 ⁺ T cell infiltration. EV-derived lncRNA-GC1 could be used to effectively predict ICI-related patient outcomes, and could be used for dynamic monitoring throughout treatments. Lower levels of EV-derived lncRNA-GC1 were associated with tumor microenvironmental characteristics such as more robust antitumor immunity—including higher levels of activated CD8 ⁺ T/NK cells and an increased TH1/TH2 ratio. Such biomarkers can be stably detected in clinical practice. These results were consistent in both the two external validation cohorts and the one prospective cohort. Conclusion EV-derived lncRNA-GC1 can be used to reliably predict immunotherapeutic outcomes in patients with GC who undergo ICI treatments, suggesting that targeted analyses of this lncRNA may be useful for guiding treatment planning, monitoring, and associated decision-making processes.