A previous validated study has identified the diagnostic value of circulating exosomal lncRNA-GC1 for detecting and monitoring gastric cancer. We aimed to further determine the predictive role of circulating exosomal lncRNA-GC1 for prognosis and chemotherapy response. We retrospectively conducted a multi-phase analysis with four independent cohorts of 981 patients. A training cohort was used to generate the predictive model. One internal and two external cohorts were recruited as validation cohorts. Patients with stage II or III gastric cancer in the combined cohort were used to evaluate the predictive value of circulating exosomal lncRNA-GC1 for chemotherapy response. In the training cohort, circulating exosomal lncRNA-GC1 was identified as an independent prognostic predictor for disease-free and overall survival. A prognostic risk stratification model based on circulating exosomal lncRNA-GC1 and AJCC stage revealed better predictive accuracy for disease-free and overall survival than the traditional AJCC stage system alone (C-index: DFS 0.701 vs 0.614; OS 0.720 vs 0.611, both P<0.05). And it has been further verified in the validation cohorts. In interaction analysis, for stage II and III GC, patients with low-level of circulating exosomal lncRNA-GC1 derived more survival benefit from adjuvant chemotherapy (P < 0.05); while those with high-level did not. Measurement of circulating exosomal lncRNA-GC1 provides clinically important prognostic information and could complement the AJCC stage to optimize decision-making for selecting patients who could benefit more from fluorouracil-based chemotherapy after surgery. The funders are listed in the Acknowledgement.

Background Early-onset gastric cancer (EOGC) is a lethal malignancy. It differs from late-onset gastric cancer (LOGC) in clinical and molecular characteristics. The current strategies for EOGC detection have certain limitations in diagnostic performance due to the rising trend in EOGC. Objective We developed a liquid biopsy signature for EOGC detection. Design We use a systematic discovery approach by analysing genome-wide transcriptomic profiling data from EOGC (n=43), LOGC (n=31) and age-matched non-disease controls (n=37) tissue samples. An extracellular vesicle-derived long non-coding RNA (EV-lncRNA) signature was identified in blood samples from a training cohort (n=299), and subsequently confirmed by qPCR in two external validation cohorts (n=462 and n=438), a preoperative/postoperative cohort (n=66) and a gastrointestinal tumour cohort (n=225). Results A three EV-lncRNA (NALT1, PTENP1 and HOTTIP) liquid biopsy signature was developed for EOGC detection with an area under the receiver operating characteristic curve (AUROC) of 0.924 (95% CI 0.889 to 0.953). This EV-lncRNA signature provided robust diagnostic performance in two external validation cohorts (Xi’an cohort: AUROC, 0.911; Beijing cohort: AUROC, 0.9323). Furthermore, the EV-lncRNA signature reliably identified resectable stage EOGC patients (stage I/II) and demonstrated better diagnostic performance than traditional GC-related biomarkers in distinguishing early-stage EOGC (stage I) from precancerous lesions. The low levels of this biomarker in postsurgery and other gastrointestinal tumour plasma samples indicated its GC specificity. Conclusions The newly developed EV-lncRNA signature effectively identified EOGC patients at a resectable stage with enhanced precision, thereby improving the prognosis of patients who would have otherwise missed the curative treatment window.

Background: The timing of surgery for patients with gastric cancer (GC) who undergo neoadjuvant chemotherapy (neoCT) was mainly guided by serial radiologic imaging. However, an earlier assessment was indispensable to avoid delayed treatment for nonresponders and excessive toxicity for responders. Our previous study has identified circulating extracellular vesicles-derived lncRNA-GC1 as a biomarker for early detection and monitoring progression of GC. However, the potential role of neoCT remains poorly understood. Methods: In this explorative biomarker analysis, we conducted a multi-cohort study to examine longitudinal levels of circulating extracellular vesicles-derived lncRNA-GC1 in 798 patients enrolled in the RESONANCE study (NCT01583361). Both circulating extracellular vesicles-derived lncRNA-GC1 and traditional gastrointestinal biomarkers were assessed at defined time nodes. Computed tomography (CT) scans were performed before treatment and 8–10 weeks and assessed based on the RECIST criteria. Results: Circulating extracellular vesicles-derived lncRNA-GC1 could be detected in 96.3% of patients at baseline, and significant reductions were observed before cycle 2 (P50%) and radiographic response (Cohen’s κ, 0.704). Importantly, circulating extracellular vesicles-derived lncRNA-GC1 maintained predictive value in two external cohorts. Patients with circulating extracellular vesicles-derived lncRNA-GC1 response showed superior disease-free survival [hazard ratio (HR), 0.6238; 95% CI, 0.4095–0.9501; P=0.0118] and overall survival (HR, 0.6131; 95% CI, 0.4016–0.9358; P=0.0090). Conclusion: Circulating extracellular vesicles-derived lncRNA-GC1 is an early marker of neoCT efficacy and predicts superior survival in GC patients treated with neoCT.

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. EV-derived lncRNA-GC1 levels were measured using real-time polymerase chain reaction (RT-PCR) 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), two external validation cohorts (n = 188 and n = 214), one expanding cohort (n = 30), and one prospective cohort (n = 192). 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. 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.