Xiaohui Lv

Objective: The relationship between surgical outcomes and metastatic sites in ovarian cancer (OC) is known, but the role of metastatic site-specific tumor burden remains unclear. Methods: We prospectively analyzed data from 202 OC patients. We developed a preoperative protocol evaluating tumor burden in 30 metastatic sites and created a predictive score for suboptimal cytoreduction, which was externally validated. Results: MRI-assessed tumor burdens demonstrated superior consistency with surgical findings compared to CT (κ = 0.4–1.0). Three site-specific tumor burdens (diaphragmatic spleen surface, hepatorenal recess, mesentery), upper abdominal tumor burden, and two clinical factors were identified as predictors of suboptimal cytoreduction. The predictive score incorporating these factors achieved an AUC of 0.873 (0.815 externally validated), outperforming metastatic site-integrated scores including the simulated Fagotti score (AUC: 0.656) and Suidan score (AUC: 0.8308). R0 resection rates were inversely correlated with predictive scores: 94.87% for scores of 0–3 versus 8.57% for scores >14. The peak of Youden’s index reached 11, and patients with predictive scores <11 had longer median progression-free survival. Conclusions: We demonstrated that site-specific tumor burden is correlated with surgical outcomes in OC. Incorporating tumor burden into preoperative assessment enhances prediction performance. We developed a clinically applicable tool, marking a shift from evaluating metastatic sites to assessing metastatic site-specific tumor burden.

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.

Metabolism-associated genes (MAGs) are important regulators of tumor progression and can affect a variety of physiological processes. In this study, we focused on the relationship between MAGs and Ovarian cancer (OC) prognosis. Metabolism-related genes were extracted from the Cancer Genome Atlas (TCGA) database. Through univariate COX and lasso regression models, a dynamic risk model based on MAGs was established. Compared with other clinical factors, demonstrated the ability of the model to predict the prognosis of patients with OC. The clinical samples were used to verify the expression of these MAGs. A metabolism-associated gene signature was constructed by LASSO Cox regression analysis in OC, which was composed of 3-MAGs (PTGIS, AOC3, and IDO1). The signature was used to classify the OC patients into high-risk and low-risk groups. The overall survival of the low-risk group was significantly better than that of the high-risk group. The analysis of the therapeutic effect of bevacizumab showed that bevacizumab was not conducive to improving the prognosis of the low-risk group. We constructed a prognostic model of MAGs in OC, which can be used to predict the prognosis of OC patients and may have a good guiding significance in the individualized treatment of patients.

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.