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Aim: To predict the prognosis of gastric cancer patients with triple-negative tumor markers. Materials & methods: Prognostic factors of the nomogram were identified through univariate and multivariate Cox regression analyses. Calibration and receiver operating characteristic curves were used to assess accuracy. Decision curve analysis and concordance indexes were utilized to compare the nomogram with the pathological tumor, node, metastasis stage. Results: A nomogram incorporating log odds of positive lymph nodes, tumor size and lymphocyte-to-monocyte ratio was constructed. The calibration and receiver operating characteristic curves (area under the curve >0.85) showed high accuracy in predicting overall survival. The concordance indexes (0.832 vs 0.760; p < 0.001) and decision curve analysis demonstrated that the nomogram was superior to the pathological tumor, node, metastasis stage. Conclusion: A prediction and risk stratification nomogram has been developed and validated for gastric cancer patients with triple-negative tumor markers. [ABSTRACT FROM AUTHOR]

Background Tumor-stroma percentage (TSP) is a prognostic risk factor in numerous solid tumors. Despite this, the prognostic significance of TSP in gastric cancer (GC) remains underexplored. Through the development of a personalized predictive model and a semi-automatic identification system, our study aimed to fully unlock the predictive potential of TSP in GC. Methods We screened GC patients from Shanghai General Hospital (SGH) between 2012 and 2019 to develop and validate a nomogram. Univariate and multivariate Cox proportional hazards regression analyses were employed to identify independent prognostic factors influencing the prognosis for GC patients. The nomogram was further validated externally by using a cohort from Bengbu Medical College (BMC). All patients underwent radical gastrectomy, with those diagnosed with locally advanced GC receiving adjuvant chemotherapy. The primary outcome measured was overall survival (OS). The semi-automatic identification of the TSP was achieved through a computer-aided detection (CAD) system, denoted as TSP-cad, while TSP identified by pathologists was labeled as TSP-visual. Results A total of 813 GC patients from SGH and 59 from BMC were enrolled in our study. TSP-visual was identified as an adverse prognostic factor for OS in GC and was found to be associated with pathological Tumor Node Metastasis staging system (pTNM) stage, T stage, N stage, perineural invasion (PNI), lymphovascular invasion (LVI), TSP-visual, tumor size, and other factors. Multivariate Cox regression using the training cohort revealed that TSP-visual (hazard ratio [HR], 2.042; 95% confidential interval [CI], 1.485–2.806; P  <   0.001), N stage (HR, 2.136; 95% CI, 1.343–3.397; P  =   0.010), PNI (HR , 1.791; 95% CI, 1.270–2.526; P  =   0.001), and LVI (HR, 1.482; 95% CI, 1.021–2.152; P  =   0.039) were independent predictors. These factors were incorporated into a novel nomogram, which exhibited strong predictive accuracy for 5-year OS in the training, internal validation, and external validation cohorts (area under the curve = 0.744, 0.759, and 0.854, respectively). The decision curve analysis of the nomogram and concordance indexes across the three cohorts outperformed the traditional pTNM (P  <   0.05). Additionally, TSP-cad assessment using a rapid multi-dynamic algorithm demonstrated good agreement with TSP-visual. Conclusions The novel nomogram based on TSP could effectively identify individuals at risk of a poor prognosis among patients with GC. TSP-cad is anticipated to enhance the evaluation process of TSP. [ABSTRACT FROM AUTHOR]

Cuproptosis, caused by excessively high copper concentrations, is urgently exploited as a potential cancer therapeutic. However, the mechanisms underlying the initiation, propagation, and ultimate execution of cuproptosis in tumors remain unknown. Here, we show that copper content is significantly elevated in gastric cancer (GC), especially in malignant tumors. Screening reveals that METTL16, an atypical methyltransferase, is a critical mediator of cuproptosis through the m6A modification on FDX1 mRNA. Furthermore, copper stress promotes METTL16 lactylation at site K229 followed by cuproptosis. The process of METTL16 lactylation is inhibited by SIRT2. Elevated METTL16 lactylation significantly improves the therapeutic efficacy of the copper ionophore– elesclomol. Combining elesclomol with AGK2, a SIRT2-specific inhibitor, induce cuproptosis in gastric tumors in vitro and in vivo. These results reveal the significance of non-histone protein METTL16 lactylation on cuproptosis in tumors. Given the high copper and lactate concentrations in GC, cuproptosis induction becomes a promising therapeutic strategy for GC. Cuproptosis regulation in tumors is unclear. Here the authors find that copper promotes METTL16 lactylation, inducing cuproptosis via stabilizing FDX1 in gastric cancer. Targeting lactyl-METTL16 and cuproptosis offers a potential feasible strategy for cancer therapy. [ABSTRACT FROM AUTHOR]