BACKGROUND: Aspirin and statins have been suggested to have potential chemopreventive effects against gastric cancer (GC), although the results of previous studies have been inconsistent. This study therefore aimed to investigate the association between the use of aspirin and statins and GC.
METHODS: A pooled analysis of seven case-control studies within the Stomach Cancer Pooling Project, including 3220 cases and 9752 controls, was conducted. Two-stage modeling analyses were used to estimate the association between aspirin and statin use and GC after adjusting for potential confounders.
RESULTS: The pooled odds ratio (OR) of GC for aspirin users versus nonusers was 0.72 (95% confidence interval [CI], 0.54-0.95). The protective effect of aspirin appeared stronger in individuals without a GC family history (OR, 0.60; 95% CI, 0.37-0.95), albeit with borderline heterogeneity between those with and without a family history (p = .064). The OR of GC decreased with increasing duration of aspirin use, with an OR of 0.41 (95% CI, 0.18-0.95) for durations of ≥15 years. An inverse, nonsignificant association with the risk of GC was observed for the use of statins alone (OR, 0.79; 95% CI, 0.52-1.18).
CONCLUSIONS: These findings suggest that aspirin use, particularly long-term use, is associated with a reduced risk of GC, whereas a similar association was not observed with statins, possibly because of the low frequency of use.

BACKGROUND: Identifying accurate prognostic factors is crucial for postoperative management of early gastric cancer (EGC) patients. Skeletal muscle quality (SMQ), defined by muscle density on computed tomography (CT) images, has been proposed as a novel prognostic factor. This study compared the prognostic significance of SMQ changes with the well-established factor of body weight (BW) loss in the postoperative EGC setting.
METHODS: This single-center retrospective study included 297 postoperative EGC patients (median age 69 years, 68.4% male) who had preoperative and 1-year-postoperative gastrectomy CT images. SMQ was defined as the modified intramuscular adipose tissue content (mIMAC = skeletal muscle density-subcutaneous fat density on CT images) and the change as ΔmIMAC. Log-rank test, Kaplan-Meier survival, and Cox proportional hazards regression analyses were used to assess the associations between prognosis and either ΔmIMAC or BW change (ΔBW). Prognosis prediction by ΔmIMAC and ΔBW was compared by using the area under the curve (AUC) of the receiver operating characteristic curve.
RESULTS: ΔmIMAC was significantly associated with prognosis (log-rank test; P = 0.037), but ΔBW was not (P = 0.243). Prognosis was significantly poorer in the severely decreased mIMAC group than in the preserved group (multivariate Cox proportional hazards regression analysis; P = 0.030) but was unaffected by BW changes (P = 0.697). The AUC indicated a higher prognostic value for ΔmIMAC than ΔBW (ΔmIMAC: AUC = 0.697, ΔBW: AUC = 0.542).
CONCLUSIONS: One-year post-gastrectomy SMQ changes may be better prognostic EGC predictors than BW changes.

BACKGROUND: This study reports the 2-year outcomes and biomarker analysis results of patients with locally advanced gastric and gastroesophageal junction (G/GEJ) adenocarcinoma who received neoadjuvant chemotherapy and immunotherapy in a phase II WuhanUHGI001 trial.
METHODS: Eligible patients with cT3/4aN+M0 locally advanced G/GEJ adenocarcinoma were screened, enrolled, and treated with 3 cycles of neoadjuvant tislelizumab and SOX followed by D2 gastrectomy and another 5 cycles of postoperative adjuvant SOX. The primary endpoint was major pathological response.
RESULTS: Of the 49 included patients, 24 (49.0%) achieved major pathological response and 13 (26.5%) achieved pathological complete response. During a median follow-up of 26.8 months, the 2-year progression-free survival (PFS) and overall survival (OS) rates were 69.4% and 81.2%, respectively. Grade 3-4 adverse events occurred in six patients (12.2%) during the neoadjuvant period, eight patients (17.0%) during the postoperative period, and seven patients (15.2%) during the adjuvant period. Biomarker analysis revealed that the pathological complete response showed no association with 2-year PFS and OS. Major pathological response showed a potentially strong association with improved 2-year PFS and OS rates. In addition, preoperative circulating tumor cells combined with pathological responses are helpful in prognosis assessment. In addition, our results showed that T downstaging, lymphocyte-to-monocyte ratio, and CD3+ T cells were independent factors that affect PFS. The signet ring cell component (SRCC), T downstaging, and neutrophil-to-lymphocyte ratio were independent factors affecting OS. Prognostic nomograms of PFS and OS constructed based on the multivariate Cox regression results demonstrated suitable calibration and discrimination ability.
CONCLUSIONS: Neoadjuvant tislelizumab plus SOX exhibits promising efficacy and acceptable toxicity in patients with locally advanced G/GEJ adenocarcinoma. In addition, our study established a prognostic risk signature and nomograms based on clinicopathological characteristics, which can accurately predict patient outcomes and aid in personalized treatment planning.

BACKGROUND: Mismatch repair deficient (dMMR) gastroesophageal cancers (GEC) are a distinct subgroup. Among patients with locally advanced disease, previous trial data suggest a good response to neoadjuvant immune checkpoint inhibitors (nICI).
METHODS: Since 2019, our institution has routinely performed MMR testing for new GEC cases. Patients diagnosed with GEC (2019-2024) were included in the study. Quantitative data are described as the median and interquartile range (IQR); qualitative data are described as quantities and percentages.
RESULTS: A total of 24 patients with dMMR GEC were identified following implementation of routine immunohistochemical testing; 14 were potentially resectable with a median follow-up of 14 months (IQR 8-27). All patients underwent pre-treatment positron emission tomography (PET; median SUV 20.9). Among the 14 potentially resectable patients, 4 underwent immediate surgery, 10 were treated with nICI, and 5 underwent surgical resection to date. All regimens included PD-1 inhibitors, with 70% receiving pembrolizumab. Re-staging PET was performed in five patients; the median post-nICI SUV was 5.1 (range 4.7-6.3). All resected specimens had gross ulceration after nICI, but 60% (N = 3) had a pathologic complete response (pCR) following nICI; one patient had a near-complete response (nCR) and one patient had a partial response (pPR). Reduction in SUV was 75% and 82% in the pCR patients, 25% in the nCR patient, and 43% in the pPR patient.
CONCLUSIONS: dMMR GECs are responsive to nICI in this limited experience, mirroring early clinical trial data. Given persistent metabolic activity and visible ulceration despite pCR, studies should continue to optimize tools for estimating post-nICI pCR in these patients.

Peritoneal recurrence (PR) in gastric cancer after curative resection has poor prognosis. Therefore, we aimed to construct a nomogram to predict PR, and establish PR score for risk stratification to guide adjuvant chemotherapy. A total of 315 patients with gastric cancer after radical surgery were included, and randomly stratified into training group (n = 221) and validation group (n = 94). Univariate and multivariate analyses were used to determine predictive factors of PR. The nomogram was constructed to predict the risk of PR. We utilized the time-dependent area under the receiver operating characteristic (ROC) curves (AUCs), calibration curves, and decision curve analysis (DCA) to evaluate the performance of the nomogram. Multivariate analysis showed that tumor site, N stage, preoperative CEA, and postoperative CA199 were independent predictors of PR. A nomogram was constructed to predict PR based on these factors. The AUC value was 0.755 in the training group and 0.715 in the validation group. The calibration curves showed good agreement between prediction and observation in the training and validation groups. The decision curve analysis displayed a good net benefit of the nomogram. The novel PR score was developed and patients were stratified into the low-, medium-, and high -risk groups. For the high-risk group, postoperative adjuvant chemotherapy significantly improved patients\' overall survival (OS) and disease-free survival (DFS). The establishment of nomogram facilitates the prediction of PR after radical gastrectomy, and a novel PR score may help guide adjuvant chemotherapy for gastric cancer.

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BACKGROUND: CD8+ T lymphocyte infiltration is closely associated with the prognosis and immunotherapy response of gastric cancer (GC). For now, the examination of CD8 infiltration levels relies on endoscopic biopsy, which is invasive and unsuitable for longitude assessment during anti-tumor therapy.
OBJECTIVE: This work aims to develop and validate a noninvasive workflow based on contrast-enhanced CT (CECT) images to evaluate the CD8+ T-cell infiltration profiles of GC.
METHODS: GC patients were retrospectively and consecutively enrolled and randomly assigned to the training (validation) or test cohort at a 7:3 ratio. All patients were binary classified into the CD8-high (infiltrated proportion ≥ 20%) or CD8-low group (infiltrated proportion < 20%) group. A total of 1170 radiomics features were extracted from each presurgical CECT series. After feature selection, fifteen radiomics features were transmitted to three independent machine-learning models for the computation of predictive radiological scores. Multilayer perceptron (MLP) was applied to merge the radiological scores with clinical factors. The predictive efficacy of the radiological scores and of the combined model was evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis in both the training and test cohorts.
RESULTS: A total of 210 patients were enrolled in this study (mean age: 63.22 ± 8.74 years, 151 men), and were randomly assigned to the training set (n = 147) or the test set (n = 63). The merged radiological score was correlated with CD8 infiltration in both the training (p = 1.8e-10) and test cohorts (p = 0.00026). The combined model integrating the radiological scores and clinical features achieved an area under the curve (AUC) value of 0.916 (95% CI: 0.872-0.960) in the training set and 0.844 (95% CI: 0.742-0.946) in the test set for classifying CD8-high GCs. The model was well-calibrated and exhibited net benefit over \"treat-all\" and\"treat-none\" strategies in decision curve analysis.
CONCLUSIONS: Artificial intelligent systems combining radiological features and clinical factors could accurately predict CD8 infiltration levels of GC, which may benefit personalized treatment of GC in the context of immunotherapy.

BACKGROUND: Vascular invasion (VI) is closely related to the metastasis, recurrence, prognosis, and treatment of gastric cancer. Currently, predicting VI preoperatively using traditional clinical examinations alone remains challenging. This study aims to explore the value of radiomics analysis based on preoperative enhanced CT images in predicting VI in gastric cancer.
METHODS: We retrospectively analyzed 194 patients with gastric adenocarcinoma who underwent enhanced CT examination. Based on pathology analysis, patients were divided into the VI group (n = 43) and the non-VI group (n = 151). Radiomics features were extracted from arterial phase (AP) and portal venous phase (PP) CT images. The radiomics score (Rad-score) was then calculated. Prediction models based on image features, clinical factors, and a combination of both were constructed. The diagnostic efficiency and clinical usefulness of the models were evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).
RESULTS: The combined prediction model included the Rad-score of AP, the Rad-score of PP, Ki-67, and Lauren classification. In the training group, the area under the curve (AUC) of the combined prediction model was 0.83 (95% CI 0.76-0.89), with a sensitivity of 64.52% and a specificity of 92.45%. In the validation group, the AUC was 0.80 (95% CI 0.67-0.89), with a sensitivity of 66.67% and a specificity of 88.89%. DCA indicated that the combined prediction model might have a greater net clinical benefit than the clinical model alone.
CONCLUSIONS: The integrated models, incorporating enhanced CT radiomics features, Ki-67, and clinical factors, demonstrate significant predictive capability for VI. Moreover, the radiomics model has the potential to optimize personalized clinical treatment selection and patient prognosis assessment.

Gastric cancer remains a significant health challenge despite advancements in diagnosis and treatment. Early detection is critical to reducing mortality, necessitating the investigation of molecular mechanisms underlying gastric cancer progression. This study focuses on BRD4 expression and its correlation with miR-26a-3p, DLG5-AS1, and JMJD1C-AS1 lncRNAs in gastric cancer. Analysis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets revealed significant upregulation of BRD4 in gastric cancer tissues compared to normal tissues, correlating negatively with miR-26a-3p and positively with DLG5-AS1 and JMJD1C-AS1 lncRNAs. Quantitative RT-PCR confirmed these findings in 25 gastric cancer tissue samples and 25 normal samples. BRD4\'s overexpression was associated with reduced survival rates and older patient age. MiR-26a-3p, a known tumor suppressor, showed decreased expression in gastric cancer tissues, with ROC analysis suggesting it, alongside BRD4, as a potential diagnostic biomarker. Additionally, bioinformatics predicted miR-26a-3p\'s interaction with BRD4 mRNA. Upregulated lncRNAs DLG5-AS1 and JMJD1C-AS1 likely act as competing endogenous RNAs, sponging miR-26a-3p, thus promoting BRD4 dysregulation. These lncRNAs have not been previously studied in gastric cancer. The findings propose a novel BRD4/lncRNA/miRNA regulatory axis in gastric cancer, highlighting the potential of BRD4, DLG5-AS1, and JMJD1C-AS1 as biomarkers for early diagnosis. Further studies with larger sample sizes and in vivo and in vitro experiments are needed to elucidate this regulatory mechanism\'s role in gastric cancer progression.

Gastric cancer (GC) remains a global disease with a high mortality rate, the lack of effective treatments and the high toxicity of side effects are primary causes for its poor prognosis. Hence, urgent efforts are needed to find safe and effective therapeutic strategies. Gypenoside (Gyp) is a widely used natural product that regulates blood glucose to improve disease progression with few toxic side effects. Given the crucial role of abnormal glycometabolism in driving tumor malignancy, it is important to explore the association between Gyp and glycometabolism in GC and understand the mechanism of action by which Gyp influences glycometabolism. In this study, we demonstrated that Gyp suppresses GC proliferation and migration both in vitro and in vivo. We identified that Gyp suppresses the malignant progression of GC by inhibiting glycolysis using network pharmacology and metabolomics. Transcriptome analysis revealed that the Hippo pathway is a key regulator of glycolysis by Gyp in GC. Furthermore, Gyp induced upregulation of LATS1/2 proteins, leading to increased YAP phosphorylation and decreased TAZ protein expression. The YAP agonist XMU-MP-1 rescued the inhibitory effect of Gyp on GC proliferation by reversing glycolysis. These findings confirmed that Gyp inhibits GC proliferation by targeting glycolysis through the Hippo pathway. Our study examined the role of Gyp in the malignant progression of GC, explored its therapeutic prospects, elucidated a mechanism by which Gyp suppresses GC proliferation through interference with the glycolytic process, thus providing a potential novel therapeutic strategy for GC patients.