Distal gastrectomy (DG) with lymph node dissection for gastric cancer is routinely performed. In this meta-analysis, we present an updated overview of the perioperative and oncological outcomes of laparoscopic DG (LDG) and robotic DG (RDG) to compare their safety and overall outcomes in patients undergoing DG. An extensive search was conducted using the MEDLINE, EMBASE, PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials from the establishment of the database to June 2023 for randomized clinical trials comparing RDG and LDG. The primary outcome was operative results, postoperative recovery, complications, adequacy of resection, and long-term survival. We identified twenty studies, evaluating 5,447 patients (1,968 and 3,479 patients treated with RDG and LDG, respectively). We observed no significant differences between the two groups in terms of the proximal resection margin, number of dissected lymph nodes, major complications, anastomosis site leakage, time to first flatus, and length of hospital stay. The RDG group had a longer operative time (P < 0.00001), lesser bleeding (P = 0.0001), longer distal resection margin (P = 0.02), earlier time to oral intake (P = 0.02), fewer overall complications (P = 0.004), and higher costs (P < 0.0001) than the LDG group. RDG is a promising approach for improving LDG owing to acceptable complications and the possibility of radical resection. Longer operative times and higher costs should not prevent researchers from exploring new applications of robotic surgery.

Aims/Background Trait emotional intelligence is associated with anxiety and depression symptoms and quality of life in cancer patients. However, studies on the relationship of trait emotional intelligence with anxiety, depression, and quality of life in gastric cancer patients are limited. This study investigates the relationship of trait emotional intelligence with depression and quality of life in gastric cancer patients to provide a theoretical basis for clinical management. Methods A total of 270 patients with gastric cancer treated in our hospital from July 2020 to July 2023 were selected, of which 31 patients with missing questionnaire entries and missed visits were screened out, resulting in the enrolment of 239 gastric cancer patients in this study. In this survey, self-administered general information questionnaires, namely Trait Emotional Intelligence Short Form (TEIQue-SF), European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30), and Hospital Anxiety and Depression Scale (HADS) were used. Results TEIQue-SF total scores were positively correlated with QLQ-C30 scores (p < 0.001) and negatively correlated with HADS-A and HADS-D scores (p < 0.001). TEIQue-SF total score was a superior positive predictor of the QLQ-C30 score (β = 0.412, p < 0.001) and a superior negative predictor of the HADS score (β = -0.740, p < 0.001). TEIQue-SF total score (β = 0.141, p = 0.006) and HADS score (β = -0.665, p < 0.001) were good predictors of QLQ-C30 score. The direct effect of TEIQue-SF total score on QLQ-C30 score was 0.141, while HADS score between TEIQue-SF total score and QLQ-C30 score had a mediated effect value of 0.492. Conclusion Trait emotional intelligence not only directly affects the quality of life, but also indirectly affects the quality of life through anxiety and depression. Clinicians should pay attention to the anxiety, depression, and emotional intelligence of patients with gastric cancer to help them improve their quality of life.

BACKGROUND: Sarcopenic obesity (SO) affects outcomes in various malignancies. However, its clinical significance in patients undergoing neoadjuvant chemotherapy (NAC) for locally advanced gastric cancer (LAGC) remains unclear. This study investigated the impact of pre- and post-NAC SO on postoperative morbidity and survival.
METHODS: Data from 207 patients with LAGC, who underwent NAC followed by radical gastrectomy between January 2010 and October 2019, were reviewed. Skeletal muscle mass and visceral fat area were measured pre- and post-NAC using computed tomography to define sarcopenia and obesity, the coexistence of which was defined as SO.
RESULTS: Among the patients, 52 (25.1%) and 38 (18.4%) developed SO before and after NAC, respectively. Both pre- (34.6%) and post- (47.4%) NAC SO were associated with the highest postoperative morbidity rates; however, only post-NAC SO was an independent risk factor for postoperative morbidity [hazard ratio (HR) = 9.550, 95% confidence interval (CI) = 2.818-32.369; P < .001]. Pre-NAC SO was independently associated with poorer 3-year overall [46.2% vs. 61.3%; HR = 1.258 (95% CI = 1.023-1.547); P = .049] and recurrence-free [39.3% vs. 55.4%; HR 1.285 (95% CI 1.045-1.579); P = .017] survival.
CONCLUSIONS: Pre-NAC SO was an independent prognostic factor in patients with LAGC undergoing NAC; post-NAC SO independently predicted postoperative morbidity.

OBJECTIVE: To evaluate the image quality of ultra-high-resolution CT (U-HRCT) images reconstructed using an improved deep-learning-reconstruction (DLR) method. Additionally, we assessed the utility of U-HRCT in visualizing gastric wall structure, detecting gastric cancer, and determining the depth of invasion.
METHODS: Forty-six patients with resected gastric cancer who underwent preoperative contrast-enhanced U-HRCT were included. The image quality of U-HRCT reconstructed using three different methods (standard DLR [AiCE], improved DLR-AiCE-Body Sharp [improved AiCE-BS], and hybrid-IR [AIDR3D]) was compared. Visualization of the gastric wall\'s three-layered structure in four regions and the visibility of gastric cancers were compared between U-HRCT and conventional HRCT (C-HRCT). The diagnostic ability of U-HRCT with the improved AiCE-BS for determining the depth of invasion of gastric cancers was assessed using postoperative pathology specimens.
RESULTS: The mean noise level of U-HRCT with the improved AiCE-BS was significantly lower than that of the other two methods (p < 0.001). The overall image quality scores of the improved AiCE-BS images were significantly higher (p < 0.001). U-HRCT demonstrated significantly better conspicuity scores for the three-layered structure of the gastric wall than C-HRCT in all regions (p < 0.001). In addition, U-HRCT was found to have superior visibility of gastric cancer in comparison to C-HRCT (p < 0.001). The correct diagnostic rates for determining the depth of invasion of gastric cancer using C-HRCT and U-HRCT were 80%.
CONCLUSIONS: U-HRCT reconstructed with the improved AiCE-BS provides clearer visualization of the three-layered gastric wall structure than other reconstruction methods. It is also valuable for detecting gastric cancer and assessing the depth of invasion.

Postoperative complications of radical gastrectomy seriously affect postoperative recovery and require accurate risk prediction. Therefore, this study aimed to develop a prediction model specifically tailored to guide perioperative clinical decision-making for postoperative complications in patients with gastric cancer. A retrospective analysis was conducted on patients who underwent radical gastrectomy at the First Affiliated Hospital of Nanjing Medical University between April 2022 and June 2023. A total of 166 patients were enrolled. Patient demographic characteristics, laboratory examination results, and surgical pathological features were recorded. Preoperative abdominal CT scans were used to segment the visceral fat region of the patients through 3Dslicer, a 3D Convolutional Neural Network (3D-CNN) to extract image features and the LASSO regression model was employed for feature selection. Moreover, an ensemble learning strategy was adopted to train the features and predict postoperative complications of gastric cancer. The prediction performance of the LGBM (Light Gradient Boosting Machine), XGB (XGBoost), RF (Random Forest), and GBDT (Gradient Boosting Decision Tree) models was evaluated through fivefold cross-validation. This study successfully constructed a model for predicting early complications following radical gastrectomy based on the optimal algorithm, LGBM. The LGBM model yielded an AUC value of 0.9232 and an accuracy of 87.28% (95% CI, 75.61-98.95%), surpassing the performance of other models. Through ensemble learning and integration of perioperative clinical data and visceral fat radiomics, a predictive LGBM model was established. This model has the potential to facilitate individualized clinical decision-making and the early recovery of patients with gastric cancer post-surgery.

Gastric cancer (GC) is a major cause of cancer-related mortality worldwide. This cancer is determined by multiple (epi)genetic and environmental factors; can occur at distinct anatomic positions of the stomach; and displays high heterogeneity, with different cellular origins and diverse histological and molecular features. This heterogeneity has hindered efforts to fully understand the pathology of GC and develop efficient therapeutics. In the past decade, great progress has been made in the study of GC, particularly in molecular subtyping, investigation of the immune microenvironment, and defining the evolutionary path and dynamics. Preclinical mouse models, particularly immunocompetent models that mimic the cellular and molecular features of human GC, in combination with organoid culture and clinical studies, have provided powerful tools for elucidating the molecular and cellular mechanisms underlying GC pathology and immune evasion, and the development of novel therapeutic strategies. Herein, we first briefly introduce current progress and challenges in GC study and subsequently summarize immunocompetent GC mouse models, emphasizing the potential application of genetically engineered mouse models in antitumor immunity and immunotherapy studies.

The gastric microbial community plays a fundamental role in gastric cancer (GC), and the two main anatomical subtypes of GC, non-cardia and cardia GC, are associated with different risk factors (Helicobacter pylori for non-cardia GC). To decipher the different microbial spatial communities of GC, we performed a multicenter retrospective analysis to characterize the gastric microbiota in 223 GC patients, including H. pylori-positive or -negative patients, with tumors and paired adjacent normal tissues, using third-generation sequencing. In the independent validation cohort, both dental plaque and GC tumoral tissue samples were collected and sequenced. The prevalence of H. pylori and oral-associated bacteria was verified using fluorescence in situ hybridization (FISH) assays in GC tumoral tissues and matched nontumoral tissues. We found that the vertical distribution of the gastric microbiota, at the upper, middle, and lower third sites of GC, was likely an important factor causing microbial diversity in GC tumor tissues. The oral-associated microbiota cluster, which included Veillonella parvula, Streptococcus oralis, and Prevotella intermedia, was more abundant in the upper third of the GC. However, H. pylori was more abundant in the lower third of the GC and exhibited a significantly high degree of microbial correlation. The oral-associated microbiota module was co-exclusive with H. pylori in the lower third site of the GC tumoral tissue. Importantly, H. pylori-negative GC patients with oral-associated gastric microbiota showed worse overall survival, while the increase in microbial abundance in H. pylori-positive GC patients showed no difference in overall survival. The prevalence of V. parvula in both the dental plaque and GC tissue samples was concordant in the independent validation phase. We showed that the oral-associated species V. parvula and S. oralis were correlated with overall survival. Our study highlights the roles of the oral-associated microbiota in the upper third of the GC. In addition, oral-associated species may serve as noninvasive screening tools for the management of GC and an independent prognostic factor for H. pylori-negative GCs.
OBJECTIVE: Our study highlights the roles of the oral-associated microbiota in the upper third of gastric cancer (GC).We showed that the oral-associated species Veillonella parvula and Streptococcus oralis were correlated with overall survival. In addition, oral-associated species may serve as noninvasive screening tools for the management of GC and an independent prognostic factor for Helicobacter pylori-negative GCs.

BACKGROUND: Gastric cancer (GC) is a leading cause of cancer-associated death worldwide. Its molecular mechanisms, especially concerning autophagy and various signaling pathways, are not fully understood. Fatty Acid Binding Protein 6 (FABP6) and RE1 Silencing Transcription Factor (REST) emerge as potential key players in this context. This study sought to analyze the functional relationship of FABP6 and REST concerning autophagy and their implications on the Akt/mTOR signaling pathway within GC cells.
METHODS: A comprehensive bioinformatics approach was used to identify key prognostic markers in GC. The effects of FABP6 and REST on autophagy along with Akt/mTOR signaling pathways were analyzed by techniques including Western blotting (WB), flow cytometry, Transwell assay, dual luciferase reporter assay, and others.
RESULTS: FABP6 was identified as overexpressed in GC, linked with poor prognosis. FABP6 silencing reduces GC cell proliferation, induces S- and G2-phase arrest, and downregulates cyclins CDK2 and CDK4. It also inhibited GC cell invasion/migration and autophagy, effects that were counteracted by MG132. When combined with PI3K inhibitor LY294002c, FABP6 knockdown showed synergistic anti-proliferative effects, modulating the Akt/mTOR pathway. Besides, the transcription factor REST has been shown to directly regulate FABP6 expression, affecting autophagy and the Akt/mTOR signaling pathway in a FABP6-dependent manner.
CONCLUSIONS: REST positively regulates autophagy and negatively affects the Akt/mTOR signaling pathway in GC cells in a FABP6-dependent manner, providing valuable insights into regulatory networks involving FABP6 and REST.

The present study aimed to identify preoperative and perioperative risk factors for postoperative infectious complications in older patients with gastric cancer. The present retrospective study included 504 patients with gastric cancer aged >65 years who underwent radical gastrectomy. After determining the cutoff values for various perioperative factors in the receiver operating characteristic curve analysis, preoperative and perioperative risk factors for the development of infectious complications after gastrectomy were examined using logistic regression analysis. Of the 504 patients who underwent gastrectomy, 95 (18.8%) developed infectious complications of grade II-V based on the Clavien-Dindo classification. In an analysis restricted to preoperative factors, male sex, low prognostic nutritional index, high visceral fat area and total gastrectomy were independent risk factors for infectious complications after gastrectomy. Among all perioperative factors, a low prognostic nutritional index and long operative duration were identified as independent risk factors for infectious complications after gastrectomy. The patients were divided into five groups according to the number of positive preoperative risk factors for infectious complications, and the incidence of infectious complications differed among the five groups (0 factors, 6.7%; 1 factor, 10.4%; 2 factors, 18.9%; 3 factors, 27.8%; and 4 factors, 47.6%; P<0.001). Older patients with gastric cancer who have a number of preoperative risk factors require careful consideration of the indication for gastrectomy and a shorter operative time to reduce infectious complications.

BACKGROUND: This study aimed to develop a novel six-gene expression biomarker panel to enhance the early detection and risk stratification of peritoneal recurrence and micrometastasis in locally advanced gastric cancer (LAGC).
METHODS: We used genome-wide transcriptome profiling and rigorous bioinformatics to identify a six-gene expression biomarker panel. This panel was validated across multiple clinical cohorts using both tissue and liquid biopsy samples to predict peritoneal recurrence and micrometastasis in patients with LAGC.
RESULTS: Through genome-wide expression profiling, we identified six mRNAs and developed a risk prediction model using 196 samples from a surgical specimen training cohort. This model, incorporating a 6-mRNA panel with clinical features, demonstrated high predictive accuracy for peritoneal recurrence in gastric cancer patients, with an AUC of 0.966 (95% CI: 0.944-0.988). Transitioning from invasive surgical or endoscopic biopsy to noninvasive liquid biopsy, the model retained its predictive efficacy (AUC = 0.963; 95% CI: 0.926-1.000). Additionally, the 6-mRNA panel effectively differentiated patients with or without peritoneal metastasis in 95 peripheral blood specimens (AUC = 0.970; 95% CI: 0.936-1.000) and identified peritoneal micrometastases with a high efficiency (AUC = 0.941; 95% CI: 0.874-1.000).
CONCLUSIONS: Our study provides a novel gene expression biomarker panel that significantly enhances early detection of peritoneal recurrence and micrometastasis in patients with LAGC. The RSA model\'s predictive capability offers a promising tool for tailored treatment strategies, underscoring the importance of integrating molecular biomarkers with clinical parameters in precision oncology.