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.

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.

Following the publication of this paper, it was drawn to the Editor\'s attention by a concerned reader that certain of the data shown in Figs. 2A and 4F were strikingly similar to data appearing in different form in other articles written by different authors at different research institutes that were submitted to their respective journals at around the same time; moreover, the same data had apparently been included in the western blots featured in Fig. 5A to show the Parkin and mito‑LCIII protein bands. As it was not clear what had been the original venue for the submission of the strikingly similar data here, the Editor requested that the authors send to us all the raw data underlying the affected figures; however, the authors were not able to comply with this request at the time of asking. Given that the authors were unable to provide the supporting data as requested, the Editor of International Journal of Oncology has decided that this paper should be retracted from the Journal on account of a lack of confidence in the presented data. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a satisfactory reply. The Editor apologizes to the readership for any inconvenience caused. [International Journal of Oncology 52: 367‑378, 2018; DOI: 10.3892/ijo.2017.4216].

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.

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.

OBJECTIVE: Ubiquitin-specific peptidase 10 (USP10), a typical de-ubiquitinase, has been found to play a double-edged role in human cancers. Previously, we reported that the expression of USP10 was negatively correlated with the depth of gastric wall invasion, lymph node metastasis, and prognosis in gastric cancer (GC) patients. However, it remains unclear whether USP10 can regulate the metastasis of GC cells through its de-ubiquitination function.
METHODS: In this study, proteome, ubiquitinome, and transcriptome analyses were conducted to comprehensively identify novel de-ubiquitination targets for USP10 in GC cells. Subsequently, a series of validation experiments, including in vitro cell culture studies, in vivo metastatic tumor models, and clinical sample analyses, were performed to elucidate the regulatory mechanism of USP10 and its de-ubiquitination targets in GC metastasis.
RESULTS: After overexpression of USP10 in GC cells, 146 proteins, 489 ubiquitin sites, and 61 mRNAs exhibited differential expression. By integrating the results of multi-omics, we ultimately screened 9 potential substrates of USP10, including TNFRSF10B, SLC2A3, CD44, CSTF2, RPS27, TPD52, GPS1, RNF185, and MED16. Among them, TNFRSF10B was further verified as a direct de-ubiquitination target for USP10 by Co-IP and protein stabilization assays. The dysregulation of USP10 or TNFRSF10B affected the migration and invasion of GC cells in vitro and in vivo models. Molecular mechanism studies showed that USP10 inhibited the epithelial-mesenchymal transition (EMT) process by increasing the stability of TNFRSF10B protein, thereby regulating the migration and invasion of GC cells. Finally, the retrospective clinical sample studies demonstrated that the downregulation of TNFRSF10B expression was associated with poor survival among 4 of 7 GC cohorts, and the expression of TNFRSF10B protein was significantly negatively correlated with the incidence of distant metastasis, diffuse type, and poorly cohesive carcinoma.
CONCLUSIONS: Our study established a high-throughput strategy for screening de-ubiquitination targets for USP10 and further confirmed that inhibiting the ubiquitination of TNFRSF10B might be a promising therapeutic strategy for GC metastasis.