Systematic review and meta-analysis of short-term outcomes: robot-assisted versus laparoscopic surgery for gastric cancer patients with visceral obesity.

The objective of this meta-analysis was to assess the comparative efficacy of robot-assisted and laparoscopic surgery in treating gastric cancer among patients characterized by a high visceral fat area (VFA). In April 2024, we conducted a comprehensive literature review using major international databases, such as PubMed, Embase, and Google Scholar. We restricted our selection to articles written in English, excluding reviews, protocols without published data, conference abstracts, and irrelevant content. Our analysis focused on continuous data using 95% confidence intervals (CIs) and standard mean differences (SMDs), while dichotomous data were assessed with odds ratios (ORs) and 95% CIs. We set the threshold for statistical significance at P < 0.05. Data extraction included baseline characteristics, primary outcomes (such as operative time, major complications, lymph node yield, and anastomotic leakage), and secondary outcomes. The meta-analysis included three cohort studies totaling 970 patients. The robotic-assisted group demonstrated a significantly longer operative time compared to the laparoscopic group, with a weighted mean difference (WMD) of - 55.76 min (95% CI - 74.03 to - 37.50; P < 0.00001). This group also showed a reduction in major complications, with an odds ratio (OR) of 2.48 (95% CI 1.09-5.66; P = 0.03) and fewer occurrences of abdominal infections (OR 3.17, 95% CI 1.41-7.14; P = 0.005), abdominal abscesses (OR 3.83, 95% CI 1.53-9.57; P = 0.004), anastomotic leaks (OR 4.09, 95% CI 1.73-9.65; P = 0.001), and pancreatic leaks (OR 8.93, 95% CI 2.33-34.13; P = 0.001). However, no significant differences were observed between the groups regarding length of hospital stay, overall complications, estimated blood loss, or lymph node yield. Based on our findings, robot-assisted gastric cancer surgery in obese patients with visceral fat appears to be correlated with fewer major complications compared to laparoscopic surgery, while maintaining similar outcomes in other surgical aspects. However, it is important to note that robot-assisted procedures do tend to have longer operative times.

[Downregulation of SETDB1 suppresses epithelial mesenchymal transition and invasion and metastasis in oral cancer via SOX7 methylation].

PURPOSE: To explore the mechanism of SETDB1 inhibiting epithelial mesenchymal transition (EMT),migration and invasion in oral cancer via SOX 7 methylation. METHODS: SETDB1 and SOX7 mRNA and protein expression levels in KB cells of oral cancer and oral mucosal epithelial ATCC cells were determined by qRT-PCR and Western blot (WB). SETDB1 si-RNA was structured, then transfect into KB cells of oral cancer by liposome-mediated method. siRNA-SETDB1 was the experimental group (si-S), siRNA empty vector was the negative control group (si-N), and untransfected KB cells were the blank control group(NC). SETDB1 mRNA and protein expression levels were detected by qRT-PCR and Western blot(WB), to verify the transfection effect. The methylation levels of SOX7 were determined by pyrosequencing. The expression of N-cadherin, Vimentin, ß-catenin, and Slug proteins was detected by WB. Cell viability was measured by MTT assay, migration ability was tested by scratch healing assay, and invasion ability was tested by Transwell chamber assay. Statistical analysis was performed with SPSS 21.0 software package. RESULTS: The results of Rt-qPCR and WB showed that the SETDB1 mRNA and protein expression decreased significantly in si-S group(P＜0.05). Pyrosequencing test results showed that the regulation of SETDB1 could significantly reduce the SOX7 methylation rate and increased the SOX7 protein expression. WB results showed that knockdown of SETDB1 significantly inhibited the expression of EMT-related proteins N-cadherin, Vimentin, ß-catenin and Slug in oral cancer KB cells (P＜0.05). The results of cell functology experiments showed that knockdown of SETDB1 could significantly inhibit survival, migration and invasion of KB cells. CONCLUSIONS: Downregulation of SETDB1 could suppress EMT, migration and invasion of oral cancer cells by regulating SOX7 methylation level, providing new ideas and targets for the diagnosis and treatment of oral cancer.

Identification of survival-associated biomarkers based on three datasets by bioinformatics analysis in gastric cancer.

BACKGROUND: Gastric cancer (GC) is one of the most common malignant tumors with poor prognosis in terms of advanced stage. However, the survival-associated biomarkers for GC remains unclear. AIM: To investigate the potential biomarkers of the prognosis of patients with GC, so as to provide new methods and strategies for the treatment of GC. METHODS: RNA sequencing data from The Cancer Genome Atlas (TCGA) database of STAD tumors, and microarray data from Gene Expression Omnibus (GEO) database (GSE19826, GSE79973 and GSE29998) were obtained. The differentially expressed genes (DEGs) between GC patients and health people were picked out using R software (x64 4.1.3). The intersections were underwent between the above obtained co-expression of differential genes (co-DEGs) and the DEGs of GC from Gene Expression Profiling Interactive Analysis database, and Gene Ontology (GO) analysis, Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis, Gene Set Enrichment Analysis (GSEA), Protein-protein Interaction (PPI) analysis and Kaplan-Meier Plotter survival analysis were performed on these DEGs. Using Immunohistochemistry (IHC) database of Human Protein Atlas (HPA), we verified the candidate Hub genes. RESULTS: With DEGs analysis, there were 334 co-DEGs, including 133 up-regulated genes and 201 down-regulated genes. GO enrichment analysis showed that the co-DEGs were involved in biological process, cell composition and molecular function pathways. KEGG enrichment analysis suggested the co-DEGs pathways were mainly enriched in ECM-receptor interaction, protein digestion and absorption pathways, etc. GSEA pathway analysis showed that co-DEGs mainly concentrated in cell cycle progression, mitotic cell cycle and cell cycle pathways, etc. PPI analysis showed 84 nodes and 654 edges for the co-DEGs. The survival analysis illustrated 11 Hub genes with notable significance for prognosis of patients were screened. Furtherly, using IHC database of HPA, we confirmed the above candidate Hub genes, and 10 Hub genes that associated with prognosis of GC were identified, namely BGN, CEP55, COL1A2, COL4A1, FZD2, MAOA, PDGFRB, SPARC, TIMP1 and VCAN. CONCLUSION: The 10 Hub genes may be the potential biomarkers for predicting the prognosis of GC, which can provide new strategies and methods for the diagnosis and treatment of GC.

Case report: Laparoscopic treatment of gastro-omental hemangioma with hemorrhage: two cases reports and review of literature.

Background: Spontaneous hemorrhage of gastro-omental hemangioma is a rare disease. The treatment strategy for this disease changes as it develops. In the acute stage, surgery is the first priority, among which laparoscopic treatment should be the most frequently considered option in large general hospitals. Due to the rarity of this disease, such cases have rarely been reported. Case description: We present the first report of two eldely cases with gastro-omental hemangioma with hemorrhage by laparoscopic treatment. Both cases were initially admitted with upper abdominal pain, and abdominal computed tomography (CT) scan revealed masses alongside the greater curvature of the stomach. Laparoscopic surgery was conducted immediately in both patients. The two cases recovered well after surgery, and no obvious abnormalities were observed in the follow-up period. Conclusion: Gastro-omental hemangioma rupture remains an uncommon cause of intraperitoneal hemorrhage. Timely diagnosis and surgery are paramount for treatment. Medical institutions with the correct technology and equipment should perform laparoscopic treatment to minimize surgical trauma and promote rapid recovery of patients with abdominal apoplexy.