Appraisal of surgical outcomes and oncological efficiency of intraoperative adverse events in robotic radical gastrectomy for gastric cancer.

BACKGROUND: Surgical quality control is a crucial determinant of evaluating the tumor efficacy. OBJECTIVE: To assess the ClassIntra grade for quality control and oncological outcomes of robotic radical surgery for gastric cancer (GC). METHODS: Data of patients undergoing robotic radical surgery for GC at a high-volume center were retrospectively analyzed. Patients were categorized into two groups, the intraoperative adverse event (iAE) group and the non-iAE group, based on the occurrence of intraoperative adverse events. The iAEs were further classified into five sublevels (ranging from I to V according to severity) based on the ClassIntra grade. Surgical performance was assessed using the Objective Structured Assessment of Technical Skill (OSATS) and the General Error Reporting Tool. RESULTS: This study included 366 patients (iAE group: n = 72 [19.7%] and non-iAE group: n = 294 [80.3%]). The proportion of ClassIntra grade II patients was the highest in the iAE group (54.2%). In total and distal gastrectomies, iAEs occurred most frequently in the suprapancreatic area (50.0% and 54.8%, respectively). In total gastrectomy, grade IV iAEs were most common during lymph node dissection in the splenic hilum area (once for bleeding [grade IV] and once for injury [grade IV]). The overall survival (OS) and disease-free survival of the non-iAE group were significantly better than those of the iAE group (Log rank P < 0.001). Uni- and multi-variate analyses showed that iAEs were key prognostic indicators, independent of tumor stage and adjuvant chemotherapy (P < 0.001). CONCLUSION: iAEs in patients who underwent robotic radical gastrectomy significantly correlated with the occurrence of postoperative complications and a poor long-term prognosis. Therefore, utilization and inclusion of ClassIntra grading as a crucial surgical quality control and prognostic indicator in the routine surgical quality evaluation system are recommended.

Protein and metabolic profiles of tyrosine kinase inhibitors co-resistant liver cancer cells.

Hepatocellular Carcinoma (HCC) patients often develop resistance to tyrosine kinase inhibitors (TKIs) like sorafenib (SR) and lenvatinib (RR). We established HCC cell lines resistant to these drugs and analyzed the correlation between protein and metabolite profiles using bioinformatics. Our analysis revealed overexpression of MISP, CHMP2B, IL-18, TMSB4X, and EFEMP1, and downregulation of IFITM3, CA4, AGR2, and SLC51B in drug-resistant cells. Differential signals are mainly enriched in steroid hormone biosynthesis, cell adhesion, and immune synapses, with metabolic pathways including cytochrome P450 drug metabolism, amino acid metabolism, and glycolysis. Proteomics and metabolomics analysis showed co-enrichment signals in drug metabolism, amino acids, glucose metabolism, ferroptosis, and other biological processes. Knocking down MISP, CHMP2B, IL-18, TMSB4X, and EFEMP1 significantly reduced drug resistance, indicating their potential as therapeutic response biomarkers. This study characterizes protein and metabolic profiles of drug-resistant HCC cells, exploring metabolite-protein relationships to enhance understanding of drug resistance mechanisms and clinical treatment.