A potential role of calpains in sulfonylureas (SUs) -mediated death of human pancreatic cancer cells (1.2B4)

Hypoglycemic agents and incidence of pancreatic cancer in diabetic patients: a meta-analysis

Background and aims: Hypoglycemic agents are the primary therapeutic approach for the treatment of diabetes and have been postulated to impact pancreatic cancer (PC) incidence in diabetic patients. We conducted a meta-analysis to further evaluate and establish the associations between four common types of hypoglycemic agents [metformin, sulfonylureas, thiazolidinediones (TZDs), and insulin] and PC incidence in individuals with diabetes mellitus (DM). Methods: A comprehensive literature search of PubMed, Web of Science, Embase, and the Cochrane Library identified studies that analyzed the relationship between hypoglycemic agents and PC published between January 2012 and September 2022. Randomized control trials (RCTs), cohorts, and case-control studies were included if there was clear and evaluated defined exposure to the involved hypoglycemic agents and reported PC outcomes in patients with DM. Furthermore, reported relative risks or odds ratios (ORs) or other provided data were required for the calculation of odds ratios. Summary odds ratio estimates with a 95% confidence interval (CI) were estimated using the random-effects model. Additionally, subgroup analysis was performed to figure out the source of heterogeneity. Sensitivity analysis and publication bias detection were also performed. Results: A total of 11 studies were identified that evaluated one or more of the hypoglycemic agents, including three case-control studies and eight cohort studies. Among these, nine focused on metformin, six on sulfonylureas, seven on TZDs, and seven on insulin. Meta-analysis of the 11 observational studies reported no significant association between metformin (OR = 1.04, 95% CI 0.73-1.46) or TZDs (OR = 1.13, 95% CI 0.73-1.75) and PC incidence, while the risk of PC increased by 79% and 185% with sulfonylureas (OR = 1.79, 95% CI 1.29-2.49) and insulin (OR = 2.85, 95% CI 1.75-4.64), respectively. Considerable heterogeneity was observed among the studies and could not be fully accounted for by study design, region, or adjustment for other hypoglycemic agents. Conclusion: Sulfonylureas and insulin may increase the incidence of pancreatic cancer in diabetic patients, with varying effects observed among different ethnicities (Asian and Western). Due to significant heterogeneity across studies, further interpretation of the relationship between hypoglycemic agents and pancreatic cancer incidence in diabetic patients requires well-adjusted data and better-organized clinical trials.

Pancreas and Adverse Drug Reactions: A Literature Review

Adverse drug reactions (ADRs) affecting the pancreas are a heterogeneous group of side effects that cause damage to pancreatic cells. Various mechanisms such as hypersensitization, sphincter of Oddi constriction, direct cytotoxic and metabolic effects on pancreatic cells, and dose-dependent idiosyncrasy lead to intrapancreatic activation of pancreatic enzymes resulting in drug-induced acute pancreatitis. Several medications have been linked with the development of pancreatic cancer. Pancreatic cancer may result from proinflammatory, proliferative, and antiapoptotic effects. Diabetogenic effect of drugs, which is understood as impairment of insulin secretion, may occur due to direct destruction of β cells, systemic toxicity affecting pancreatic islets and cell membrane glucose transporters, induction of Th1-type autoimmune response, and impairment of voltage-gated calcium channels in β cells, endoplasmic reticulum stress, and insulin signaling. A better understanding of ADRs that affect the pancreas may contribute to improving the awareness of clinicians and patients and reducing potential harmful side effects of implemented therapies.

Identification and Validation of Prognostic Model for Pancreatic Ductal Adenocarcinoma Based on Necroptosis-Related Genes

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors with a poor prognosis. Recently, necroptosis has been reported to participate in the progression of multiple tumors. However, few studies have revealed the relationship between necroptosis and PDAC, and the role of necroptosis in PDAC has not yet been clarified.

Methods: The mRNA expression data and corresponding clinical information of PDAC patients were downloaded from the TCGA and GEO databases. The necroptosis-related genes (NRGs) were obtained from the CUSABIO website. Consensus clustering was performed to divide PDAC patients into two clusters. Univariate and LASSO Cox regression analyses were applied to screen the NRGs related to prognosis to construct the prognostic model. The predictive value of the prognostic model was evaluated by Kaplan-Meier survival analysis and ROC curve. Univariate and multivariate Cox regression analyses were used to evaluate whether the risk score could be used as an independent predictor of PDAC prognosis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and single-sample gene set enrichment analysis (ssGSEA) were used for functional enrichment analysis. Finally, using qRT-PCR examined NRGs mRNA expression in vitro.

Results: Based on the TCGA database, a total of 22 differential expressed NRGs were identified, among which eight NRGs (CAPN2, CHMP4C, PLA2G4F, PYGB, BCL2, JAK3, PLA2G4C and STAT4) that may be related to prognosis were screened by univariate Cox regression analysis. And CAPN2, CHMP4C, PLA2G4C and STAT4 were further selected to construct the prognostic model. Kaplan-Meier survival analysis and ROC curve showed that there was a significant correlation between the risk model and prognosis. Univariate and multivariate Cox regression analyses showed that the risk score of the prognostic model could be used as an independent predictor. The model efficacy was further demonstrated in the GEO cohort. Functional analysis revealed that there were significant differences in immune status between high and low-risk groups. Finally, the qRT-PCR results revealed a similar dysregulation of NRGs in PDAC cell lines.

Conclusion: This study successfully constructed and verified a prognostic model based on NRGs, which has a good predictive value for the prognosis of PDAC patients.