Combined Alcohol Exposure and KRAS Mutation in Human Pancreatic Ductal Epithelial Cells Induces Proliferation and Alters Subtype Signatures Determined by Multi-Omics Analysis

Screening and identification of potential biomarkers for pancreatic cancer: An integrated bioinformatics analysis

Pancreatic cancer is one of the highly invasive and the seventh most common cause of death among cancers worldwide. To identify essential genes and the involved mechanisms in pancreatic cancer, we used bioinformatics analysis to identify potential biomarkers for pancreatic cancer management. Gene expression profiles of pancreatic cancer patients and normal tissues were screened and downloaded from The Cancer Genome Atlas (TCGA) bioinformatics database. The Differentially expressed genes (DEGs) were identified among gene expression signatures of normal and pancreatic cancer, using R software. Then, enrichment analysis of the DEGs, including Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, was performed by an interactive and collaborative HTML5 gene list enrichment analysis tool (enrichr) and ToppGene. The protein-protein interaction (PPI) network was also constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and ToppGenet web based tool followed by identifying hub genes of the top 100 DEGs in pancreatic cancer using Cytoscape software. Over 2000 DEGs with variable log2 fold (LFC) were identified among 34,706 genes. Principal component analysis showed that the top 20 DEGs, including H1-4, H1-5, H4C3, H4C2, RN7SL2, RN7SL3, RN7SL4P, RN7SKP80, SCARNA12, SCARNA10, SCARNA5, SCARNA7, SCARNA6, SCARNA21, SCARNA9, SCARNA13, SNORA73B, SNORA53, SNORA54 might distinguish pancreatic cancer from normal tissue. GO analysis showed that the top DEGs have more enriched in the negative regulation of gene silencing, negative regulation of chromatin organization, negative regulation of chromatin silencing, nucleosome positioning, regulation of chromatin silencing, and nucleosomal DNA binding. KEGG analysis identified an association between pancreatic cancer and systemic lupus erythematosus, alcoholism, neutrophil extracellular trap formation, and viral carcinogenesis. In PPI network analysis, we found that the different types of histone-encoding genes are involved as hub genes in the carcinogenesis of pancreatic cancer. In conclusion, our bioinformatics analysis identified genes that were significantly related to the prognosis of pancreatic cancer patients. These genes and pathways could serve as new potential prognostic markers and be used to develop treatments for pancreatic cancer patients.

Malondialdehyde-Acetaldehyde Extracellular Matrix Protein Adducts Attenuate Unfolded Protein Response During Alcohol and Smoking-Induced Pancreatitis

BACKGROUND & AIMS

Epidemiological studies have established alcohol and smoking as independent risk factors for recurrent acute pancreatitis and chronic pancreatitis. However, the molecular players responsible for the progressive loss of pancreatic parenchyma and fibroinflammatory response are poorly characterized.

METHODS

Tandem mass tag-based proteomic and bioinformatics analyses were performed on the pancreata of mice exposed to alcohol, cigarette smoke, or a combination of alcohol and cigarette smoke. Biochemical, immunohistochemistry, and transcriptome analyses were performed on the pancreatic tissues and primary acinar cells treated with cerulein in combination with ethanol (50 mmol/L) and cigarette smoke extract (40 μg/mL) for the mechanistic studies.

RESULTS

A unique alteration in the pancreatic proteome was observed in mice exposed chronically to the combination of alcohol and cigarette smoke (56.5%) compared with cigarette smoke (21%) or alcohol (17%) alone. The formation of toxic metabolites (P < .001) and attenuated unfolded protein response (P < .04) were the significantly altered pathways on combined exposure. The extracellular matrix (ECM) proteins showed stable malondialdehyde-acetaldehyde (MAA) adducts in the pancreata of the combination group and chronic pancreatitis patients with a history of smoking and alcohol consumption. Interestingly, MAA-ECM adducts significantly suppressed expression of X-box-binding protein-1, leading to acinar cell death in the presence of alcohol and smoking. The stable MAA-ECM adducts persist even after alcohol and smoking cessation, and significantly delay pancreatic regeneration by abrogating the expression of cyclin-dependent kinases (CDK7 and CDK5) and regeneration markers.

CONCLUSIONS

The combined alcohol and smoking generate stable MAA-ECM adducts that increase endoplasmic reticulum stress and acinar cell death due to attenuated unfolded protein response and suppress expression of cell cycle regulators. Targeting aldehyde adducts might provide a novel therapeutic strategy for the management of recurrent acute pancreatitis and chronic pancreatitis.