ArticleMolecular biotechnology2026
Genome Mining for Hub Genes Related to Endoplasmic Reticulum Stress in Pancreatitis: A Perspective from In Silico Characterization.
Article in Molecular biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Article
- Targeting PFKFB3 to restore glucose metabolism in acute pancreatitis via nanovesicle delivery.Molecular medicine (Cambridge, Mass.) · 2025Article
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2 authors.
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Abstract
Pancreatitis, as a common exocrine pancreatic disease, poses a daunting challenge to patients' health and the medical system. Endoplasmic reticulum stress (ERS) plays an essential role in the pathologic process of pancreatitis. However, its mechanism is not fully understood. Therefore, this study was designed to deepen the understanding of the pathogenic mechanism of the disease by screening key ERS-related genes (ERSRGs) associated with pancreatitis. Pancreatitis mRNA data for GSE194331 (Normal: 32, Pancreatitis: 87) and pancreatitis GSE143754 (Normal: 9, Pancreatitis: 6) were downloaded from the GEO database and were used as a training and validation set, respectively. First, the training set GSE194331 was differentially expressed and intersected with the ERSRGs (n = 265) obtained from the MSigDB database to result in 42 differentially expressed ERSRGs (DE-ERSRGs). Subsequently, five candidate genes were further screened by PPI network and MCC and MCODE algorithms. However, according to the ROC curve results, AUC values of CCND1, BCL2, PIK3R1, and BCL2L1 were all greater than 0.6, indicating that they had good diagnostic performance, which was verified by the GSE143754 data set. Based on the GeneMANIA network, it was found that hub genes BCL2 and BCL2L1 may be the key factors in the regulation of mitochondrial metabolism. 24 differentially expressed pancreatitis-related genes (DE-PRGs) were found by difference analysis and Venn analysis. Hub genes BCL2 and PIK3R1 that were significantly correlated with 24 DE-PRGs were determined by Spearman analysis. ssGSEA algorithm was further used to reveal the significant correlation between these hub genes and the immune microenvironment of pancreatitis. The miRNA and lncRNA targeting hub genes were predicted using miRWalk, TargetScan, miRDB, and ENCORI databases, providing research directions for the mechanism of pancreatitis. Finally, the Network Analyst website was used to predict potential compounds associated with the hub gene. In conclusion, this study not only further supports the role of ERS in the development of pancreatitis but also provides a new perspective and direction for the development of biomarkers and mechanism of pancreatitis. At the same time, the results of this study provide a reliable research direction for the targeted treatment of pancreatitis.
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