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Updated: Jan 15, 2026
Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing ChIP-seq
Published on: April 19, 2013
Bioinformatics analysis to investigate the genetic associations between diabetes and pancreatic cancer
Jian-Bin Wei1,2, Xiao-Min Chen1,3
1The Third Clinical Medical College, Fujian Medical University, Fuzhou, China.
Aims:
Epidemiological studies indicate a heightened risk of pancreatic adenocarcinoma (PAAD) in patients with type 2 diabetes mellitus (T2DM). This study investigates the molecular mechanisms underlying their comorbidity.
Materials And Methods:
Common DEGs between T2DM and PAAD were identified from GEO datasets. Functional and pathway enrichment analyses were performed via PPI, GO, and KEGG. Core genes were screened and their diagnostic value was validated by ROC curves. Immune infiltration and TF-mRNA-miRNA regulatory networks were constructed to explore disease mechanisms. Core gene expression and prognostic significance in PAAD were assessed using GEPIA2 and HPA. Potential therapeutics targeting core genes were predicted via the Therapeutic Target Database.
Results:
A total of 35 DEGs were identified. GO analysis linked these genes to cell adhesion and extracellular matrix (ECM) components. KEGG enrichment highlighted ECM-receptor interaction as the top pathway. Key ECM-related molecules-ITGA3, FN1, LAMB3, ITGA2, and LAMC2-were upregulated in both T2DM and PAAD. Six potential therapeutic agents targeting ITGA2, LAMB3, and FN1 were identified.
Conclusion:
Three genes and associated known drugs identified in this study may serve as potential targets for treating the coexistence of the two diseases.
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