Genetic Susceptibility to Pancreatic Cancer: A Genome-Wide Association Study

Authors

  • Rida Naz Regional Blood Centre, Dera Ismail Khan 29050, Khyber Pakhtunkhwa, Pakistan Author
  • Muska Hayat Khyber Teaching Hospital – MTI, Peshawar, Peshawar, Pakistan Author

Keywords:

Pancreatic Cancer, Genome-Wide Association Study, SNP, Genetic Susceptibility, PDAC, Eqtl Analysis

Abstract

Pancreatic ductal adenocarcinoma (PDAC), the predominant and most lethal form of pancreatic cancer, continues to pose significant diagnostic and therapeutic challenges due to its aggressive progression, late-stage detection, and resistance to conventional therapies. This genome-wide association study (GWAS) aimed to identify common genetic variants associated with PDAC susceptibility and elucidate potential molecular mechanisms underlying disease pathogenesis. A total of 4,500 individuals (2,250 PDAC cases and 2,250 matched controls) were genotyped using high-density SNP arrays, and rigorous quality control and statistical analyses were applied. Eight SNP clusters across multiple chromosomal regions achieved genome-wide significance (p < 5×10⁻⁸), with the strongest associations observed on chromosomes 3p, 9p21, and 17q, implicating loci near CDKN2A, BRCA1/2, and inflammation-related genes. Replication analysis in an independent cohort of 2,400 individuals confirmed the direction and magnitude of association for several top-ranked SNPs. Looking at the function of these variants, many are found non-coding regions and eQTL studies connect them to changes in the expression of nearby genes in pancreatic tissues. These methods also pointed out that DNA repair, immune signaling and the KRAS pathway are disturbed in the mechanism of epidermal growth factor receptor activity. In aggregate, these results indicate that PDAC risk may be caused by many genes working together and reveal fresh information about its genetics. It supports findings for certain regions suspected in pancreatic cancer and also finds new possible regions which increases our understanding of the disease and forms a base for future use in precision medicine, risk predictions, early detection and targeted treatments.

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Published

2025-06-30