Identification of genetic variants predictive of early onset pancreatic cancer through a population science analysis of functional genomic datasets
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Jinyun Chen1, Xifeng Wu1,4, Yujing Huang1, Wei Chen1, Randall E. Brand2, Ann M. Killary3,4, Subrata Sen3,4, Marsha L. Frazier1,4
1Department of Epidemiology The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
2Department of Gastroenterology, Hepatology, and Nutrition, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
3Department of Translational Molecular Pathology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
4Program in Human and Molecular Genetics, The University of Texas Graduate School of Biomedical Sciences, Houston, Texas, USA
Subrata Sen, email: [email protected]
Ann M. Killary, email: [email protected]
Keywords: SNP, genetic variant, age at diagnosis, pathway, pancreatic cancer
Received: September 14, 2015 Accepted: January 01, 2016 Published: July 29, 2016
Biomarkers are critically needed for the early detection of pancreatic cancer (PC) are urgently needed. Our purpose was to identify a panel of genetic variants that, combined, can predict increased risk for early-onset PC and thereby identify individuals who should begin screening at an early age. Previously, we identified genes using a functional genomic approach that were aberrantly expressed in early pathways to PC tumorigenesis. We now report the discovery of single nucleotide polymorphisms (SNPs) in these genes associated with early age at diagnosis of PC using a two-phase study design. In silico and bioinformatics tools were used to examine functional relevance of the identified SNPs. Eight SNPs were consistently associated with age at diagnosis in the discovery phase, validation phase and pooled analysis. Further analysis of the joint effects of these 8 SNPs showed that, compared to participants carrying none of these unfavorable genotypes (median age at PC diagnosis 70 years), those carrying 1–2, 3–4, or 5 or more unfavorable genotypes had median ages at diagnosis of 64, 63, and 62 years, respectively (P = 3.0E–04). A gene-dosage effect was observed, with age at diagnosis inversely related to number of unfavorable genotypes (Ptrend = 1.0E–04). Using bioinformatics tools, we found that all of the 8 SNPs were predicted to play functional roles in the disruption of transcription factor and/or enhancer binding sites and most of them were expression quantitative trait loci (eQTL) of the target genes. The panel of genetic markers identified may serve as susceptibility markers for earlier PC diagnosis.
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