Association of Genetic Variants Affecting microRNAs and Pancreatic Cancer Risk

Abstract

Genetic factors play an important role in the susceptibility to pancreatic cancer (PC). However, established loci explain a small proportion of genetic heritability for PC; therefore, more progress is needed to find the missing ones. We aimed at identifying single nucleotide polymorphisms (SNPs) affecting PC risk through effects on micro-RNA (miRNA) function. We searched in silico the genome for SNPs in miRNA seed sequences or 3 prime untranslated regions (3'UTRs) of miRNA target genes. Genome-wide association data of PC cases and controls from the Pancreatic Cancer Cohort (PanScan) Consortium and the Pancreatic Cancer Case–Control (PanC4) Consortium were re-analyzed for discovery, and genotyping data from two additional consortia (PanGenEU and PANDoRA) were used for replication, for a total of 14,062 cases and 11,261 controls. None of the SNPs reached genome-wide significance in the meta-analysis, but for three of them the associations were in the same direction in all the study populations and showed lower value of p in the meta-analyses than in the discovery phase. Specifically, rs7985480 was consistently associated with PC risk (OR = 1.12, 95% CI 1.07–1.17, p = 3.03 × 10−6 in the meta-analysis). This SNP is in linkage disequilibrium (LD) with rs2274048, which modulates binding of various miRNAs to the 3'UTR of UCHL3, a gene involved in PC progression. In conclusion, our results expand the knowledge of the genetic PC risk through miRNA-related SNPs and show the usefulness of functional prioritization to identify genetic polymorphisms associated with PC risk.

Clustering analysis revealed the autophagy classification and potential autophagy regulators' sensitivity of pancreatic cancer based on multi‐omics data

“…However, although some large PDAC consortiums such as PanScan, PanC4, and PANDoRA have been finished to detect possible loci, only small number of loci reaching the genome‐wide significance. Ye Lu, et al 58 , 59 have tried to explore more potential loci and miRNA‐related loci by secondary analysis under a recessive model, but many of the meta‐analysis results did not reach the genome‐wide statistical significance. The false negative outcomes may come from the high significance threshold in meta‐analysis, indicating the necessity of the development of new integrating method rather than simply pooled analysis.…”

Genetic Susceptibility in Understanding of Pancreatic Ductal Adenocarcinoma Risk: A Decade-Long Effort of the PANDORA Consortium

“…Out of SNPs in 3 prime untranslated regions (3′UTRs) of miRNA target genes, only rs7985480 was consistently associated with PDAC risk ( Table 1 ). These results, alongside studies considering expression quantitative traits (eQTL) and those on SNPs in long noncoding RNA, proved the usefulness of functional prioritization to identify PDAC risk-associated genetic polymorphisms ( 28–30 ).…”

Circulating Cell-Free Nucleic Acids as Biomarkers for Diagnosis and Prognosis of Pancreatic Cancer

“…A re-analysis of data from two consortia (PanGenEU and PANDoRA) with 14,062 PCa and 11,261 healthy controls found no SNPs reaching genome-wide significance; however, three SNPs showed the same direction and a lower p -value in the meta-analyses than in the discovery phase. Specifically, rs7985480 was associated with PCa risk (OR = 1.12) in linkage disequilibrium with rs2274048 , acting by modulating binding of miRNAs to the 3’UTR of UCHL3 , a gene involved in PCa progression, suggesting that miRNA-related SNPs are promising and useful targets for PCa risk association [ 78 ].…”