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.
Association of Genetic Variants Affecting microRNAs and Pancreatic Cancer Risk / Y. Lu, C. Corradi, M. Gentiluomo, E. Lopez De Maturana, G.E. Theodoropoulos, S. Roth, E. Maiello, L. Morelli, L. Archibugi, J.R. Izbicki, P. Sarlos, V. Kiudelis, M. Oliverius, M.N. Aoki, Y. Vashist, C.H.J. Van Eijck, M. Gazouli, R. Talar-Wojnarowska, A. Mambrini, R. Pezzilli, B. Bueno-de-Mesquita, P. Hegyi, P. Soucek, J.P. Neoptolemos, G. Di Franco, C. Sperti, E.F. Kauffmann, V. Hlavac, F.G. Uzunoglu, S. Ermini, E. Malecka-Panas, M. Lucchesi, G. Vanella, F. Dijk, B. Mohelnikova-Duchonova, F. Bambi, M.C. Petrone, K. Jamroziak, F. Guo, K. Kolarova, G. Capretti, A.C. Milanetto, L. Ginocchi, M. Lovecek, M. Puzzono, H.W.M. Van Laarhoven, S. Carrara, A. Ivanauskas, K. Papiris, D. Basso, P.G. Arcidiacono, F. Izbeki, R. Chammas, P. Vodicka, T. Hackert, C. Pasquali, M.L. Piredda, E. Costello-Goldring, G.M. Cavestro, A. Szentesi, F. Tavano, B. Wlodarczyk, H. Brenner, E. Kreivenaite, X. Gao, S. Bunduc, R.C.H. Vermeulen, M.A. Schneider, A. Latiano, D. Gioffreda, S.G.G. Testoni, J. Kupcinskas, R.T. Lawlor, G. Capurso, N. Malats, D. Campa, F. Canzian. - In: FRONTIERS IN GENETICS. - ISSN 1664-8021. - 12:(2021 Aug), pp. 693933.1-693933.11. [10.3389/fgene.2021.693933]
Association of Genetic Variants Affecting microRNAs and Pancreatic Cancer Risk
S.G.G. Testoni;
2021
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.
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