The incidence of pancreatic ductal adenocarcinoma (PDAC) is different among males and females. This disparity cannot be fully explained by the difference in terms of exposure to known risk factors; therefore, the lower incidence in women could be attributed to sex-specific hormones. A two-phase association study was conducted in 12,387 female subjects (5436 PDAC cases and 6951 controls) to assess the effect on risk of developing PDAC of single nucleotide polymorphisms (SNPs) in 208 genes involved in oestrogen and pregnenolone biosynthesis and oestrogen-mediated signalling. In the discovery phase 14 polymorphisms showed a statistically significant association (P < 0.05). In the replication none of the findings were validated. In addition, a gene-based analysis was performed on the 208 selected genes. Four genes (NR5A2, MED1, NCOA2 and RUNX1) were associated with PDAC risk, but only NR5A2 showed an association (P = 4.08 × 10-5) below the Bonferroni-corrected threshold of statistical significance. In conclusion, despite differences in incidence between males and females, our study did not identify an effect of common polymorphisms in the oestrogen and pregnenolone pathways in relation to PDAC susceptibility. However, we validated the previously reported association between NR5A2 gene variants and PDAC risk.

• MeSH
• Adenocarcinoma * pathology   MeSH
• Carcinoma, Pancreatic Ductal * pathology   MeSH
• Estrogens genetics   MeSH
• Humans MeSH
• Pancreatic Neoplasms * epidemiology   genetics   pathology   MeSH
• Pregnenolone MeSH
• Check Tag
• Humans MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Estrogens MeSH
• Pregnenolone MeSH

Pancreatic cancer, a complex disease, emerges as a severe health problem worldwide and it exhibits a poor prognosis and high mortality. Risk factors associated with sporadic pancreatic cancer remain poorly understood, even less is known about disease prognosis due to its rapid progression. The PANcreatic Disease ReseArch (PANDoRA) consortium, of which the authors are members, was established to coordinate the efforts of different research groups to uncover new genetic factors for pancreatic cancer risk, response to treatment, and patient survival. PANDoRA consortium has contributed to the identification of several low-penetrance risk loci for the disease both by candidate variants approach and genome-wide association studies, including those in cell-cycle and DNA damage response, telomere homeostasis, SCL and ABC transporters, ABO locus variability, mitochondrial metabolism and it participated on collaborative genome-wide association study approach and implementation of a search for functional-based pancreatic cancer risk loci and long noncoding RNAs. Complex studies covering genetic, environmental and microenvironmental factors in the pancreatic cancer onset, progression and its prognosis are warranted.

• MeSH
• Genome-Wide Association Study MeSH
• Carcinoma, Pancreatic Ductal * genetics   pathology   MeSH
• Genetic Predisposition to Disease MeSH
• Polymorphism, Single Nucleotide MeSH
• Humans MeSH
• Pancreatic Neoplasms * genetics   pathology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Although 21 pancreatic cancer susceptibility loci have been identified in individuals of European ancestry through genome-wide association studies (GWASs), much of the heritability of pancreatic cancer risk remains unidentified. A recessive genetic model could be a powerful tool for identifying additional risk variants. To discover recessively inherited pancreatic cancer risk loci, we performed a re-analysis of the largest pancreatic cancer GWAS, the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including 8,769 cases and 7,055 controls of European ancestry. Six single nucleotide polymorphisms (SNPs) showed associations with pancreatic cancer risk according to a recessive model of inheritance. We replicated these variants in 3,212 cases and 3,470 controls collected from the PANcreatic Disease ReseArch (PANDoRA) consortium. The results of the meta-analyses confirmed that rs4626538 (7q32.2), rs7008921 (8p23.2) and rs147904962 (17q21.31) showed specific recessive effects (p<10-5) compared with the additive effects (p>10-3), although none of the six SNPs reached the conventional threshold for genome-wide significance (p < 5×10-8). Additional bioinformatic analysis explored the functional annotations of the SNPs and indicated a possible relationship between rs36018702 and expression of the BCL2L11 and BUB1 genes, which are known to be involved in pancreatic biology. Our findings, while not conclusive, indicate the importance of considering non-additive genetic models when performing GWAS analysis. The SNPs associated with pancreatic cancer in this study could be used for further meta-analysis for recessive association of SNPs and pancreatic cancer risk and might be a useful addiction to improve the performance of polygenic risk scores.

• Keywords
• genetic polymorphisms, genome-wide association study, pancreatic cancer, recessive model, susceptibility,
• Publication type
• Journal Article MeSH

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.

• Keywords
• genetic polymorphisms, miRNA, pancreatic cancer, pancreatic ductal adenocarcinoma, susceptibility,
• Publication type
• Journal Article MeSH

Although pancreatic ductal adenocarcinoma (PDAC) survival is poor, there are differences in patients' response to the treatments. Detection of predictive biomarkers explaining these differences is of the utmost importance. In a recent study two genetic markers (CD44-rs353630 and CHI3L2-rs684559) were reported to be associated with survival after PDAC resection. We attempted to replicate the associations in 1856 PDAC patients (685 resected with stage I/II) from the PANcreatic Disease ReseArch (PANDoRA) consortium. We also analysed the combined effect of the two genotypes in order to compare our results with what was previously reported. Additional stratified analyses considering TNM stage of the disease and whether the patients received surgery were also performed. We observed no statistically significant associations, except for the heterozygous carriers of CD44-rs353630, who were associated with worse OS (HR = 5.01; 95% CI 1.58-15.88; p = 0.006) among patients with stage I disease. This association is in the opposite direction of those reported previously, suggesting that data obtained in such small subgroups are hardly replicable and should be considered cautiously. The two polymorphisms combined did not show any statistically significant association. Our results suggest that the effect of CD44-rs353630 and CHI3L2-rs684559 cannot be generalized to all PDAC patients.

• MeSH
• Hyaluronan Receptors genetics   MeSH
• Chitinases genetics   MeSH
• Carcinoma, Pancreatic Ductal genetics   mortality   MeSH
• Polymorphism, Single Nucleotide MeSH
• Kaplan-Meier Estimate MeSH
• Middle Aged MeSH
• Humans MeSH
• Biomarkers, Tumor genetics   MeSH
• Pancreatic Neoplasms genetics   mortality   MeSH
• Aged MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Hyaluronan Receptors MeSH
• CD44 protein, human MeSH Browser
• CHI3L2 protein, human MeSH Browser
• Chitinases MeSH
• Biomarkers, Tumor MeSH

BACKGROUND: Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes. METHODS: We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided. RESULTS: We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P ≤ 1.3 × 10-5), the strongest associations were detected in five pathways and gene sets, including maturity-onset diabetes of the young, regulation of beta-cell development, role of epidermal growth factor (EGF) receptor transactivation by G protein-coupled receptors in cardiac hypertrophy pathways, and the Nikolsky breast cancer chr17q11-q21 amplicon and Pujana ATM Pearson correlation coefficient (PCC) network gene sets. We identified and validated rs876493 and three correlating SNPs (PGAP3) and rs3124737 (CASP7) from the Pujana ATM PCC gene set as eQTLs in two normal derived pancreas tissue datasets. CONCLUSION: Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.

• MeSH
• Genome-Wide Association Study methods   MeSH
• Carcinoma, Pancreatic Ductal genetics   MeSH
• Genetic Predisposition to Disease MeSH
• Polymorphism, Single Nucleotide MeSH
• Humans MeSH
• Pancreatic Neoplasms genetics   MeSH
• Models, Statistical MeSH
• Case-Control Studies MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Meta-Analysis MeSH

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10-8). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10-14), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10-10), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10-8), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10-8). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene.

• MeSH
• Genome-Wide Association Study MeSH
• Databases, Genetic MeSH
• Carcinoma, Pancreatic Ductal genetics   MeSH
• Genetic Predisposition to Disease MeSH
• Hepatocyte Nuclear Factor 1-beta genetics   MeSH
• Hepatocyte Nuclear Factor 4 genetics   MeSH
• Intracellular Signaling Peptides and Proteins MeSH
• Polymorphism, Single Nucleotide MeSH
• Humans MeSH
• Intercellular Signaling Peptides and Proteins MeSH
• Pancreatic Neoplasms genetics   MeSH
• Proteins genetics   MeSH
• Repressor Proteins genetics   MeSH
• Tensins genetics   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Meta-Analysis MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• Hepatocyte Nuclear Factor 1-beta MeSH
• Hepatocyte Nuclear Factor 4 MeSH
• HNF1B protein, human MeSH Browser
• HNF4G protein, human MeSH Browser
• Intracellular Signaling Peptides and Proteins MeSH
• Intercellular Signaling Peptides and Proteins MeSH
• NOC2L protein, human MeSH Browser
• Proteins MeSH
• Repressor Proteins MeSH
• Tensins MeSH
• TNS3 protein, human MeSH Browser
• Ucma protein, human MeSH Browser