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  1. Antwi SO, Bamlet WR, Pedersen KS, Chaffee KG, Risch HA, Shivappa N, et al.
    Carcinogenesis, 2018 07 30;39(8):1056-1067.
    PMID: 29800239 DOI: 10.1093/carcin/bgy072
    Diets with high inflammatory potential are suspected to increase risk for pancreatic cancer (PC). Using pooled analyses, we examined whether this association applies to populations from different geographic regions and population subgroups with varying risks for PC, including variation in ABO blood type. Data from six case-control studies (cases, n = 2414; controls, n = 4528) in the Pancreatic Cancer Case-Control Consortium (PanC4) were analyzed, followed by replication in five nested case-control studies (cases, n = 1268; controls, n = 4215) from the Pancreatic Cancer Cohort Consortium (PanScan). Two polymorphisms in the ABO locus (rs505922 and rs8176746) were used to infer participants' blood types. Dietary questionnaire-derived nutrient/food intake was used to compute energy-adjusted dietary inflammatory index (E-DII®) scores to assess inflammatory potential of diet. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using multivariable-adjusted logistic regression. Higher E-DII scores, reflecting greater inflammatory potential of diet, were associated with increased PC risk in PanC4 [ORQ5 versus Q1=2.20, 95% confidence interval (CI) = 1.85-2.61, Ptrend < 0.0001; ORcontinuous = 1.20, 95% CI = 1.17-1.24], and PanScan (ORQ5 versus Q1 = 1.23, 95% CI = 0.92-1.66, Ptrend = 0.008; ORcontinuous = 1.09, 95% CI = 1.02-1.15). As expected, genotype-derived non-O blood type was associated with increased PC risk in both the PanC4 and PanScan studies. Stratified analyses of associations between E-DII quintiles and PC by genotype-derived ABO blood type did not show interaction by blood type (Pinteraction = 0.10 in PanC4 and Pinteraction=0.13 in PanScan). The results show that consuming a pro-inflammatory diet and carrying non-O blood type are each individually, but not interactively, associated with increased PC risk.
  2. Childs EJ, Mocci E, Campa D, Bracci PM, Gallinger S, Goggins M, et al.
    Nat Genet, 2015 Aug;47(8):911-6.
    PMID: 26098869 DOI: 10.1038/ng.3341
    Pancreatic cancer is the fourth leading cause of cancer death in the developed world. Both inherited high-penetrance mutations in BRCA2 (ref. 2), ATM, PALB2 (ref. 4), BRCA1 (ref. 5), STK11 (ref. 6), CDKN2A and mismatch-repair genes and low-penetrance loci are associated with increased risk. To identify new risk loci, we performed a genome-wide association study on 9,925 pancreatic cancer cases and 11,569 controls, including 4,164 newly genotyped cases and 3,792 controls in 9 studies from North America, Central Europe and Australia. We identified three newly associated regions: 17q25.1 (LINC00673, rs11655237, odds ratio (OR) = 1.26, 95% confidence interval (CI) = 1.19-1.34, P = 1.42 × 10(-14)), 7p13 (SUGCT, rs17688601, OR = 0.88, 95% CI = 0.84-0.92, P = 1.41 × 10(-8)) and 3q29 (TP63, rs9854771, OR = 0.89, 95% CI = 0.85-0.93, P = 2.35 × 10(-8)). We detected significant association at 2p13.3 (ETAA1, rs1486134, OR = 1.14, 95% CI = 1.09-1.19, P = 3.36 × 10(-9)), a region with previous suggestive evidence in Han Chinese. We replicated previously reported associations at 9q34.2 (ABO), 13q22.1 (KLF5), 5p15.33 (TERT and CLPTM1), 13q12.2 (PDX1), 1q32.1 (NR5A2), 7q32.3 (LINC-PINT), 16q23.1 (BCAR1) and 22q12.1 (ZNRF3). Our study identifies new loci associated with pancreatic cancer risk.
  3. Klein AP, Wolpin BM, Risch HA, Stolzenberg-Solomon RZ, Mocci E, Zhang M, et al.
    Nat Commun, 2018 02 08;9(1):556.
    PMID: 29422604 DOI: 10.1038/s41467-018-02942-5
    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.
  4. Walsh N, Zhang H, Hyland PL, Yang Q, Mocci E, Zhang M, et al.
    J Natl Cancer Inst, 2019 Jun 01;111(6):557-567.
    PMID: 30541042 DOI: 10.1093/jnci/djy155
    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.

  5. Machiela MJ, Zhou W, Karlins E, Sampson JN, Freedman ND, Yang Q, et al.
    Nat Commun, 2016 06 13;7:11843.
    PMID: 27291797 DOI: 10.1038/ncomms11843
    To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases.
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