Literature DB >> 27579533

Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21.

Mingfeng Zhang1, Zhaoming Wang2,3,4, Ofure Obazee5, Jinping Jia1, Erica J Childs6, Jason Hoskins1, Gisella Figlioli5, Evelina Mocci6, Irene Collins1, Charles C Chung2,3, Christopher Hautman1, Alan A Arslan7,8,9, Laura Beane-Freeman2, Paige M Bracci10, Julie Buring11,12, Eric J Duell13, Steven Gallinger14, Graham G Giles15,16,17, Gary E Goodman18, Phyllis J Goodman19, Aruna Kamineni20, Laurence N Kolonel21, Matthew H Kulke22, Núria Malats23, Sara H Olson24, Howard D Sesso25,11,12, Kala Visvanathan26, Emily White18,27, Wei Zheng28,29, Christian C Abnet2, Demetrius Albanes2, Gabriella Andreotti2, Lauren Brais22, H Bas Bueno-de-Mesquita30,31,32, Daniela Basso33, Sonja I Berndt2, Marie-Christine Boutron-Ruault34,35,36, Maarten F Bijlsma37, Hermann Brenner38,39,40, Laurie Burdette2,3, Daniele Campa41, Neil E Caporaso2, Gabriele Capurso42, Giulia Martina Cavestro43, Michelle Cotterchio44,45, Eithne Costello46, Joanne Elena47, Ugo Boggi48, J Michael Gaziano11,12,49, Maria Gazouli50, Edward L Giovannucci25,51,52, Michael Goggins53,54,55, Myron Gross56, Christopher A Haiman57, Manal Hassan58, Kathy J Helzlsouer47, Nan Hu2, David J Hunter59,60,61, Elzbieta Iskierka-Jazdzewska62, Mazda Jenab63, Rudolf Kaaks64, Timothy J Key65, Kay-Tee Khaw66, Eric A Klein67, Manolis Kogevinas68,69,70, Vittorio Krogh71, Juozas Kupcinskas72, Robert C Kurtz73, Maria T Landi2, Stefano Landi41, Loic Le Marchand21, Andrea Mambrini74, Satu Mannisto75, Roger L Milne15,16, Rachel E Neale76, Ann L Oberg77, Salvatore Panico78, Alpa V Patel79, Petra H M Peeters80,31, Ulrike Peters18,27, Raffaele Pezzilli81, Miquel Porta69,82,83, Mark Purdue2, J Ramón Quiros84, Elio Riboli31, Nathaniel Rothman2, Aldo Scarpa85, Ghislaine Scelo63, Xiao-Ou Shu28,29, Debra T Silverman2, Pavel Soucek86, Oliver Strobel87, Malin Sund88, Ewa Małecka-Panas89, Philip R Taylor2, Francesca Tavano90, Ruth C Travis65, Mark Thornquist18, Anne Tjønneland91, Geoffrey S Tobias2, Dimitrios Trichopoulos25,92,93, Yogesh Vashist94, Pavel Vodicka95, Jean Wactawski-Wende96, Nicolas Wentzensen2, Herbert Yu21, Kai Yu2, Anne Zeleniuch-Jacquotte8,97, Charles Kooperberg98, Harvey A Risch99, Eric J Jacobs79, Donghui Li58, Charles Fuchs22,51, Robert Hoover2, Patricia Hartge2, Stephen J Chanock2, Gloria M Petersen100, Rachael S Stolzenberg-Solomon2, Brian M Wolpin22, Peter Kraft25,101, Alison P Klein6,102, Federico Canzian5, Laufey T Amundadottir1.   

Abstract

Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88x10 -15), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22x10 -9) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70x10 -8). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 ( NR5A2), chr8q24.21 ( MYC) and chr5p15.33 ( CLPTM1L- TERT) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal ( n = 10) and tumor ( n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7x10 -8). This finding was validated in a second set of paired ( n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5x10 -4-2.0x10 -3). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology.

Entities:  

Keywords:  GWAS; NR5A2 ; fine-mapping; imputation; pancreatic cancer

Mesh:

Year:  2016        PMID: 27579533      PMCID: PMC5340084          DOI: 10.18632/oncotarget.11041

Source DB:  PubMed          Journal:  Oncotarget        ISSN: 1949-2553


INTRODUCTION

Although relatively rare, pancreatic tumors are highly lethal. Over 80% of patients present with advanced disease at the time of diagnosis and the five year survival is only 7% [1, 2]. This disease is currently the third leading cause of cancer deaths in the United States, sixth in Europe and seventh worldwide [3-5]. In contrast to most other cancers, mortality rates for pancreatic cancer are not improving [6, 7]. In the U.S., it is predicted to become the second leading cause of cancer-related deaths by 2030 [7]. Pancreatic cancer risk has been associated with smoking, obesity, diabetes and pancreatitis [8]. A small fraction of the familial aggregation of pancreatic cancer can be accounted for by rare, moderately or highly penetrant mutations [9]. Furthermore, genome-wide association studies (GWAS) have identified common variants at 13 loci associated with risk of pancreatic cancer in European populations and at 5 loci in Asian populations (at the GWAS threshold of P < 5.0×10−8), or a total of 18 loci [10-15]. Imputation has proven to be a powerful tool in genome-wide association studies (GWAS) by facilitating investigation of variants not directly assessed on genotyping arrays, the merging of GWAS datasets genotyped on different arrays, and fine-mapping of risk loci [16]. To discover additional pancreatic cancer susceptibility loci for individuals of European ancestry, we imputed three GWAS datasets including a total of 5,107 cases and 8,845 controls (PanScan I-III, Stage I) [12]. For replication of promising signals, we first genotyped an additional 1,912 cases and 3,763 controls (PANDoRA; Replication 1), and then further assessed promising signals in a second set of 4,164 cases and 3,792 controls (PanC4; Replication 2). We identified three new susceptibility signals that achieved genome-wide significance for pancreatic cancer risk.

RESULTS

We conducted imputation of three published pancreatic cancer GWAS datasets performed in individuals of European ancestry, PanScan I, II and III [10-12] using the 1000G (Phase 1, version 3) reference dataset [17]. We included 9,132,527 genotyped or imputed SNPs with an imputation information (INFO) score >0.5 and minor allele frequency (MAF) >0.01, and performed a fixed effects meta-analysis to combine association results for a total of 5,107 pancreatic cancer cases and 8,845 control subjects [10-12]. Little evidence of systematic inflation due to population stratification was observed (λ = 1.02 for PanScan I+II and λ = 1.07 for PanScan III). We attempted replication of promising findings in two stages. In the first replication stage, we genotyped 15 promising variants in 1,912 pancreatic cancer cases and 3,763 control subjects from the PANcreatic Disease ReseArch (PANDoRA) consortium, a case-control consortium including studies from eight European countries [18]. In the second replication stage, we assessed the three most significant variants based on the meta-nanalyses results for PanScan I+II, PanScan III and PANDoRA using 4,164 pancreatic cancer cases and 3,792 controls from the Pancreatic Cancer Case-Control Consortium (PanC4), including studies from the U.S., Canada, Europe and Australia [15]. In total, the discovery and replication stages included 11,183 cases and 16,400 controls (Supplementary Table 1). In the meta-analysis of PanScan I-III (Stage I), two new variants were identified at genome-wide significance (P < 5.0×10−8), one on chromosome 1q32.1 (rs2816938: P = 1.71×10−10, OR = 1.23 95% CI 1.15-1.31) and one on 8q24.21 (rs10094872, P = 3.55×10−8, OR = 1.18 95% CI 1.11-1.25) (Table 1, Supplemental Table 2). After adjusting the analysis on 1q32.1 for the previously reported GWAS SNP rs3790844 (r2 = 0.097 in 1000G EUR populations) [11], the association for rs2816938 remained statistically significant (PConditional = 3.06×10−6, OR = 1.17). This was also true for the signal at 8q24.21, marked by rs10094872, after adjusting for the GWAS SNP rs1561927 (r2 = 0.01 in 1000G EUR) [12] (PConditional = 1.09×10−7, OR = 1.16). The signal at 1q32.1 is located ~11 kb upstream of NR5A2, a gene that encodes a nuclear transcription factor known to play important roles in multiple aspects of pancreatic development and function [19, 20]. The SNP at 8q24.21 is located ~28 kb upstream of MYC, in a susceptibility locus previously reported for bladder cancer (tagged by rs9642880; r2 = 0.64 in 1000G EUR) [21-23] and ~850 kb upstream of a previously reported pancreatic cancer susceptibility locus [12].
Table 1

Association results for three new pancreatic cancer susceptibility signals

ChrNearest gene(s)aSNPPositionbAllelescINFOdStageAllelic OR (95% CI)Minor allele frequencyePfConditional analysis
MinorMajorControlsCasesConditional PAllelic OR (95% CI)
1q32.1NR5A2rs2816938199,985,368AT1.00PanScan I-II1.25 (1.16-1.35)0.2160.2551.57 × 10−8
1.00PanScan III1.19 (1.06-1.33)0.2310.2552.21 × 10−3
Stage I1.23 (1.15-1.31)1.71 × 10−103.06 × 10−61.17 (1.09-1.25)
PANDoRA1.18 (1.07-1.30)0.2040.2261.12 × 10−3
0.78PanC41.16 (1.07-1.26)0.1670.1895.77 × 10−5
Combined1.20 (1.15-1.25)4.88 × 10−15
8q24.21MYCrs10094872128719884TA0.93PanScan I-II1.19 (1.11-1.28)0.3500.3899.49 × 10−7
0.94PanScan III1.14 (1.03-1.27)0.3450.3679.27 × 10−3
Stage I1.18 (1.11-1.25)3.55 × 10−81.09 × 10−71.16 (1.13-1.19)
PANDoRANANANANA
0.96PanC41.10 (1.03-1.18)0.3590.3823.87 × 10−4
Combined1.15 (1.10-1.20)3.22×10−9
5p15.33TERT, CLPTM1Lrs352261311295373TC0.73PanScan I-II0.63 (0.52-0.78)0.0410.0291.61 × 10−5
0.79PanScan III0.65 (0.49-0.87)0.0360.0283.27 × 10−3
Stage I0.64 (0.54-0.76)1.80 × 10−73.43 × 10−70.66 (0.61-0.72)
PANDoRA0.83 (0.65-1.05)0.0330.0260.125
0.87PanC40.75 (0.60-0.93)0.0230.0171.01 × 10−2
Combined0.71 (0.63-0.80)1.70×10−8

Results are shown from an unconditional logistic regression of the genotypes generated in PanScan I, II and III as well as the two replication studies.

Closest RefSeq gene(s).

Position of SNP in NCBI genome build 37 (Hg19).

Minor and major alleles.

Quality of imputation metric.

Minor allele frequencies (MAF) are not listed for meta-analysis results.

1 d.f. score test; Chr: chromosome and band; OR, per-allele OR for the minor allele adjusted for for age, sex, study, arm and significant principal components for PanScan I+II; per-allele OR adjusted for age, sex, geographic region and significant principal components for PanScan III; per-allele OR adjusted for age, sex and study for PANDoRA; per-allele OR adjusted for age, sex, study and significant principal components for PanC4. The number of case and control subjects in the combined set of PanScan I, II, III, PANDoRA and PanC4 were: rs2816938 (11,158/16,343), rs10094872 (9,269/12,635) and rs35226131 (11,143/16,308). Text in bold indicates the combined meta-analysis results. NA: Note that the TaqMan assay for rs10094872 on chr8q24.21 failed manufacturing and was therefore not attempted in the PANDoRA samples.

Results are shown from an unconditional logistic regression of the genotypes generated in PanScan I, II and III as well as the two replication studies. Closest RefSeq gene(s). Position of SNP in NCBI genome build 37 (Hg19). Minor and major alleles. Quality of imputation metric. Minor allele frequencies (MAF) are not listed for meta-analysis results. 1 d.f. score test; Chr: chromosome and band; OR, per-allele OR for the minor allele adjusted for for age, sex, study, arm and significant principal components for PanScan I+II; per-allele OR adjusted for age, sex, geographic region and significant principal components for PanScan III; per-allele OR adjusted for age, sex and study for PANDoRA; per-allele OR adjusted for age, sex, study and significant principal components for PanC4. The number of case and control subjects in the combined set of PanScan I, II, III, PANDoRA and PanC4 were: rs2816938 (11,158/16,343), rs10094872 (9,269/12,635) and rs35226131 (11,143/16,308). Text in bold indicates the combined meta-analysis results. NA: Note that the TaqMan assay for rs10094872 on chr8q24.21 failed manufacturing and was therefore not attempted in the PANDoRA samples. A total of 15 promising variants (P < 5.0×10−6) were selected for replication in 1,912 pancreatic cancer cases and 3,763 control subjects from the European PANDoRA case-control consortium [18]. After a meta-analysis of PanScan I, II and III and PANDoRA results, the three most promising variants (Supplemental Table 2) were carried forward to replication in PanC4 [15]. The meta-analysis of PanScan I-III with PANDoRA and PanC4 confirmed the signals on chr1q32.1 (P = 4.88×10−15, OR = 1.20 95% CI 1.15-1.25) and chr8q24.21 (P = 3.22×10−9, OR = 1.15 95% CI 1.10-1.20). In addition, a new signal in the multicancer region on chr5p15.33, upstream of TERT, was detected (rs35226131, P = 1.70×10−8, OR = 0.71 95% CI 0.63-0.80) (Table 1). After conditioning the analysis in PanScan I, II and III on the two reported pancreatic cancer susceptibility loci at 5p15.33, rs36115365 [24] (tagging the fine-mapped signal for rs401681 [11] in CLPTM1L) and rs2736098 [12] (tagging the signal in TERT), the signal was still near GWAS significant (PUnconditional = 1.80×10−7, OR = 0.64; PConditional = 3.43×10−7, OR = 0.66). This SNP (rs35226131) is located ~200bps upstream of the transcriptional start site (TSS) of TERT, and marks the least common of the three loci with a MAF of 0.036 in the 1000G EUR populations. The LD between rs35226131 and the previously reported signals is low (r2 = 0.009 for rs36115365 and r2 = 0.011 fo rs2736098) in 1000G EUR.

Regional plots for three signals associated with pancreatic cancer risk

The −log10(P value) (Y left axis) for Stage I (PanScan I-III, in gray), PANDoRA (purple) and PanC4 (light blue) was plotted on the genomic coordinates (X axis; NCBI genome build 37). Superimposed blue lines depicts likelihood ratio statistics (right Y axis) estimating putative recombination hotspots in the region. This was performed 5 times, each time utilizing 100 random EUR samples from the 1000 Genomes population (EUR, n = 503) (Y right axis). The combined data for Stage I, PANDoRA and PanC4 for three regions: panel A. rs2816938 (1q32.1), panel B. rs10094872 (8q24.21), and panel C: rs3226131 (5p13.33) are shown in red.

Bioinformatic analysis of susceptibility alleles and differential expression analysis

In order to take the first steps towards understanding the functional ramifications at these three new susceptibility signals, we conducted in silico bioinformatic analyses using HaploReg and RegulomeDB [25, 26]. Supporting evidence for putative regulatory function on gene expression was seen for the three loci, particularly for chr1q32.1 and 5p15.33, with open chromatin, modified histones and transcription factor binding in multiple tissues, including those derived from the pancreas and other gastrointestinal tissues (Supplemental Table 3). At chr5p15.33, one of the four variants highly correlated with rs35226131 is a missense variant in the second exon of TERT (rs61748181: r2 = 1, D' = 1 in 1000G EUR) whereby the minor allele, associated with reduced risk of pancreatic cancer, changes amino acid 279 from alanine to threonine (A279T). We assessed expression quantitative trait loci (eQTL) for the three variants in GTEx [27] and the nearest genes (NR5A2 for 1q32.1; TERT and CLPTM1L for 5p14.33; MYC and PVT1 for 8q24.21; Supplementary Table 4) in histologically normal post-mortem pancreatic tissue samples (n = 149). The minor allele of the SNP that marks the signal on 8q24.21 (rs10094872) and was associated with increased risk of pancreatic cancer, was associated with decreased PVT1 expression (β = −0.23, P = 0.0053) (Supplemental Figure 1). Nominally significant eQTLs (P < 0.05) were not seen for MYC (P = 0.29) or for the SNPs on chr5p15.33 (P = 0.91 for CLPTM1L; TERT was not expressed) or 1q32.1 (P = 0.68 for NR5A2). We furthermore assessed differential expression of the same genes in pancreatic cell lines (n = 9) and pancreatic ductal adenocarcinoma (PDAC) samples (n = 8) as compared with histologically normal pancreatic tissue samples (n = 10) by RNAseq [28] (Supplemental Tables 5-7). The most notable differences were seen for NR5A2 on chr1q32.1 where mRNA expression was markedly lower in pancreatic tumor samples (average fold change -7.6, P = 5.7×10−8) and cell lines (average fold change -32.7, P = 1.5×10−14) than in histologically normal pancreatic tissue samples (Supplemental Table 7). We further validated this finding in an independent set of paired histologically normal and tumor derived (PDAC) pancreatic tissue samples from 20 individuals by RT-qPCR for three NR5A2 isoforms and noted decreased expression in tumors for the majority of pairs (average fold change for paired samples was -78.5 for isoform 1, P = 2.0×10−3; -95.7 fold for isoform 2, P = 7.5×10−4; -31.3 fold for isoform 3, P = 1.5×10−3) (Figure 2).
Figure 2

Expression of three NR5A2 isoforms in paired histologically normal and tumor derived pancreatic tissue samples

Blue bars indicate expression in histologically normal samples and red in tumor derived samples. A. NR5A2 isoform 1, B. NR5A2 isoform 2 and C. NR5A2 isoform 3. Note that no expression was seen for isoform 1 in either the normal or tumor derived sample from Subject 3. Error bars represent standard deviation from four replicates.

Expression of three NR5A2 isoforms in paired histologically normal and tumor derived pancreatic tissue samples

Blue bars indicate expression in histologically normal samples and red in tumor derived samples. A. NR5A2 isoform 1, B. NR5A2 isoform 2 and C. NR5A2 isoform 3. Note that no expression was seen for isoform 1 in either the normal or tumor derived sample from Subject 3. Error bars represent standard deviation from four replicates.

Technical validation of imputed SNPs

To assess imputation quality, we performed TaqMan genotyping in 678 samples from PanScan I and III (see Materials and Methods). The correlation (r2) between the imputed genotypes and those measured by TaqMan was 0.98 for rs2816938 (1q32.1), 0.90 for rs10094872 (8q24.21) and 0.37 for rs35226131 (5p15.33). Due to the lower correlation between imputed and directly assayed genotypes for rs35226131, we performed a second validation in an additional 875 samples, including both rs35226131 as well as the perfectly correlated coding SNP on 5p15.33 mentioned above, rs61748181. The imputed-genotyped r2 for rs35226131 improved to 0.44 in the second validation set, and was 0.55 for rs61748181. Genotype concordance for the most likely imputed genotypes and directly assayed genotypes (see Materials and Methods) for rs35226131 improved from 86.4% in the first validation set to 94.4% in the second set, and was 96.2% for rs61748181 in the second set. Since rs61748181 was directly genotyped in one of the replication studies (PanC4), we performed a meta-analysis of PanScan I-III (OR = 0.62 95% CI 0.52-0.75, P = 5.37×10−7) and PanC4 (OR = 0.67 95% CI 0.55-0.85, P = 1.91×10−4) data. This revealed a highly significant association for rs61748181 (OR = 0.64 95% CI 0.56-0.74, P = 1.28×10−10) that was stronger than that seen for rs35226131 (OR = 0.68 95% CI 0.59-0.79, P = 1.91×10−8). These results suggest that the association results at this potentially new pancreatic cancer risk locus are reliable.

DISCUSSION

In this study, we performed imputation across three pancreatic cancer GWAS datasets, namely PanScan I, II and III [10-12], using 1000G reference data. Through replication of promising variants in individuals from two independent pancreatic cancer case-control consortia, PANDoRA and PanC4, we identified three new GWAS significant risk signals for pancreatic cancer. They are independent signals in previously established pancreatic cancer risk loci on chromosomes 1q32.1, 5p15.33 and 8q24.21, as per conditional analysis, supporting their importance for pancreatic cancer risk. The signal on 1q32.1 is located in NR5A2, a gene that encodes nuclear receptor subfamily 5 group A member 2 (NR5A2), a transcription factor important for pancreatic development and adult function in the pancreas, liver, intestine and ovary, where it regulates cholesterol synthesis, bile acid homeostasis and steroidogenesis [19, 20]. NR5A2 is an important regulator of exocrine function in the adult pancreas where it maintains homeostasis and promotes regeneration of acinar cells after inflammation caused by chemically induced pancreatitis, and protects the pancreas from KRAS driven pre-neoplastic changes [29-31]. Other studies have indicated a growth inducing role for NR5A2 in pancreatic cancer [32, 33]. Highly correlated variants (r2>0.7) span ~25 kb on chr1q32.1 from ~11 kb upstream of the TSS to within the second intron of the gene. We observed significantly lower mRNA expression of NR5A2 in the majority of pancreatic tumors and cell lines tested compared with histologically normal pancreatic tissue samples, indicating a possible role for reduced NR5A2 expression in pancreatic cancer. Although an expression QTL was not observed in GTEx data, the relationship between the two currently known pancreatic cancer risk loci on 1q32.1 and NR5A2 expression remains to be studied in greater detail. The tag SNP on 8q24.21 is located ~28 kb upstream of MYC at an established bladder cancer risk locus [21-23] that is ~850 kb upstream of our previously reported pancreatic cancer susceptibility locus [12]. Multiple independent susceptibility loci on 8q24.21, distributed over a 2 Mb region, are known to influence risk of bladder, breast, prostate, colorectal, lung, ovarian, pancreatic, renal cancer, glioma and chronic lymphocytic leukemia (CLL) [34-38]. Deregulated expression of MYC, a transcription factor that regulates multiple aspects of cell growth and proliferation, occurs in a broad range of human tumors [39]. Although the proximity of rs10094872 to MYC indicates that it may be the most likely target gene, 8q24.21 is known for long range chromosomal interactions, and additional candidate genes, including PVT1 (183 kb), POU5F1B (290 kb), CCAT2 (305 kb) and MIR1205-MIR1208 (253-442 kb), could be involved [40-44]. Several of the 8q24.21 risk loci interact with the MYC and PVT1 promoters through long range chromosomal interaction, and allele-specific effects on gene expression have been reported for both genes [42, 45]. An expression QTL for MYC has been described for the bladder cancer risk locus in histologically normal bladder samples from Chinese subjects, albeit from a very small set [46], but not in adipose or blood tissue samples from European subjects [22]. We noted an eQTL for rs10094872 and PVT1 expression in pancreatic tissue samples in GTEx, indicating that PVT1 may be a target gene for this locus. Replication of these findings is required in independent sample sets. PVT1 encodes a long noncoding RNA that is often amplified and upregulated along with MYC across multiple cancers. Recently, it has been shown to increase MYC protein levels and potentiate its activity [47]. In pancreatic cancer, PVT1 expression is associated with gemcitabine sensitivity in human pancreatic cancer cells and may be associated with poor prognosis [47-49]. The signal on chr5p15.33 lies in another multicancer susceptibility region reported by GWAS for bladder cancer, breast cancer, chronic lymphocytic leukemia, glioma, lung cancer, melanoma, non-melanoma skin cancer, ovarian cancer, pancreatic cancer, prostate cancer and testicular germ cell cancer [11, 12, 23, 37, 50–60]. For the 6 independent susceptibility loci that have been identified in the TERT-CLPTM1L gene region, the same alleles are associated with an increased risk for some cancers but decreased risk of others [24, 60, 61]. Two independent pancreatic cancer susceptibility loci have previously been identified on chr5p15.33 through GWAS [11, 12, 24]. The first one, described in PanScan II [11] was marked by an intronic SNP (rs401681) in CLPTM1L that has since been fine-mapped to rs451360 (and a set of highly correlated variants including rs36115365) [24]. A second independent signal on 5p15.33 was identified in PanScan III, tagged by a synonymous SNP (rs2736098) in the second exon of TERT [12]. Recently, a third risk locus, marked by rs2853677, was identified in this genomic region through a candidate gene analysis of the TERT and TERC genes [62]; however this variant did not attain GWAS significance in our study (PanScan I-III, P = 4.2×10−4). The TERT gene encodes the catalytic subunit of telomerase, known for its critical role in maintaining telomere ends and the increased telomerase activity frequently seen in human cancers [63-65]. Telomere-independent functions for TERT include regulation of gene expression, cell survival, epithelial to mesenchymal transition (EMT) and mitochondrial function [66]. The neighboring gene encodes cleft lip and palate associated transmembrane 1 like (CLPTM1L) protein that promotes growth and survival in pancreatic and lung cancer, respectively, and is overexpressed in some cancers [67-69]. The SNP (rs35226131) that marks the new risk signal on 5p15.33 reported here, and highly correlated variants, are located in the TERT promoter (~200-500 bp upstream of the TSS) and could potentially influence its expression. Additionally, it is perfectly correlated with a nonsynonomous variant in TERT (rs61748181, A279T) that was recently reported as a novel lung adenocarcinoma risk locus by deep sequencing and direct genotyping of 5,164 cases and 5,716 controls of European ancestry [70]. The threonine substitution at this amino acid in TERT negatively influences telomere length and proliferation in esophageal cancer cell lines compared with alanine, and leads to reduced Wnt signaling through destabilization of complexes containing TERT, transcription activator BRG-1 and β-catenin [71]. As the TERT-279T variant is protective for pancreatic cancer in our study, and for lung cancer [70], the underlying mechanism at this locus may relate to increased TERT activity via canonical and/or non-canonical TERT pathways. This hypothesis needs to be formally investigated by future molecular studies. In conclusion, through imputation of three existing GWAS datasets and replication in two independent case-control consortia, we identified three new susceptibility signals for pancreatic cancer in populations of European ancestry. They are located in genomic regions previously reported by GWAS of pancreatic cancer, further supporting their importance for pancreatic cancer risk. Further work is required to identify target genes and explain the underlying biological mechanisms.

MATERIALS AND METHODS

Study participants

Participants were drawn from the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium (PanC4) and include individuals from 17 cohort and 11 case-control studies genotyped in three previous GWAS phases, namely PanScan I, PanScan II and PanScan III [10-12]. Two replication cohorts were included, the PANDoRA consortium [18] (Replication I) and the Pancreatic Cancer Case-Control Consortium (PanC4) [15] (Replication 2). Cases were defined as individuals diagnosed with adenocarcinoma of the pancreas. Each study obtained informed consent from study participants and approval from its Institutional Review Board (IRB) including IRB certification permitting data sharing in accordance with the NIH Policy for Sharing of Data Obtained in NIH Supported or Conducted Genome-Wide Association Studies (GWAS). The PanScan and PanC4 GWAS data are available through dbGAP (accession numbers phs000206.v5.p3 and phs000648.v1.p1, respectively).

Genotyping, imputation and association analysis

GWAS genotyping was performed at the Cancer Genomics Research Laboratory (CGR) of the National Cancer Institute (NCI) of the National Institutes of Health (NIH) using the Illumina HumanHap series arrays (Illumina HumanHap550 Infinium II, Human 610-Quad) for PanScan I-II, and the Illumina Omni series arrays (OmniExpress, Omni1M, Omni2.5 and Omni5M) for PanScan III [10-12]. The 1000 Genomes (1000G) Phase 1, Release 3 [17] reference dataset was used to impute the PanScan I-III GWAS datasets using IMPUTE2 [72] as previously described [12, 24]. Due to the large overlap of variants on genotyping arrays for PanScan I and II, these datasets were imputed and analyzed together. The PanScan III data was imputed and analyzed separately. For quality control, variants were excluded based on: 1) completion rate < 90%; 2) MAF < 0.01; 3) Hardy-Weinberg Proportion P value < 1×10−6; 4) low quality imputation score (IMPUTE 2 INFO score < 0.5). After quality control, 9,132,527 SNPs in 5,107 pancreatic cancer cases and 8,845 controls of European ancestry were included in the analysis. The association analysis was performed using SNPTEST [73] based on probabilistic genotypes from IMPUTE2 [72] using the same adjustments for study, geographical region, age, sex and population substructure as were used in PanScan [10-12]. The score test of the log additive genetic effect was used. A meta-analysis of data from PanScan I & II with PanScan III was performed using the fixed-effects inverse-variance method based on β estimates and standard errors. Heterogeneity was not observed for the SNPs identified as GWAS significant or suggestive in the combined study (Pheterogeneity ≥0.30) The estimated inflation of the test statistic, λ, was 1.02 for PanScan I+II and 1.07 for PanScan III, respectively (using variants with MAF>0.01 and INFO>0.5) [74].

Replication

Fifteen variants giving promising signals (P < 5.0×10−6) were selected for replication in the PANDoRA consortium (Replication 1) [18]. Genotyping was performed by custom TaqMan genotyping assays (Applied Biosystems) at the German Cancer Research Center (DKFZ) in Heidelberg, Germany in 3,343 pancreatic cancer cases and 4,998 controls, of which 2,820 cases and 3,909 controls had complete demographic and clinical data and did not overlap with other study samples. Duplicate quality control samples (n = 541 pairs) showed 99.67% genotype concordance. Samples on a few plates were not genotyped for all variants. Unfortunately these plates contained more cases than controls. We excluded 908 cases and 146 controls, either with low genotyping completion rate (< 80%) or not genotyped, resulting in a total of 1,912 cases and 3,763 controls in the final analyses. The association analysis for PANDoRA was adjusted for age, gender and study in the same manner as previously described [12]. Three variants from the meta-analysis of PanScan and PANDoRA were then selected for a second replication in the Pancreatic Cancer Case-Control Consortium (PanC4) [15] (Replication 2). Genotyping for PanC4 had previously been performed at the Johns Hopkins Center for Inherited Disease Research (CIDR) using the IlluminaHumanOmniExpressExome-8v1 array followed by imputation using 100G Phase 3, version 1 [75] and IMPUTE2. Association analysis was performed in 4,164 pancreatic cancer cases and 3,792 control subjects of European ancestry as previously described [15]. Variants at 3 chromosomal locations were extracted from the results and meta-analyses conducted as described above. Heterogeneity between studies was assessed using the Cochran's Q-test. IMPUTE2 information scores were 0.78 (rs2816938), 0.96 (rs10094872) and 0.87 (rs35226131) for the three reported variants. Recombination hotspots for association plots were generated as previously described using SequenceLDhot (10-12). The recombination hotspot inference was performed 5 times, each time utilizing a hundred random sampled EUR from the 1000 Genomes (EUR, n = 503). The linkage disequilibrium heatmap was prepared using the 1000 Genomes Phase 3 EUR data (n = 505, CEU+FIN+GBR+IBS+TSI), and snp.plotter R software package [76].

Validation of imputation accuracy

Imputation accuracy was assessed by direct TaqMan genotyping or Sanger sequencing. TaqMan genotyping assays (ABI, Foster City, CA) were optimized for three SNPs (rs2816938 on 1q32.1, rs35226131 on 5p15.33 and rs10094872 on 8q24.21) in the independent regions. In an analysis of 678 samples from PanScan I and III [10, 12, 77], the allelic r2 measured between imputed and assayed genotypes [78] were 0.98, 0.37 and 0.90, respectively. A second validation in an additional 875 samples from PanScan I included two perfectly correlated SNPs on 5p15.33, rs35226131 and rs61748181; the allelic r2 in this set was 0.44 and 0.55, respectively. We also assessed concordance between the most likely imputed genotypes and directly measured genotypes as follows: samples with imputed allelic dosage ranging from 0-0.5 were designated as being of the homozygous common genotype; samples ranging from 0.51-1.5 as being of the heterozygous genotype and samples ranging from 1.51-2.0 as being of the rare homozygous genotype.

Bioinformatic analysis of functional potential

HaploReg v4.1 (http://www.broadinstitute.org/mammals/haploreg/haploreg.php) was used to annotate functional and regulatory potential of the most significant germline variants at each locus as well as highly correlated variants (r2>0.7) that mark each of the regions identified [25]. RegulomeDB (http://regulomedb.org/) was used to assess and score regulatory potential of variants in each locus [26]. Expression quantitative trait locus (eQTL) effects were assessed using the Genotype-Tissue Expression Project (GTEx) database (http://www.gtexportal.org/home/) for pancreatic tissues (n = 149 samples) [27].

Analysis of gene expression

Gene expression was assessed for five genes that are closest to the reported variants on chromosomes 1q32.1 (NR5A2), 5p15.33 (TERT and CLPTM1L), and 8q24.21 (MYC and PVT1). We first assessed differential expression of these genes in pancreatic tumor samples (PDAC, n = 8), histologically normal (non-malignant) pancreatic tissue samples (n = 10), and pancreatic cell lines (n = 9) by RNA-sequencing as described previously [28]. We compared gene expression in tumors and cell lines to histologically normal pancreatic tissue samples by EdgeR analysis [28]. P-values represent an exact test of the differential expression of each gene in histologically normal and tumor derived samples using normalized read counts in EdgeR. We also assessed the expression of one of these genes (NR5A2) in a second independent tissue sample set that included 20 fresh frozen paired histologically normal pancreatic samples (adjacent to tumor) and pancreatic ductal adenocarcinoma (PDAC) tumor samples. RNA samples were isolated from fresh frozen tissues and reverse transcribed to cDNA as previously described [28]. Three NR5A2 isoforms (isoform 1: NM_205860, isoform 2: NM_003822, and isoform 3: uc009wzh.3) were tested using TaqMan gene expression assays (Thermo Fisher Scientific, isoform 1: Hs00894632_m1, isoform2: Hs00892375_m1 and a custom assay, for isoform 3 forward primer: 5′CTTTTCGCCGGAGTTGAAT3′; reverse primer: 5′GTCCGGAAGCCCAGCA3′; probe: 5′ CTGTGCTGCCCGTGTCC3′) and a 7900HT system (ABI). Each reaction was run in triplicate and analyzed according to the ΔΔCt method using B2M (Hs99999907_m1), GAPDH (Hs99999905_m1) and PPIA (Hs99999904_m1) as housekeeping genes. P-values represent two-sided T-tests of the difference in expression between histologically normal and tumor derived samples. All tissue samples were obtained from the Mayo Clinic in Rochester, MN. The project was approved by the Institutional Review Boards of the Mayo Clinic and the NIH. Nine pancreatic cancer cell lines (AsPC-1, BxPC-3, Hs766T, SU.86.86, SW1990, CFPAC-1, Capan-1, PANC-1, MIA PaCa-2) were purchased from ATCC and cultured as recommended (http://www.ATCC.com). The cell lines were tested for authentication with a panel of short tandem repeats (STR) using the Identifiler kit (Life Technologies) and compared with the ATCC and the DSMZ (German Collection of Microorganisms and Cell Cultures) STR Profile Databases. All cell lines matched the listed profiles.
  76 in total

1.  Common genetic variants on 8q24 contribute to susceptibility to bladder cancer in a Chinese population.

Authors:  Meilin Wang; Miaomiao Wang; Wei Zhang; Lin Yuan; Guangbo Fu; Qingyi Wei; Zhengdong Zhang
Journal:  Carcinogenesis       Date:  2009-04-15       Impact factor: 4.944

2.  Transcriptome analysis of pancreatic cancer reveals a tumor suppressor function for HNF1A.

Authors:  Jason W Hoskins; Jinping Jia; Marta Flandez; Hemang Parikh; Wenming Xiao; Irene Collins; Mickey A Emmanuel; Abdisamad Ibrahim; John Powell; Lizhi Zhang; Nuria Malats; William R Bamlet; Gloria M Petersen; Francisco X Real; Laufey T Amundadottir
Journal:  Carcinogenesis       Date:  2014-09-18       Impact factor: 4.944

3.  An expressed retrogene of the master embryonic stem cell gene POU5F1 is associated with prostate cancer susceptibility.

Authors:  Joan P Breyer; Daniel C Dorset; Travis A Clark; Kevin M Bradley; Tiina A Wahlfors; Kate M McReynolds; William H Maynard; Sam S Chang; Michael S Cookson; Joseph A Smith; Johanna Schleutker; William D Dupont; Jeffrey R Smith
Journal:  Am J Hum Genet       Date:  2014-02-27       Impact factor: 11.025

4.  Genome-wide association study of pancreatic cancer in Japanese population.

Authors:  Siew-Kee Low; Aya Kuchiba; Hitoshi Zembutsu; Akira Saito; Atsushi Takahashi; Michiaki Kubo; Yataro Daigo; Naoyuki Kamatani; Suenori Chiku; Hirohiko Totsuka; Sumiko Ohnami; Hiroshi Hirose; Kazuaki Shimada; Takuji Okusaka; Teruhiko Yoshida; Yusuke Nakamura; Hiromi Sakamoto
Journal:  PLoS One       Date:  2010-07-29       Impact factor: 3.240

5.  Cancer incidence and mortality patterns in Europe: estimates for 40 countries in 2012.

Authors:  J Ferlay; E Steliarova-Foucher; J Lortet-Tieulent; S Rosso; J W W Coebergh; H Comber; D Forman; F Bray
Journal:  Eur J Cancer       Date:  2013-02-26       Impact factor: 9.162

6.  A genome-wide association study identifies pancreatic cancer susceptibility loci on chromosomes 13q22.1, 1q32.1 and 5p15.33.

Authors:  Gloria M Petersen; Laufey Amundadottir; Charles S Fuchs; Peter Kraft; Rachael Z Stolzenberg-Solomon; Kevin B Jacobs; Alan A Arslan; H Bas Bueno-de-Mesquita; Steven Gallinger; Myron Gross; Kathy Helzlsouer; Elizabeth A Holly; Eric J Jacobs; Alison P Klein; Andrea LaCroix; Donghui Li; Margaret T Mandelson; Sara H Olson; Harvey A Risch; Wei Zheng; Demetrius Albanes; William R Bamlet; Christine D Berg; Marie-Christine Boutron-Ruault; Julie E Buring; Paige M Bracci; Federico Canzian; Sandra Clipp; Michelle Cotterchio; Mariza de Andrade; Eric J Duell; J Michael Gaziano; Edward L Giovannucci; Michael Goggins; Göran Hallmans; Susan E Hankinson; Manal Hassan; Barbara Howard; David J Hunter; Amy Hutchinson; Mazda Jenab; Rudolf Kaaks; Charles Kooperberg; Vittorio Krogh; Robert C Kurtz; Shannon M Lynch; Robert R McWilliams; Julie B Mendelsohn; Dominique S Michaud; Hemang Parikh; Alpa V Patel; Petra H M Peeters; Aleksandar Rajkovic; Elio Riboli; Laudina Rodriguez; Daniela Seminara; Xiao-Ou Shu; Gilles Thomas; Anne Tjønneland; Geoffrey S Tobias; Dimitrios Trichopoulos; Stephen K Van Den Eeden; Jarmo Virtamo; Jean Wactawski-Wende; Zhaoming Wang; Brian M Wolpin; Herbert Yu; Kai Yu; Anne Zeleniuch-Jacquotte; Joseph F Fraumeni; Robert N Hoover; Patricia Hartge; Stephen J Chanock
Journal:  Nat Genet       Date:  2010-01-24       Impact factor: 38.330

7.  Genotype imputation with thousands of genomes.

Authors:  Bryan Howie; Jonathan Marchini; Matthew Stephens
Journal:  G3 (Bethesda)       Date:  2011-11-01       Impact factor: 3.154

8.  Functional characterization of CLPTM1L as a lung cancer risk candidate gene in the 5p15.33 locus.

Authors:  Michael A James; Weidong Wen; Yian Wang; Lauren A Byers; John V Heymach; Kevin R Coombes; Luc Girard; John Minna; Ming You
Journal:  PLoS One       Date:  2012-06-04       Impact factor: 3.240

Review 9.  PVT1: a rising star among oncogenic long noncoding RNAs.

Authors:  Teresa Colombo; Lorenzo Farina; Giuseppe Macino; Paola Paci
Journal:  Biomed Res Int       Date:  2015-03-26       Impact factor: 3.411

10.  Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia.

Authors:  Sonja I Berndt; Christine F Skibola; Vijai Joseph; Nicola J Camp; Alexandra Nieters; Zhaoming Wang; Wendy Cozen; Alain Monnereau; Sophia S Wang; Rachel S Kelly; Qing Lan; Lauren R Teras; Nilanjan Chatterjee; Charles C Chung; Meredith Yeager; Angela R Brooks-Wilson; Patricia Hartge; Mark P Purdue; Brenda M Birmann; Bruce K Armstrong; Pierluigi Cocco; Yawei Zhang; Gianluca Severi; Anne Zeleniuch-Jacquotte; Charles Lawrence; Laurie Burdette; Jeffrey Yuenger; Amy Hutchinson; Kevin B Jacobs; Timothy G Call; Tait D Shanafelt; Anne J Novak; Neil E Kay; Mark Liebow; Alice H Wang; Karin E Smedby; Hans-Olov Adami; Mads Melbye; Bengt Glimelius; Ellen T Chang; Martha Glenn; Karen Curtin; Lisa A Cannon-Albright; Brandt Jones; W Ryan Diver; Brian K Link; George J Weiner; Lucia Conde; Paige M Bracci; Jacques Riby; Elizabeth A Holly; Martyn T Smith; Rebecca D Jackson; Lesley F Tinker; Yolanda Benavente; Nikolaus Becker; Paolo Boffetta; Paul Brennan; Lenka Foretova; Marc Maynadie; James McKay; Anthony Staines; Kari G Rabe; Sara J Achenbach; Celine M Vachon; Lynn R Goldin; Sara S Strom; Mark C Lanasa; Logan G Spector; Jose F Leis; Julie M Cunningham; J Brice Weinberg; Vicki A Morrison; Neil E Caporaso; Aaron D Norman; Martha S Linet; Anneclaire J De Roos; Lindsay M Morton; Richard K Severson; Elio Riboli; Paolo Vineis; Rudolph Kaaks; Dimitrios Trichopoulos; Giovanna Masala; Elisabete Weiderpass; María-Dolores Chirlaque; Roel C H Vermeulen; Ruth C Travis; Graham G Giles; Demetrius Albanes; Jarmo Virtamo; Stephanie Weinstein; Jacqueline Clavel; Tongzhang Zheng; Theodore R Holford; Kenneth Offit; Andrew Zelenetz; Robert J Klein; John J Spinelli; Kimberly A Bertrand; Francine Laden; Edward Giovannucci; Peter Kraft; Anne Kricker; Jenny Turner; Claire M Vajdic; Maria Grazia Ennas; Giovanni M Ferri; Lucia Miligi; Liming Liang; Joshua Sampson; Simon Crouch; Ju-Hyun Park; Kari E North; Angela Cox; John A Snowden; Josh Wright; Angel Carracedo; Carlos Lopez-Otin; Silvia Bea; Itziar Salaverria; David Martin-Garcia; Elias Campo; Joseph F Fraumeni; Silvia de Sanjose; Henrik Hjalgrim; James R Cerhan; Stephen J Chanock; Nathaniel Rothman; Susan L Slager
Journal:  Nat Genet       Date:  2013-06-16       Impact factor: 41.307

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  41 in total

1.  Genetic and Circulating Biomarker Data Improve Risk Prediction for Pancreatic Cancer in the General Population.

Authors:  Brian M Wolpin; Peter Kraft; Jihye Kim; Chen Yuan; Ana Babic; Ying Bao; Clary B Clish; Michael N Pollak; Laufey T Amundadottir; Alison P Klein; Rachael Z Stolzenberg-Solomon; Pari V Pandharipande; Lauren K Brais; Marisa W Welch; Kimmie Ng; Edward L Giovannucci; Howard D Sesso; JoAnn E Manson; Meir J Stampfer; Charles S Fuchs
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-04-22       Impact factor: 4.254

Review 2.  Genome-Wide Association Studies of Cancer in Diverse Populations.

Authors:  Sungshim L Park; Iona Cheng; Christopher A Haiman
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2017-06-21       Impact factor: 4.254

Review 3.  Inherited pancreatic cancer.

Authors:  Fei Chen; Nicholas J Roberts; Alison P Klein
Journal:  Chin Clin Oncol       Date:  2017-12

4.  Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer.

Authors:  Naomi Walsh; Han Zhang; Paula L Hyland; Qi Yang; Evelina Mocci; Mingfeng Zhang; Erica J Childs; Irene Collins; Zhaoming Wang; Alan A Arslan; Laura Beane-Freeman; Paige M Bracci; Paul Brennan; Federico Canzian; Eric J Duell; Steven Gallinger; Graham G Giles; Michael Goggins; Gary E Goodman; Phyllis J Goodman; Rayjean J Hung; Charles Kooperberg; Robert C Kurtz; Núria Malats; Loic LeMarchand; Rachel E Neale; Sara H Olson; Ghislaine Scelo; Xiao O Shu; Stephen K Van Den Eeden; Kala Visvanathan; Emily White; Wei Zheng; Demetrius Albanes; Gabriella Andreotti; Ana Babic; William R Bamlet; Sonja I Berndt; Ayelet Borgida; Marie-Christine Boutron-Ruault; Lauren Brais; Paul Brennan; Bas Bueno-de-Mesquita; Julie Buring; Kari G Chaffee; Stephen Chanock; Sean Cleary; Michelle Cotterchio; Lenka Foretova; Charles Fuchs; J Michael M Gaziano; Edward Giovannucci; Michael Goggins; Thilo Hackert; Christopher Haiman; Patricia Hartge; Manal Hasan; Kathy J Helzlsouer; Joseph Herman; Ivana Holcatova; Elizabeth A Holly; Robert Hoover; Rayjean J Hung; Vladimir Janout; Eric A Klein; Robert C Kurtz; Daniel Laheru; I-Min Lee; Lingeng Lu; Núria Malats; Satu Mannisto; Roger L Milne; Ann L Oberg; Irene Orlow; Alpa V Patel; Ulrike Peters; Miquel Porta; Francisco X Real; Nathaniel Rothman; Howard D Sesso; Gianluca Severi; Debra Silverman; Oliver Strobel; Malin Sund; Mark D Thornquist; Geoffrey S Tobias; Jean Wactawski-Wende; Nick Wareham; Elisabete Weiderpass; Nicolas Wentzensen; William Wheeler; Herbert Yu; Anne Zeleniuch-Jacquotte; Peter Kraft; Donghui Li; Eric J Jacobs; Gloria M Petersen; Brian M Wolpin; Harvey A Risch; Laufey T Amundadottir; Kai Yu; Alison P Klein; Rachael Z Stolzenberg-Solomon
Journal:  J Natl Cancer Inst       Date:  2019-06-01       Impact factor: 13.506

Review 5.  Racial Disparity in Gastrointestinal Cancer Risk.

Authors:  Hassan Ashktorab; Sonia S Kupfer; Hassan Brim; John M Carethers
Journal:  Gastroenterology       Date:  2017-08-12       Impact factor: 22.682

6.  Impact of Sixteen Established Pancreatic Cancer Susceptibility Loci in American Jews.

Authors:  Samantha A Streicher; Alison P Klein; Sara H Olson; Laufey T Amundadottir; Andrew T DeWan; Hongyu Zhao; Harvey A Risch
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2017-07-28       Impact factor: 4.254

7.  Genome-Wide Association Study Data Reveal Genetic Susceptibility to Chronic Inflammatory Intestinal Diseases and Pancreatic Ductal Adenocarcinoma Risk.

Authors:  Fangcheng Yuan; Rayjean J Hung; Naomi Walsh; Han Zhang; Elizabeth A Platz; William Wheeler; Lei Song; Alan A Arslan; Laura E Beane Freeman; Paige Bracci; Federico Canzian; Mengmeng Du; Steven Gallinger; Graham G Giles; Phyllis J Goodman; Charles Kooperberg; Loic Le Marchand; Rachel E Neale; Jonas Rosendahl; Ghislaine Scelo; Xiao-Ou Shu; Kala Visvanathan; Emily White; Wei Zheng; Demetrius Albanes; Pilar Amiano; Gabriella Andreotti; Ana Babic; William R Bamlet; Sonja I Berndt; Paul Brennan; Bas Bueno-de-Mesquita; Julie E Buring; Peter T Campbell; Stephen J Chanock; Charles S Fuchs; J Michael Gaziano; Michael G Goggins; Thilo Hackert; Patricia Hartge; Manal M Hassan; Elizabeth A Holly; Robert N Hoover; Verena Katzke; Holger Kirsten; Robert C Kurtz; I-Min Lee; Nuria Malats; Roger L Milne; Neil Murphy; Kimmie Ng; Ann L Oberg; Miquel Porta; Kari G Rabe; Francisco X Real; Nathaniel Rothman; Howard D Sesso; Debra T Silverman; Ian M Thompson; Jean Wactawski-Wende; Xiaoliang Wang; Nicolas Wentzensen; Lynne R Wilkens; Herbert Yu; Anne Zeleniuch-Jacquotte; Jianxin Shi; Eric J Duell; Laufey T Amundadottir; Donghui Li; Gloria M Petersen; Brian M Wolpin; Harvey A Risch; Kai Yu; Alison P Klein; Rachael Stolzenberg-Solomon
Journal:  Cancer Res       Date:  2020-07-08       Impact factor: 12.701

8.  A Transcriptome-Wide Association Study Identifies Candidate Susceptibility Genes for Pancreatic Cancer Risk.

Authors:  Duo Liu; Dan Zhou; Yanfa Sun; Jingjing Zhu; Dalia Ghoneim; Chong Wu; Qizhi Yao; Eric R Gamazon; Nancy J Cox; Lang Wu
Journal:  Cancer Res       Date:  2020-09-09       Impact factor: 12.701

9.  Analysis of Heritability and Genetic Architecture of Pancreatic Cancer: A PanC4 Study.

Authors:  Fei Chen; Erica J Childs; Evelina Mocci; Paige Bracci; Steven Gallinger; Donghui Li; Rachel E Neale; Sara H Olson; Ghislaine Scelo; William R Bamlet; Amanda L Blackford; Michael Borges; Paul Brennan; Kari G Chaffee; Priya Duggal; Manal J Hassan; Elizabeth A Holly; Rayjean J Hung; Michael G Goggins; Robert C Kurtz; Ann L Oberg; Irene Orlow; Herbert Yu; Gloria M Petersen; Harvey A Risch; Alison P Klein
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-04-23       Impact factor: 4.254

10.  A Transcriptome-Wide Association Study Identifies Novel Candidate Susceptibility Genes for Pancreatic Cancer.

Authors:  Jun Zhong; Ashley Jermusyk; Lang Wu; Jason W Hoskins; Irene Collins; Evelina Mocci; Mingfeng Zhang; Lei Song; Charles C Chung; Tongwu Zhang; Wenming Xiao; Demetrius Albanes; Gabriella Andreotti; Alan A Arslan; Ana Babic; William R Bamlet; Laura Beane-Freeman; Sonja Berndt; Ayelet Borgida; Paige M Bracci; Lauren Brais; Paul Brennan; Bas Bueno-de-Mesquita; Julie Buring; Federico Canzian; Erica J Childs; Michelle Cotterchio; Mengmeng Du; Eric J Duell; Charles Fuchs; Steven Gallinger; J Michael Gaziano; Graham G Giles; Edward Giovannucci; Michael Goggins; Gary E Goodman; Phyllis J Goodman; Christopher Haiman; Patricia Hartge; Manal Hasan; Kathy J Helzlsouer; Elizabeth A Holly; Eric A Klein; Manolis Kogevinas; Robert J Kurtz; Loic LeMarchand; Núria Malats; Satu Männistö; Roger Milne; Rachel E Neale; Kimmie Ng; Ofure Obazee; Ann L Oberg; Irene Orlow; Alpa V Patel; Ulrike Peters; Miquel Porta; Nathaniel Rothman; Ghislaine Scelo; Howard D Sesso; Gianluca Severi; Sabina Sieri; Debra Silverman; Malin Sund; Anne Tjønneland; Mark D Thornquist; Geoffrey S Tobias; Antonia Trichopoulou; Stephen K Van Den Eeden; Kala Visvanathan; Jean Wactawski-Wende; Nicolas Wentzensen; Emily White; Herbert Yu; Chen Yuan; Anne Zeleniuch-Jacquotte; Robert Hoover; Kevin Brown; Charles Kooperberg; Harvey A Risch; Eric J Jacobs; Donghui Li; Kai Yu; Xiao-Ou Shu; Stephen J Chanock; Brian M Wolpin; Rachael Z Stolzenberg-Solomon; Nilanjan Chatterjee; Alison P Klein; Jill P Smith; Peter Kraft; Jianxin Shi; Gloria M Petersen; Wei Zheng; Laufey T Amundadottir
Journal:  J Natl Cancer Inst       Date:  2020-10-01       Impact factor: 13.506

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