Laufey T. Ámundadóttir

We performed integrated genomic, transcriptomic, and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1, and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1, and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine.

We conducted a two-stage genome-wide association study of pancreatic cancer, a cancer with one of the lowest survival rates worldwide. We genotyped 558,542 SNPs in 1,896 individuals with pancreatic cancer and 1,939 controls drawn from 12 prospective cohorts plus one hospital-based case-control study. We conducted a combined analysis of these groups plus an additional 2,457 affected individuals and 2,654 controls from eight case-control studies, adjusting for study, sex, ancestry and five principal components. We identified an association between a locus on 9q34 and pancreatic cancer marked by the SNP rs505922 (combined P = 5.37 x 10(-8); multiplicative per-allele odds ratio 1.20; 95% confidence interval 1.12-1.28). This SNP maps to the first intron of the ABO blood group gene. Our results are consistent with earlier epidemiologic evidence suggesting that people with blood group O may have a lower risk of pancreatic cancer than those with groups A or B.

We conducted a genome-wide association study of pancreatic cancer in 3,851 affected individuals (cases) and 3,934 unaffected controls drawn from 12 prospective cohort studies and 8 case-control studies. Based on a logistic regression model for genotype trend effect that was adjusted for study, age, sex, self-described ancestry and five principal components, we identified eight SNPs that map to three loci on chromosomes 13q22.1, 1q32.1 and 5p15.33. Two correlated SNPs, rs9543325 (P = 3.27 x 10(-11), per-allele odds ratio (OR) 1.26, 95% CI 1.18-1.35) and rs9564966 (P = 5.86 x 10(-8), per-allele OR 1.21, 95% CI 1.13-1.30), map to a nongenic region on chromosome 13q22.1. Five SNPs on 1q32.1 map to NR5A2, and the strongest signal was at rs3790844 (P = 2.45 x 10(-10), per-allele OR 0.77, 95% CI 0.71-0.84). A single SNP, rs401681 (P = 3.66 x 10(-7), per-allele OR 1.19, 95% CI 1.11-1.27), maps to the CLPTM1L-TERT locus on 5p15.33, which is associated with multiple cancers. Our study has identified common susceptibility loci for pancreatic cancer that warrant follow-up studies.

The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation.To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases.Genomewide association studies (GWAS) published up to January 15, 2015.GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available.Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population.Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation.Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]).It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

Obesity has been proposed as a risk factor for pancreatic cancer.Pooled data were analyzed from the National Cancer Institute Pancreatic Cancer Cohort Consortium (PanScan) to study the association between prediagnostic anthropometric measures and risk of pancreatic cancer. PanScan applied a nested case-control study design and included 2170 cases and 2209 control subjects. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression for cohort-specific quartiles of body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]), weight, height, waist circumference, and waist to hip ratio as well as conventional BMI categories (underweight, <18.5; normal weight, 18.5-24.9; overweight, 25.0-29.9; obese, 30.0-34.9; and severely obese, > or = 35.0). Models were adjusted for potential confounders.In all of the participants, a positive association between increasing BMI and risk of pancreatic cancer was observed (adjusted OR for the highest vs lowest BMI quartile, 1.33; 95% CI, 1.12-1.58; P(trend) < .001). In men, the adjusted OR for pancreatic cancer for the highest vs lowest quartile of BMI was 1.33 (95% CI, 1.04-1.69; P(trend) < .03), and in women it was 1.34 (95% CI, 1.05-1.70; P(trend) = .01). Increased waist to hip ratio was associated with increased risk of pancreatic cancer in women (adjusted OR for the highest vs lowest quartile, 1.87; 95% CI, 1.31-2.69; P(trend) = .003) but less so in men.These findings provide strong support for a positive association between BMI and pancreatic cancer risk. In addition, centralized fat distribution may increase pancreatic cancer risk, especially in women.

Smoking is an established risk factor for pancreatic cancer; however, detailed examination of the association of smoking intensity, smoking duration, and cumulative smoking dose with pancreatic cancer is limited. The authors analyzed pooled data from the international Pancreatic Cancer Cohort Consortium nested case-control study (1,481 cases, 1,539 controls). Odds ratios and 95% confidence intervals were calculated by using unconditional logistic regression. Smoking intensity effects were examined with an excess odds ratio model that was linear in pack-years and exponential in cigarettes smoked per day and its square. When compared with never smokers, current smokers had a significantly elevated risk (odds ratio (OR) = 1.77, 95% confidence interval (CI): 1.38, 2.26). Risk increased significantly with greater intensity (> or =30 cigarettes/day: OR = 1.75, 95% CI: 1.27, 2.42), duration (> or =50 years: OR = 2.13, 95% CI: 1.25, 3.62), and cumulative smoking dose (> or =40 pack-years: OR = 1.78, 95% CI: 1.35, 2.34). Risk more than 15 years after smoking cessation was similar to that for never smokers. Estimates of excess odds ratio per pack-year declined with increasing intensity, suggesting greater risk for total exposure delivered at lower intensity for longer duration than for higher intensity for shorter duration. This finding and the decline in risk after smoking cessation suggest that smoking has a late-stage effect on pancreatic carcinogenesis.

Alison Klein and colleagues report a genome-wide meta-analysis to identify loci associated with pancreatic cancer risk. They identify associated variants at 17q25.1, 3q29, 7p13 and 2p13.3. Pancreatic cancer is the fourth leading cause of cancer death in the developed world1. Both inherited high-penetrance mutations in BRCA2 (ref. 2), ATM3, PALB2 (ref. 4), BRCA1 (ref. 5), STK11 (ref. 6), CDKN2A7 and mismatch-repair genes8 and low-penetrance loci are associated with increased risk9,10,11,12. 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 Chinese12. We replicated previously reported associations at 9q34.2 (ABO)9, 13q22.1 (KLF5)10, 5p15.33 (TERT and CLPTM1)10,11, 13q12.2 (PDX1)11, 1q32.1 (NR5A2)10, 7q32.3 (LINC-PINT)11, 16q23.1 (BCAR1)11 and 22q12.1 (ZNRF3)11. Our study identifies new loci associated with pancreatic cancer risk.

Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.

The contribution of low-penetrant susceptibility variants to cancer is not clear. With the aim of searching for genetic factors that contribute to cancer at one or more sites in the body, we have analyzed familial aggregation of cancer in extended families based on all cancer cases diagnosed in Iceland over almost half a century.We have estimated risk ratios (RRs) of cancer for first- and up to fifth-degree relatives both within and between all types of cancers diagnosed in Iceland from 1955 to 2002 by linking patient information from the Icelandic Cancer Registry to an extensive genealogical database, containing all living Icelanders and most of their ancestors since the settlement of Iceland. We evaluated the significance of the familial clustering for each relationship separately, all relationships combined (first- to fifth-degree relatives) and for close (first- and second-degree) and distant (third- to fifth-degree) relatives. Most cancer sites demonstrate a significantly increased RR for the same cancer, beyond the nuclear family. Significantly increased familial clustering between different cancer sites is also documented in both close and distant relatives. Some of these associations have been suggested previously but others not.We conclude that genetic factors are involved in the etiology of many cancers and that these factors are in some cases shared by different cancer sites. However, a significantly increased RR conferred upon mates of patients with cancer at some sites indicates that shared environment or nonrandom mating for certain risk factors also play a role in the familial clustering of cancer. Our results indicate that cancer is a complex, often non-site-specific disease for which increased risk extends beyond the nuclear family.

Meredith Yeager and colleagues with the Cancer Genetics Markers of Susceptibility (CGEMS) initiative report a new association to prostate cancer at chromosome 8q24. This defines a new locus, region 4, which shows association to prostate cancer susceptibility independent of previously reported associations at 8q24. We report a genome-wide association study in 10,286 cases and 9,135 controls of European ancestry in the Cancer Genetic Markers of Susceptibility (CGEMS) initiative. We identify a new association with prostate cancer risk on chromosome 8q24 (rs620861, P = 1.3 × 10−10, heterozygote OR = 1.17, 95% CI 1.10–1.24; homozygote OR = 1.33, 95% CI 1.21–1.45). This defines a new locus associated with prostate cancer susceptibility on 8q24.

Abstract A recent genome-wide association study (PanScan) identified significant associations at the ABO gene locus with risk of pancreatic cancer, but the influence of specific ABO genotypes remains unknown. We determined ABO genotypes (OO, AO, AA, AB, BO, and BB) in 1,534 cases and 1,583 controls from 12 prospective cohorts in PanScan, grouping participants by genotype-derived serologic blood type (O, A, AB, and B). Adjusted odds ratios (ORs) for pancreatic cancer by ABO alleles were calculated using logistic regression. Compared with blood type O, the ORs for pancreatic cancer in subjects with types A, AB, and B were 1.38 [95% confidence interval (95% CI), 1.18–1.62], 1.47 (95% CI, 1.07–2.02), and 1.53 (95% CI, 1.21–1.92), respectively. The incidence rates for blood types O, A, AB, and B were 28.9, 39.9, 41.8, and 44.5 cases per 100,000 subjects per year. An increase in risk was noted with the addition of each non-O allele. Compared with OO genotype, subjects with AO and AA genotype had ORs of 1.33 (95% CI, 1.13–1.58) and 1.61 (95% CI, 1.22–2.18), whereas subjects with BO and BB genotypes had ORs of 1.45 (95% CI, 1.14–1.85) and 2.42 (1.28–4.57). The population attributable fraction for non-O blood type was 19.5%. In a joint model with smoking, current smokers with non-O blood type had an adjusted OR of 2.68 (95% CI, 2.03–3.54) compared with nonsmokers of blood type O. We concluded that ABO genotypes were significantly associated with pancreatic cancer risk. Cancer Res; 70(3); 1015–23

The activity of the kinase Aurora-A (Aur-A) peaks during mitosis and depends on phosphorylation by one or more unknown kinases. Mitotic phosphorylation sites were mapped by mass spec sequencing of recombinant Aur-A protein that had been activated by incubation in extracts of metaphase-arrested Xenopus eggs. Three sites were identified: serine 53 (Ser-53), threonine 295 (Thr-295), and serine 349 (Ser-349), which are equivalent to Ser-51, Thr-288, and Ser-342, respectively, in human Aur-A. To ask how phosphorylation of these residues might affect kinase activity, each was mutated to either alanine or aspartic acid, and the recombinant proteins were then tested for their ability to be activated by M phase extract. Mutation of Thr-295, which resides in the activation loop of the kinase, to either alanine or aspartic acid abolished activity. The S349A mutant had slightly reduced activity, indicating that phosphorylation is not required for activity. The S349D mutation completely blocked activation, suggesting that Ser-349 is important for either the structure or regulation of Aur-A. Finally, like human Aur-A, overexpression of Xenopus Aur-A transformed NIH 3T3 cells and led to tumors in nude mice. These results provide further evidence that Xenopus Aur-A is a functional ortholog of human Aur-A and, along with the recently described crystal structure of human Aur-A, should help in future studies of the mechanisms that regulate Aur-A activity during mitotic progression.

We have identified the Drosophila transmembrane molecule kekkon 1 (kek1) as an inhibitor of the epidermal growth factor receptor (EGFR) and demonstrate that it acts in a negative feedback loop to modulate the activity of the EGFR tyrosine kinase. During oogenesis, kek1 is expressed in response to the Gurken/EGFR signaling pathway, and loss of kek1 activity is associated with an increase in EGFR signaling. Consistent with our loss-of-function studies, we demonstrate that ectopic overexpression of kek1 mimics a loss of EGFR activity. We show that the extracellular and transmembrane domains of Kek1 can inhibit and physically associate with the EGFR, suggesting potential models for this inhibitory mechanism.

A family history of pancreatic cancer has consistently been associated with increased risk of pancreatic cancer. However, uncertainty remains about the strength of this association. Results from previous studies suggest a family history of select cancers (i.e., ovarian, breast and colorectal) could also be associated, although not as strongly, with increased risk of pancreatic cancer. We examined the association between a family history of 5 types of cancer (pancreas, prostate, ovarian, breast and colorectal) and risk of pancreatic cancer using data from a collaborative nested case-control study conducted by the Pancreatic Cancer Cohort Consortium. Cases and controls were from cohort studies from the United States, Europe and China, and a case-control study from the Mayo Clinic. Analyses of family history of pancreatic cancer included 1,183 cases and 1,205 controls. A family history of pancreatic cancer in a parent, sibling or child was associated with increased risk of pancreatic cancer [multivariate-adjusted odds ratios (ORs) = 1.76, 95% confidence interval (CI) = 1.19-2.61]. A family history of prostate cancer was also associated with increased risk (OR = 1.45, 95% CI = 1.12-1.89). There were no statistically significant associations with a family history of ovarian cancer (OR = 0.82, 95% CI = 0.52-1.31), breast cancer (OR = 1.21, 95% CI = 0.97-1.51) or colorectal cancer (OR = 1.17, 95% CI = 0.93-1.47). Our results confirm a moderate sized association between a family history of pancreatic cancer and risk of pancreatic cancer and also provide evidence for an association with a family history of prostate cancer worth further study.

The genetic regulation of the human epigenome is not fully appreciated. Here we describe the effects of genetic variants on the DNA methylome in human lung based on methylation-quantitative trait loci (meQTL) analyses. We report 34,304 cis- and 585 trans-meQTLs, a genetic–epigenetic interaction of surprising magnitude, including a regulatory hotspot. These findings are replicated in both breast and kidney tissues and show distinct patterns: cis-meQTLs mostly localize to CpG sites outside of genes, promoters and CpG islands (CGIs), while trans-meQTLs are over-represented in promoter CGIs. meQTL SNPs are enriched in CTCF-binding sites, DNaseI hypersensitivity regions and histone marks. Importantly, four of the five established lung cancer risk loci in European ancestry are cis-meQTLs and, in aggregate, cis-meQTLs are enriched for lung cancer risk in a genome-wide analysis of 11,587 subjects. Thus, inherited genetic variation may affect lung carcinogenesis by regulating the human methylome. The effects of genetic variation on DNA methylation patterns are poorly understood. Here, Shi et al.systematically map methylation-quantitative trait loci in lung, breast and kidney tissue to reveal the impact of inherited variation on the human methylome, which also affects cancer risk.

We developed an absolute risk model to identify individuals in the general population at elevated risk of pancreatic cancer.Using data on 3,349 cases and 3,654 controls from the PanScan Consortium, we developed a relative risk model for men and women of European ancestry based on non-genetic and genetic risk factors for pancreatic cancer. We estimated absolute risks based on these relative risks and population incidence rates.Our risk model included current smoking (multivariable adjusted odds ratio (OR) and 95% confidence interval: 2.20 [1.84-2.62]), heavy alcohol use (>3 drinks/day) (OR: 1.45 [1.19-1.76]), obesity (body mass index >30 kg/m(2)) (OR: 1.26 [1.09-1.45]), diabetes >3 years (nested case-control OR: 1.57 [1.13-2.18], case-control OR: 1.80 [1.40-2.32]), family history of pancreatic cancer (OR: 1.60 [1.20-2.12]), non-O ABO genotype (AO vs. OO genotype) (OR: 1.23 [1.10-1.37]) to (BB vs. OO genotype) (OR 1.58 [0.97-2.59]), rs3790844(chr1q32.1) (OR: 1.29 [1.19-1.40]), rs401681(5p15.33) (OR: 1.18 [1.10-1.26]) and rs9543325(13q22.1) (OR: 1.27 [1.18-1.36]). The areas under the ROC curve for risk models including only non-genetic factors, only genetic factors, and both non-genetic and genetic factors were 58%, 57% and 61%, respectively. We estimate that fewer than 3/1,000 U.S. non-Hispanic whites have more than a 5% predicted lifetime absolute risk.Although absolute risk modeling using established risk factors may help to identify a group of individuals at higher than average risk of pancreatic cancer, the immediate clinical utility of our model is limited. However, a risk model can increase awareness of the various risk factors for pancreatic cancer, including modifiable behaviors.

Diabetes is a suspected risk factor for pancreatic cancer, but questions remain about whether it is a risk factor or a result of the disease. This study prospectively examined the association between diabetes and the risk of pancreatic adenocarcinoma in pooled data from the NCI pancreatic cancer cohort consortium (PanScan).The pooled data included 1,621 pancreatic adenocarcinoma cases and 1,719 matched controls from twelve cohorts using a nested case-control study design. Subjects who were diagnosed with diabetes near the time (<2 years) of pancreatic cancer diagnosis were excluded from all analyses. All analyses were adjusted for age, race, gender, study, alcohol use, smoking, BMI, and family history of pancreatic cancer.Self-reported diabetes was associated with a forty percent increased risk of pancreatic cancer (OR = 1.40, 95 % CI: 1.07, 1.84). The association differed by duration of diabetes; risk was highest for those with a duration of 2-8 years (OR = 1.79, 95 % CI: 1.25, 2.55); there was no association for those with 9+ years of diabetes (OR = 1.02, 95 % CI: 0.68, 1.52).These findings provide support for a relationship between diabetes and pancreatic cancer risk. The absence of association in those with the longest duration of diabetes may reflect hypoinsulinemia and warrants further investigation.

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value=5.5 × 10⁻³¹) and is higher in men (p value=0.002) but lower in participants of African ancestry (p value=0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.

Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25–50% increase in the prediction R2) for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10−5). Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure.

Chronic inflammation increases the risk of developing one of several types of cancer. Inflammatory responses are currently thought to be controlled by mechanisms that rely on transcriptional networks that are distinct from those involved in cell differentiation. The orphan nuclear receptor NR5A2 participates in a wide variety of processes, including cholesterol and glucose metabolism in the liver, resolution of endoplasmic reticulum stress, intestinal glucocorticoid production, pancreatic development and acinar differentiation. In genome-wide association studies, single nucleotide polymorphisms in the vicinity of NR5A2 have previously been associated with the risk of pancreatic adenocarcinoma. In mice, Nr5a2 heterozygosity sensitizes the pancreas to damage, impairs regeneration and cooperates with mutant Kras in tumour progression. Here, using a global transcriptomic analysis, we describe an epithelial-cell-autonomous basal pre-inflammatory state in the pancreas of Nr5a2+/- mice that is reminiscent of the early stages of pancreatitis-induced inflammation and is conserved in histologically normal human pancreases with reduced expression of NR5A2 mRNA. In Nr5a2+/-mice, NR5A2 undergoes a marked transcriptional switch, relocating from differentiation-specific to inflammatory genes and thereby promoting gene transcription that is dependent on the AP-1 transcription factor. Pancreatic deletion of Jun rescues the pre-inflammatory phenotype, as well as binding of NR5A2 to inflammatory gene promoters and the defective regenerative response to damage. These findings support the notion that, in the pancreas, the transcriptional networks involved in differentiation-specific functions also suppress inflammatory programmes. Under conditions of genetic or environmental constraint, these networks can be subverted to foster inflammation.

Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case–control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways ( P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis ( P = 2.0 × 10 −6 , 1.6 × 10 −5 , 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways ( NR5A2 , ABO and SHH ), the pancreatic development pathway remained significant ( P = 8.3 × 10 −5 ), whereas the others did not. The most significant genes ( P < 0.01) in the five pathways were NR5A2 , HNF1A , HNF4G and PDX1 for pancreatic development; ABO for H.pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer.

Most men diagnosed with prostate cancer will experience indolent disease; hence, discovering genetic variants that distinguish aggressive from nonaggressive prostate cancer is of critical clinical importance for disease prevention and treatment. In a multistage, case-only genome-wide association study of 12,518 prostate cancer cases, we identify two loci associated with Gleason score, a pathological measure of disease aggressiveness: rs35148638 at 5q14.3 (RASA1, P=6.49 × 10−9) and rs78943174 at 3q26.31 (NAALADL2, P=4.18 × 10−8). In a stratified case–control analysis, the SNP at 5q14.3 appears specific for aggressive prostate cancer (P=8.85 × 10−5) with no association for nonaggressive prostate cancer compared with controls (P=0.57). The proximity of these loci to genes involved in vascular disease suggests potential biological mechanisms worthy of further investigation. Prostate cancer often does not progress to invasive disease and thus markers predicting the course of the disease progression are critical for optimal treatment choices. Here the authors show that variants at two genetic loci correlate with the aggressiveness of prostate cancer.

Abstract 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 &gt;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.

Although relatively rare, pancreatic tumors are highly lethal [1]. In the United States, an estimated 48,960 individuals will be diagnosed with pancreatic cancer and 40,560 will die from this disease in 2015 [1]. Globally, 337,872 new pancreatic cancer cases and 330,391 deaths were estimated in 2012 [2]. In contrast to most other cancers, mortality rates for pancreatic cancer are not improving; in the US, it is predicted to become the second leading cause of cancer related deaths by 2030 [3, 4]. The vast majority of tumors arise in the exocrine pancreas, with pancreatic ductal adenocarcinoma (PDAC) accounting for approximately 95% of tumors. Tumors arising in the endocrine pancreas (pancreatic neuroendocrine tumors) represent less than 5% of all pancreatic tumors [5]. Smoking, type 2 diabetes mellitus (T2D), obesity and pancreatitis are the most consistent epidemiological risk factors for pancreatic cancer [5]. Family history is also a risk factor for developing pancreatic cancer with odds ratios (OR) ranging from 1.7-2.3 for first-degree relatives in most studies, indicating that shared genetic factors may play a role in the etiology of this disease [6-9]. This review summarizes the current knowledge of germline pancreatic cancer risk variants with a special emphasis on common susceptibility alleles identified through Genome Wide Association Studies (GWAS).

Abstract Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.

Most expression quantitative trait locus (eQTL) studies to date have been performed in heterogeneous tissues as opposed to specific cell types. To better understand the cell-type–specific regulatory landscape of human melanocytes, which give rise to melanoma but account for &lt;5% of typical human skin biopsies, we performed an eQTL analysis in primary melanocyte cultures from 106 newborn males. We identified 597,335 cis -eQTL SNPs prior to linkage disequilibrium (LD) pruning and 4997 eGenes (FDR &lt; 0.05). Melanocyte eQTLs differed considerably from those identified in the 44 GTEx tissue types, including skin. Over a third of melanocyte eGenes, including key genes in melanin synthesis pathways, were unique to melanocytes compared to those of GTEx skin tissues or TCGA melanomas. The melanocyte data set also identified trans -eQTLs, including those connecting a pigmentation-associated functional SNP with four genes, likely through cis -regulation of IRF4 . Melanocyte eQTLs are enriched in cis -regulatory signatures found in melanocytes as well as in melanoma-associated variants identified through genome-wide association studies. Melanocyte eQTLs also colocalized with melanoma GWAS variants in five known loci. Finally, a transcriptome-wide association study using melanocyte eQTLs uncovered four novel susceptibility loci, where imputed expression levels of five genes ( ZFP90 , HEBP1 , MSC , CBWD1 , and RP11-383H13.1 ) were associated with melanoma at genome-wide significant P -values. Our data highlight the utility of lineage-specific eQTL resources for annotating GWAS findings, and present a robust database for genomic research of melanoma risk and melanocyte biology.

Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown.To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples).We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction.By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.

BackgroundThe causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain.MethodsUsing a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures.FindingsGenetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07–1.11]), esophageal squamous cell carcinoma (1.16 [1.06–1.26]), lung cancer (1.06 [1.03–1.08]) and basal cell carcinoma (1.05 [1.02–1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99–1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99–1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95–1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98–1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activity, mimicking a hypothetical intervention to reduce cancer risk, was associated (P < 0.0006) with increased risk of inflammatory bowel disease but not bleeding.InterpretationThe PUFA biosynthesis pathway may be an intervention target for prevention of colorectal cancer and esophageal squamous cell carcinoma but with potential for increased risk of inflammatory bowel disease.FundingCancer Resesrch UK (C52724/A20138, C18281/A19169). UK Medical Research Council (MR/P014054/1). National Institute for Health Research (NIHR202411). UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4). National Cancer Institute (R00 CA215360). National Institutes of Health (U01 CA164973, R01 CA60987, R01 CA72520, U01 CA74806, R01 CA55874, U01 CA164973 and U01 CA164973).

We have assessed five signal transduction pathways to determine the role each might play in the malignant transformation of mammary epithelium initiated by neu, heregulin/NDF, TGFα, v-Ha-ras and c-myc in transgenic mice. The study involves a molecular and pharmacologic assessment of Erk/MAP kinase, Jnk/SAP kinase, PI 3-kinase, protein kinase C, and the Src-related kinases Lck and Fyn. Our results indicate that oncogenes capable of transforming mammary gland epithelium activate and require specific signal transduction pathways. For example, mammary tumors initiated by neu, v-Ha-ras and c-myc have high levels of active Erk/MAP kinase and their anchorage independent growth is strongly inhibited by PD098059, an inhibitor of Mek/MAP kinase kinase. By contrast, Erk/MAP kinase activity is weak in tumors initiated by TFGα and heregulin/NDF and the corresponding cell lines are not growth inhibited by PD098059. Similarly, PI 3-kinase is strongly activated in neu, TGFα and heregulin/NDF initiated tumor cell lines, but not in c-myc or v-Ha-ras initiated tumor cell lines. The anchorage independent growth of all these tumor cell lines are, however, inhibited by the specific PI 3-kinase inhibitor LY294001. Further illustrating this oncogene-based specificity, PP1, a specific inhibitor of the Src-like kinases, Lck and Fyn, blocks anchorage-independent cell growth only in the TGFα initiated mammary tumor cell line. Taken together with additional observations, we conclude that certain oncogenes reliably require the recruitment/activation of specific signal transduction pathways. Such specific relationships between the initiating oncogene and a required pathway may reflect a direct activating effect or the parallel activation of a pathway that is a necessary oncogenic collaborator for transformation in the mammary gland. The work points to a molecular basis for targeting therapy when an initiating oncogene can be implicated; for example, because of amplification, increased expression, genetic alteration, or heritable characteristics.

Recently, genome-wide association studies have identified loci across a segment of chromosome 8q24 (128,100,000–128,700,000) associated with the risk of breast, colon and prostate cancers. At least three regions of 8q24 have been independently associated with prostate cancer risk; the most centromeric of which appears to be population specific. Haplotypes in two contiguous but independent loci, marked by rs6983267 and rs1447295, have been identified in the Cancer Genetic Markers of Susceptibility project ( http://cgems.cancer.gov ), which genotyped more than 5,000 prostate cancer cases and 5,000 controls of European origin. The rs6983267 locus is also strongly associated with colorectal cancer. To ascertain a comprehensive catalog of common single-nucleotide polymorphisms (SNPs) across the two regions, we conducted a resequence analysis of 136 kb (chr8: 128,473,000–128,609,802) using the Roche/454 next-generation sequencing technology in 39 prostate cancer cases and 40 controls of European origin. We have characterized a comprehensive catalog of common (MAF > 1%) SNPs within this region, including 442 novel SNPs and have determined the pattern of linkage disequilibrium across the region. Our study has generated a detailed map of genetic variation across the region, which should be useful for choosing SNPs for fine mapping of association signals in 8q24 and investigations of the functional consequences of select common variants.

Subjects with non-O ABO blood group alleles have increased risk of pancreatic cancer. Glycosyltransferase activity is greater for the A(1) versus A(2) variant, whereas O01 and O02 variants are nonfunctioning. We hypothesized: 1) A(1) allele would confer greater risk than A(2) allele, 2) protective effect of the O allele would be equivalent for O01 and O02 variants, 3) secretor phenotype would modify the association with risk.We determined ABO variants and secretor phenotype from single nucleotide polymorphisms in ABO and FUT2 genes in 1,533 cases and 1,582 controls from 12 prospective cohort studies. Adjusted odds ratios (OR) for pancreatic cancer were calculated using logistic regression.An increased risk was observed in participants with A(1) but not A(2) alleles. Compared with subjects with genotype O/O, genotypes A(2)/O, A(2)/A(1), A(1)/O, and A(1)/A(1) had ORs of 0.96 (95% CI, 0.72-1.26), 1.46 (95% CI, 0.98-2.17), 1.48 (95% CI, 1.23-1.78), and 1.71 (95% CI, 1.18-2.47). Risk was similar for O01 and O02 variant O alleles. Compared with O01/O01, the ORs for each additional allele of O02, A(1), and A(2) were 1.00 (95% CI, 0.87-1.14), 1.38 (95% CI, 1.20-1.58), and 0.96 (95% CI, 0.77-1.20); P, O01 versus O02 = 0.94, A(1) versus A(2) = 0.004. Secretor phenotype was not an effect modifier (P-interaction = 0.63).Among participants in a large prospective cohort consortium, ABO allele subtypes corresponding to increased glycosyltransferase activity were associated with increased pancreatic cancer risk.These data support the hypothesis that ABO glycosyltransferase activity influences pancreatic cancer risk rather than actions of other nearby genes on chromosome 9q34.

A small number of common susceptibility loci have been identified for pancreatic cancer, one of which is marked by rs401681 in the TERT-CLPTM1L gene region on chromosome 5p15.33. Because this region is characterized by low linkage disequilibrium, we sought to identify whether additional single nucleotide polymorphisms (SNPs) could be related to pancreatic cancer risk, independently of rs401681. We performed an in-depth analysis of genetic variability of the telomerase reverse transcriptase (TERT) and the telomerase RNA component (TERC) genes, in 5,550 subjects with pancreatic cancer and 7,585 controls from the PANcreatic Disease ReseArch (PANDoRA) and the PanScan consortia. We identified a significant association between a variant in TERT and pancreatic cancer risk (rs2853677, odds ratio = 0.85; 95% confidence interval = 0.80-0.90, p = 8.3 × 10(-8)). Additional analysis adjusting rs2853677 for rs401681 indicated that the two SNPs are independently associated with pancreatic cancer risk, as suggested by the low linkage disequilibrium between them (r(2) = 0.07, D' = 0.28). Three additional SNPs in TERT reached statistical significance after correction for multiple testing: rs2736100 (p = 3.0 × 10(-5) ), rs4583925 (p = 4.0 × 10(-5) ) and rs2735948 (p = 5.0 × 10(-5) ). In conclusion, we confirmed that the TERT locus is associated with pancreatic cancer risk, possibly through several independent variants.

Pancreatic cancer presents as advanced disease in >80% of patients; yet, appropriate ages to consider prevention and early detection strategies are poorly defined. We investigated age-specific associations and attributable risks of pancreatic cancer for established modifiable and non-modifiable risk factors.We included 167 483 participants from two prospective US cohort studies with 1190 incident cases of pancreatic cancer during >30 years of follow-up; 5107 pancreatic cancer cases and 8845 control participants of European ancestry from a completed multicenter genome-wide association study (GWAS); and 248 893 pancreatic cancer cases documented in the US Surveillance, Epidemiology, and End Results (SEER) Program. Across different age categories, we investigated cigarette smoking, obesity, diabetes, height, and non-O blood group in the prospective cohorts; weighted polygenic risk score of 22 previously identified single nucleotide polymorphisms in the GWAS; and male sex and black race in the SEER Program.In the prospective cohorts, all five risk factors were more strongly associated with pancreatic cancer risk among younger participants, with associations attenuated among those aged >70 years. The hazard ratios comparing participants with three to five risk factors with those with no risk factors were 9.24 [95% confidence interval (CI) 4.11-20.77] among those aged ≤60 years, 3.00 (95% CI 1.85-4.86) among those aged 61-70 years, and 1.46 (95% CI 1.10-1.94) among those aged >70 years (Pheterogeneity = 3×10-5). These factors together were related to 65.6%, 49.7%, and 17.2% of incident pancreatic cancers in these age groups, respectively. In the GWAS and the SEER Program, the associations with the polygenic risk score, male sex, and black race were all stronger among younger individuals (Pheterogeneity ≤0.01).Established risk factors are more strongly associated with earlier-onset pancreatic cancer, emphasizing the importance of age at initiation for cancer prevention and control programs targeting this highly lethal malignancy.

The etiology of RCC is incompletely understood and the inherited genetic contribution uncertain. Although there are rare mendelian forms of RCC stemming from inherited mutations, most cases are thought to be sporadic. We sought to determine the extent of familial aggregation among Icelandic RCC patients in general. Medical and pathologic records for all patients diagnosed with RCC in Iceland between 1955 and 1999 were reviewed. This included a total of 1,078 RCC cases, 660 males and 418 females. With the use of an extensive computerized database containing genealogic information on 630,000 people in Iceland during the past 11 centuries, several analyses were conducted to determine whether the patients were more related to each other than members drawn at random from the population. Patients with RCC were significantly more related to each other than were subjects in matched groups of controls. This relatedness extended beyond the nuclear family. RRs were significantly greater than 1.0 for siblings, parents and cousins of probands. RRs were 2-3 for first-degree relatives and 1.6 for third-degree relatives. The risk of RCC is significantly higher for members of the extended family of an affected individual, as well as the nuclear family. Our results indicate that germline mutations are significantly involved in what has been defined as sporadic RCC.

<h3>Background and objective</h3> Survival of patients with pancreatic adenocarcinoma is limited and few prognostic factors are known. We conducted a two-stage genome-wide association study (GWAS) to identify germline variants associated with survival in patients with pancreatic adenocarcinoma. <h3>Methods</h3> We analysed overall survival in relation to single nucleotide polymorphisms (SNPs) among 1005 patients from two large GWAS datasets, PanScan I and ChinaPC. Cox proportional hazards regression was used in an additive genetic model with adjustment for age, sex, clinical stage and the top four principal components of population stratification. The first stage included 642 cases of European ancestry (PanScan), from which the top SNPs (p≤10⁻⁵) were advanced to a joint analysis with 363 additional patients from China (ChinaPC). <h3>Results</h3> In the first stage of cases of European descent, the top-ranked loci were at chromosomes 11p15.4, 18p11.21 and 1p36.13, tagged by rs12362504 (p=1.63×10⁻⁷), rs981621 (p=1.65×10⁻⁷) and rs16861827 (p=3.75×10⁻⁷), respectively. 131 SNPs with p≤10⁻⁵ were advanced to a joint analysis with cases from the ChinaPC study. In the joint analysis, the top-ranked SNP was rs10500715 (minor allele frequency, 0.37; p=1.72×10⁻⁷) on chromosome 11p15.4, which is intronic to the <i>SET binding factor 2 (SBF2)</i> gene. The HR (95% CI) for death was 0.74 (0.66 to 0.84) in PanScan I, 0.79 (0.65 to 0.97) in ChinaPC and 0.76 (0.68 to 0.84) in the joint analysis. <h3>Conclusions</h3> Germline genetic variation in the <i>SBF2</i> locus was associated with overall survival in patients with pancreatic adenocarcinoma of European and Asian ancestry. This association should be investigated in additional large patient cohorts.

Genome-wide association studies (GWAS) of 10 different cancers have identified pleiotropic cancer predisposition loci across a region of chromosome 5p15.33 that includes the TERT and CLPTM1L genes. Of these, susceptibility alleles for pancreatic cancer have mapped to the CLPTM1L gene, thus prompting an investigation of the function of CLPTM1L in the pancreas. Immunofluorescence analysis indicated that CLPTM1L localized to the endoplasmic reticulum where it is likely embedded in the membrane, in accord with multiple predicted transmembrane domains. Overexpression of CLPTM1L enhanced growth of pancreatic cancer cells in vitro (1.3-1.5-fold; PDAY7 < 0.003) and in vivo (3.46-fold; PDAY68 = 0.039), suggesting a role in tumor growth; this effect was abrogated by deletion of two hydrophilic domains. Affinity purification followed by mass spectrometry identified an interaction between CLPTM1L and non-muscle myosin II (NMM-II), a protein involved in maintaining cell shape, migration, and cytokinesis. The two proteins colocalized in the cytoplasm and, after treatment with a DNA-damaging agent, at the centrosomes. Overexpression of CLPTM1L and depletion of NMM-II induced aneuploidy, indicating that CLPTM1L may interfere with normal NMM-II function in regulating cytokinesis. Immunohistochemical analysis revealed enhanced staining of CLPTM1L in human pancreatic ductal adenocarcinoma (n = 378) as compared with normal pancreatic tissue samples (n = 17; P = 1.7 × 10(-4)). Our results suggest that CLPTM1L functions as a growth-promoting gene in the pancreas and that overexpression may lead to an abrogation of normal cytokinesis, indicating that it should be considered as a plausible candidate gene that could explain the effect of pancreatic cancer susceptibility alleles on chr5p15.33.

Abstract Background: Many cancers share specific genetic risk factors, including both rare high-penetrance mutations and common SNPs identified through genome-wide association studies (GWAS). However, little is known about the overall shared heritability across cancers. Quantifying the extent to which two distinct cancers share genetic origin will give insights to shared biological mechanisms underlying cancer and inform design for future genetic association studies. Methods: In this study, we estimated the pair-wise genetic correlation between six cancer types (breast, colorectal, lung, ovarian, pancreatic, and prostate) using cancer-specific GWAS summary statistics data based on 66,958 case and 70,665 control subjects of European ancestry. We also estimated genetic correlations between cancers and 14 noncancer diseases and traits. Results: After adjusting for 15 pair-wise genetic correlation tests between cancers, we found significant (P &amp;lt; 0.003) genetic correlations between pancreatic and colorectal cancer (rg = 0.55, P = 0.003), lung and colorectal cancer (rg = 0.31, P = 0.001). We also found suggestive genetic correlations between lung and breast cancer (rg = 0.27, P = 0.009), and colorectal and breast cancer (rg = 0.22, P = 0.01). In contrast, we found no evidence that prostate cancer shared an appreciable proportion of heritability with other cancers. After adjusting for 84 tests studying genetic correlations between cancer types and other traits (Bonferroni-corrected P value: 0.0006), only the genetic correlation between lung cancer and smoking remained significant (rg = 0.41, P = 1.03 × 10−6). We also observed nominally significant genetic correlations between body mass index and all cancers except ovarian cancer. Conclusions: Our results highlight novel genetic correlations and lend support to previous observational studies that have observed links between cancers and risk factors. Impact: This study demonstrates modest genetic correlations between cancers; in particular, breast, colorectal, and lung cancer share some degree of genetic basis. Cancer Epidemiol Biomarkers Prev; 26(9); 1427–35. ©2017 AACR.

Pancreatic ductal adenocarcinoma (PDAC) is driven by the accumulation of somatic mutations, epigenetic modifications and changes in the micro-environment. New approaches to investigating disruptions of gene expression networks promise to uncover key regulators and pathways in carcinogenesis. We performed messenger RNA-sequencing in pancreatic normal (n = 10) and tumor (n = 8) derived tissue samples, as well as in pancreatic cancer cell lines (n = 9), to determine differential gene expression (DE) patterns. Sub-network enrichment analyses identified HNF1A as the regulator of the most significantly and consistently dysregulated expression sub-network in pancreatic tumor tissues and cells (median P = 7.56×10(-7), median rank = 1, range = 1-25). To explore the effects of HNF1A expression in pancreatic tumor-derived cells, we generated stable HNF1A-inducible clones in two pancreatic cancer cell lines (PANC-1 and MIA PaCa-2) and observed growth inhibition (5.3-fold, P = 4.5×10(-5) for MIA PaCa-2 clones; 7.2-fold, P = 2.2×10(-5) for PANC-1 clones), and a G0/G1 cell cycle arrest and apoptosis upon induction. These effects correlated with HNF1A-induced down-regulation of 51 of 84 cell cycle genes (e.g. E2F1, CDK2, CDK4, MCM2/3/4/5, SKP2 and CCND1), decreased expression of anti-apoptotic genes (e.g. BIRC2/5/6 and AKT) and increased expression of pro-apoptotic genes (e.g. CASP4/9/10 and APAF1). In light of the established role of HNF1A in the regulation of pancreatic development and homeostasis, our data suggest that it also functions as an important tumor suppressor in the pancreas.

Abstract Leptin is an adipokine involved in regulating energy balance, which has been identified as a potential biologic link in the development of obesity-associated cancers, such as pancreatic cancer. In this prospective, nested case–control study of 470 cases and 1,094 controls from five U.S. cohorts, we used conditional logistic regression to evaluate pancreatic cancer risk by prediagnostic plasma leptin, adjusting for race/ethnicity, diabetes, body mass index, physical activity, plasma C-peptide, adiponectin, and 25-hydroxyvitamin D. Because of known differences in leptin levels by gender, analyses were conducted separately for men and women. We also evaluated associations between 32 tagging SNPs in the leptin receptor (LEPR) gene and pancreatic cancer risk. Leptin levels were higher in female versus male control participants (median, 20.8 vs. 6.7 ng/mL; P &amp;lt; 0.0001). Among men, plasma leptin was positively associated with pancreatic cancer risk and those in the top quintile had a multivariable-adjusted OR of 3.02 [95% confidence interval (CI), 1.27–7.16; Ptrend = 0.02] compared with men in the bottom quintile. Among women, circulating leptin was not associated with pancreatic cancer risk (Ptrend = 0.21). Results were similar across cohorts (Pheterogeneity = 0.88 for two male cohorts and 0.35 for three female cohorts). In genetic analyses, rs10493380 in LEPR was associated with increased pancreatic cancer risk among women, with an OR per minor allele of 1.54 (95% CI, 1.18–2.02; multiple hypothesis-corrected P = 0.03). No SNPs were significantly associated with risk in men. In conclusion, higher prediagnostic levels of plasma leptin were associated with an elevated risk of pancreatic cancer among men, but not among women. Cancer Res; 76(24); 7160–7. ©2016 AACR.

<h3>Objective</h3> Telomere shortening occurs as an early event in pancreatic tumorigenesis, and genetic variants at the telomerase reverse transcriptase (<i>TERT</i>) gene region have been associated with pancreatic cancer risk. However, it is unknown whether prediagnostic leucocyte telomere length is associated with subsequent risk of pancreatic cancer. <h3>Design</h3> We measured prediagnostic leucocyte telomere length in 386 pancreatic cancer cases and 896 matched controls from five prospective US cohorts. ORs and 95% CIs were calculated using conditional logistic regression. Matching factors included year of birth, cohort (which also matches on sex), smoking status, fasting status and month/year of blood collection. We additionally examined single-nucleotide polymorphisms (SNPs) at the <i>TERT</i> region in relation to pancreatic cancer risk and leucocyte telomere length using logistic and linear regression, respectively. <h3>Results</h3> Shorter prediagnostic leucocyte telomere length was associated with higher risk of pancreatic cancer (comparing extreme quintiles of telomere length, OR 1.72; 95% CI 1.07 to 2.78; p_trend=0.048). Results remained unchanged after adjustment for diabetes, body mass index and physical activity. Three SNPs at <i>TERT</i> (linkage disequilibrium r²&lt;0.25) were associated with pancreatic cancer risk, including rs401681 (per minor allele OR 1.33; 95% CI 1.12 to 1.59; p=0.002), rs2736100 (per minor allele OR 1.36; 95% CI 1.13 to 1.63; p=0.001) and rs2736098 (per minor allele OR 0.75; 95% CI 0.63 to 0.90; p=0.002). The minor allele for rs401681 was associated with shorter telomere length (p=0.023). <h3>Conclusions</h3> Prediagnostic leucocyte telomere length and genetic variants at the <i>TERT</i> gene region were associated with risk of pancreatic cancer.

Abstract Pancreatic cancer is the fourth leading cause of cancer-related deaths in Japan. To identify risk loci, we perform a meta-analysis of three genome-wide association studies comprising 2,039 pancreatic cancer patients and 32,592 controls in the Japanese population. Here, we identify 3 (13q12.2, 13q22.1, and 16p12.3) genome-wide significant loci ( P &lt; 5.0 × 10 −8 ), of which 16p12.3 has not been reported in the Western population. The lead single nucleotide polymorphism (SNP) at 16p12.3 is rs78193826 (odds ratio = 1.46, 95% confidence interval = 1.29-1.66, P = 4.28 × 10 −9 ), an Asian-specific, nonsynonymous glycoprotein 2 ( GP2 ) gene variant. Associations between selected GP2 gene variants and pancreatic cancer are replicated in 10,822 additional cases and controls of East Asian origin. Functional analyses using cell lines provide supporting evidence of the effect of rs78193826 on KRAS activity. These findings suggest that GP2 gene variants are probably associated with pancreatic cancer susceptibility in populations of East Asian ancestry.

We previously showed that TGFα synergizes with c-myc in mammary tumorigenesis through inhibition of Myc-induced apoptosis. We therefore examined the effects of growth factors on apoptosis induction in several cell lines from MMTV-mycmammary tumors. When EGF was withdrawn or TGFβ1 was added, cells became apoptotic after 15 h (by ELISA and morphology). Northern and Western analysis revealed high levels of Bax and p53, and low or undetectable levels of Bcl-2 and Bcl-xSunder all treatment conditions. In contrast, Bcl-xLexpression was highest in the presence of EGF or TGFα, with a significant reduction upon removal of EGF or exposure to TGFβ. In mouse mammary tumors, the relative Bcl-xL/Bax ratio was higher in TGFα/Myc double transgenics than in Myc single transgenics, in agreement with thein vitrodata. Our results suggest a role for Bcl-xLin the regulation of apoptosis by EGF and TGFβ in mammary epithelial cells.

Most, if not all, of the cellular functions of the BRCA1 protein are mediated through heterodimeric complexes composed of BRCA1 and a related protein, BARD1. Some breast-cancer-associated BRCA1 missense mutations disrupt the function of the BRCA1/BARD1 complex. It is therefore pertinent to determine whether variants of BARD1 confer susceptibility to breast cancer. Recently, a missense BARD1 variant, Cys557Ser, was reported to be at increased frequencies in breast cancer families. We investigated the role of the BARD1 Cys557Ser variant in a population-based cohort of 1,090 Icelandic patients with invasive breast cancer and 703 controls. We then used a computerized genealogy of the Icelandic population to study the relationships between the Cys557Ser variant and familial clustering of breast cancer.The Cys557Ser allele was present at a frequency of 0.028 in patients with invasive breast cancer and 0.016 in controls (odds ratio [OR] = 1.82, 95% confidence interval [CI] 1.11-3.01, p = 0.014). The alleleic frequency was 0.037 in a high-predisposition group of cases defined by having a family history of breast cancer, early onset of breast cancer, or multiple primary breast cancers (OR = 2.41, 95% CI 1.22-4.75, p = 0.015). Carriers of the common Icelandic BRCA2 999del5 mutation were found to have their risk of breast cancer further increased if they also carried the BARD1 variant: the frequency of the BARD1 variant allele was 0.047 (OR = 3.11, 95% CI 1.16-8.40, p = 0.046) in 999del5 carriers with breast cancer. This suggests that the lifetime probability of a BARD1 Cys557Ser/BRCA2 999del5 double carrier developing breast cancer could approach certainty. Cys557Ser carriers, with or without the BRCA2 mutation, had an increased risk of subsequent primary breast tumors after the first breast cancer diagnosis compared to non-carriers. Lobular and medullary breast carcinomas were overrepresented amongst Cys557Ser carriers. We found that an excess of ancestors of contemporary carriers lived in a single county in the southeast of Iceland and that all carriers shared a SNP haplotype, which is suggestive of a founder event. Cys557Ser was found on the same SNP haplotype background in the HapMap Project CEPH sample of Utah residents.Our findings suggest that BARD1 Cys557Ser is an ancient variant that confers risk of single and multiple primary breast cancers, and this risk extends to carriers of the BRCA2 999del5 mutation.

Measurements of serum prostate-specific antigen (PSA) protein levels form the basis for a widely used test to screen men for prostate cancer. Germline variants in the gene that encodes the PSA protein (KLK3) have been shown to be associated with both serum PSA levels and prostate cancer. Based on a resequencing analysis of a 56 kb region on chromosome 19q13.33, centered on the KLK3 gene, we fine mapped this locus by genotyping tag SNPs in 3,522 prostate cancer cases and 3,338 controls from five case-control studies. We did not observe a strong association with the KLK3 variant, reported in previous studies to confer risk for prostate cancer (rs2735839; P = 0.20) but did observe three highly correlated SNPs (rs17632542, rs62113212 and rs62113214) associated with prostate cancer [P = 3.41 × 10(-4), per-allele trend odds ratio (OR) = 0.77, 95% CI = 0.67-0.89]. The signal was apparent only for nonaggressive prostate cancer cases with Gleason score <7 and disease stage <III (P = 4.72 × 10(-5), per-allele trend OR = 0.68, 95% CI = 0.57-0.82) and not for advanced cases with Gleason score >8 or stage ≥III (P = 0.31, per-allele trend OR = 1.12, 95% CI = 0.90-1.40). One of the three highly correlated SNPs, rs17632542, introduces a non-synonymous amino acid change in the KLK3 protein with a predicted benign or neutral functional impact. Baseline PSA levels were 43.7% higher in control subjects with no minor alleles (1.61 ng/ml, 95% CI = 1.49-1.72) than in those with one or more minor alleles at any one of the three SNPs (1.12 ng/ml, 95% CI = 0.96-1.28) (P = 9.70 × 10(-5)). Together our results suggest that germline KLK3 variants could influence the diagnosis of nonaggressive prostate cancer by influencing the likelihood of biopsy.

Pancreatic tumors cause changes in whole-body metabolism, but whether prediagnostic circulating metabolites predict survival is unknown.We measured 82 metabolites by liquid chromatography-mass spectrometry in prediagnostic plasma from 484 pancreatic cancer case patients enrolled in four prospective cohort studies. Association of metabolites with survival was evaluated using Cox proportional hazards models adjusted for age, cohort, race/ethnicity, cancer stage, fasting time, and diagnosis year. After multiple-hypothesis testing correction, a P value of .0006 or less (.05/82) was considered statistically significant. Based on the results, we evaluated 33 tagging single-nucleotide polymorphisms (SNPs) in the ACO1 gene, requiring a P value of less than .002 (.05/33) for statistical significance. All statistical tests were two-sided.Two metabolites in the tricarboxylic acid (TCA) cycle--isocitrate and aconitate--were statistically significantly associated with survival. Participants in the highest vs lowest quintile had hazard ratios (HRs) for death of 1.89 (95% confidence interval [CI] = 1.06 to 3.35, Ptrend < .001) for isocitrate and 2.54 (95% CI = 1.42 to 4.54, Ptrend < .001) for aconitate. Isocitrate is interconverted with citrate via the intermediate aconitate in a reaction catalyzed by the enzyme aconitase 1 (ACO1). Therefore, we investigated the citrate to aconitate plus isocitrate ratio and SNPs in the ACO1 gene. The ratio was strongly associated with survival (P trend < .001) as was the SNP rs7874815 in the ACO1 gene (hazard ratio for death per minor allele = 1.37, 95% CI = 1.16 to 1.61, P < .001). Patients had an approximately three-fold hazard for death when possessing one or more minor alleles at rs7874851 and high aconitate or isocitrate.Prediagnostic circulating levels of TCA cycle intermediates and inherited ACO1 genotypes were associated with survival among patients with pancreatic cancer.

Pancreatic cancer is an aggressive, difficult-to-treat disease that is on track to become the second most deadly malignancy in adults by 2030.1Rahib L. Smith B.D. Aizenberg R. et al.Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States.Cancer Res. 2014; 74: 2913-2921Crossref PubMed Scopus (3761) Google Scholar Although significant advances in treatment are being made, screening and early detection hold the greatest promise in affecting mortality. Effective screening for pancreatic cancer, per National Cancer Institute recommendations, should: (1) demonstrate ability to detect early cancer; (2) show that screening reduces cancer mortality, and (3) prove that benefits of screening outweigh harms.2Screening tests. National Cancer Institute.https://www.cancer.gov/about-cancer/screening/screening-testsGoogle Scholar Pancreatic cancer presents several challenges in meeting these screening criteria, including its relatively low incidence in the general population, the small independent effect sizes of known environmental and nutritional risk factors, limited ability to detect the highest-risk premalignant lesions (ie, pancreatic intraepithelial neoplasia), early metastasis, and resistance to standard treatments that can be curative in other cancer types. Here we discuss the current state of pancreatic cancer screening and recommend strategic steps needed to overcome these challenges and allow proper studies to be performed to ultimately demonstrate efficacy, decreased mortality, and favorable balance of benefit over harm. Implementation of an effective screening test requires identification of a target population. Because of its relatively low incidence, sensitivity and specificity levels of existing techniques are inadequate for pancreatic cancer screening in the general population.3Owens D.K. Davidson K.W. et al.US Preventive Services Task ForceScreening for pancreatic cancer: US Preventive Services Task Force reaffirmation recommendation statement.JAMA. 2019; 322: 438-444Crossref PubMed Scopus (101) Google Scholar Individuals meeting specific criteria based on family history of pancreatic cancer and/or presence of pathogenic germline variants (PGV) in relevant cancer risk genes, referred to as high-risk individuals (HRIs), are currently the only cohort with published guidelines recommending pancreatic cancer screening at regular intervals.4Goggins M. Overbeek K.A. Brand R. et al.Management of patients with increased risk for familial pancreatic cancer: updated recommendations from the International Cancer of the Pancreas Screening (CAPS) Consortium.Gut. 2020; 69: 7-17Crossref PubMed Scopus (164) Google Scholar, 5Syngal S. Brand R.E. Church J.M. et al.ACG clinical guideline: genetic testing and management of hereditary gastrointestinal cancer syndromes.Am J Gastroenterol. 2015; 110 (quiz 263): 223-262Crossref PubMed Scopus (815) Google Scholar, 6National Comprehensive Cancer Network. Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic. Version 1.2021. National Comprehensive Cancer Network, 2020.Google Scholar In Table 1, we summarized the current genetic and family history inclusion criteria for pancreatic cancer screening. These recommendations have been made based on expert consensus opinion, and the collection of supporting evidence is ongoing.Table 1Definitions of High-Risk Individuals, Estimated Risk, and Initiation of Screening RecommendationsInclusion criteriaPublished risk estimatesInitiation of screening recommendationsPeutz-Jeghers syndromeSTK11 PGV or meeting clinical diagnostic criteriaCumulative risk by age 70 y, 32%–36%Age 30 y or olderFamilial atypical multiple mole and melanomaCDKN2A PGVCumulative risk by 75 y, 17%SIR, 21.8Age 35 y or olderFPCOverall SIR in FPC kindreds: 9.0Age 50 y or older or 10 y younger than youngest diagnosis of PDA in family 2 or more relatives with PDA1 FDR SIR, 4.5 First- or second-degree relative with PDA2 FDR SIR, 6.43 FDR SIR, 32Hereditary pancreatitisPRSS1 PGV or confirmed family history of pancreatitisSymptomatic pancreatitisSIR, 53Cumulative risk to 70 y, 33%–44%Age 40 y or olderConfirmed PGV in below listed genesFirst- or second-degree relative with PDAAge 50 y or older or 10 y younger than youngest diagnosis of PDA in family ATMOR, 4.2–5.7— BRCA1RR, 2.6— BRCA2RR, 3.5–5.9— MLH1, MSH2, MSH6, PMS2, EPCAMCumulative risk to 70 y, 3.68%6.8% MLH10.5% MSH21.4% MSH6— PALB2Not known—FDR, first-degree relative; FPC, familial pancreatic cancer; OR, odds ratio; PDA, pancreatic ductal adenocarcinoma; RR, risk ratio; SIR, standardized incidence ratio. Open table in a new tab FDR, first-degree relative; FPC, familial pancreatic cancer; OR, odds ratio; PDA, pancreatic ductal adenocarcinoma; RR, risk ratio; SIR, standardized incidence ratio. Published screening studies in HRIs have shown promise in the ability to detect early cancer (T1N0M0) and precursor lesions with high-grade dysplasia, another important criteria for effective screening programs. However, these studies have been limited by relatively small sample sizes, short follow-up, heterogeneity of inclusion criteria, and variability in screening techniques.7Overbeek KA, Levink IJM, Koopmann BDM, et al. Long-term yield of pancreatic cancer surveillance in high-risk individuals [published online ahead of print April 5, 2021]. Gut https://doi.org/10.1136/gutjnl-2020-323611Google Scholar A meta-analysis of 16 studies published between 2004 and 2016, which included 1550 participants, found nearly 2% of HRIs had pancreatic cancer or a high-grade precursor lesion identified.8Paiella S. Salvia R. De Pastena M. et al.Screening/surveillance programs for pancreatic cancer in familial high-risk individuals: a systematic review and proportion meta-analysis of screening results.Pancreatology. 2018; 18: 420-428Crossref PubMed Scopus (21) Google Scholar A 2018 study of 350 HRIs found that 9 of 10 incident pancreatic cancers discovered during a median follow-up time of 5.6 years were surgically resectable,9Canto M.I. Almario J.A. Schulick R.D. et al.Risk of neoplastic progression in individuals at high risk for pancreatic cancer undergoing long-term surveillance.Gastroenterology. 2018; 155: 740-751.e2Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar with a resulting 5-year survival rate of 60% in the surgically treated group.10Canto M.I. Kerdsirichairat T. Yeo C.J. et al.Surgical outcomes after pancreatic resection of screening-detected lesions in individuals at high risk for developing pancreatic cancer.J Gastrointest Surg. 2020; 24: 1101-1110Crossref PubMed Scopus (21) Google Scholar The study cohort included 97% of patients meeting criteria based on family history of pancreatic cancer alone, and gene status was unknown for the majority. This is relevant in light of a 2021 study that found a cumulative incidence of pancreatic cancer of 3.1% at 5 years and 4.7% at 10 years, with all cases occurring in PGV carriers.7Overbeek KA, Levink IJM, Koopmann BDM, et al. Long-term yield of pancreatic cancer surveillance in high-risk individuals [published online ahead of print April 5, 2021]. Gut https://doi.org/10.1136/gutjnl-2020-323611Google Scholar This study also found that 4 of 8 incident pancreatic cancers were resectable. This shift toward detection of earlier stage, resectable disease is encouraging, but larger studies with longer follow-up will be needed to exclude the possibility of lead-time bias. Two large-scale studies of ovarian cancer and prostate cancer both found that increased detection of early-stage disease did not result in a corresponding decrease in cancer mortality after long-term follow-up of 16 years and 10 years, respectively.11Menon U. Gentry-Maharaj A. Burnell M. et al.Ovarian cancer population screening and mortality after long-term follow-up in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS): a randomised controlled trial.Lancet. 2021; 397: 2182-2193Abstract Full Text Full Text PDF PubMed Scopus (57) Google Scholar,12Martin R.M. Donovan J.L. Turner E.L. et al.Effect of a low-intensity PSA-based screening intervention on prostate cancer mortality: the CAP randomized clinical trial.JAMA. 2018; 319: 883-895Crossref PubMed Scopus (204) Google Scholar In addition, it is important to note that several of the published pancreatic cancer screening series have reported cancers diagnosed between screening examinations and advanced cancers apparently missed with current screening techniques.13Corral J.E. Mareth K.F. Riegert-Johnson D.L. et al.Diagnostic yield from screening asymptomatic individuals at high risk for pancreatic cancer: a meta-analysis of cohort studies.Clin Gastroenterol Hepatol. 2019; 17: 41-53Abstract Full Text Full Text PDF PubMed Scopus (42) Google Scholar Understanding the possible explanations for these interval or missed cancers and the strategies to reduce them will require consistency in intervals and methods for screening across centers and more clearly defined study populations. National Cancer Institute and World Health Organization14World Health Organization Screening ProgrammesA Short Guide. Increase Effectiveness, Maximize Benefits and Minimize Harm. World Health Organization, 2020Google Scholar recommendations for effective screening also involve the weighing of benefits vs harms, both at the individual and societal level. Pancreatic cancer screening techniques have relatively low procedural risks, but published studies have reported a substantial number of noncancerous findings, including branch duct intrapapillary mucinous neoplasms, chronic pancreatitis, and extrapancreatic findings. This raises the possibility of overdiagnosis or overtreatment, issues that have complicated screening efforts for lung and prostate cancers.15Callister M.E.J. Sasieni P. Robbins H.A. Overdiagnosis in lung cancer screening.Lancet Respir Med. 2021; 9: 7-9Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar,16Loeb S. Bjurlin M.A. Nicholson J. et al.Overdiagnosis and overtreatment of prostate cancer.Eur Urol. 2014; 65: 1046-1055Abstract Full Text Full Text PDF PubMed Scopus (539) Google Scholar A 2019 meta-analysis found that pancreatic cancer screening in 1660 patients led to 473 abnormal imaging examinations and 257 surgical procedures, with 43 pancreatic cancers and 25 findings of high-grade dysplasia in intrapapillary mucinous neoplasms or pancreatic intraepithelial neoplasia 3 lesions.13Corral J.E. Mareth K.F. Riegert-Johnson D.L. et al.Diagnostic yield from screening asymptomatic individuals at high risk for pancreatic cancer: a meta-analysis of cohort studies.Clin Gastroenterol Hepatol. 2019; 17: 41-53Abstract Full Text Full Text PDF PubMed Scopus (42) Google Scholar Although perioperative mortality is <2% in high-volume centers, consideration of risk for postoperative complications, including diabetes after surgery, for what might ultimately prove to be a benign lesion is a necessary part of individual risk–benefit analysis in current screening programs. Other unintended individual-level harms can include anxiety associated with screening procedures or abnormal findings that require additional follow-up. Small studies in HRIs have suggested no significant psychological impact with screening, but additional studies in this area are needed. Currently available imaging modalities have a reasonable ability to detect lesions >1 cm, but not precursor lesions. These modalities are also expensive and, in the case of endoscopic ultrasound (EUS), invasive. Even with consensus recommendations for HRIs, insurance coverage is variable and can impact access to care. The cost and highly specialized nature of these modalities also creates disparities in access both economically and geographically. Cost–benefit analyses will be an important part of the necessary steps toward meeting National Institutes of Health and World Health Organization standards for screening, and will be critical to developing guidelines for medical necessity and consistent insurance coverage. Significant evolution in the recognition and treatment of precursor lesions will be required before the aims of screening can ultimately shift from proving reduction in mortality due to detection of early-stage pancreatic cancers to reduction of cancer incidence. Implementing strategies to address screening challenges in pancreatic cancer is a critical and timely issue. Expanded use of germline genetic testing in patients with pancreatic cancer has led to increased recognition of genes linked to pancreatic cancer risk. Germline testing identifies a clinically relevant PGV in approximately 10% of patients with pancreatic cancer,17Brand R. Borazanci E. Speare V. et al.Prospective study of germline genetic testing in incident cases of pancreatic adenocarcinoma.Cancer. 2018; 124: 3520-3527Crossref PubMed Scopus (37) Google Scholar, 18Yurgelun M.B. Chittenden A.B. Morales-Oyarvide V. et al.Germline cancer susceptibility gene variants, somatic second hits, and survival outcomes in patients with resected pancreatic cancer.Genet Med. 2019; 21: 213-223Abstract Full Text Full Text PDF PubMed Scopus (85) Google Scholar, 19Shindo K. Yu J. Suenaga M. et al.Deleterious germline mutations in patients with apparently sporadic pancreatic adenocarcinoma.J Clin Oncol. 2017; 35: 3382-3390Crossref PubMed Scopus (203) Google Scholar, 20Grant R.C. Selander I. Connor A.A. et al.Prevalence of germline mutations in cancer predisposition genes in patients with pancreatic cancer.Gastroenterology. 2015; 148: 556-564Abstract Full Text Full Text PDF PubMed Scopus (195) Google Scholar, 21Hu C. Hart S.N. Bamlet W.R. et al.Prevalence of pathogenic mutations in cancer predisposition genes among pancreatic cancer patients.Cancer Epidemiol Biomarkers Prev. 2016; 25: 207-211Crossref PubMed Scopus (88) Google Scholar and at least another 2%–5% of pancreatic cancers occur in individuals with a family history of pancreatic cancer but without an identifiable PGV. For all individuals with a newly diagnosed pancreatic cancer, germline genetic testing is now part of routine care recommended by National Comprehensive Cancer Network6National Comprehensive Cancer Network. Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic. Version 1.2021. National Comprehensive Cancer Network, 2020.Google Scholar and American Society of Clinical Oncology22Stoffel E.M. McKernin S.E. Brand R. et al.Evaluating susceptibility to pancreatic cancer: ASCO Provisional Clinical Opinion.J Clin Oncol. 2019; 37: 153-164Crossref PubMed Scopus (71) Google Scholar guidelines, regardless of family history. The National Comprehensive Cancer Network guidelines also now recommend germline genetic testing for individuals who have a first-degree relative with pancreatic cancer.6National Comprehensive Cancer Network. Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic. Version 1.2021. National Comprehensive Cancer Network, 2020.Google Scholar These expanded criteria for genetic testing will identify new HRIs eligible for pancreatic surveillance based on the consensus guidelines. With more than 60,000 new cases of pancreatic cancer per year in the United States, and known rates of PGV identification and positive family history of pancreatic cancer, in combination with increased awareness of pancreatic cancer detection, at least 120,000 individuals will be eligible for surveillance annually in the United States alone. At this volume, it is likely that both genetic testing and imaging or procedures will be performed by an increasing number of centers and providers. Our main goal was to address an important step in the World Health Organization screening program pathway: to conduct and report testing using agreed on and standardized methods. This step is critical to move toward eventual reporting of outcomes on a scale large enough to demonstrate screening efficacy. There is a need to optimize screening algorithms and collection of longitudinal demographic, genetic, imaging, and biomarker data over an extended period of time. Although consortia and multicenter collaborations are ideal for data collection, it is likely that a significant proportion of screening will be performed outside of these efforts, further emphasizing the need for standardization. Here, we outline important elements that can be incorporated into current practice to improve and standardize data collection for HRIs and pave the road for future research to establish the efficacy of screening and to recognize novel risk factors, markers, or imaging characteristics of early-stage cancer or precursor lesions. The type of data we collect today, and how we collect those data, will determine our ability to ultimately reduce the mortality of pancreatic cancer with a favorable ratio of benefit to harm at an acceptable societal cost. The collection and documentation of cancer family history is a key component of risk stratification and clinical management for families at risk for pancreatic cancer. In a general clinic setting, pertinent positive family history, including primary site of cancer and age at diagnosis in first- and second-degree relatives, is sufficient for determining surveillance eligibility.5Syngal S. Brand R.E. Church J.M. et al.ACG clinical guideline: genetic testing and management of hereditary gastrointestinal cancer syndromes.Am J Gastroenterol. 2015; 110 (quiz 263): 223-262Crossref PubMed Scopus (815) Google Scholar The gold standard for cancer genetic counseling and the best practice approach for the high-risk clinic setting is a 3-generation pedigree, including information about primary cancer sites and ages at diagnosis for all relatives with cancer history. Confirmation of pancreatic cancer diagnoses via medical records is preferred when possible, particularly for second- or third-degree relatives, as accuracy of reporting decreases beyond first-degree relationships.23Ziogas A. Anton-Culver H. Validation of family history data in cancer family registries.Am J Prev Med. 2003; 24: 190-198Abstract Full Text Full Text PDF PubMed Scopus (197) Google Scholar Pedigree documentation should also include results of genetic testing and the specific genes analyzed for any family member completing it. Discovery of new genes or new associations with known genes over time might mean that updated testing is indicated for HRIs or their tested family members.24Riley B.D. Culver J.O. Skrzynia C. et al.Essential elements of genetic cancer risk assessment, counseling, and testing: updated recommendations of the National Society of Genetic Counselors.J Genet Couns. 2012; 21: 151-161Crossref PubMed Scopus (228) Google Scholar With the evolving use of multigene panel testing, there has been considerable variation in the content of genetic testing offered to HRIs. Current testing in this setting should include a minimum list of the following genes from published surveillance guidelines4Goggins M. Overbeek K.A. Brand R. et al.Management of patients with increased risk for familial pancreatic cancer: updated recommendations from the International Cancer of the Pancreas Screening (CAPS) Consortium.Gut. 2020; 69: 7-17Crossref PubMed Scopus (164) Google Scholar,5Syngal S. Brand R.E. Church J.M. et al.ACG clinical guideline: genetic testing and management of hereditary gastrointestinal cancer syndromes.Am J Gastroenterol. 2015; 110 (quiz 263): 223-262Crossref PubMed Scopus (815) Google Scholar: APC, ATM, BRCA1, BRCA2, CDKN2A, MLH1, MSH2, MSH6, PALB2, PMS2, STK11, and TP53. Among families who present meeting criteria for familial pancreatic cancer, about 15%–20% have an identifiable pathogenic germline variant, leaving 80%–85% of the heritable component of familial pancreatic cancer unknown. Standard collection of full pedigrees in this setting will power studies to identify new genetic associations. Documentation of full pedigree information in high-risk families will also allow improvements in penetrance estimation and risk modeling to provide accurate risk information to patients and families that will refine surveillance guidelines over time. We therefore include standardized reporting of pedigrees in HRIs (Table 2).Table 2Proposed Areas of Standardization of Template Use in High-Risk IndividualsAreas of standardizationProposed template elementsExamplesFamily historyPedigree templates (ie, commercially available templates [Prodigy])3- to 4-generation pedigree with PGV informationConfirmation of reported pancreatic cancers with recordsGenetic testingMinimum gene list and plan for updatingPanels including all known genes linked to pancreatic cancer riskUpdated testing for families with outdated resultsIndication for screeningPathogenic germline variants in specific genes or family historyFamilial pancreatic cancerPathogenic germline variantsFamily history of pancreatic cancerAcquisition of specific EUS viewsConfirmation of capture of 8 key views of the pancreas and peripancreatic structures from the duodenal and gastric positionDuodenal views:Distal CBD/proximal PD/ampulla viewPorta hepatisHOP with PDPancreas parenchyma, portal confluenceGastric views:Celiac axis, SMA, aortaTail of pancreas view with splenorenal angleBody of pancreas view at level of SA and SVRight lateral pancreas margin (PD toward HOP)EUS procedural detailsTemplated acquisition of procedural data pointsType of EUS performed (radial vs linear); length of procedure; sedation usedEUS parenchymal descriptorsUse of templated drop-down menu for specific predefined parenchymal changesHyperechoic foci or strands; lobularity; microcysts; atrophy; calcifications; heterogeneous pancreas; fatty pancreasEUS pancreatic duct descriptorsUse of drop-down menu for specific measurements and characteristics of MPDRecord diameter in head, body, and tail of pancreasStricture, wall irregularities, filling defects and ampullary examinationSolid and cystic lesion descriptorsUse of drop-down menu for characteristics and biopsy/aspiration techniques and detailsSize in 2 dimensions; location; echogenicity; communication with MPD; cystic component; vascular invasion; upstream dilation or atrophy; EUS impressionTissue acquisitionUse of template for procedural details and tissue or fluid obtainedTechnical details (needle size, approach, number of passes); biopsy details (amount of fluid or number of cores obtained)Testing performed (cytology, tumor sequencing, fluid analysis, other cyst fluid–based biomarkers)Assessment of EUS adequacy and overall impressionTemplate for assessment of procedural adequacy, recommendations for future imagingProvide scale of adequacy (adequate, partially adequate or limited/inadequate) and ability to make recommendations based on examination (recommend continued use of EUS vs other modalities for screening)Assessment of overall impressionTemplate for overall impression and changes (if applicable) to prior EUS examinationProvide description of overall impression (normal/abnormal of uncertain significance/worrisome or significant abnormalities and provide comparison to prior examinationCBD, common bile duct; HOP, head of pancreas; MPD, main pancreatic duct; PC, pancreatic cancer; PD, pancreatic duct; SA, splenic artery; SMA, superior mesenteric artery; SV, splenic vein. Open table in a new tab CBD, common bile duct; HOP, head of pancreas; MPD, main pancreatic duct; PC, pancreatic cancer; PD, pancreatic duct; SA, splenic artery; SMA, superior mesenteric artery; SV, splenic vein. Improving identification of individuals at risk for pancreatic cancer will also require a deeper understanding of all significant contributing risk factors. Both modifiable and nonmodifiable risk factors beyond the known high-/moderate-penetrance genes contribute to pancreatic cancer risk, but understanding the impact of, and interactions among, individual risk factors in HRIs remains elusive. Standard documentation of known pancreatic cancer risk factors should be part of high-risk care, and will help to drive discovery, risk stratification, and risk modeling in this population. Key risk factor variables to document include history of diabetes, along with current fasting blood glucose or hemoglobin A1C and time of onset and course of pre-existing diabetes; current weight and BMI; blood type; current and past smoking; and current and past alcohol use, including binge drinking. Few studies have comprehensively investigated the effects of modifiable factors including dietary habits, nutrition, or physical activity on pancreatic cancer risk, and future efforts to document these variables in HRIs may be warranted. Most studies have found imaging by magnetic resonance imaging (MRI), magnetic resonance cholangiopancreatography, and EUS to be superior to other modalities, similar to each other in accuracy and complementary for early lesion detection.13Corral J.E. Mareth K.F. Riegert-Johnson D.L. et al.Diagnostic yield from screening asymptomatic individuals at high risk for pancreatic cancer: a meta-analysis of cohort studies.Clin Gastroenterol Hepatol. 2019; 17: 41-53Abstract Full Text Full Text PDF PubMed Scopus (42) Google Scholar At present, there is no other surveillance test, including serum-based or endoscopically obtained biomarkers, that compares in accuracy or yield. Both EUS and MRI have excellent accuracy for the detection of pancreatic masses or cystic lesions >1 cm and changes in pancreatic duct caliber. EUS, however, currently has a higher sensitivity in the identification of small lesions (<1 cm) and in the identification of parenchymal abnormalities. Although MRI images are stored and accessible, EUS images are rarely, if ever, recorded in a high-resolution manner. This significantly limits both the clinical ability to compare studies between multiple time points and the potential for image analysis-based research. Although radiology reporting is increasingly standardized, there are no specific templates developed for patients undergoing screening procedures. EUS reporting is less frequently templated and most current reporting templates have been developed for different contexts, which leads to further gaps in both clinical care and research. With an expected increase in demand for these studies, it is imperative that we enhance our ability to acquire and report EUS abnormalities in a standardized manner. The goal of EUS imaging in HRIs is to provide complete and reproducible examination of the pancreas and generate a uniform format report that can allow for both image and description comparison between time points and across different providers. A first step in standardization is to create a definition of a complete examination defined by imaging landmarks to assess imaging adequacy. Reporting of landmarks should be analogous to now-established colonoscopy standards,25Lieberman D. Nadel M. Smith R.A. et al.Standardized colonoscopy reporting and data system: report of the Quality Assurance Task Group of the National Colorectal Cancer Roundtable.Gastrointest Endosc. 2007; 65: 757-766Abstract Full Text Full Text PDF PubMed Scopus (244) Google Scholar and recording of these landmarks should be mandatory. A list of proposed EUS landmarks is provided in Table 2. Adequacy of a pancreatic EUS examination can be analogous to colonoscopy quality assessment,26Rex D.K. Schoenfeld P.S. Cohen J. et al.Quality indicators for colonoscopy.Gastrointest Endosc. 2015; 81: 31-53Abstract Full Text Full Text PDF PubMed Scopus (571) Google Scholar and will depend on procedural-, anatomic-, and sedation-related factors. However, this assessment will likely be impactful, as it will guide further recommendations and use of EUS in surveillance. Standardized reporting exists for pancreatic mass27Al-Hawary M.M. Francis I.R. Chari S.T. et al.Pancreatic ductal adenocarcinoma radiology reporting template: consensus statement of the Society of Abdominal Radiology and the american Pancreatic Association.Gastroenterology. 2014; 146: 291-304.e1Abstract Full Text Full Text PDF PubMed Scopus (158) Google Scholar or cystic neoplasia assessment, and these can generally be adopted for screening of HRIs. However, in only a minority of patients are these findings identified, and our current understanding of evolution of pancreatic precursors suggests that more subtle findings, such as parenchymal changes, can be important to recognize precursors.28Konings I. Cahen D.L. Harinck F. et al.Evolution of features of chronic pancreatitis during endoscopic ultrasound-based surveillance of individuals at high risk for pancreatic cancer.Endosc Int Open. 2018; 6: E541-E548Crossref PubMed Google Scholar,29Catalano M.F. Sahai A. Levy M. et al.EUS-based criteria for the diagnosis of chronic pancreatitis: the Rosemont classification.Gastrointest Endosc. 2009; 69: 1251-1261Abstract Full Text Full Text PDF PubMed Scopus (359) Google Scholar Most of these parenchymal changes were initially described in relation to chronic pancreatitis-associated changes, but have since been associated with changes observed in neoplastic progression.28Konings I. Cahen D.L. Harinck F. et al.Evolution of features of chronic pancreatitis during endoscopic ultrasound-based surveillance of individuals at high risk for pancreatic cancer.Endosc Int Open. 2018; 6: E541-E548Crossref PubMed Google Scholar,30LeBlanc J.K. Chen J.H. Al-Haddad M. et al.Can endoscopic ultrasound predict pancreatic intraepithelial neoplasia lesions in chronic pancreatitis?: a retrospective study of pathologic correlation.Pancreas. 2014; 43: 849-854Crossref PubMed Scopus (17) Google Scholar Improved resolution of B-mode EUS imaging and enhanced imaging modalities (ie, elastography and contrast enhancement) will likely further improve our ability to characterize parenchymal changes associated with early neoplastic development. An obvious parallel to draw on is the unequivocal benefit of high-resolution white light and virtual chromoendoscopy in detection of gastric and colonic neoplasia in luminal imaging. Substantial efforts have been made to define and characterize mucosal changes and patterns, and only through these efforts was the significance of these findings validated.31Shaukat A. Kaltenbach T. Dominitz J.A. et al.Endoscopic recognition and management strategies for malignant colorectal polyps: recommendations of the US Multi-Society Task Force on Colorectal Cancer.Gastroenterology. 2020; 159: 1916-1934.e2Abstract Full Text Full Text PDF PubMed Scopus (20) Google Scholar A similar effort might be required to understand the parenchymal changes seen in pancreatic EUS, to understand the temporal evolution of these changes in HRIs, and perhaps to identify the phenotype of pancreatic parenchymal changes associated with specific germline mutational status. This can only be accomplished if we define specific terminology and use predetermined image-capture areas to document these changes. An achievable immediate goal for the EUS field will be to standardize image capture and template reporting. This will result in higher-quality care in surveillance of HRIs and allow comparison of data between time points and providers. We would even propose the creation of a training module to aid in uniform image capture and terminology use by providers who care for HRIs. These objectives can likely be fulfilled with currently available technologies and resources. However, the evolving role of enhanced image analysis and artificial intelligence–based evaluation will require higher quality and resolution image capture and the ability to store these images or video segments for future analysis. This is a much more resource-intensive proposition, which will likely require greater integration of EUS images in standard image repositories, such as picture archiving and communication systems. This is an area where multicenter collaborative consortiums will play a critical role. We are at an inflection point in the history of pancreatic cancer screening. There is an increasing opportunity to decrease mortality of pancreatic cancer through early detection, and the growing number of patients who will be eligible for screening highlights the importance of well-organized, large-scale, long-term, longitudinal follow-up studies of a population with sufficiently high risk for cancer that screening impact can be assessed adequately. Undoubtedly, progress toward more effective early-detection biomarkers and less invasive (and less expensive) screening approaches will become available in the future. However, for patients with familial pancreatic cancer and those with pathogenic germline variants that increase risk for pancreatic cancer, cross-sectional and endoscopic imaging will likely remain the cornerstone of surveillance for a period of time. Consortiums like PRECEDE (Pancreatic Cancer Early Detection),32The Pancreatic Cancer Early Detection Research Consortium (PRECEDE).www.precedestudy.orgGoogle Scholar CAPS (Cancer of the Pancreas Screening),33Canto M.I. Harinck F. Hruban R.H. et al.International Cancer of the Pancreas Screening (CAPS) Consortium summit on the management of patients with increased risk for familial pancreatic cancer.Gut. 2013; 62: 339-347Crossref PubMed Scopus (496) Google Scholar the Dutch Familial Pancreatic Cancer Surveillance study,7Overbeek KA, Levink IJM, Koopmann BDM, et al. Long-term yield of pancreatic cancer surveillance in high-risk individuals [published online ahead of print April 5, 2021]. Gut https://doi.org/10.1136/gutjnl-2020-323611Google Scholar and EUROPAC (European Registry of Hereditary Pancreatitis and Familial Pancreatic Cancer)34The European Registry of Hereditary Pancreatitis and Familial Pancreatic Cancer (EUROPAC). Volume 2021.Google Scholar are well positioned to collect these data and, given the relatively low event rate in surveillance cohorts, these large, multi-institutional studies will be critical in defining the natural history and predictors of progression. However, given the expected volume of screening procedures, it is essential that standardization is broadly practiced even outside of these registries and that we define and develop resources to achieve a common standard irrespective of the practice setting.

Genome-wide association studies (GWASs) have discovered 20 risk loci in the human genome where germline variants associate with risk of pancreatic ductal adenocarcinoma (PDAC) in populations of European ancestry. Here, we fine-mapped one such locus on chr16q23.1 (rs72802365, p = 2.51 × 10-17, OR = 1.36, 95% CI = 1.31-1.40) and identified colocalization (PP = 0.87) with aberrant exon 5-7 CTRB2 splicing in pancreatic tissues (pGTEx = 1.40 × 10-69, βGTEx = 1.99; pLTG = 1.02 × 10-30, βLTG = 1.99). Imputation of a 584 bp structural variant overlapping exon 6 of CTRB2 into the GWAS datasets resulted in a highly significant association with pancreatic cancer risk (p = 2.83 × 10-16, OR = 1.36, 95% CI = 1.31-1.42), indicating that it may underlie this signal. Exon skipping attributable to the deletion (risk) allele introduces a premature stop codon in exon 7 of CTRB2, yielding a truncated chymotrypsinogen B2 protein that lacks chymotrypsin activity, is poorly secreted, and accumulates intracellularly in the endoplasmic reticulum (ER). We propose that intracellular accumulation of a nonfunctional chymotrypsinogen B2 protein leads to ER stress and pancreatic inflammation, which may explain the increased pancreatic cancer risk in carriers of CTRB2 exon 6 deletion alleles.

Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

The transmembrane protein Kekkon 1 (Kek1) has previously been shown to act in a negative feedback loop to downregulate the Drosophila Epidermal Growth Factor Receptor (DER) during oogenesis. We show that this protein plays a similar role in other DER-mediated developmental processes. Structure-function analysis reveals that the extracellular Leucine-Rich Repeat (LRR) domains of Kek1 are critical for its function through direct association with DER, whereas its cytoplasmic domain is required for apical subcellular localization. In addition, the use of chimeric proteins between Kek1 extracellular and transmembrane domains fused to DER intracellular domain indicates that Kek1 forms an heterodimer with DER in vivo. To characterize more precisely the mechanism underlying the Kek1/DER interaction, we used mammalian ErbB/EGFR cell-based assays. We show that Kek1 is capable of physically interacting with each of the known members of the mammalian ErbB receptor family and that the Kek1/EGFR interaction inhibits growth factor binding, receptor autophosphorylation and Erk1/2 activation in response to EGF. Finally, in vivo experiments show that Kek1 expression potently suppresses the growth of mouse mammary tumor cells derived from aberrant ErbB receptors activation, but does not interfere with the growth of tumor cells derived from activated Ras. Our results underscore the possibility that Kek1 may be used experimentally to inhibit ErbB receptors and point to the possibility that, as yet uncharacterized, mammalian transmembrane LRR proteins might act as modulators of growth factor signalling.

Given the changing demographics of Western populations, the numbers of pancreatic cancer cases are projected to increase during the next decade. Diabetes, recent cigarette smoking, and excess body weight are the cancer's most consistent risk factors. The search for common and rare germline variants that influence risk of pancreatic cancer through genome-wide association studies and high-throughput-sequencing-based studies is underway and holds the promise of increasing the knowledge of variants and genes that play a role in inherited susceptibility of this disease. Research reported in this review has advanced the understanding of pancreatic cancer.

Abstract Individuals from pancreatic cancer families are at increased risk, not only of pancreatic cancer, but also of melanoma, breast, ovarian, and colon cancers. While some of the increased risk may be due to mutations in high-penetrance genes (i.e., BRCA2, PALB2, ATM, p16/CDKN2A or DNA mismatch repair genes), common genetic variants may also be involved. In a high-risk population of cases with either a family history of pancreatic cancer or early-onset pancreatic cancer (diagnosis before the age of 50 years), we examined the role of genetic variants previously associated with risk of pancreatic, breast, ovarian, or prostate cancer. We genotyped 985 cases (79 early-onset cases, 906 cases with a family history of pancreatic cancer) and 877 controls for 215,389 SNPs using the iSelect Collaborative Oncological Gene-Environment Study (iCOGS) array with custom content. Logistic regression was performed using a log-linear additive model. We replicated several previously reported pancreatic cancer susceptibility loci, including recently identified variants on 2p13.3 and 7p13 (2p13.3, rs1486134: OR = 1.36; 95% CI, 1.13–1.63; P = 9.29 × 10−4; 7p13, rs17688601: OR = 0.76; 95% CI, 0.63–0.93; P = 6.59 × 10−3). For the replicated loci, the magnitude of association observed in these high-risk patients was similar to that observed in studies of unselected patients. In addition to the established pancreatic cancer loci, we also found suggestive evidence of association (P &amp;lt; 5 × 10−5) to pancreatic cancer for SNPs at HDAC9 (7p21.1) and COL6A2 (21q22.3). Even in high-risk populations, common variants influence pancreatic cancer susceptibility. Cancer Epidemiol Biomarkers Prev; 25(7); 1185–91. ©2016 AACR.

Altered regulation of endoplasmic reticulum (ER) homeostasis has been implicated in many cancers and has recently become a therapeutic and chemosensitization target of interest. We have identified Cleft Lip and Palate Transmembrane 1-Like (CLPTM1L)/Cisplatin Resistance Related Protein 9 (CRR9) as an ER stress related mediator of cytoprotection in pancreatic cancer. We recently demonstrated that CLPTM1L is highly expressed in pancreatic ductal adenocarcinoma and associated with poor outcome. Furthermore, we have discovered that CLPTM1L interacts with phosphoinositol-3-kinase-alpha at the tumor cell surface and causes up-regulation of Bcl-xL and pAkt mediated survival signaling. Here, we demonstrate surface relocalization and survival signaling by CLPTM1L triggered by endoplasmic reticular (ER) stress. We demonstrate the interaction of CLPTM1L with the central ER stress survival mediator, Glucose Regulated Protein 78 (GRP78)/Binding Immunoglobulin Protein (BiP) and PI3K-alpha /p110α. This interaction and surface relocalization of CLPTM1L and GRP78 is induced by ER stress, including that caused by treatment with gemcitabine. We demonstrate that the extracellular loop of CLPTM1L is required for gemcitabine resistance and interaction with GRP78. This interaction and the chemoresistance effect conferred by this pathway is targetable with our recently developed inhibitory CLPTM1L antibodies, which may represent novel modalities of chemosensitization and treatment of pancreatic adenocarcinoma. Anchorage independent growth, GRP78-mediated chemoresistance, and Akt phosphorylation were abrogated by inhibition of CLPTM1L. These findings demonstrate a novel and potentially targetable mechanism of cytoprotection and chemoresistance in pancreatic tumors.

Pancreatic cancer is the third leading cause of cancer death in the United States, and 80% of patients present with advanced, incurable disease. Risk markers for pancreatic cancer have been characterized, but combined models are not used clinically to identify individuals at high risk for the disease.Within a nested case-control study of 500 pancreatic cancer cases diagnosed after blood collection and 1,091 matched controls enrolled in four U.S. prospective cohorts, we characterized absolute risk models that included clinical factors (e.g., body mass index, history of diabetes), germline genetic polymorphisms, and circulating biomarkers.Model discrimination showed an area under ROC curve of 0.62 via cross-validation. Our final integrated model identified 3.7% of men and 2.6% of women who had at least 3 times greater than average risk in the ensuing 10 years. Individuals within the top risk percentile had a 4% risk of developing pancreatic cancer by age 80 years and 2% 10-year risk at age 70 years.Risk models that include established clinical, genetic, and circulating factors improved disease discrimination over models using clinical factors alone.Absolute risk models for pancreatic cancer may help identify individuals in the general population appropriate for disease interception.

Abstract Background Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance. Methods We complemented a new conventional PC GWAS (1D) with genome spatial autocorrelation analysis (2D) permitting to prioritize low frequency variants not detected by GWAS. These were further expanded via Hi-C map (3D) interactions to gain additional insight into the inherited basis of PC. In silico functional analysis of public genomic information allowed prioritization of potentially relevant candidate variants. Results We identified several new variants located in genes for which there is experimental evidence of their implication in the biology and function of pancreatic acinar cells. Among them is a novel independent variant in NR5A2 (rs3790840) with a meta-analysis p value = 5.91E−06 in 1D approach and a Local Moran’s Index (LMI) = 7.76 in 2D approach. We also identified a multi-hit region in CASC8 —a lncRNA associated with pancreatic carcinogenesis—with a lowest p value = 6.91E−05. Importantly, two new PC loci were identified both by 2D and 3D approaches: SIAH3 (LMI = 18.24), CTRB2/BCAR1 (LMI = 6.03), in addition to a chromatin interacting region in XBP1 —a major regulator of the ER stress and unfolded protein responses in acinar cells—identified by 3D; all of them with a strong in silico functional support. Conclusions This multi-step strategy, combined with an in-depth in silico functional analysis, offers a comprehensive approach to advance the study of PC genetic susceptibility and could be applied to other diseases.

Background and Aims Pancreatic ductal adenocarcinoma is an aggressive disease most often diagnosed after local progression or metastatic dissemination, precluding resection and resulting in a high mortality rate. For individuals with elevated personal risk of the development of pancreatic cancer, EUS is a frequently used advanced imaging and diagnostic modality. However, variability in the expertise and definition of EUS findings exists among gastroenterologists, as well as a lack of standardized reporting of relevant findings at the time of examination. Adoption of standardized EUS reporting, using a universally accepted and agreed on terminology, is needed. Methods A consensus statement designed to create a standardized reporting template was authored by a multidisciplinary group of experts in pancreatic diseases that includes gastroenterologists, radiologists, surgeons, oncologists, and geneticists. This statement was developed using a modified Delphi process as part of the Pancreatic Cancer Early Detection Consortium, and >75% agreement was required to reach consensus. Results We identified reporting elements and present standardized reporting templates for EUS indications, procedural data, EUS image capture, and descriptors of findings, tissue sampling, and postprocedural assessment of adequacy. Conclusions Adoption of this standardized EUS reporting template should improve consistency in clinical decision-making for individuals with elevated risk of pancreatic cancer by providing complete and accurate reporting of pancreatic abnormalities. Standardization will also help to facilitate research and clinical trial design by using clearly defined and consistent imaging descriptions, thus allowing for comparison of results across different centers. Pancreatic ductal adenocarcinoma is an aggressive disease most often diagnosed after local progression or metastatic dissemination, precluding resection and resulting in a high mortality rate. For individuals with elevated personal risk of the development of pancreatic cancer, EUS is a frequently used advanced imaging and diagnostic modality. However, variability in the expertise and definition of EUS findings exists among gastroenterologists, as well as a lack of standardized reporting of relevant findings at the time of examination. Adoption of standardized EUS reporting, using a universally accepted and agreed on terminology, is needed. A consensus statement designed to create a standardized reporting template was authored by a multidisciplinary group of experts in pancreatic diseases that includes gastroenterologists, radiologists, surgeons, oncologists, and geneticists. This statement was developed using a modified Delphi process as part of the Pancreatic Cancer Early Detection Consortium, and >75% agreement was required to reach consensus. We identified reporting elements and present standardized reporting templates for EUS indications, procedural data, EUS image capture, and descriptors of findings, tissue sampling, and postprocedural assessment of adequacy. Adoption of this standardized EUS reporting template should improve consistency in clinical decision-making for individuals with elevated risk of pancreatic cancer by providing complete and accurate reporting of pancreatic abnormalities. Standardization will also help to facilitate research and clinical trial design by using clearly defined and consistent imaging descriptions, thus allowing for comparison of results across different centers.

Pancreatic cancer is a highly lethal cancer with limited diagnostic and therapeutic modalities.To begin to explore the genomic landscape of pancreatic cancer, we used massively parallel sequencing to catalog and compare transcribed regions and potential regulatory elements in two human cell lines derived from normal and cancerous pancreas.By RNA-sequencing, we identified 2,146 differentially expressed genes in these cell lines that were enriched in cancer related pathways and biological processes that include cell adhesion, growth factor and receptor activity, signaling, transcription and differentiation. Our high throughput Chromatin immunoprecipitation (ChIP) sequence analysis furthermore identified over 100,000 regions enriched in epigenetic marks, showing either positive (H3K4me1, H3K4me3, RNA Pol II) or negative (H3K27me3) correlation with gene expression. Notably, an overall enrichment of RNA Pol II binding and depletion of H3K27me3 binding were seen in the cancer derived cell line as compared to the normal derived cell line. By selecting genes for further assessment based on this difference, we confirmed enhanced expression of aldehyde dehydrogenase 1A3 (ALDH1A3) in two larger sets of pancreatic cancer cell lines and in tumor tissues as compared to normal derived tissues.As aldehyde dehydrogenase (ALDH) activity is a key feature of cancer stem cells, our results indicate that a member of the ALDH superfamily, ALDH1A3, may be upregulated in pancreatic cancer, where it could mark pancreatic cancer stem cells.

Objective To elucidate the genetic architecture of gene expression in pancreatic tissues. Design We performed expression quantitative trait locus (eQTL) analysis in histologically normal pancreatic tissue samples (n=95) using RNA sequencing and the corresponding 1000 genomes imputed germline genotypes. Data from pancreatic tumour-derived tissue samples (n=115) from The Cancer Genome Atlas were included for comparison. Results We identified 38 615 cis -eQTLs (in 484 genes) in histologically normal tissues and 39 713 cis -eQTL (in 237 genes) in tumour-derived tissues (false discovery rate &lt;0.1), with the strongest effects seen near transcriptional start sites. Approximately 23% and 42% of genes with significant cis -eQTLs appeared to be specific for tumour-derived and normal-derived tissues, respectively. Significant enrichment of cis -eQTL variants was noted in non-coding regulatory regions, in particular for pancreatic tissues (1.53-fold to 3.12-fold, p≤0.0001), indicating tissue-specific functional relevance. A common pancreatic cancer risk locus on 9q34.2 (rs687289) was associated with ABO expression in histologically normal (p=5.8×10 −8 ) and tumour-derived (p=8.3×10 −5 ) tissues. The high linkage disequilibrium between this variant and the O blood group generating deletion variant in ABO (exon 6) suggested that nonsense-mediated decay (NMD) of the ‘O’ mRNA might explain this finding. However, knockdown of crucial NMD regulators did not influence decay of the ABO ‘O’ mRNA, indicating that a gene regulatory element influenced by pancreatic cancer risk alleles may underlie the eQTL. Conclusions We have identified cis -eQTLs representing potential functional regulatory variants in the pancreas and generated a rich data set for further studies on gene expression and its regulation in pancreatic tissues.

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.

Abstract Background The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci. Methods We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci. Results We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci. Conclusions Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

The Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases workshop was a 1.5-day scientific conference at the National Institutes of Health (Bethesda, MD) that engaged clinical and basic science investigators interested in diseases of the pancreas. This report provides a summary of the proceedings from the workshop. The goals of the workshop were to forge connections and identify gaps in knowledge that could guide future research directions. Presentations were segregated into six major theme areas, including 1) pancreas anatomy and physiology, 2) diabetes in the setting of exocrine disease, 3) metabolic influences on the exocrine pancreas, 4) genetic drivers of pancreatic diseases, 5) tools for integrated pancreatic analysis, and 6) implications of exocrine-endocrine cross talk. For each theme, multiple presentations were followed by panel discussions on specific topics relevant to each area of research; these are summarized here. Significantly, the discussions resulted in the identification of research gaps and opportunities for the field to address. In general, it was concluded that as a pancreas research community, we must more thoughtfully integrate our current knowledge of normal physiology as well as the disease mechanisms that underlie endocrine and exocrine disorders so that there is a better understanding of the interplay between these compartments.

Genome-wide association studies have found type 2 diabetes-associated variants in the HNF1B gene to exhibit reciprocal associations with prostate cancer risk. We aimed to identify whether these variants may have an effect on cancer risk in general versus a specific effect on prostate cancer only.In a collaborative analysis, we collected data from GWAS of cancer phenotypes for the frequently reported variants of HNF1B, rs4430796 and rs7501939, which are in linkage disequilibrium (r(2) = 0.76, HapMap CEU). Overall, the analysis included 16 datasets on rs4430796 with 19,640 cancer cases and 21,929 controls; and 21 datasets on rs7501939 with 26,923 cases and 49,085 controls. Malignancies other than prostate cancer included colorectal, breast, lung and pancreatic cancers, and melanoma. Meta-analysis showed large between-dataset heterogeneity that was driven by different effects in prostate cancer and other cancers. The per-T2D-risk-allele odds ratios (95% confidence intervals) for rs4430796 were 0.79 (0.76, 0.83)] per G allele for prostate cancer (p<10(-15) for both); and 1.03 (0.99, 1.07) for all other cancers. Similarly for rs7501939 the per-T2D-risk-allele odds ratios (95% confidence intervals) were 0.80 (0.77, 0.83) per T allele for prostate cancer (p<10(-15) for both); and 1.00 (0.97, 1.04) for all other cancers. No malignancy other than prostate cancer had a nominally statistically significant association.The examined HNF1B variants have a highly specific effect on prostate cancer risk with no apparent association with any of the other studied cancer types.

Abstract Recent genome-wide association studies have identified independent susceptibility loci for prostate cancer that could influence risk through interaction with other, possibly undetected, susceptibility loci. We explored evidence of interaction between pairs of 13 known susceptibility loci and single nucleotide polymorphisms (SNP) across the genome to generate hypotheses about the functionality of prostate cancer susceptibility regions. We used data from Cancer Genetic Markers of Susceptibility: Stage I included 523,841 SNPs in 1,175 cases and 1,100 controls; Stage II included 27,383 SNPs in an additional 3,941 cases and 3,964 controls. Power calculations assessed the magnitude of interactions our study is likely to detect. Logistic regression was used with alternative methods that exploit constraints of gene–gene independence between unlinked loci to increase power. Our empirical evaluation demonstrated that an empirical Bayes (EB) technique is powerful and robust to possible violation of the independence assumption. Our EB analysis identified several noteworthy interacting SNP pairs, although none reached genome-wide significance. We highlight a Stage II interaction between the major prostate cancer susceptibility locus in the subregion of 8q24 that contains POU5F1B and an intronic SNP in the transcription factor EPAS1, which has potentially important functional implications for 8q24. Another noteworthy result involves interaction of a known prostate cancer susceptibility marker near the prostate protease genes KLK2 and KLK3 with an intronic SNP in PRXX2. Overall, the interactions we have identified merit follow-up study, particularly the EPAS1 interaction, which has implications not only in prostate cancer but also in other epithelial cancers that are associated with the 8q24 locus. Cancer Res; 71(9); 3287–95. ©2011 AACR.

Abstract Background The minor allele of SNP rs3803662 has been shown to correlate with increased breast cancer risk and with lower expression of TOX3 . The SNP is closely located to TOX3 residing within an uncharacterised gene LOC643714 . The aim of the study was to examine the association of the risk allele with expression of TOX3 and LOC643714, and of mRNA levels and genotype with clinical and pathological characteristics. Methods The SNP was genotyped in DNA isolated from blood and normal tissue from 160 breast cancer patients and mRNA levels were measured by microarrays and quantitative real-time (qRT)-PCR in breast tumours. Association with clinical and pathological characteristics was analysed by parametric tests. Results An association of the risk allele of rs3803662 with lower TOX3 expression was confirmed in oestrogen receptor (ER) positive tumours. It was more often observed in lobular tumours (p = 0.04), and carriers of the risk allele who had been diagnosed with luminal A tumours had shorter overall survival (OS) than carriers of the non-risk allele (p = 0.01). Positive correlation between the mRNA levels of TOX3 and LOC643714 was observed (r = 0.44 and p &lt; 0.001). Association analysis with tumour pathology showed that low TOX3 and LOC643714 expression correlated with high Ki67 levels (p = 0.026 and p = 0.002) and the basal subtype (p &lt; 0.001 and p &lt; 0.001), whereas high expression correlated with ER (p = 0.004 and p &lt; 0.001) and progesterone receptor (PgR) (p = 0.005 and p &lt; 0.001) expression. Furthermore, high TOX3 and LOC643714 correlated with positive lymph nodes (p &lt; 0.001 and p = 0.01). Patients with ER positive tumours and high levels of TOX3 mRNA had shorter overall- and distant metastasis free-survival (p = 0.017 and p = 0.021), an effect mostly attributable to patients with luminal B tumours. Conclusions The results suggest that the effect of the risk allele of rs3803662 is strongest in luminal A tumours and that the expression levels of TOX3 and/or LOC643714 affect the progression of breast cancer. The effect may vary depending on the subtype and developmental stage of the tumour.

BackgroundGenome-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.

Abstract Background: Leukocyte telomere length has been associated with risk of subsequent pancreatic cancer. Few prospective studies have evaluated the association of prediagnostic leukocyte telomere length with pancreatic cancer survival. Methods: We prospectively examined the association of prediagnostic leukocyte telomere length with overall survival (OS) time among 423 participants diagnosed with pancreatic adenocarcinoma between 1984 and 2008 within the Health Professionals Follow-up Study, Nurses' Health Study, Physicians' Health Study, and Women's Health Initiative. We measured prediagnostic leukocyte telomere length in banked blood samples using quantitative PCR. Cox proportional hazards models were used to estimate HRs for OS with adjustment for potential confounders. We also evaluated 10 SNPs at the telomerase reverse transcriptase locus. Results: Shorter prediagnostic leukocyte telomere length was associated with reduced OS among patients with pancreatic cancer (Ptrend = 0.04). The multivariable-adjusted HR for OS comparing the lowest with highest quintiles of leukocyte telomere length was 1.39 (95% confidence interval, 1.01–1.93), corresponding to a 3-month difference in median OS time. In an analysis excluding cases with blood collected within 2 years of cancer diagnosis, the association was moderately stronger (HR, 1.55; 95% confidence interval, 1.09–2.21; comparing the lowest with highest quintiles; Ptrend = 0.01). No prognostic association or effect modification for the prognostic association of prediagnostic leukocyte telomere length was noted in relation to the studied SNPs. Conclusions: Prediagnostic leukocyte telomere length was associated with pancreatic cancer survival. Impact: Prediagnostic leukocyte telomere length can be a prognostic biomarker in pancreatic cancer.

<h2>Abstract</h2> The complex relationship between chromatin accessibility, transcriptional regulation, and cancer transitions presents a daunting puzzle. Terekhanova et al. created a pan-cancer epigenetic and transcriptomic atlas at single-cell resolution, yielding important insights into the underlying chromatin architecture of cancer transitions and novel discoveries with the potential to advance precision medicine.

Single nucleotide polymorphisms (SNPs) in the KLK3 gene on chromosome 19q13.33 are associated with serum prostate-specific antigen (PSA) levels. Recent genome wide association studies of prostate cancer have yielded conflicting results for association of the same SNPs with prostate cancer risk. Since the KLK3 gene encodes the PSA protein that forms the basis for a widely used screening test for prostate cancer, it is critical to fully characterize genetic variation in this region and assess its relationship with the risk of prostate cancer. We have conducted a next-generation sequence analysis in 78 individuals of European ancestry to characterize common (minor allele frequency, MAF >1%) genetic variation in a 56 kb region on chromosome 19q13.33 centered on the KLK3 gene (chr19:56,019,829-56,076,043 bps). We identified 555 polymorphic loci in the process including 116 novel SNPs and 182 novel insertion/deletion polymorphisms (indels). Based on tagging analysis, 144 loci are necessary to tag the region at an r (2) threshold of 0.8 and MAF of 1% or higher, while 86 loci are required to tag the region at an r (2) threshold of 0.8 and MAF >5%. Our sequence data augments coverage by 35 and 78% as compared to variants in dbSNP and HapMap, respectively. We observed six non-synonymous amino acid or frame shift changes in the KLK3 gene and three changes in each of the neighboring genes, KLK15 and KLK2. Our study has generated a detailed map of common genetic variation in the genomic region surrounding the KLK3 gene, which should be useful for fine-mapping the association signal as well as determining the contribution of this locus to prostate cancer risk and/or regulation of PSA expression.

Genome-wide association studies (GWAS) have identified multiple SNPs associated with prostate cancer (PrCa). Population isolates may have different sets of risk alleles for PrCa constituting unique population and individual risk profiles.To test this hypothesis, associations between 31 GWAS SNPs of PrCa were examined among 979 PrCa cases and 1,251 controls of Ashkenazic descent using logistic regression. We also investigated risks by age at diagnosis, pathological features of PrCa, and family history of cancer. Moreover, we examined associations between cumulative number of risk alleles and PrCa and assessed the utility of risk alleles in PrCa risk prediction by comparing the area under the curve (AUC) for different logistic models.Of the 31 genotyped SNPs, 8 were associated with PrCa at p ≤ 0.002 (corrected p-value threshold) with odds ratios (ORs) ranging from 1.22 to 1.42 per risk allele. Four SNPs were associated with aggressive PrCa, while three other SNPs showed potential interactions for PrCa by family history of PrCa (rs8102476; 19q13), lung cancer (rs17021918; 4q22), and breast cancer (rs10896449; 11q13). Men in the highest vs. lowest quartile of cumulative number of risk alleles had ORs of 3.70 (95% CI 2.76-4.97); 3.76 (95% CI 2.57-5.50), and 5.20 (95% CI 2.94-9.19) for overall PrCa, aggressive cancer and younger age at diagnosis, respectively. The addition of cumulative risk alleles to the model containing age at diagnosis and family history of PrCa yielded a slightly higher AUC (0.69 vs. 0.64).These data define a set of risk alleles associated with PrCa in men of Ashkenazic descent and indicate possible genetic differences for PrCa between populations of European and Ashkenazic ancestry. Use of genetic markers might provide an opportunity to identify men at highest risk for younger age of onset PrCa; however, their clinical utility in identifying men at highest risk for aggressive cancer remains limited.

Due mainly to a late stage at diagnosis and lack of effective treatment modalities, pancreatic cancer (PC) is a highly lethal malignancy with an overall 5-year survival rate of only 12%.1Siegel R.L. Miller K.D. Wagle N.S. et al.Cancer statistics, 2023.CA A Cancer J. Clin. 2023; 73: 17-48Crossref PubMed Scopus (425) Google Scholar Separating patients into those diagnosed with late-stage disease with distant metastases and those diagnosed with localized tumors reveals a striking difference of 3% vs. 44% 5-year survival rates, respectively. Increasing the fraction of patients detected at an early stage, when PC is most likely to be curable, could therefore be of a major benefit. While imaging-based early-detection screening methods (e.g., endoscopic ultrasound and magnetic resonance imaging) are increasingly recommended for carriers of germline pathogenic variants in cancer susceptibility genes conferring a high lifetime risk of pancreatic cancer, such screening is not practical in the general population due to the low incidence of PC and a lack of a proven benefit. Recently, Placido et al. designed an artificial intelligence (AI) tool to predict PC up to 3 years before diagnosis based on electronic healthcare records.2Placido D. Yuan B. Hjaltelin J.X. et al.A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories.Nat. Med. 2023; 29: 1113-1122Crossref PubMed Scopus (1) Google Scholar Prior to using deep learning algorithms, advanced risk assessment model building requires large and comprehensive datasets for training, development, and testing. Without enough statistical power, such prediction models are not likely to succeed. Placido et al. used disease trajectories for 9 million patients from two independent healthcare systems (the Danish National Patient Registry [DNPR] and the United States Veterans Affairs [US-VA]). The population-wide DNPR dataset is one of the largest and most comprehensive longitudinal real-world clinical datasets available containing 229 million hospital diagnoses for 8.6 million patients diagnosed in Denmark from 1977 to 2018. This resource provides unique opportunities for clinical risk assessment model building. For validation, Placido et al. used longitudinal clinical records from the US-VA dataset, which includes 16 million patients diagnosed from 1999 to 2020. After quality control, 6 and 3 million patients were selected from the DNPR and US-VA datasets for AI model training and testing, including 23,985 and 3,864 PC cases, respectively. It is worth noting that (1) the healthcare records in the DNPR dataset had longer (median 23 years in DNPR vs. 12 years in US-VA) but less dense (median 22 records patient in DNPR vs. 188 records per patient in US-VA) disease trajectories, (2) the majority of patients in the DNPR dataset were of Northern European background compared to a more diverse population in the US-VA dataset, and (3) gender distribution in the DNPR dataset was balanced (49.7% male vs. 50.3% female), while a majority of patients in the US-VA were male (85.7% male vs. 14.3% female). The heterogeneity between these two datasets highlights potential challenges for cross-applications of machine learning (ML) models trained in different healthcare systems and populations but also provided an opportunity to compare AI models in two real-life healthcare systems. Both the DNPR and US-VA datasets were randomly split into training (80%), development (10%), and testing (10%) subsets for the downstream ML and test process, respectively. Development of deep learning methods is crucial to analyzing such large-scale but also potentially noisy clinical datasets. Placido et al. developed a sequential AI model to train longitudinal disease trajectories (including 2,000 level 3 International Classification of Diseases [ICD] codes) with time stamps to predict time-dependent (3, 6, 12, 36, or 60 months after the time of risk assessment) risk scores. Among the four ML models (bag-of-words, gated recurrent unit [GRU], multilayer perceptron [MLP], and Transformer) tested in this study, the self-attention-based Transformer model3Vaswani A. Shazeer N. Parmar N. et al.Attention is all you need.Adv. Neural Inf. Process. Syst. 2017; : 5998-6008Google Scholar performed best with an area under the receiver operating characteristic (AUROC) curve of 0.88 within 3 years prior to diagnoses of PC in the DNPR dataset. Moreover, the GRU, MLP, and Transformer models outperformed a previously published non-AI-based prediction model that integrated polygenic risk scores (PRS) and clinical risk factors from 1,042 pancreatic ductal adenocarcinoma (PDAC) cases and 10,420 matched cancer-free controls drawn from the UK Biobank (AUROC of 0.83).4Sharma S. Tapper W.J. Collins A. et al.Predicting pancreatic cancer in the UK Biobank Cohort using polygenic risk scores and diabetes mellitus.Gastroenterology. 2022; 162: 1665-1674.e2Abstract Full Text Full Text PDF PubMed Scopus (12) Google Scholar An out-of-box validation is vital for any risk prediction model. Placido et al. applied the best ML model trained in the DNPR dataset to disease records from patients in the independent US-VA dataset. Compared with the DNPR dataset, prediction performance in US-VA declined from an AUROC of 0.88 to 0.71 for PC occurrence within 3 years after assessment. Due to differences between the two healthcare systems, Placido et al. also retrained and revaluated the AI model in the US-VA dataset with an improved performance (AUROC of 0.78) for PC occurring within 3 years. Validation in the US-VA dataset suggested that model generalizability can be tricky when using data from different healthcare systems, and retraining AI models from scratch for each clinical dataset is likely to improve risk prediction performance. This, however, may not always be possible due to differences in healthcare systems across regions and countries and the fact that health records may be distributed across many healthcare systems (e.g., different doctors’ offices and hospital systems). Furthermore, to assess the performance of their models in a setting more similar to a realistic PC surveillance program, Placido et al. excluded diagnoses within the 3 months prior to PC diagnoses for model training. This yielded a relative risk (RR) = 58.7 for DNPR and RR = 33.1 for US-VA for the 0.1% highest-risk individuals over the age of 50 during the 12-month prediction period. Previous known clinical and lifestyle risk factors for PC include type 2 diabetes (T2D), pancreatitis, smoking, and obesity, as well as both common and rare germline genetic variants.5Stolzenberg-Solomon R.Z. Amundadottir L.T. Epidemiology and inherited Predisposition for Sporadic pancreatic adenocarcinoma.Hematol Oncol Clin North Am. 2015; 29: 619-640Abstract Full Text Full Text PDF PubMed Scopus (25) Google Scholar While lifestyle and genetic risk factors were not assessed in the current study, disease codes representing 23 known PC risk factors (a subset of the 2,000 level 3 ICD codes) were chosen to test a “known risk factor” model. This reduced prediction accuracy (from AUROC of 0.88 to 0.84), indicating that as of yet unknown risk factors may improve PC risk prediction accuracy. Moreover, by a feature extraction approach, most known risk factors made a significant contribution to the ML prediction of PC occurrence. While a deep ML algorithm typically is a black box for users, it is important to know which features contribute to the best-performing ML prediction models. The top contributing features were therefore extracted from clinical records with time to PC diagnosis within 0–6, 6–12, 12–24 and 24–36 months after assessment for all patients who developed PC. This indicated known (e.g., T2D, acute pancreatitis) but also potentially novel PC risk indicators (e.g., gallstones, gastritis, reflux disease), possibly pointing to mechanisms related to inflammation of the pancreas, in line with pancreatitis. However, more work is needed to establish if these possibly new risk indicators directly influence PC risk or not. Not surprisingly, no single diagnosis had sufficient power to predict PC. Although this study provides the best prediction model for PC risk assessment available to date in the general population, sensitivity in DNPR was only 8% and 4% for PC occurring within 1 and 3 years after assessment, respectively. Therefore, additional model improvements are important. This could be achieved by including (1) rare high-risk germline variants, (2) PRS (improvements in current PRS models are expected with larger ongoing genome-wide association studies of PDAC by the Pancreatic Cancer Cohort Consortium, the Pancreatic Cancer Case-Control Consortium, and other studies), (3) lifestyle factors, (4) blood-derived biomarkers, and (5) imaging-based indicators, as well as (6) separately analyzing patients diagnosed with the more lethal PDAC vs. the less lethal pancreatic neuroendocrine tumor subtype, when training deep ML models (Figure 1). This may significantly improve risk prediction accuracy and identify individuals at a greatly increased risk of developing PC or those already with undiagnosed early-stage PC. In addition to evaluating the performance of different AI models using AUROC and RR as done here by Placido et al., comparing the number of patients identified at a high-risk of PC using an absolute risk framework might also help. In summary, the study by Placido et al. shows that cutting-edge AI methods may indeed help improve early PC risk prediction and identify individuals from the general population that would benefit from surveillance strategies now only used in carriers of germline pathogenic variants. Further AI modeling based on the above recommendations has the potential to predict PC with an even higher accuracy. An important next step before such models can be more widely applied is to assess how surveillance strategies designed for such groups of high-risk individuals facilitate early PC detection in clinical trials and improve survival while minimizing overdiagnoses and potential harm. The authors are supported by the Intramural Research Program (IRP) of the Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute (NCI), US National Institutes of Health (NIH). The content of this publication does not necessarily reflect the views or policies of the US Department of Health and Human Services, nor does the mention of trade names, commercial products, or organizations imply endorsement by the US Government. The authors declare no competing interests.

Genome-wide association studies (GWAS) have identified multiple common susceptibility loci for pancreatic cancer. Here we report fine-mapping and functional analysis of one such locus residing in a 610 kb gene desert on chr13q22.1 (marked by rs9543325). The closest candidate genes, KLF5, KLF12, PIBF1, DIS3 and BORA, range in distance from 265-586 kb. Sequencing three sub-regions containing the top ranked SNPs by imputation P-value revealed a 30 bp insertion/deletion (indel) variant that was significantly associated with pancreatic cancer risk (rs386772267, P = 2.30 × 10−11, OR = 1.22, 95% CI 1.15–1.28) and highly correlated to rs9543325 (r2 = 0.97 in the 1000 Genomes EUR population). This indel was the most significant cis-eQTL variant in a set of 222 histologically normal pancreatic tissue samples (β = 0.26, P = 0.004), with the insertion (risk-increasing) allele associated with reduced DIS3 expression. DIS3 encodes a catalytic subunit of the nuclear RNA exosome complex that mediates RNA processing and decay, and is mutated in several cancers. Chromosome conformation capture revealed a long range (570 kb) physical interaction between a sub-region of the risk locus, containing rs386772267, and a region ∼6 kb upstream of DIS3. Finally, repressor regulatory activity and allele-specific protein binding by transcription factors of the TCF/LEF family were observed for the risk-increasing allele of rs386772267, indicating that expression regulation at this risk locus may be influenced by the Wnt signaling pathway. In conclusion, we have identified a putative functional indel variant at chr13q22.1 that associates with decreased DIS3 expression in carriers of pancreatic cancer risk-increasing alleles, and could therefore affect nuclear RNA processing and/or decay.

Chromosome 8q24 has emerged as an important genetic susceptibility region for several cancers, including prostate cancer; however, little is known about the contribution of DNA methylation in this region to risk. We prospectively evaluated DNA methylation at 8q24 in relation to prostate cancer using pre-diagnostic blood samples from 694 prostate cancer cases (including 172 aggressive cases) and 703 controls in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. We used logistic regression to estimate odds ratios and 95% confidence intervals. Although none remained significant after adjustment for multiple testing (q>0.05), of the 50 CpG sites meeting quality control, we identified 8 sites that were nominally associated with prostate cancer (Ptrend<0.05), including 6 correlated (Spearman ρ: 0.20–0.52) sites in POU5F1B and 2 intergenic sites (most significant site: Chr8:128428897 in POU5F1B, Ptrend=0.01). We also identified two correlated (ρ=0.39) sites in MYC (Chr8:128753187 and Chr8:128753154) that were associated with aggressive (Ptrend=0.02 and 0.03), but not non-aggressive disease (Ptrend=0.70 and 0.20; Pheterogeneity=0.01 and 4.6 × 10−3). These findings persisted after adjustment for the top 8q24 prostate cancer variants in our study. Although requiring replication, our findings provide some evidence that 8q24 DNA methylation levels may be associated with prostate cancer risk.

Abstract Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P &amp;lt; 5 × 10–8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82–0.93; former smokers 1.00, 95% CI, 0.91–1.07; current smokers 1.25, 95% CI 1.12–1.40, Pinteraction = 3.08 × 10–9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. Significance: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.

Genetic variation on the Y chromosome has not been convincingly implicated in prostate cancer risk. To comprehensively analyze the role of inherited Y chromosome variation in prostate cancer risk in individuals of European ancestry, we genotyped 34 binary Y chromosome markers in 3,995 prostate cancer cases and 3,815 control subjects drawn from four studies. In this set, we identified nominally significant association between a rare haplogroup, E1b1b1c, and prostate cancer in stage I (P = 0.012, OR = 0.51; 95% confidence interval 0.30-0.87). Population substructure of E1b1b1c carriers suggested Ashkenazi Jewish ancestry, prompting a replication phase in individuals of both European and Ashkenazi Jewish ancestry. The association was not significant for prostate cancer overall in studies of either Ashkenazi Jewish (1,686 cases and 1,597 control subjects) or European (686 cases and 734 control subjects) ancestry (P(meta) = 0.078), but a meta-analysis of stage I and II studies revealed a nominally significant association with prostate cancer risk (P(meta) = 0.010, OR = 0.77; 95% confidence interval 0.62-0.94). Comparing haplogroup frequencies between studies, we noted strong similarities between those conducted in the US and France, in which the majority of men carried R1 haplogroups, resembling Northwestern European populations. On the other hand, Finns had a remarkably different haplogroup distribution with a preponderance of N1c and I1 haplogroups. In summary, our results suggest that inherited Y chromosome variation plays a limited role in prostate cancer etiology in European populations but warrant follow-up in additional large and well characterized studies of multiple ethnic backgrounds.

Melanoma cases may exist in pancreatic cancer kindreds, whereas there is increased risk of pancreatic cancer in familial melanoma. The two cancers may share genetic susceptibility variants in common.Three dbGaP (datasets in Genotypes and Phenotypes)-deposited GWAS (genome-wide association study) datasets (MD Anderson melanoma, PanScan 1, and PanScan 2 for pancreatic cancer) were used. Thirty-seven melanoma susceptibility variants in 22 genomic regions from published GWAS, plus melanoma-related genes and pathways were examined for pancreatic cancer risk in the PanScan datasets. Conversely, nine known pancreatic cancer susceptibility variants were examined for melanoma risk in the MD Anderson dataset.In the PanScan data, initial associations were found with melanoma susceptibility variants in NCOA6 [rs4911442; OR, 1.32; 95% confidence interval (CI), 1.03-1.70; P = 0.03], YWHAZP5 (rs17119461; OR, 2.62; 95% CI, 1.08-6.35; P = 0.03), and YWHAZP5 (rs17119490; OR, 2.62; 95% CI, 1.08-6.34; P = 0.03), TYRP1 (P = 0.04), and IFNA13 (P = 0.04). In the melanoma dataset, two pancreatic cancer susceptibility variants were associated: NR5A2 (rs12029406; OR, 1.39; 95% CI, 1.01-1.92; P = 0.04) and CLPTM1L-TERT (rs401681; OR, 1.16; 95% CI, 1.01-1.34; P = 0.04). None of these associations remained significant after correcting for multiple comparisons.Reported variants of melanoma genes and pathways do not play a role in pancreatic cancer predisposition. Reciprocally, pancreatic cancer susceptibility variants are not associated with melanoma risk.Known melanoma-related genes and pathways, as well as GWAS-derived susceptibility variants of melanoma and pancreatic cancer, do not explain the shared genetic etiology of these two cancers. Cancer Epidemiol Biomarkers Prev; 23(6); 1121-4. ©2014 AACR.

Chromosome 8q24 has emerged as an important region for genetic susceptibility to various cancers, but little is known about the contribution of DNA methylation at 8q24. To evaluate variability in DNA methylation levels at 8q24 and the relationship with cancer susceptibility single nucleotide polymorphisms (SNPs) in this region, we quantified DNA methylation levels in peripheral blood at 145 CpG sites nearby 8q24 cancer susceptibility SNPs or MYC using pyrosequencing among 80 Caucasian men in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. For the 60 CpG sites meeting quality control, which also demonstrated temporal stability over a 5-year period, we calculated pairwise Spearman correlations for DNA methylation levels at each CpG site with 42 8q24 cancer susceptibility SNPs. To account for multiple testing, we adjusted P values into q values reflecting the false discovery rate (FDR). In contrast to the MYC CpG sites, most sites nearby the SNPs demonstrated good reproducibility, high methylation levels, and moderate-high between-individual variation. We observed 10 statistically significant (FDR < 0.05) CpG site-SNP correlations. These included correlations between an intergenic CpG site at Chr8:128393157 and the prostate cancer SNP rs16902094 (ρ = -0.54; P = 9.7 × 10(-7); q = 0.002), a PRNCR1 CpG site at Chr8:128167809 and the prostate cancer SNP rs1456315 (ρ = 0.52; P = 1.4 × 10(-6); q = 0.002), and two POU5F1B CpG sites and several prostate/colorectal cancer SNPs (for Chr8:128498051 and rs6983267, ρ = 0.46; P = 2.0 × 10(-5); q = 0.01). This is the first report of correlations between blood DNA methylation levels and cancer susceptibility SNPs at 8q24, suggesting that DNA methylation at this important susceptibility locus may contribute to cancer risk.

Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the TERT and CLPTM1L genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.

We have investigated microsatellite instability (MSI) in colorectal, gastric, endometrial and ovarian cancer as a result of mismatch repair (MMR) deficiency. We detected frameshift mutations in several genes that carry short repeated sequences and are important in cell fidelity and growth control; hMSH3, hMSH6, BAX, IGFIIR, TGFbetaIIR, E2F4 and BRCA2. Accumulation of mutations was heterogeneous and mainly restricted to tumours showing MSI at several loci (MSI-H). Both insertions and deletions were evident and occasional intratumour heterogeneity was evident with more than one different additional allele in the tumour. Most MSI-H tumours had acquired mutations in more than one gene and longer repeated sequences were more frequently targets for mutations. The TGFbetaIIR gene was mutated in 62%, the hMSH3 gene in 43%, the E2F4 gene in 35%, the hMSH6 in 32%, the BAX gene in 32%, the IGFIIR gene in 26%, and the BRCA2 gene in 2% of the MSI-H tumours. Homozygous mutations or mutation of both alleles were evident in all genes except BRCA2, in total 23/105 mutated cases, varying from 7% for BAX to 50% for E2F4. E2F4 mutations were exclusively found in colon tumours and E2F4 polymorphisms was found in 8% of cases. No difference in mutation prevalence was noted between cancer types apart from TGFbetaIIR mutations, which were frequently found in colon and gastric tumours but not in endometrial tumours, suggesting that endometrial tumours progress by a different route where TGFbetaIIR mutations are less favourable.

Epidemiological studies have suggested positive associations for iron and red meat intake with risk of pancreatic ductal adenocarcinoma (PDAC). Inherited pathogenic variants in genes involved in the hepcidin-regulating iron metabolism pathway are known to cause iron overload and hemochromatosis. The objective of this study was to determine whether common genetic variation in the hepcidin-regulating iron metabolism pathway is associated with PDAC. We conducted a pathway analysis of the hepcidin-regulating genes using single nucleotide polymorphism (SNP) summary statistics generated from 4 genome-wide association studies in 2 large consortium studies using the summary data-based adaptive rank truncated product method. Our population consisted of 9253 PDAC cases and 12,525 controls of European descent. Our analysis included 11 hepcidin-regulating genes [bone morphogenetic protein 2 (BMP2), bone morphogenetic protein 6 (BMP6), ferritin heavy chain 1 (FTH1), ferritin light chain (FTL), hepcidin (HAMP), homeostatic iron regulator (HFE), hemojuvelin (HJV), nuclear factor erythroid 2-related factor 2 (NRF2), ferroportin 1 (SLC40A1), transferrin receptor 1 (TFR1), and transferrin receptor 2 (TFR2)] and their surrounding genomic regions (±20 kb) for a total of 412 SNPs. The hepcidin-regulating gene pathway was significantly associated with PDAC (P = 0.002), with the HJV, TFR2, TFR1, BMP6, and HAMP genes contributing the most to the association. Our results support that genetic susceptibility related to the hepcidin-regulating gene pathway is associated with PDAC risk and suggest a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate effect modification by intake of iron-rich foods on this association.

The purpose of this study was to examine the pathology of all germ cell tumours of the testis diagnosed in Iceland 1955–2002. A total of 214 patients were included in the study. The current age‐standardized incidence was found to be 6.1 per 100,000 and had increased almost fourfold during the study period. Seminoma was diagnosed in 55% of cases. Non‐seminomas were diagnosed in 45%, and these were further classified as mixed germ cell tumours (33%), embryonal carcinoma (8%), teratoma (3%), and yolk sac tumour (n=1). The mean age at diagnosis was significantly higher for the seminomas than the non‐seminomas (38 years versus 29 years) (p&lt;0.001) and the non‐seminomas were diagnosed at a significantly higher stage than the seminomas (p&lt;0.001). Thus, in seminoma patients the tumour was localized to the testis (stage I) in 81% of cases, in 17% of patients the tumour had spread to the lymph nodes (stage II or III), and only 2% had extranodal metastasis at diagnosis (stage IV). In contrast, in the non‐seminoma patients, the tumours were found to be stage I in 56%, stage II or III in 24%, and stage IV in 20% of cases. No significant difference in staging was found between non‐seminoma subtypes. Identification of necrosis or vascular invasion was significantly associated with metastatic disease at diagnosis (p=0.002). During the study period a significant increase in stage I tumours was found as well as a decrease in the size of the tumours.

Abstract Background: Whether circulating polyunsaturated fatty acid (PUFA) levels are associated with pancreatic cancer risk is uncertain. Mendelian randomization (MR) represents a study design using genetic instruments to better characterize the relationship between exposure and outcome. Methods: We utilized data from genome-wide association studies within the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case–Control Consortium, involving approximately 9,269 cases and 12,530 controls of European descent, to evaluate associations between pancreatic cancer risk and genetically predicted plasma n-6 PUFA levels. Conventional MR analyses were performed using individual-level and summary-level data. Results: Using genetic instruments, we did not find evidence of associations between genetically predicted plasma n-6 PUFA levels and pancreatic cancer risk [estimates per one SD increase in each PUFA-specific weighted genetic score using summary statistics: linoleic acid odds ratio (OR) = 1.00, 95% confidence interval (CI) = 0.98–1.02; arachidonic acid OR = 1.00, 95% CI = 0.99–1.01; and dihomo-gamma-linolenic acid OR = 0.95, 95% CI = 0.87–1.02]. The OR estimates remained virtually unchanged after adjustment for covariates, using individual-level data or summary statistics, or stratification by age and sex. Conclusions: Our results suggest that variations of genetically determined plasma n-6 PUFA levels are not associated with pancreatic cancer risk. Impact: These results suggest that modifying n-6 PUFA levels through food sources or supplementation may not influence risk of pancreatic cancer.

Abstract Background: In Western populations, pancreatic ductal adenocarcinoma (PDAC) risk has been found to be greater among individuals with non-O blood types than those with O blood type. However, the association has not been fully evaluated with respect to FUT2 (determining secretor status) and FUT3 (determining Lewis antigens) status, two biologically important genes in the expression of ABO blood groups with PDAC. Methods: We examined interactions in data from 8,027 cases and 11,362 controls in large pancreatic cancer consortia (PanScan I-III and PanC4) by using genetic variants to predict ABO blood groups (rs505922 and rs8176746), secretor status (rs601338), and Lewis antigens (rs812936, rs28362459, and rs3894326). Multivariable logistic regression was used to estimate ORs and 95% confidence intervals (CI) of the risk of PDAC adjusted for age and sex. We examined multiplicative interactions of ABO with secretor status and Lewis antigens by considering each product term between ABO and secretor and between ABO and Lewis antigens individually. Results: We found that the increased risk associated with non-O blood groups was somewhat stronger among secretors than nonsecretors [ORs, 1.28 (95% CI, 1.15–1.42) and 1.17 (95% CI, 1.03–1.32) respectively; Pinteraction = 0.002]. We did not find any interactions between ABO and Lewis antigens. Conclusions: Our large consortia data provide evidence of effect modification in the association between non-O blood type and pancreatic cancer risk by secretor status. Impact: Our results indicate that the association between ABO blood type and PDAC risk may vary by secretor status, but not by Lewis antigens.

Testicular germ cell tumors (TGCT) arise by multistep carcinogenesis pathways involving selective losses and gains of chromosome material. To locate cancer genes underlying this selection, we performed a genome-wide study of allelic imbalance (AI) in 32 tumors, using 710 microsatellite markers. The highest prevalence of AI was found at 12p, in line with previous studies finding consistent gain of the region in TGCTs. High frequency of AI was also observed at chromosome arms 4p, 9q, 10p, 11q, 11p, 13q, 16q, 18p, and 22q. Within 39 candidate regions identified by mapping of smallest regions of overlap (SROs), the highest frequency of AI was at 12p11.21∼p11.22 (62%), 12p12.1∼p13.1 (53%), 12p13.1∼p13.2 (53%), 11q14.1∼q14.2 (53%), 11p13∼p14.3 (47%), 9q21.13∼q21.32 (47%), and 4p15.1∼p15.2 (44%). Two genes known to be involved in cancer reside in these regions, ETV6 at 12p13.2 (TEL oncogene) and WT1 at 11p13. We also found a significant association (P = 0.02) between AI at 10q21.1∼q22.2 and higher clinical stage. This study contributes to the ongoing search for genes involved in transformation of germ cells and provides a useful reference point to previous studies using cytogenetic techniques to map chromosome changes in TGCTs.

The KRAS gene is the most frequently mutated gene in pancreatic cancer, and no successful anti-Ras therapy has been developed. Gastrin has been shown to stimulate pancreatic cancer in an autocrine fashion. We hypothesized that reactivation of the peptide gastrin collaborates with KRAS during pancreatic carcinogenesis.LSL-Kras; P48-Cre (KC) mutant KRAS transgenic mice were crossed with gastrin-KO (GKO) mice to develop GKO/KC mice. Pancreata were examined for 8 months for stage of pancreatic intraepithelial neoplasia lesions, inflammation, fibrosis, gastrin peptide, and microRNA expression. Pancreatic intraepithelial neoplasias from mice were collected by laser capture microdissection and subjected to reverse-phase protein microarray, for gastrin and protein kinases associated with signal transduction. Gastrin mRNA was measured by RNAseq in human pancreatic cancer tissues and compared to that in normal pancreas.In the absence of gastrin, PanIN progression, inflammation, and fibrosis were significantly decreased and signal transduction was reversed to the canonical pathway with decreased KRAS. Gastrin re-expression in the PanINs was mediated by miR-27a. Gastrin mRNA expression was significantly increased in human pancreatic cancer samples compared to normal human pancreas controls.This study supports the mitogenic role of gastrin in activation of KRAS during pancreatic carcinogenesis.

Abstract We analyzed summary-level data from genome-wide association studies (GWAS) of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) contributing to risk, as well as the distribution of their associated effect sizes. All cancers evaluated showed polygenicity, involving at a minimum thousands of independent susceptibility variants. For some malignancies, particularly chronic lymphoid leukemia (CLL) and testicular cancer, there are a larger proportion of variants with larger effect sizes than those for other cancers. In contrast, most variants for lung and breast cancers have very small associated effect sizes. For different cancer sites, we estimate a wide range of GWAS sample sizes, required to explain 80% of GWAS heritability, varying from 60,000 cases for CLL to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores, compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that polygenic risk scores have substantial potential for risk stratification for relatively common cancers such as breast, prostate and colon, but limited potential for other cancer sites because of modest heritability and lower disease incidence.

We show how to use reports of cancer in family members to discover additional genetic associations or confirm previous findings in genome-wide association (GWA) studies conducted in case-control, cohort, or cross-sectional studies. Our novel family history-based approach allows economical association studies for multiple cancers, without genotyping of relatives (as required in family studies), follow-up of participants (as required in cohort studies), or oversampling of specific cancer cases (as required in case-control studies). We empirically evaluate the performance of the proposed family history-based approach in studying associations with prostate and ovarian cancers, using data from GWA studies previously conducted within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. The family history-based method may be particularly useful for investigating genetic susceptibility to rare diseases for which accruing cases may be very difficult, by using disease information from nongenotyped relatives of participants in multiple case-control and cohort studies designed primarily for other purposes.

The presence of pancreatic cancer (PC) in melanoma-prone families has been consistently associated with an increased frequency of CDKN2A mutations, the major high-risk susceptibility gene identified for melanoma. However, the precise relationship between CDKN2A, melanoma and PC remains unknown. We evaluated a recently identified PC susceptibility gene PALB2 using both sequencing and tagging to determine whether PALB2 might explain part of the relationship between CDKN2A, melanoma, and PC. No disease-related mutations were identified from sequencing PALB2 in multiple pancreatic cancer patients or other mutation carrier relatives of PC patients from the eight melanoma-prone families with CDKN2A mutations and PC. In addition, no significant associations were observed between 11 PALB2 tagging SNPs and melanoma risk in 23 melanoma-prone families with CDKN2A mutations or the subset of 11 families with PC or PC-related CDKN2A mutations. The results suggested that PALB2 does not explain the relationship between CDKN2A, melanoma, and pancreatic cancer in these melanoma-prone families.

Abstract Background: The higher risk of pancreatic cancer in Ashkenazi Jews compared with non-Jews is only partially explained by the increased frequency of BRCA1 and BRCA2 mutations in Ashkenazi Jews. Methods: We evaluated the impact of 16 established pancreatic cancer susceptibility loci in a case–control sample of American Jews, largely Ashkenazi, including 406 full-Jewish pancreatic cancer patients and 2,332 full-Jewish controls, genotyped as part of the Pancreatic Cancer Cohort and Case–Control Consortium I/II (PanScan I/II), Pancreatic Cancer Case-Control Consortium (PanC4), and Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA) datasets. We compared risk in full-Jewish subjects with risk in part-Jewish; non-Jewish Southern European; and in the combined non-Jewish Eastern, Northern, Southern, and Western European (non-Jewish white European) subjects from the same datasets. Jewish ancestries were genetically identified using seeded Fast principal component analysis. Data were analyzed by unconditional logistic regression, and adjusted for age, sex, and principal components. Results: One SNP on chromosome 13q22.1 (rs9543325; OR, 1.36; 95% confidence interval, 1.16–1.58; P = 10−4.1) was significant in full-Jews. Individual ORs and minor allele frequencies were similar between Jewish and non-Jewish white European subjects. The average ORs across the 16 pancreatic cancer susceptibility loci for full-Jewish, full- plus part-Jewish, non-Jewish Southern European, and non-Jewish white European subjects were 1.25, 1.30, 1.31, and 1.26, respectively. Conclusions: The 16 pancreatic cancer susceptibility loci similarly impact Jewish and non-Jewish white European subjects, both individually and as summary odds. Impact: These 16 pancreatic cancer susceptibility loci likely do not explain the higher risk seen in Ashkenazi Jews. Cancer Epidemiol Biomarkers Prev; 26(10); 1540–8. ©2017 AACR.

Abstract Background: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level. Methods: We conducted a gene–environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I–III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case–control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics. Results: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P &amp;lt; 1.25 × 10−6) was observed in the meta-analysis (PGxE = 1.2 ×10−6, PJoint = 4.2 ×10−7). Conclusions: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans. Impact: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.

Registry-based epidemiologic studies suggest associations between chronic inflammatory intestinal diseases and pancreatic ductal adenocarcinoma (PDAC). As genetic susceptibility contributes to a large proportion of chronic inflammatory intestinal diseases, we hypothesize that the genomic regions surrounding established genome-wide associated variants for these chronic inflammatory diseases are associated with PDAC. We examined the association between PDAC and genomic regions (±500 kb) surrounding established common susceptibility variants for ulcerative colitis, Crohn's disease, inflammatory bowel disease, celiac disease, chronic pancreatitis, and primary sclerosing cholangitis. We analyzed summary statistics from genome-wide association studies data for 8,384 cases and 11,955 controls of European descent from two large consortium studies using the summary data-based adaptive rank truncated product method to examine the overall association of combined genomic regions for each inflammatory disease group. Combined genomic susceptibility regions for ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis were associated with PDAC at P values < 0.05 (0.0040, 0.0057, 0.011, and 3.4 × 10-6, respectively). After excluding the 20 PDAC susceptibility regions (±500 kb) previously identified by GWAS, the genomic regions for ulcerative colitis, Crohn disease, and inflammatory bowel disease remained associated with PDAC (P = 0.0029, 0.0057, and 0.0098, respectively). Genomic regions for celiac disease (P = 0.22) and primary sclerosing cholangitis (P = 0.078) were not associated with PDAC. Our results support the hypothesis that genomic regions surrounding variants associated with inflammatory intestinal diseases, particularly, ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis are associated with PDAC. SIGNIFICANCE: The joint effects of common variants in genomic regions containing susceptibility loci for inflammatory bowel disease and chronic pancreatitis are associated with PDAC and may provide insights to understanding pancreatic cancer etiology.

The “Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases” Workshop was a 1.5-day scientific conference at the National Institutes of Health (Bethesda, MD) that engaged clinical and basic science investigators interested in diseases of the pancreas. This report summarizes the workshop proceedings. The goal of the workshop was to forge connections and identify gaps in knowledge that could guide future research directions. Presentations were segregated into 6 major themes, including (a) Pancreas Anatomy and Physiology; (b) Diabetes in the Setting of Exocrine Disease; (c) Metabolic Influences on the Exocrine Pancreas; (d) Genetic Drivers of Pancreatic Diseases; (e) Tools for Integrated Pancreatic Analysis; and (f) Implications of Exocrine-Endocrine Crosstalk. For each theme, there were multiple presentations followed by panel discussions on specific topics relevant to each area of research; these are summarized herein. Significantly, the discussions resulted in the identification of research gaps and opportunities for the field to address. In general, it was concluded that as a pancreas research community, we must more thoughtfully integrate our current knowledge of the normal physiology as well as the disease mechanisms that underlie endocrine and exocrine disorders so that there is a better understanding of the interplay between these compartments.

Objective The objective of this study was to fine-map common pancreatic cancer susceptibility regions. Methods We conducted targeted Roche-454 resequencing across 428 kb in 3 genomic regions identified in genome-wide association studies (GWAS) of pancreatic cancer, on chromosomes 1q32.1, 5p15.33, and 13q22.1. Results An analytical pipeline for calling genotypes was developed using HapMap samples sequenced on chr5p15.33. Concordance to 1000 Genomes data for chr5p15.33 was greater than 96%. The concordance for chr1q32.1 and chr13q22.1 with pancreatic cancer GWAS data was greater than 99%. Between 9.2% and 19.0% of variants detected were not present in 1000 Genomes for the respective continental population. The majority of completely novel single-nucleotide polymorphisms (SNPs) were less common (minor allele frequency [MAF], ≤5%) or rare (MAF, ≤2%), illustrating the value of enlarging test sets for discovery of less common variants. Using the data set, we examined haplotype blocks across each region using a tag SNP analysis (r2 > 0.8 for MAF of ≥5%) and determined that at least 196, 243, and 63 SNPs are required for fine-mapping chr1q32.1, chr5p15.33, and chr13q22.1, respectively, in European populations. Conclusions We have characterized germline variation in 3 regions associated with pancreatic cancer risk and show that targeted resequencing leads to the discovery of novel variants and improves the completeness of germline sequence variants for fine-mapping GWAS susceptibility loci.

The evidence of a relation between folate intake and one-carbon metabolism (OCM) with pancreatic cancer (PanCa) is inconsistent. In this study, the association between genes and single-nucleotide polymorphisms (SNPs) related to OCM and PanCa was assessed.Using biochemical knowledge of the OCM pathway, we identified thirty-seven genes and 834 SNPs to examine in association with PanCa. Our study included 1,408 cases and 1,463 controls nested within twelve cohorts (PanScan). The ten SNPs and five genes with lowest p values (<0.02) were followed up in 2,323 cases and 2,340 controls from eight case-control studies (PanC4) that participated in PanScan2. The correlation of SNPs with metabolite levels was assessed for 649 controls from the European Prospective Investigation into Cancer and Nutrition.When both stages were combined, we observed suggestive associations with PanCa for rs10887710 (MAT1A) (OR 1.13, 95 %CI 1.04-1.23), rs1552462 (SYT9) (OR 1.27, 95 %CI 1.02-1.59), and rs7074891 (CUBN) (OR 1.91, 95 %CI 1.12-3.26). After correcting for multiple comparisons, no significant associations were observed in either the first or second stage. The three suggested SNPs showed no correlations with one-carbon biomarkers.This is the largest genetic study to date to examine the relation between germline variations in OCM-related genes polymorphisms and the risk of PanCa. Suggestive evidence for an association between polymorphisms and PanCa was observed among the cohort-nested studies, but this did not replicate in the case-control studies. Our results do not strongly support the hypothesis that genes related to OCM play a role in pancreatic carcinogenesis.

Heritability analysis suggests that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases. Polygenic risk-score (PRS) is a widely used modelling technique that requires only availability of summary-level data from the discovery samples. We propose two modifications to improve the performance of PRS. First, we propose threshold dependent winners curse adjustments for marginal association coefficients that are used to weight the SNPs in PRS. Second, to exploit various external functional/annotation knowledge that might identify subset of SNPs highly enriched for association signals, we consider using variable thresholds for SNPs selection. We applied our methods to the GWAS summary-level data of fourteen complex diseases. Our analysis shows that while a simple winners curse correction uniformly leads to enhancement of performance of the models across traits, incorporation of functional SNPs was beneficial for only selected traits. Compared to standard PRS algorithm, the proposed methods in combination leads to substantial efficiency gain (25-50% increase in the prediction R2) for five out of fifteen diseases. As an example, for GWAS of type 2 diabetes, the lasso-based winners curse correction improves prediction R2 from 2.29% based on standard PRS to 3.1% (P=0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P=2.0E-5). Our simulation studies provided further clarification why differential treatment of certain category of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction due to non-uniform linkage disequilibrium structure.

Expression QTL (eQTL) analyses have suggested many genes mediating genome-wide association study (GWAS) signals but most GWAS signals still lack compelling explanatory genes. We have leveraged an adipose-specific gene regulatory network to infer expression regulator activities and phenotypic master regulators (MRs), which were used to detect activity QTLs (aQTLs) at cardiometabolic trait GWAS loci. Regulator activities were inferred with the VIPER algorithm that integrates enrichment of expected expression changes among a regulator’s target genes with confidence in their regulator-target network interactions and target overlap between different regulators (i.e., pleiotropy). Phenotypic MRs were identified as those regulators whose activities were most important in predicting their respective phenotypes using random forest modeling. While eQTLs were typically more significant than aQTLs in cis , the opposite was true among candidate MRs in trans . Several GWAS loci colocalized with MR trans -eQTLs/aQTLs in the absence of colocalized cis -QTLs. Intriguingly, at the 1p36.1 BMI GWAS locus the EPHB2 cis -aQTL was stronger than its cis -eQTL and colocalized with the GWAS signal and 35 BMI MR trans -aQTLs, suggesting the GWAS signal may be mediated by effects on EPHB2 activity and its downstream effects on a network of BMI MRs. These MR and aQTL analyses represent systems genetic methods that may be broadly applied to supplement standard eQTL analyses for suggesting molecular effects mediating GWAS signals.

Three authors are not included in the author byline. Laufey T. Amundadottir should be listed as the 8th author and affiliated with the Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. The contributions of this author are as follows: Performed the experiments, contributed reagents/materials/analysis/tools. Stephen J Chanock should be listed as the 15th author and affiliated with the National Cancer Institute, Division of Cancer Epidemiology & Genetics, Rockville. MD. The contributions of this author are as follows: performed the experiments, funded GWAS. Stephen Van Den Eeden should be listed as the 44th author and affiliated with the Kaiser Permanente Division of Research. 2000 Broadway, Oakland, CA 94612. The contributions of this author are as follows: conceived and designed the experiments, wrote the manuscript.