18 research outputs found

    Exome sequencing identifies nonsegregating nonsense ATM and PALB2 variants in familial pancreatic cancer.

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    We sequenced 11 germline exomes from five families with familial pancreatic cancer (FPC). One proband had a germline nonsense variant in ATM with somatic loss of the variant allele. Another proband had a nonsense variant in PALB2 with somatic loss of the variant allele. Both variants were absent in a relative with FPC. These findings question the causal mechanisms of ATM and PALB2 in these families and highlight challenges in identifying the causes of familial cancer syndromes using exome sequencing

    Exome-wide association study of pancreatic cancer risk

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    We conducted a case-control exome-wide association study to discover germline variants in coding regions that affect risk for pancreatic cancer, combining data from 5 studies. We analyzed exome and genome sequencing data from 437 patients with pancreatic cancer (cases) and 1922 individuals not known to have cancer (controls). In the primary analysis, BRCA2 had the strongest enrichment for rare inactivating variants (17/437 cases vs 3/1922 controls) (P=3.27x10(-6); exome-wide statistical significance threshold P<2.5x10(-6)). Cases had more rare inactivating variants in DNA repair genes than controls, even after excluding 13 genes known to predispose to pancreatic cancer (adjusted odds ratio, 1.35, P=.045). At the suggestive threshold (P<.001), 6 genes were enriched for rare damaging variants (UHMK1, AP1G2, DNTA, CHST6, FGFR3, and EPHA1) and 7 genes had associations with pancreatic cancer risk, based on the sequence-kernel association test. We confirmed variants in BRCA2 as the most common high-penetrant genetic factor associated with pancreatic cancer and we also identified candidate pancreatic cancer genes. Large collaborations and novel approaches are needed to overcome the genetic heterogeneity of pancreatic cancer predisposition

    Meta-Analysis of 1,200 Transcriptomic Profiles Identifies a Prognostic Model for Pancreatic Ductal Adenocarcinoma

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    PURPOSE: With a dismal 8% median 5-year overall survival, pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy. Only 10% to 20% of patients are eligible for surgery, and more than 50% of these patients will die within 1 year of surgery. Building a molecular predictor of early death would enable the selection of patients with PDAC who are at high risk. MATERIALS AND METHODS: We developed the Pancreatic Cancer Overall Survival Predictor (PCOSP), a prognostic model built from a unique set of 89 PDAC tumors in which gene expression was profiled using both microarray and sequencing platforms. We used a meta-analysis framework that was based on the binary gene pair method to create gene expression barcodes that were robust to biases arising from heterogeneous profiling platforms and batch effects. Leveraging the largest compendium of PDAC transcriptomic data sets to date, we show that PCOSP is a robust single-sample predictor of early death—1 year or less—after surgery in a subset of 823 samples with available transcriptomics and survival data. RESULTS: The PCOSP model was strongly and significantly prognostic, with a meta-estimate of the area under the receiver operating curve of 0.70 (P = 2.6E−22) and d-index (robust hazard ratio) of 1.9 (range, 1.6 to 2.3; ( = 1.4E−04) for binary and survival predictions, respectively. The prognostic value of PCOSP was independent of clinicopathologic parameters and molecular subtypes. Over-representation analysis of the PCOSP 2,619 gene pairs—1,070 unique genes—unveiled pathways associated with Hedgehog signaling, epithelial–mesenchymal transition, and extracellular matrix signaling. CONCLUSION: PCOSP could improve treatment decisions by identifying patients who will not benefit from standard surgery/chemotherapy but who may benefit from a more aggressive treatment approach or enrollment in a clinical trial

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

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    Background Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes. Methods We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided. Results We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P Conclusion Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.Peer reviewe

    Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer.

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

    Trajectories of physical activity, from young adulthood to older adulthood, and pancreatic cancer risk; a population-based case-control study in Ontario, Canada

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    Abstract Background There is inconsistent evidence on the association between physical activity and pancreatic cancer risk and few studies have investigated early life or life-course physical activity. The objective of this study was to evaluate the association between trajectories of physical activity across the life-course and pancreatic cancer risk. Methods A population-based case-control study was conducted (2011–2013) using cases (n = 315) from the Ontario Pancreas Cancer Study and controls (n = 1254) from the Ontario Cancer Risk Factor Study. Self-reported recall of moderate and vigorous physical activity was measured at three time points: young adulthood (20s–30s), mid-adulthood (40s–50s) and older-adulthood (1 year prior to questionnaire completion). Physical activity trajectories were identified using latent class analysis. Odds ratios (OR) and 95% confidence intervals (CI) were estimated from multivariable logistic regression adjusted for covariates: age, sex, race, alcohol, smoking, vegetable, fruit and meat consumption, and family history of pancreatic cancer. Results Six life-course physical activity trajectories were identified: inactive at all ages (41.2%), low activity at all ages (31.9%), increasingly active (3.6%), high activity in young adulthood with substantial decrease (13.0%), high activity in young adulthood with slight decrease (5.0%), and persistent high activity (5.3%). Compared to the inactive at all ages trajectory, the associations between each trajectory and pancreatic cancer after confounder adjustment were: low activity at all ages (OR: 1.11; 95% CI: 0.75, 1.66), increasingly active (OR: 1.11; 95% CI: 0.56, 2.21), high activity in young adulthood with substantial decrease in older adulthood (OR: 0.76; 95% CI: 0.47, 1.23), high activity in young adulthood with slight decrease in older adulthood (OR: 0.98; 95% CI: 0.62, 1.53), and persistently high activity (OR: 1.50; 95% CI: 0.86, 2.62). When time periods were evaluated separately, the OR for the association between high moderate activity in the 20s–30s and pancreatic cancer was 0.89 (95% CI: 0.64, 1.25) and some sex differences were observed. Conclusion Distinct life-course physical activity trajectories were identified, but there was no evidence that any of the trajectories were associated with pancreatic cancer. Future studies with larger sample sizes are needed to understand the associations between physical activity trajectories over the life-course and pancreatic cancer risk

    Exome sequencing identifies nonsegregating nonsense ATM and PALB2variants in familial pancreatic cancer

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    Abstract We sequenced 11 germline exomes from five families with familial pancreatic cancer (FPC). One proband had a germline nonsense variant in ATM with somatic loss of the variant allele. Another proband had a nonsense variant in PALB2 with somatic loss of the variant allele. Both variants were absent in a relative with FPC. These findings question the causal mechanisms of ATM and PALB2 in these families and highlight challenges in identifying the causes of familial cancer syndromes using exome sequencing
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