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

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.

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

Solution Structure of CCL19 and Identification of Overlapping CCR7 and PSGL-1 Binding Sites

CCL19 and CCL21 are chemokines involved in the trafficking of immune cells, particularly within the lymphatic system, through activation of CCR7. Concurrent expression of PSGL-1 and CCR7 in naive T-cells enhances recruitment of these cells to secondary lymphoid organs by CCL19 and CCL21. Here the solution structure of CCL19 is reported. It contains a canonical chemokine domain. Chemical shift mapping shows the N-termini of PSGL-1 and CCR7 have overlapping binding sites for CCL19 and binding is competitive. Implications for the mechanism of PSGL-1’s enhancement of resting T-cell recruitment are discussed

Solution Structure of CCL19 and Identification of Overlapping CCR7 and PSGL‑1 Binding Sites

CCL19 and CCL21 are chemokines involved in the trafficking of immune cells, particularly within the lymphatic system, through activation of CCR7. Concurrent expression of PSGL-1 and CCR7 in naive T-cells enhances recruitment of these cells to secondary lymphoid organs by CCL19 and CCL21. Here the solution structure of CCL19 is reported. It contains a canonical chemokine domain. Chemical shift mapping shows the N-termini of PSGL-1 and CCR7 have overlapping binding sites for CCL19 and binding is competitive. Implications for the mechanism of PSGL-1’s enhancement of resting T-cell recruitment are discussed