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

Abstract

Background: Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes. Methods: We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided. Results: We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P 1.3 Â 10 À5 ), the strongest associations were detected in five pathways and gene sets, including maturity-onset diabetes of the young, regulation of beta-cell development, role of epidermal growth factor (EGF) receptor transactivation by G protein-coupled receptors in cardiac hypertrophy pathways, and the Nikolsky breast cancer chr17q11-q21 amplicon and Pujana ATM Pearson correlation coefficient (PCC) network gene sets. We identified and validated rs876493 and three correlating SNPs (PGAP3) and rs3124737 (CASP7) from the Pujana ATM PCC gene set as eQTLs in two normal derived pancreas tissue datasets. Conclusion: Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.

Non-coding RNAs in Pancreatic Ductal Adenocarcinoma

“…In addition, PDAC development requires the involvement of various signal transduction pathways including the Hippo, Hedgehog, Wnt/Notch, JNK, PI3K, K-ras, and transforming growth factor (TGF) -β signaling pathways. Moreover, genome-wide association studies (GWAS) have identified a large number of pathways and gene sets involved in the development of PDAC (8,9).…”

Pathway-based analysis enables deeper mining of GWAS data on H/L in chickens

“…However, pinpointing the causative variation is more di cult. To reveal the mechanism through which a mutation site affects a phenotype and to perform subsequent functional research, GWAS joint analysis on multiple genomic levels can be used and biological pathway analysis can be applied to detect the superposition of multiple minor genes by examining genes involved in the same biological pathway, thus enabling deeper mining of GWAS data [10][11][12][13]. With the development of genome sequencing technology and the continuous improvement of statistical methods, GWAS is expected to be more e ciently applied to gene identi cation for important traits in livestock and poultry and to play an increasingly important role in animal breeding.…”

Inhibition of PTP1B blocks pancreatic cancer progression by targeting the PKM2/AMPK/mTOC1 pathway

“…Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal cancers in the world with the worst prognosis, and its incidence has increased in recent years 1 . To date, the rate of pancreatic cancer incidence nearly equals its mortality due to diagnosis at later stage and the lack of early detection markers 2 .…”