Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00209805%3A_____%2F19%3A00078121" target="_blank" >RIV/00209805:_____/19:00078121 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11130/19:10395476 RIV/61988987:17110/19:A21026Z4
Result on the web
<a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=30541042" target="_blank" >https://www.ncbi.nlm.nih.gov/pubmed/?term=30541042</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1093/jnci/djy155" target="_blank" >10.1093/jnci/djy155</a>
Alternative languages
Result language
angličtina
Original language name
Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer
Original language description
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 1.3 105 ), 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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30204 - Oncology
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of the National Cancer Institute
ISSN
0027-8874
e-ISSN
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Volume of the periodical
111
Issue of the periodical within the volume
6
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
"djy155"
UT code for WoS article
000474267400006
EID of the result in the Scopus database
2-s2.0-85068554437