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dc.contributor.authorPan, Y
dc.contributor.authorLiu, H
dc.contributor.authorWang, Y
dc.contributor.authorKang, X
dc.contributor.authorLiu, Z
dc.contributor.authorOwzar, K
dc.contributor.authorHan, Y
dc.contributor.authorSu, L
dc.contributor.authorWei, Y
dc.contributor.authorHung, RJ
dc.contributor.authorBrhane, Y
dc.contributor.authorMcLaughlin, J
dc.contributor.authorBrennan, P
dc.contributor.authorBickeböller, H
dc.contributor.authorRosenberger, A
dc.contributor.authorHoulston, RS
dc.contributor.authorCaporaso, N
dc.contributor.authorTeresa Landi, M
dc.contributor.authorHeinrich, J
dc.contributor.authorRisch, A
dc.contributor.authorWu, X
dc.contributor.authorYe, Y
dc.contributor.authorChristiani, DC
dc.contributor.authorAmos, CI
dc.contributor.authorWei, Q
dc.coverage.spatialEngland
dc.date.accessioned2023-08-01T14:24:26Z
dc.date.available2023-08-01T14:24:26Z
dc.date.issued2017-03-17
dc.identifierARTN 44634
dc.identifiersrep44634
dc.identifier.citationScientific Reports, 2017, 7 (1), pp. 44634 -
dc.identifier.issn2045-2322
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/5911
dc.identifier.eissn2045-2322
dc.identifier.eissn2045-2322
dc.identifier.doi10.1038/srep44634
dc.description.abstractmRNA splicing is an important mechanism to regulate mRNA expression. Abnormal regulation of this process may lead to lung cancer. Here, we investigated the associations of 11,966 single-nucleotide polymorphisms (SNPs) in 206 mRNA splicing-related genes with lung cancer risk by using the summary data from six published genome-wide association studies (GWASs) of Transdisciplinary Research in Cancer of the Lung (TRICL) (12,160 cases and 16,838 controls) and another two lung cancer GWASs of Harvard University (984 cases and 970 controls) and deCODE (1,319 cases and 26,380 controls). We found that a total of 12 significant SNPs with false discovery rate (FDR) ≤0.05 were mapped to one novel gene PRPF6 and two previously reported genes (DHX16 and LSM2) that were also confirmed in this study. The six novel SNPs in PRPF6 were in high linkage disequilibrium and associated with PRPF6 mRNA expression in lymphoblastoid cells from 373 Europeans in the 1000 Genomes Project. Taken together, our studies shed new light on the role of mRNA splicing genes in the development of lung cancer.
dc.formatElectronic
dc.format.extent44634 -
dc.languageeng
dc.language.isoeng
dc.publisherNATURE PORTFOLIO
dc.relation.ispartofScientific Reports
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectGenetic Predisposition to Disease
dc.subjectGenome-Wide Association Study
dc.subjectHumans
dc.subjectLinkage Disequilibrium
dc.subjectLung Neoplasms
dc.subjectMolecular Sequence Annotation
dc.subjectPolymorphism, Single Nucleotide
dc.subjectQuantitative Trait Loci
dc.subjectRNA Splicing
dc.subjectRNA, Messenger
dc.subjectReproducibility of Results
dc.subjectRisk Factors
dc.titleAssociations between genetic variants in mRNA splicing-related genes and risk of lung cancer: a pathway-based analysis from published GWASs.
dc.typeJournal Article
dcterms.dateAccepted2017-02-06
dc.date.updated2023-08-01T14:24:01Z
rioxxterms.versionVoR
rioxxterms.versionofrecord10.1038/srep44634
rioxxterms.licenseref.startdate2017-03-17
rioxxterms.typeJournal Article/Review
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/28304396
pubs.issue1
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Cancer Genomics
pubs.publication-statusPublished online
pubs.publisher-urlhttp://dx.doi.org/10.1038/srep44634
pubs.volume7
icr.researchteamCancer Genomics
dc.contributor.icrauthorHoulston, Richard
icr.provenanceDeposited by Mr Arek Surman (impersonating Prof Richard Houlston) on 2023-08-01. Deposit type is initial. No. of files: 1. Files: Associations between genetic variants in mRNA splicing-related genes and risk of lung cancer a pathway-based analysis from p.pdf


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