Publication:
Identification of cancer related genes using a comprehensive map of human gene expression

dc.affiliation.dptoUC3M. Departamento de Matemáticases
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Modelización, Simulación Numérica y Matemática Industriales
dc.contributor.authorTorrente Orihuela, Ester Aurora
dc.contributor.authorLukk, Margus
dc.contributor.authorXue, Vincent
dc.contributor.authorParkinson, Helen
dc.contributor.authorRung, Johan
dc.contributor.authorBrazma, Alvis
dc.contributor.funderEuropean Commissionen
dc.date.accessioned2022-11-14T12:11:29Z
dc.date.available2022-11-14T12:11:29Z
dc.date.issued2016-06-20
dc.description.abstractRapid accumulation and availability of gene expression datasets in public repositories have enabled large-scale meta-analyses of combined data. The richness of cross-experiment data has provided new biological insights, including identification of new cancer genes. In this study, we compiled a human gene expression dataset from similar to 40,000 publicly available Affymetrix HG-U133Plus2 arrays. After strict quality control and data normalisation the data was quantified in an expression matrix of similar to 20,000 genes and similar to 28,000 samples. To enable different ways of sample grouping, existing annotations where subjected to systematic ontology assisted categorisation and manual curation. Groups like normal tissues, neoplasmic tissues, cell lines, homoeotic cells and incompletely differentiated cells were created. Unsupervised analysis of the data confirmed global structure of expression consistent with earlier analysis but with more details revealed due to increased resolution. A suitable mixed-effects linear model was used to further investigate gene expression in solid tissue tumours, and to compare these with the respective healthy solid tissues. The analysis identified 1,285 genes with systematic expression change in cancer. The list is significantly enriched with known cancer genes from large, public, peer-reviewed databases, whereas the remaining ones are proposed as new cancer gene candidates. The compiled dataset is publicly available in the ArrayExpress Archive. It contains the most diverse collection of biological samples, making it the largest systematically annotated gene expression dataset of its kind in the public domain.en
dc.description.sponsorshipAB received funding from the EurocanPlatform grant of FP7 frameworks from the European Commission. AT was partially supported by the Ramón Areces Foundation.en
dc.format.extent20es
dc.identifier.bibliographicCitationTorrente A, Lukk M, Xue V, Parkinson H, Rung J, Brazma A (2016) Identification of Cancer Related Genes Using a Comprehensive Map of Human Gene Expression. PLoS ONE 11(6): e0157484. doi:10.1371/journal.pone.0157484en
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0157484
dc.identifier.issn1932-6203
dc.identifier.publicationfirstpage1es
dc.identifier.publicationissue6es
dc.identifier.publicationlastpage20es
dc.identifier.publicationtitlePLoS Oneen
dc.identifier.publicationvolume11es
dc.identifier.urihttps://hdl.handle.net/10016/36009
dc.identifier.uxxiAR/0000018036
dc.language.isoengen
dc.publisherPLOSen
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/260791/EurocanPlatformen
dc.rights© 2016 Torrente et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en
dc.rightsAtribución 3.0 Españaes
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subject.ecienciaBiología y Biomedicinaes
dc.subject.otherMixed-effects modelen
dc.subject.otherMicroarray dataen
dc.subject.otherData setsen
dc.subject.otherResourceen
dc.subject.otherTissuesen
dc.subject.otherUpdateen
dc.subject.otherAtlasen
dc.titleIdentification of cancer related genes using a comprehensive map of human gene expressionen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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