Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes

Extracting relevant information from large-scale data offers unprecedented opportunities in cancerology. We applied independent component analysis (ICA) to bladder cancer transcriptome data sets and interpreted the components using gene enrichment analysis and tumor-associated molecular, clinicopath...

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Autores: Biton, Anne, Bernard-Pierrot, Isabelle, Lou, Yinjun, Krucker, Clémentine, Chapeaublanc, Elodie, Rubio Pérez, Carlota, 1990-, López Bigas, Núria, Kamoun, Aurélie, Neuzillet, Yann, Gestraud, Pierre, Grieco, Luca, Rebouissou, Sandra, deReyniès, Aurélien, Benhamou, Simone, Lebret, Thierry, Southgate, Jennifer, Barillot, Emmanuel, Allory, Yves, Zinovyev, Andrei, Radvanyi, François
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2014
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/23723
Acceso en línea:http://hdl.handle.net/10230/23723
http://dx.doi.org/10.1016/j.celrep.2014.10.035
Access Level:acceso abierto
Palabra clave:Càncer -- Aspectes genètics -- Informàtica
Càncer -- Aspectes moleculars -- Informàtica
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spelling Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypesBiton, AnneBernard-Pierrot, IsabelleLou, YinjunKrucker, ClémentineChapeaublanc, ElodieRubio Pérez, Carlota, 1990-López Bigas, NúriaKamoun, AurélieNeuzillet, YannGestraud, PierreGrieco, LucaRebouissou, SandradeReyniès, AurélienBenhamou, SimoneLebret, ThierrySouthgate, JenniferBarillot, EmmanuelAllory, YvesZinovyev, AndreiRadvanyi, FrançoisCàncer -- Aspectes genètics -- InformàticaCàncer -- Aspectes moleculars -- InformàticaExtracting relevant information from large-scale data offers unprecedented opportunities in cancerology. We applied independent component analysis (ICA) to bladder cancer transcriptome data sets and interpreted the components using gene enrichment analysis and tumor-associated molecular, clinicopathological, and processing information. We identified components associated with biological processes of tumor cells or the tumor microenvironment, and other components revealed technical biases. Applying ICA to nine cancer types identified cancer-shared and bladder-cancer-specific components. We characterized the luminal and basal-like subtypes of muscle-invasive bladder cancers according to the components identified. The study of the urothelial differentiation component, specific to the luminal subtypes, showed that a molecular urothelial differentiation program was maintained even in those luminal tumors that had lost morphological differentiation. Study of the genomic alterations associated with this component coupled with functional studies revealed a protumorigenic role for PPARG in luminal tumors. Our results support the inclusion of ICA in the exploitation of multiscale data sets.This work is part of the “Cartes d’Identité des Tumeurs” (CIT) program funded and developed by the “Ligue Nationale contre le Cancer” (LNCC) (http://cit.ligue-cancer.net). We thank E. Voirin, N. Servant, G. Lucotte, and P. Hupé for their help with bioinformatics data management and analysis. We thank members of the bladder cancer CIT consortium (P. Maillé and D. Vordos, Henri Mondor Hospital; M. Sibony, Cochin Hospital; A. Laplanche, IGR, INSERM; Y. Denoux and V. Molinié, Foch Hospital; E. Letouzé, LNCC) for their constant support. This work was supported by the LNCC (to “Oncologie Moléculaire” and “Computational Systems Biology of Cancer” accredited teams), the Institut Curie (to F.R., E.B., A.Z.), the “Centre National de la Recherche Scientifique” (CNRS) (to F.R.), the “Institut National de la Santé et de la Recherche Médicale” (INSERM) (to E.B., A.Z., S.B., and Y.A.), the INCa (INCa_2960 and 4382 to F.R. and Y.A.), ITMO cancer, systems biology program (to A.Z., E.B., and F.R.), the Labex (no. ANR-10-LBX-0038) part of the IDEX PSL (no. ANR-10-IDEX-0001-02 PSL) (to F.R.), and York Against Cancer (to J.S.). A.B. was supported by a grant from the INCa, from the LNCC, and by NIH grant 5U24 CA143799-04 as part of TCGA project, Y.L. by a grant from the “Fondation Franco-Chinoise pour la Science et ses Applications” (FFCSA), Y.N. by a grant from the “Fondation ARC pour la recherche sur le cancer,” and A.K. by a grant from the LNCCElsevier201520152014info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/23723http://dx.doi.org/10.1016/j.celrep.2014.10.035reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésCell Reports. 2014;9(4):1235-45© 2014, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 International http://creativecommons.org/licenses/by-nc-nd/3.0/ http://dx.doi.org/10.1016/j.celrep.2014.10.035http://creativecommons.org/licenses/by-nc-nd/3.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/237232026-06-12T07:21:37Z
dc.title.none.fl_str_mv Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes
title Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes
spellingShingle Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes
Biton, Anne
Càncer -- Aspectes genètics -- Informàtica
Càncer -- Aspectes moleculars -- Informàtica
title_short Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes
title_full Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes
title_fullStr Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes
title_full_unstemmed Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes
title_sort Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes
dc.creator.none.fl_str_mv Biton, Anne
Bernard-Pierrot, Isabelle
Lou, Yinjun
Krucker, Clémentine
Chapeaublanc, Elodie
Rubio Pérez, Carlota, 1990-
López Bigas, Núria
Kamoun, Aurélie
Neuzillet, Yann
Gestraud, Pierre
Grieco, Luca
Rebouissou, Sandra
deReyniès, Aurélien
Benhamou, Simone
Lebret, Thierry
Southgate, Jennifer
Barillot, Emmanuel
Allory, Yves
Zinovyev, Andrei
Radvanyi, François
author Biton, Anne
author_facet Biton, Anne
Bernard-Pierrot, Isabelle
Lou, Yinjun
Krucker, Clémentine
Chapeaublanc, Elodie
Rubio Pérez, Carlota, 1990-
López Bigas, Núria
Kamoun, Aurélie
Neuzillet, Yann
Gestraud, Pierre
Grieco, Luca
Rebouissou, Sandra
deReyniès, Aurélien
Benhamou, Simone
Lebret, Thierry
Southgate, Jennifer
Barillot, Emmanuel
Allory, Yves
Zinovyev, Andrei
Radvanyi, François
author_role author
author2 Bernard-Pierrot, Isabelle
Lou, Yinjun
Krucker, Clémentine
Chapeaublanc, Elodie
Rubio Pérez, Carlota, 1990-
López Bigas, Núria
Kamoun, Aurélie
Neuzillet, Yann
Gestraud, Pierre
Grieco, Luca
Rebouissou, Sandra
deReyniès, Aurélien
Benhamou, Simone
Lebret, Thierry
Southgate, Jennifer
Barillot, Emmanuel
Allory, Yves
Zinovyev, Andrei
Radvanyi, François
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Càncer -- Aspectes genètics -- Informàtica
Càncer -- Aspectes moleculars -- Informàtica
topic Càncer -- Aspectes genètics -- Informàtica
Càncer -- Aspectes moleculars -- Informàtica
description Extracting relevant information from large-scale data offers unprecedented opportunities in cancerology. We applied independent component analysis (ICA) to bladder cancer transcriptome data sets and interpreted the components using gene enrichment analysis and tumor-associated molecular, clinicopathological, and processing information. We identified components associated with biological processes of tumor cells or the tumor microenvironment, and other components revealed technical biases. Applying ICA to nine cancer types identified cancer-shared and bladder-cancer-specific components. We characterized the luminal and basal-like subtypes of muscle-invasive bladder cancers according to the components identified. The study of the urothelial differentiation component, specific to the luminal subtypes, showed that a molecular urothelial differentiation program was maintained even in those luminal tumors that had lost morphological differentiation. Study of the genomic alterations associated with this component coupled with functional studies revealed a protumorigenic role for PPARG in luminal tumors. Our results support the inclusion of ICA in the exploitation of multiscale data sets.
publishDate 2014
dc.date.none.fl_str_mv 2014
2015
2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/23723
http://dx.doi.org/10.1016/j.celrep.2014.10.035
url http://hdl.handle.net/10230/23723
http://dx.doi.org/10.1016/j.celrep.2014.10.035
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Cell Reports. 2014;9(4):1235-45
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/3.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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