Pathway and network analysis of more than 2500 whole cancer genomes

The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as par...

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Autores: Reyna, Matthew A., Haan, David, Paczkowska, Marta, Verbeke, Lieven P.C., Vazquez, Miguel, Kahraman, Abdullah, Pulido-Tamayo, Sergio, Barenboim, Jonathan, Wadi, Lina, Dhingra, Priyanka, Shrestha, Raunak, Getz, Gad, Lawrence, Michael S., Pedersen, Jackob S., Rubin, Mark A., Wheeler, David A., Brunak, Søren, Izarzugaza, Jose M.G., PCAWG Drivers and Functional Interpretation Working Group, PCAWG Consortium, Deu-Pons, Jordi, Gut, Ivo Glynne, Muiños, Ferran, Mularoni, Loris, Rubio Pérez, Carlota, 1990-, Tamborero Noguera, David
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/44323
Acceso en línea:http://hdl.handle.net/10230/44323
http://dx.doi.org/10.1038/s41467-020-14367-0
Access Level:acceso abierto
Palabra clave:Càncer
Genòmica
Genètica
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network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Pathway and network analysis of more than 2500 whole cancer genomes
title Pathway and network analysis of more than 2500 whole cancer genomes
spellingShingle Pathway and network analysis of more than 2500 whole cancer genomes
Reyna, Matthew A.
Càncer
Genòmica
Genètica
title_short Pathway and network analysis of more than 2500 whole cancer genomes
title_full Pathway and network analysis of more than 2500 whole cancer genomes
title_fullStr Pathway and network analysis of more than 2500 whole cancer genomes
title_full_unstemmed Pathway and network analysis of more than 2500 whole cancer genomes
title_sort Pathway and network analysis of more than 2500 whole cancer genomes
dc.creator.none.fl_str_mv Reyna, Matthew A.
Haan, David
Paczkowska, Marta
Verbeke, Lieven P.C.
Vazquez, Miguel
Kahraman, Abdullah
Pulido-Tamayo, Sergio
Barenboim, Jonathan
Wadi, Lina
Dhingra, Priyanka
Shrestha, Raunak
Getz, Gad
Lawrence, Michael S.
Pedersen, Jackob S.
Rubin, Mark A.
Wheeler, David A.
Brunak, Søren
Izarzugaza, Jose M.G.
PCAWG Drivers and Functional Interpretation Working Group
PCAWG Consortium
Deu-Pons, Jordi
Gut, Ivo Glynne
Muiños, Ferran
Mularoni, Loris
Rubio Pérez, Carlota, 1990-
Tamborero Noguera, David
author Reyna, Matthew A.
author_facet Reyna, Matthew A.
Haan, David
Paczkowska, Marta
Verbeke, Lieven P.C.
Vazquez, Miguel
Kahraman, Abdullah
Pulido-Tamayo, Sergio
Barenboim, Jonathan
Wadi, Lina
Dhingra, Priyanka
Shrestha, Raunak
Getz, Gad
Lawrence, Michael S.
Pedersen, Jackob S.
Rubin, Mark A.
Wheeler, David A.
Brunak, Søren
Izarzugaza, Jose M.G.
PCAWG Drivers and Functional Interpretation Working Group
PCAWG Consortium
Deu-Pons, Jordi
Gut, Ivo Glynne
Muiños, Ferran
Mularoni, Loris
Rubio Pérez, Carlota, 1990-
Tamborero Noguera, David
author_role author
author2 Haan, David
Paczkowska, Marta
Verbeke, Lieven P.C.
Vazquez, Miguel
Kahraman, Abdullah
Pulido-Tamayo, Sergio
Barenboim, Jonathan
Wadi, Lina
Dhingra, Priyanka
Shrestha, Raunak
Getz, Gad
Lawrence, Michael S.
Pedersen, Jackob S.
Rubin, Mark A.
Wheeler, David A.
Brunak, Søren
Izarzugaza, Jose M.G.
PCAWG Drivers and Functional Interpretation Working Group
PCAWG Consortium
Deu-Pons, Jordi
Gut, Ivo Glynne
Muiños, Ferran
Mularoni, Loris
Rubio Pérez, Carlota, 1990-
Tamborero Noguera, David
author2_role author
author
author
author
author
author
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
Genòmica
Genètica
topic Càncer
Genòmica
Genètica
description The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/44323
http://dx.doi.org/10.1038/s41467-020-14367-0
url http://hdl.handle.net/10230/44323
http://dx.doi.org/10.1038/s41467-020-14367-0
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Nature Communications. 2020 Feb 5;11(1):729
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature Research
publisher.none.fl_str_mv Nature Research
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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spelling Pathway and network analysis of more than 2500 whole cancer genomesReyna, Matthew A.Haan, DavidPaczkowska, MartaVerbeke, Lieven P.C.Vazquez, MiguelKahraman, AbdullahPulido-Tamayo, SergioBarenboim, JonathanWadi, LinaDhingra, PriyankaShrestha, RaunakGetz, GadLawrence, Michael S.Pedersen, Jackob S.Rubin, Mark A.Wheeler, David A.Brunak, SørenIzarzugaza, Jose M.G.PCAWG Drivers and Functional Interpretation Working GroupPCAWG ConsortiumDeu-Pons, JordiGut, Ivo GlynneMuiños, FerranMularoni, LorisRubio Pérez, Carlota, 1990-Tamborero Noguera, DavidCàncerGenòmicaGenèticaThe catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.B.J.R. received funding from NIH grants U24CA211000 and R01HG007069. J.M.S. received funding from NIH grants U24CA143858, R01CA180778, and U24CA210990. J.R. received funding from the Ontario Institute for Cancer Research (OICR) Investigator Award provided by the Government of Ontario, Operating Grant from Cancer Research Society (CRS) (#21089), the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant (#RGPIN-2016-06485), and the Canadian Institutes of Health Research (CIHR) Project Grant. K.M. received funding from IWT/SBO NEMOA and FWO 3G046318 and G.0371.06 grants. J.M.G.I. received funding from the Novo Nordisk Foundation (NNF17OC0027594 and NNF14CC0001) and the Innovation Fund Denmark (5184-00102B). S.B. received funding from the Novo Nordisk Foundation (NNF17OC0027594 and NNF14CC0001). J.B. received funding from the BioTalent Canada Student Internship Program. A.V. and M.V. received funding from the Joint BSC-IRB-CRG Program in Computational Biology and the Severo Ochoa Award (SEV 2015-0493). M.A.R. was supported in part by the National Cancer Institute of the NIH (Cancer Target Discovery and Development Network grant U01CA217875)Nature Research202020202020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/44323http://dx.doi.org/10.1038/s41467-020-14367-0reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésNature Communications. 2020 Feb 5;11(1):729© 2020 Matthew A. Reyna. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were madehttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/443232026-06-12T07:21:37Z
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