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dc.contributor.authorReyna, Matthew A.
dc.contributor.authorHaan, David
dc.contributor.authorPaczkowska, Marta
dc.contributor.authorVerbeke, Lieven P. C.
dc.contributor.authorVazquez, Miguel
dc.contributor.authorKahraman, Abdullah
dc.contributor.authorPulido-Tamayo, Sergio
dc.contributor.authorBarenboim, Jonathan
dc.contributor.authorWadi, Lina
dc.contributor.authorDhingra, Priyanka
dc.contributor.authorShrestha, Raunak
dc.contributor.authorGetz, Gad
dc.contributor.authorLawrence, Michael S.
dc.contributor.authorPedersen, Jakob Skou
dc.contributor.authorRubin, Mark A.
dc.contributor.authorWheeler, David A.
dc.contributor.authorBrunak, Søren
dc.contributor.authorIzarzugaza, Jose M. G.
dc.contributor.authorKhurana, Ekta
dc.contributor.authorMarchal, Kathleen
dc.contributor.authorvon Mering, Christian
dc.contributor.authorSahinalp, S. Cenk
dc.contributor.authorValencia, Alfonso
dc.contributor.authorReimand, Jüri
dc.contributor.authorStuart, Joshua M.
dc.contributor.authorRaphael, Benjamin J.
dc.date.accessioned2022-02-10T20:36:42Z
dc.date.available2021-10-27T20:34:53Z
dc.date.available2022-02-10T20:36:42Z
dc.date.issued2020-02
dc.date.submitted2018-12
dc.identifier.issn2041-1723
dc.identifier.urihttps://hdl.handle.net/1721.1/136327.2
dc.description.abstract© 2020, The Author(s). 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.en_US
dc.language.isoen
dc.publisherSpringer Science and Business Media LLCen_US
dc.relation.isversionofhttp://dx.doi.org/10.1038/s41467-020-14367-0en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNatureen_US
dc.titlePathway and network analysis of more than 2500 whole cancer genomesen_US
dc.typeArticleen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.relation.journalNature Communicationsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-01-06T19:39:24Z
dspace.orderedauthorsReyna, MA; Haan, D; Paczkowska, M; Verbeke, LPC; Vazquez, M; Kahraman, A; Pulido-Tamayo, S; Barenboim, J; Wadi, L; Dhingra, P; Shrestha, R; Getz, G; Lawrence, MS; Pedersen, JS; Rubin, MA; Wheeler, DA; Brunak, S; Izarzugaza, JMG; Khurana, E; Marchal, K; von Mering, C; Sahinalp, SC; Valencia, A; Abascal, F; Amin, SB; Bader, GD; Bandopadhayay, P; Beroukhim, R; Bertl, J; Boroevich, KA; Busanovich, J; Campbell, PJ; Carlevaro-Fita, J; Chakravarty, D; Chan, CWY; Chen, K; Choi, JK; Deu-Pons, J; Diamanti, K; Feuerbach, L; Fink, JL; Fonseca, NA; Frigola, J; Gambacorti-Passerini, C; Garsed, DW; Gerstein, M; Guo, Q; Gut, IG; Hamilton, MP; Haradhvala, NJ; Harmanci, AO; Helmy, M; Herrmann, C; Hess, JM; Hobolth, A; Hodzic, E; Hong, C; Hornshøj, H; Isaev, K; Johnson, R; Johnson, TA; Juul, M; Juul, RI; Kahles, A; Kellis, M; Kim, J; Kim, JK; Kim, Y; Komorowski, J; Korbel, JO; Kumar, S; Lanzós, A; Larsson, E; Lee, D; Lehmann, KV; Li, S; Li, X; Lin, Z; Liu, EM; Lochovsky, L; Lou, S; Madsen, T; Martincorena, I; Martinez-Fundichely, A; Maruvka, YE; McGillivray, PD; Meyerson, W; Muiños, F; Mularoni, L; Nakagawa, H; Nielsen, MM; Park, K; Park, K; Pons, T; Reyes-Salazar, I; Rheinbay, E; Rubio-Perez, C; Saksena, G; Salichos, L; Sander, Cen_US
dspace.date.submission2021-01-06T19:39:27Z
mit.journal.volume11en_US
mit.journal.issue1en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work Neededen_US


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