Show simple item record

dc.contributor.authorShukla, Ankit
dc.contributor.authorNguyen, Thu HM
dc.contributor.authorMoka, Sarat B
dc.contributor.authorEllis, Jonathan J
dc.contributor.authorGrady, John P
dc.contributor.authorOey, Harald
dc.contributor.authorCristino, Alexandre S
dc.contributor.authorKhanna, Kum Kum
dc.contributor.authorKroese, Dirk P
dc.contributor.authorKrause, Lutz
dc.contributor.authorDray, Eloise
dc.contributor.authorFink, J Lynn
dc.contributor.authorDuijf, Pascal HG
dc.date.accessioned2020-06-26T03:06:25Z
dc.date.available2020-06-26T03:06:25Z
dc.date.issued2020
dc.identifier.issn2041-1723
dc.identifier.doi10.1038/s41467-020-14286-0
dc.identifier.urihttp://hdl.handle.net/10072/394947
dc.description.abstractChromosome arm aneuploidies (CAAs) are pervasive in cancers. However, how they affect cancer development, prognosis and treatment remains largely unknown. Here, we analyse CAA profiles of 23,427 tumours, identifying aspects of tumour evolution including probable orders in which CAAs occur and CAAs predicting tissue-specific metastasis. Both haematological and solid cancers initially gain chromosome arms, while only solid cancers subsequently preferentially lose multiple arms. 72 CAAs and 88 synergistically co-occurring CAA pairs multivariately predict good or poor survival for 58% of 6977 patients, with negligible impact of whole-genome doubling. Additionally, machine learning identifies 31 CAAs that robustly alter response to 56 chemotherapeutic drugs across cell lines representing 17 cancer types. We also uncover 1024 potential synthetic lethal pharmacogenomic interactions. Notably, in predicting drug response, CAAs substantially outperform  mutations and focal deletions/amplifications combined. Thus, CAAs predict cancer prognosis, shape tumour evolution, metastasis and drug response, and may advance precision oncology.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLC
dc.relation.ispartofpagefrom449:1
dc.relation.ispartofpageto449:14
dc.relation.ispartofissue1
dc.relation.ispartofjournalNature Communications
dc.relation.ispartofvolume11
dc.subject.fieldofresearchBiological sciences
dc.subject.fieldofresearchcode31
dc.titleChromosome arm aneuploidies shape tumour evolution and drug response
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationShukla, A; Nguyen, THM; Moka, SB; Ellis, JJ; Grady, JP; Oey, H; Cristino, AS; Khanna, KK; Kroese, DP; Krause, L; Dray, E; Fink, JL; Duijf, PHG, Chromosome arm aneuploidies shape tumour evolution and drug response, Nature Communications , 2020, 11 (1), pp. 449:1-449:14
dcterms.dateAccepted2019-12-16
dcterms.licensehttps://creativecommons.org/licenses/by/4.0/
dc.date.updated2020-06-26T03:03:16Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© The Author(s) 2020. 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 made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
gro.hasfulltextFull Text
gro.griffith.authorCristino, Alex


Files in this item

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record