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Chromosome arm aneuploidies shape tumour evolution and drug response

Author

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  • Ankit Shukla

    (University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute)

  • Thu H. M. Nguyen

    (University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute)

  • Sarat B. Moka

    (The University of Queensland)

  • Jonathan J. Ellis

    (University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute)

  • John P. Grady

    (University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute)

  • Harald Oey

    (University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute)

  • Alexandre S. Cristino

    (Griffith University)

  • Kum Kum Khanna

    (QIMR Berghofer Medical Research Institute)

  • Dirk P. Kroese

    (The University of Queensland)

  • Lutz Krause

    (University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute)

  • Eloise Dray

    (UT Health San Antonio)

  • J. Lynn Fink

    (University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute)

  • Pascal H. G. Duijf

    (University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute
    Queensland University of Technology)

Abstract

Chromosome 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.

Suggested Citation

  • Ankit Shukla & Thu H. M. Nguyen & Sarat B. Moka & Jonathan J. Ellis & John P. Grady & Harald Oey & Alexandre S. Cristino & Kum Kum Khanna & Dirk P. Kroese & Lutz Krause & Eloise Dray & J. Lynn Fink & , 2020. "Chromosome arm aneuploidies shape tumour evolution and drug response," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14286-0
    DOI: 10.1038/s41467-020-14286-0
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    Cited by:

    1. Rong Xiao & Deshu Xu & Meili Zhang & Zhanghua Chen & Li Cheng & Songjie Du & Mingfei Lu & Tonghai Zhou & Ruoyan Li & Fan Bai & Yue Huang, 2024. "Aneuploid embryonic stem cells drive teratoma metastasis," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Leanne M. Brown & Ryan A. Hagenson & Tilen Koklič & Iztok Urbančič & Lu Qiao & Janez Strancar & Jason M. Sheltzer, 2024. "An elevated rate of whole-genome duplications in cancers from Black patients," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    3. Filipe Correia Martins & Dominique-Laurent Couturier & Ines Santiago & Carolin Margarethe Sauer & Maria Vias & Mihaela Angelova & Deborah Sanders & Anna Piskorz & James Hall & Karen Hosking & Anumithr, 2022. "Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    4. Dan Daniel Erdmann-Pham & Sanjit Singh Batra & Timothy K. Turkalo & James Durbin & Marco Blanchette & Iwei Yeh & Hunter Shain & Boris C. Bastian & Yun S. Song & Daniel S. Rokhsar & Dirk Hockemeyer, 2023. "Tracing cancer evolution and heterogeneity using Hi-C," Nature Communications, Nature, vol. 14(1), pages 1-17, December.

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