TY - JOUR
T1 - Chromosome arm aneuploidies shape tumour evolution and drug response
AU - Shukla, Ankit
AU - Nguyen, Thu H.M.
AU - Moka, Sarat B.
AU - Ellis, Jonathan J.
AU - Grady, John P.
AU - Oey, Harald
AU - Cristino, Alexandre S.
AU - Khanna, Kum Kum
AU - Kroese, Dirk P.
AU - Krause, Lutz
AU - Dray, Eloise
AU - Fink, J. Lynn
AU - Duijf, Pascal H.G.
N1 - Funding Information:
We thank Dr. Nikolaus Schultz (MSKCC) for sharing a script to aid in computing segmental chromosomal copy number alterations. We thank Dr. Marianna Datseris for her constructive advice and editing the manuscript and Dr. John Kemp for supervisory support. The results of this study are in part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga. This study makes use of data generated by the Molecular Taxonomy of Breast Cancer International Consortium. Funding for the project was provided by Cancer Research UK and the British Columbia Cancer Agency Branch. This work has been supported by the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS), under grant number CE140100049 (to D.P.K.), funding from the University of Queensland Diamantina Institute and the School of Biomedical Sciences at Queensland University of Technology and a National Breast Cancer Foundation Career Development Fellowship (to P.H.G.D.).
Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12/1
Y1 - 2020/12/1
N2 - 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.
AB - 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.
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U2 - 10.1038/s41467-020-14286-0
DO - 10.1038/s41467-020-14286-0
M3 - Article
C2 - 31974379
AN - SCOPUS:85078156187
SN - 2041-1723
VL - 11
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 449
ER -