Multi-omics and machine learning reveal context-specific gene regulatory activities of PML::RARA in acute promyelocytic leukemia

William Villiers; Audrey Kelly; Xiaohan He; James Kaufman-Cook; Abdurrahman Elbasir; Halima Bensmail; Paul Lavender; Richard Dillon; Borbála Mifsud; Cameron S. Osborne

doi:10.1038/s41467-023-36262-0

Nature Communications (Feb 2023)

Multi-omics and machine learning reveal context-specific gene regulatory activities of PML::RARA in acute promyelocytic leukemia

William Villiers,
Audrey Kelly,
Xiaohan He,
James Kaufman-Cook,
Abdurrahman Elbasir,
Halima Bensmail,
Paul Lavender,
Richard Dillon,
Borbála Mifsud,
Cameron S. Osborne

Affiliations

William Villiers: Department of Medical and Molecular Genetics, King’s College London
Audrey Kelly: School of Immunology & Microbial Sciences, MRC and Asthma UK Centre in Allergic Mechanisms of Asthma, King’s College London
Xiaohan He: Department of Medical and Molecular Genetics, King’s College London
James Kaufman-Cook: Department of Medical and Molecular Genetics, King’s College London
Abdurrahman Elbasir: ICT Division, College of Science and Engineering, Hamad Bin Khalifa University
Halima Bensmail: Qatar Computing Research Institute, Hamad Bin Khalifa University
Paul Lavender: School of Immunology & Microbial Sciences, MRC and Asthma UK Centre in Allergic Mechanisms of Asthma, King’s College London
Richard Dillon: Department of Medical and Molecular Genetics, King’s College London
Borbála Mifsud: College of Health and Life Sciences, Hamad Bin Khalifa University, Education City
Cameron S. Osborne: Department of Medical and Molecular Genetics, King’s College London

DOI: https://doi.org/10.1038/s41467-023-36262-0
Journal volume & issue: Vol. 14, no. 1
pp. 1 – 17

Abstract

Read online

The PML-RARA gene fusion is the characteristic driver of Acute Promyelocytic Leukaemia (APL) and is known to bind to the genome. Here, the authors characterise the impact of PML-RARA on gene regulation in APL cell lines and patient samples using transcriptomics, epigenomics, and machine learning.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

About the journal