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Abstract
The epigenetic landscape plays a critical role in cancer progression, yet its therapeutic potential remains underexplored. Glucocorticoids are essential components of treatments for lymphoid cancers, but resistance, driven in part by epigenetic changes at glucocorticoid-response elements, poses a major challenge to effective therapies. Here we show that glucocorticoid treatment induces distinct patterns of chromosomal organization in glucocorticoid-sensitive and resistant acute lymphoblastic leukemia xenograft models. These glucocorticoid-response elements are primed by the pioneer transcription factor PU.1, which interacts with the glucocorticoid receptor. Eviction of PU.1 promotes receptor binding, increasing the expression of genes involved in apoptosis and facilitating a stronger therapeutic response. Treatment with a PU.1 inhibitor enhances glucocorticoid sensitivity, demonstrating the clinical potential of targeting this pathway. This study uncovers a mechanism involving PU.1 and the glucocorticoid receptor, linking transcription factor activity with drug response, and suggesting potential therapeutic strategies for overcoming resistance.
Glucocorticoid resistance is partly due to epigenetic alterations, but the regulatory mechanisms driving these remain poorly understood. Here, a link between the activity of a lineage-specific transcription factor PU.1 and epigenetic modulators mediating the response to glucocorticoids is described in acute lymphoblastic leukemia.
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1 Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Shanghai, China (GRID:grid.412277.5) (ISNI:0000 0004 1760 6738); University of Technology, Centre for Health Technologies and the School of Biomedical Engineering, Sydney, Australia (GRID:grid.117476.2) (ISNI:0000 0004 1936 7611)
2 Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Shanghai, China (GRID:grid.412277.5) (ISNI:0000 0004 1760 6738)
3 Hebei University of Engineering, Hebei Key Laboratory of Medical Data Science, Institute of Biomedical Informatics, School of Medicine, Handan, China (GRID:grid.412028.d) (ISNI:0000 0004 1757 5708)
4 UNSW Sydney, Children’s Cancer Institute, Lowy Cancer Research Centre, School of Clinical Medicine, UNSW Medicine & Health, UNSW Centre for Childhood Cancer Research, Sydney, Australia (GRID:grid.1005.4) (ISNI:0000 0004 4902 0432)
5 Shanghai Jiao Tong University School of Medicine, Department of Orthopedics and Precision Research Center for Refractory Diseases, Shanghai General Hospital, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293)
6 University of York, Centre for Blood Research, England, UK (GRID:grid.5685.e) (ISNI:0000 0004 1936 9668)
7 University of York, York Biomedical Research Institute, England, UK (GRID:grid.5685.e) (ISNI:0000 0004 1936 9668)
8 Albert Einstein College of Medicine, Department of Cell Biology, Randwick, USA (GRID:grid.251993.5) (ISNI:0000 0001 2179 1997)
9 Neuroscience Research Australia, Randwick, Australia (GRID:grid.250407.4) (ISNI:0000 0000 8900 8842); The University of Sydney, Brain and Mind Centre, Translational Research Collective, Faculty of Medicine and Health, Sydney, Australia (GRID:grid.1013.3) (ISNI:0000 0004 1936 834X)
10 University of Technology, Centre for Health Technologies and the School of Biomedical Engineering, Sydney, Australia (GRID:grid.117476.2) (ISNI:0000 0004 1936 7611)
11 University of York, Metabolomics & Proteomics Laboratory, Bioscience Technology Facility, Department of Biology, England, UK (GRID:grid.5685.e) (ISNI:0000 0004 1936 9668)