Acute myeloid leukaemia (AML) is a rapidly fatal blood cancer that is characterised by the accumulation of immature myeloid cells in the blood and bone marrow as a result of blocked differentiation. Methods which identify master transcriptional regulators of AML subtype-specific leukaemia cell states and their combinations could be critical for discovering novel differentiation-inducing therapies. In this proof-of-concept study, we demonstrate a novel utility of the Mogrify® algorithm in identifying combinations of transcription factors (TFs) and drugs, which recapitulate granulocytic differentiation of the NB4 acute promyelocytic leukaemia (APL) cell line, using two different approaches. In the first approach, Connectivity Map (CMAP) analysis of these TFs and their target networks outperformed standard approaches, retrieving ATRA as the top hit. We identify dimaprit and mebendazole as a drug combination which induces myeloid differentiation. In the second approach, we show that genetic manipulation of specific Mogrify®-identified TFs (MYC and IRF1) leads to co-operative induction of APL differentiation, as does pharmacological targeting of these TFs using currently available compounds. We also show that loss of IRF1 blunts ATRA-mediated differentiation, and that MYC represses IRF1 expression through recruitment of PML-RARα, the driver fusion oncoprotein in APL, to the IRF1 promoter. Finally, we demonstrate that these drug combinations can also induce differentiation of primary patient-derived APL cells, and highlight the potential of targeting MYC and IRF1 in high-risk APL. Thus, these results suggest that Mogrify® could be used for drug discovery or repositioning in leukaemia differentiation therapy for other subtypes of leukaemia or cancers.
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The raw and processed data were submitted to NCBI GEO. The accession number will be available upon publication.
The source code of our pipeline will be available upon publication. Source code for the Mogrify® algorithm is not available.
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The authors would like to acknowledge Dr. Sonia P. Chothani for providing the RNA-Seq data analysis pipeline, the ssCMAP developer, Dr. Shu-Dong Zhang, for helpful discussion on the algorithm’s internal calculations, the Duke-NUS Genome Biology Facility (DGBF) for RNA, ChIP- and ATAC-sequencing services, as well as Dr. Gee Chuan Wong/Bryan Y.W. Teo, SGH Department of Haematology for providing primary APL samples. This work was funded by the National Medical Research Council (NMRC) of Singapore (MOH-000059/MOH-CSASI18may-0002) and NMRC/CIRG/1429/2015 to STO). OJLR is supported by NMRC YIRG (NMRC/OFYIRG/0022/2016) and by a Singapore National Research Foundation grant [NRF-CRP20-2017-0002].
OJLR is a co-inventor of the patent (WO/2017/106932) and is a co-founder, shareholder and director of Mogrify Ltd, a cell therapy company. All other authors declare no competing interest.
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Lee, L.M., Christodoulou, E.G., Shyamsunder, P. et al. A novel network pharmacology approach for leukaemia differentiation therapy using Mogrify®. Oncogene 41, 5160–5175 (2022). https://doi.org/10.1038/s41388-022-02505-5