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Malyukova A, Lahnalampi M, Falqués-Costa T, Pölönen P, Sipola M, Mehtonen J, Teppo S, Akopyan K, Viiliainen J, Lohi O, Hagström-Andersson AK, Heinäniemi M, Sangfelt O. Sequential drug treatment targeting cell cycle and cell fate regulatory programs blocks non-genetic cancer evolution in acute lymphoblastic leukemia. Genome Biol 2024; 25:143. [PMID: 38822412 PMCID: PMC11143599 DOI: 10.1186/s13059-024-03260-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 04/26/2024] [Indexed: 06/03/2024] Open
Abstract
BACKGROUND Targeted therapies exploiting vulnerabilities of cancer cells hold promise for improving patient outcome and reducing side-effects of chemotherapy. However, efficacy of precision therapies is limited in part because of tumor cell heterogeneity. A better mechanistic understanding of how drug effect is linked to cancer cell state diversity is crucial for identifying effective combination therapies that can prevent disease recurrence. RESULTS Here, we characterize the effect of G2/M checkpoint inhibition in acute lymphoblastic leukemia (ALL) and demonstrate that WEE1 targeted therapy impinges on cell fate decision regulatory circuits. We find the highest inhibition of recovery of proliferation in ALL cells with KMT2A-rearrangements. Single-cell RNA-seq and ATAC-seq of RS4;11 cells harboring KMT2A::AFF1, treated with the WEE1 inhibitor AZD1775, reveal diversification of cell states, with a fraction of cells exhibiting strong activation of p53-driven processes linked to apoptosis and senescence, and disruption of a core KMT2A-RUNX1-MYC regulatory network. In this cell state diversification induced by WEE1 inhibition, a subpopulation transitions to a drug tolerant cell state characterized by activation of transcription factors regulating pre-B cell fate, lipid metabolism, and pre-BCR signaling in a reversible manner. Sequential treatment with BCR-signaling inhibitors dasatinib, ibrutinib, or perturbing metabolism by fatostatin or AZD2014 effectively counteracts drug tolerance by inducing cell death and repressing stemness markers. CONCLUSIONS Collectively, our findings provide new insights into the tight connectivity of gene regulatory programs associated with cell cycle and cell fate regulation, and a rationale for sequential administration of WEE1 inhibitors with low toxicity inhibitors of pre-BCR signaling or metabolism.
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Affiliation(s)
- Alena Malyukova
- Department of Cell and Molecular Biology, Karolinska Institutet, Biomedicum, Solnavägen 9, 171 77, Stockholm, Sweden.
| | - Mari Lahnalampi
- The Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Ton Falqués-Costa
- Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden
| | - Petri Pölönen
- The Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Mikko Sipola
- The Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Juha Mehtonen
- The Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Susanna Teppo
- Tampere Center for Child, Adolescent and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Center, Tampere University Hospital, Tampere, Finland
| | - Karen Akopyan
- Department of Cell and Molecular Biology, Karolinska Institutet, Biomedicum, Solnavägen 9, 171 77, Stockholm, Sweden
| | - Johanna Viiliainen
- Department of Cell and Molecular Biology, Karolinska Institutet, Biomedicum, Solnavägen 9, 171 77, Stockholm, Sweden
| | - Olli Lohi
- Tampere Center for Child, Adolescent and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Center, Tampere University Hospital, Tampere, Finland
| | | | - Merja Heinäniemi
- The Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland.
| | - Olle Sangfelt
- Department of Cell and Molecular Biology, Karolinska Institutet, Biomedicum, Solnavägen 9, 171 77, Stockholm, Sweden.
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Pina C. Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230052. [PMID: 38432321 PMCID: PMC10909511 DOI: 10.1098/rstb.2023.0052] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 12/04/2023] [Indexed: 03/05/2024] Open
Abstract
Transcriptional noise is proposed to participate in cell fate changes, but contributions to mammalian cell differentiation systems, including cancer, remain associative. Cancer evolution is driven by genetic variability, with modulatory or contributory participation of epigenetic variants. Accumulation of epigenetic variants enhances transcriptional noise, which can facilitate cancer cell fate transitions. Acute myeloid leukaemia (AML) is an aggressive cancer with strong epigenetic dependencies, characterized by blocked differentiation. It constitutes an attractive model to probe links between transcriptional noise and malignant cell fate regulation. Gcn5/KAT2A is a classical epigenetic transcriptional noise regulator. Its loss increases transcriptional noise and modifies cell fates in stem and AML cells. By reviewing the analysis of KAT2A-depleted pre-leukaemia and leukaemia models, I discuss that the net result of transcriptional noise is diversification of cell fates secondary to alternative transcriptional programmes. Cellular diversification can enable or hinder AML progression, respectively, by differentiation of cell types responsive to mutations, or by maladaptation of leukaemia stem cells. KAT2A-dependent noise-responsive genes participate in ribosome biogenesis and KAT2A loss destabilizes translational activity. I discuss putative contributions of perturbed translation to AML biology, and propose KAT2A loss as a model for mechanistic integration of transcriptional and translational control of noise and fate decisions. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.
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Affiliation(s)
- Cristina Pina
- College of Health, Medicine and Life Sciences, Brunel University London, Kingston Lane, Uxbridge, London, UB8 3PH, United Kingdom
- CenGEM – Centre for Genome Engineering and Maintenance, Brunel University London, Kingston Lane, Uxbridge, London, UB8 3PH, United Kingdom
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Isobe T, Kucinski I, Barile M, Wang X, Hannah R, Bastos HP, Chabra S, Vijayabaskar M, Sturgess KH, Williams MJ, Giotopoulos G, Marando L, Li J, Rak J, Gozdecka M, Prins D, Shepherd MS, Watcham S, Green AR, Kent DG, Vassiliou GS, Huntly BJ, Wilson NK, Göttgens B. Preleukemic single-cell landscapes reveal mutation-specific mechanisms and gene programs predictive of AML patient outcomes. CELL GENOMICS 2023; 3:100426. [PMID: 38116120 PMCID: PMC10726426 DOI: 10.1016/j.xgen.2023.100426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/13/2023] [Accepted: 09/29/2023] [Indexed: 12/21/2023]
Abstract
Acute myeloid leukemia (AML) and myeloid neoplasms develop through acquisition of somatic mutations that confer mutation-specific fitness advantages to hematopoietic stem and progenitor cells. However, our understanding of mutational effects remains limited to the resolution attainable within immunophenotypically and clinically accessible bulk cell populations. To decipher heterogeneous cellular fitness to preleukemic mutational perturbations, we performed single-cell RNA sequencing of eight different mouse models with driver mutations of myeloid malignancies, generating 269,048 single-cell profiles. Our analysis infers mutation-driven perturbations in cell abundance, cellular lineage fate, cellular metabolism, and gene expression at the continuous resolution, pinpointing cell populations with transcriptional alterations associated with differentiation bias. We further develop an 11-gene scoring system (Stem11) on the basis of preleukemic transcriptional signatures that predicts AML patient outcomes. Our results demonstrate that a single-cell-resolution deep characterization of preleukemic biology has the potential to enhance our understanding of AML heterogeneity and inform more effective risk stratification strategies.
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Affiliation(s)
- Tomoya Isobe
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Iwo Kucinski
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Melania Barile
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Xiaonan Wang
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Rebecca Hannah
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Hugo P. Bastos
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Shirom Chabra
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - M.S. Vijayabaskar
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Katherine H.M. Sturgess
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Matthew J. Williams
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - George Giotopoulos
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Ludovica Marando
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Juan Li
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Justyna Rak
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
- Hematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - Malgorzata Gozdecka
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
- Hematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - Daniel Prins
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Mairi S. Shepherd
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Sam Watcham
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Anthony R. Green
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - David G. Kent
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
- York Biomedical Research Institute, Department of Biology, University of York, York, UK
| | - George S. Vassiliou
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
- Hematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - Brian J.P. Huntly
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Nicola K. Wilson
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Berthold Göttgens
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
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