State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemia.
Journal
Leukemia
ISSN: 1476-5551
Titre abrégé: Leukemia
Pays: England
ID NLM: 8704895
Informations de publication
Date de publication:
02 Feb 2024
02 Feb 2024
Historique:
received:
20
10
2023
accepted:
05
01
2024
revised:
22
12
2023
medline:
3
2
2024
pubmed:
3
2
2024
entrez:
2
2
2024
Statut:
aheadofprint
Résumé
Chronic myeloid leukemia (CML) is initiated and maintained by BCR::ABL which is clinically targeted using tyrosine kinase inhibitors (TKIs). TKIs can induce long-term remission but are also not curative. Thus, CML is an ideal system to test our hypothesis that transcriptome-based state-transition models accurately predict cancer evolution and treatment response. We collected time-sequential blood samples from tetracycline-off (Tet-Off) BCR::ABL-inducible transgenic mice and wild-type controls. From the transcriptome, we constructed a CML state-space and a three-well leukemogenic potential landscape. The potential's stable critical points defined observable disease states. Early states were characterized by anti-CML genes opposing leukemia; late states were characterized by pro-CML genes. Genes with expression patterns shaped similarly to the potential landscape were identified as drivers of disease transition. Re-introduction of tetracycline to silence the BCR::ABL gene returned diseased mice transcriptomes to a near healthy state, without reaching it, suggesting parts of the transition are irreversible. TKI only reverted the transcriptome to an intermediate disease state, without approaching a state of health; disease relapse occurred soon after treatment. Using only the earliest time-point as initial conditions, our state-transition models accurately predicted both disease progression and treatment response, supporting this as a potentially valuable approach to time clinical intervention, before phenotypic changes become detectable.
Identifiants
pubmed: 38307941
doi: 10.1038/s41375-024-02142-9
pii: 10.1038/s41375-024-02142-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
ID : U01CA250046
Organisme : U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
ID : U01CA250046
Organisme : U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
ID : U01CA250046
Informations de copyright
© 2024. The Author(s).
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