ArticleScience advances2022
Dynamic patterns of microRNA expression during acute myeloid leukemia state-transition.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Multiomic State-Transitions Reveal Post-Treatment Transcriptome Desynchronization in Acute Myeloid Leukemia.bioRxiv : the preprint server for biology · 2026Article
- Temporal Expression Analysis to Unravel Gene Regulatory Dynamics by microRNAs.Methods in molecular biology (Clifton, N.J.) · 2025Article
- State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemia.Leukemia · 2024Article
- Transcriptome free energy can serve as a dynamic patient-specific biomarker in acute myeloid leukemia.NPJ systems biology and applications · 2024Article
- State-transition Modeling of Blood Transcriptome Predicts Disease Evolution and Treatment Response in Chronic Myeloid Leukemia.bioRxiv : the preprint server for biology · 2023Article
- Acquired miR-142 deficit in leukemic stem cells suffices to drive chronic myeloid leukemia into blast crisis.Nature communications · 2023Article
- The immunogenic radiation and new players in immunotherapy and targeted therapy for head and neck cancer.Frontiers in oral health · 2023Review
- Data driven model discovery and interpretation for CAR T-cell killing using sparse identification and latent variables.Frontiers in immunology · 2023Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
MicroRNAs (miRNAs) have been shown to hold prognostic value in acute myeloid leukemia (AML); however, the temporal dynamics of miRNA expression in AML are poorly understood. Using serial samples from a mouse model of AML to generate time-series miRNA sequencing data, we are the first to show that the miRNA transcriptome undergoes state-transition during AML initiation and progression. We modeled AML state-transition as a particle undergoing Brownian motion in a quasi-potential and validated the AML state-space and state-transition model to accurately predict time to AML in an independent cohort of mice. The critical points of the model provided a framework to align samples from mice that developed AML at different rates. Our mathematical approach allowed discovery of dynamic processes involved during AML development and, if translated to humans, has the potential to predict an individual's disease trajectory.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.