ArticleCancer research2020
State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Development of Acute Myeloid Leukemia.
Article in Cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 32 citations in OpenAlex.
- ProteinNetworkSight: a user-friendly platform for transforming co-expression patterns into actionable therapeutic insights through interactive network visualization.Nucleic acids research · 2026Article
- Multiomic State-Transitions Reveal Post-Treatment Transcriptome Desynchronization in Acute Myeloid Leukemia.bioRxiv : the preprint server for biology · 2026Article
- Cell State Transitions Drive the Evolution of Disease Progression in B-Lymphoblastic Leukemia.Cancer research communications · 2026Article
- Deciphering the topological landscape of glioma using a network theory framework.Scientific reports · 2024Article
- 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
- Proteomics and mathematical modeling of longitudinal CSF differentiates fast versus slow ALS progression.Annals of clinical and translational neurology · 2023Article
- Acquired miR-142 deficit in leukemic stem cells suffices to drive chronic myeloid leukemia into blast crisis.Nature communications · 2023Article
- Epigenetics as a mediator of plasticity in cancer.Science (New York, N.Y.) · 2023Review
- The immunogenic radiation and new players in immunotherapy and targeted therapy for head and neck cancer.Frontiers in oral health · 2023Review
- Dissecting cell fate dynamics in pediatric glioblastoma through the lens of complex systems and cellular cybernetics.Biological cybernetics · 2022Review
- Comparing Bayesian-Based Reconstruction Strategies in Topology-Based Pathway Enrichment Analysis.Biomolecules · 2022Article
- Synchrony of biomarker variability indicates a critical transition: Application to mortality prediction in hemodialysis.iScience · 2022Article
- Comparison of cell state models derived from single-cell RNA sequencing data: graph versus multi-dimensional space.Mathematical biosciences and engineering : MBE · 2022Article
- Dynamic patterns of microRNA expression during acute myeloid leukemia state-transition.Science advances · 2022Article
- Roadmap on plasticity and epigenetics in cancer.Physical biology · 2022Review
- Tipping the Balance: A Criticality Perspective.Entropy (Basel, Switzerland) · 2022Article
- A Review of Mathematical and Computational Methods in Cancer Dynamics.Frontiers in oncology · 2022Review
- A review of dynamical systems approaches for the detection of chaotic attractors in cancer networks.Patterns (New York, N.Y.) · 2021Review
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20 authors at 2 institutions in 1 country.
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Abstract
Temporal dynamics of gene expression inform cellular and molecular perturbations associated with disease development and evolution. Given the complexity of high-dimensional temporal genomic data, an analytic framework guided by a robust theory is needed to interpret time-sequential changes and to predict system dynamics. Here we model temporal dynamics of the transcriptome of peripheral blood mononuclear cells in a two-dimensional state-space representing states of health and leukemia using time-sequential bulk RNA-seq data from a murine model of acute myeloid leukemia (AML). The state-transition model identified critical points that accurately predict AML development and identifies stepwise transcriptomic perturbations that drive leukemia progression. The geometry of the transcriptome state-space provided a biological interpretation of gene dynamics, aligned gene signals that are not synchronized in time across mice, and allowed quantification of gene and pathway contributions to leukemia development. Our state-transition model synthesizes information from multiple cell types in the peripheral blood and identifies critical points in the transition from health to leukemia to guide interpretation of changes in the transcriptome as a whole to predict disease progression. SIGNIFICANCE: These findings apply the theory of state transitions to model the initiation and development of acute myeloid leukemia, identifying transcriptomic perturbations that accurately predict time to disease development.
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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.