ReviewBiochimica et biophysica acta. Reviews on cancer2017
Mathematical models of cell phenotype regulation and reprogramming: Make cancer cells sensitive again!
Review in Biochimica et biophysica acta. Reviews on cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Transition between cell states of sensitivity reveals molecular vulnerability of drug-tolerant cells.Molecular systems biology · 2025Article
- Metabolic Objectives and Trade-Offs: Inference and Applications.Metabolites · 2025Review
- Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia.Cell reports. Medicine · 2024Article
- Quantifying cancer cell plasticity with gene regulatory networks and single-cell dynamics.Frontiers in network physiology · 2023Review
- Review
- Review
- Landscape and kinetic path quantify critical transitions in epithelial-mesenchymal transition.Biophysical journal · 2021Article
- Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer.eLife · 2021Article
- Data-Driven Math Model of FLT3-ITD Acute Myeloid Leukemia Reveals Potential Therapeutic Targets.Journal of personalized medicine · 2021Article
- Article
- Towards control of cellular decision-making networks in the epithelial-to-mesenchymal transition.Physical biology · 2019Review
- A multi-state model of chemoresistance to characterize phenotypic dynamics in breast cancer.Scientific reports · 2018Article
- Phenotypic Plasticity, Bet-Hedging, and Androgen Independence in Prostate Cancer: Role of Non-Genetic Heterogeneity.Frontiers in oncology · 2018Review
- Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems.PLoS computational biology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
A cell's phenotype is the observable actualization of complex interactions between its genome, epigenome, and local environment. While traditional views in cancer have held that cellular and tumor phenotypes are largely functions of genomic instability, increasing attention has recently been given to epigenetic and microenvironmental influences. Such non-genetic factors allow cancer cells to experience intrinsic diversity and plasticity, and at the tumor level can result in phenotypic heterogeneity and treatment evasion. In 2006, Takahashi and Yamanaka exploited the epigenome's plasticity by "reprogramming" differentiated cells into a pluripotent state by inducing expression of a cocktail of four transcription factors. Recent advances in cancer biology have shown not only that cellular reprogramming is possible for malignant cells, but it may provide a foundation for future therapies. Nevertheless, cell reprogramming experiments are frequently plagued by low efficiency, activation of aberrant transcriptional programs, instability, and often rely on expertise gathered from systems which may not translate directly to cancer. Here, we review a theoretical framework tracing back to Waddington's epigenetic landscape which may be used to derive quantitative and qualitative understanding of cellular reprogramming. Implications for tumor heterogeneity, evolution and adaptation are discussed in the context of designing new treatments to re-sensitize recalcitrant tumors. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
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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.