ArticlePLoS computational biology2022
A model for the intrinsic limit of cancer therapy: Duality of treatment-induced cell death and treatment-induced stemness.
Article in PLoS computational biology, 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, 24 citations in OpenAlex.
- Cell State Transitions Drive the Evolution of Disease Progression in B-Lymphoblastic Leukemia.Cancer research communications · 2026Article
- Optimal dosing of anti-cancer treatment under drug-induced plasticity.NPJ systems biology and applications · 2025Article
- A statistical framework for detecting therapy-induced resistance from drug screens.NPJ systems biology and applications · 2025Article
- TRENDY: gene regulatory network inference enhanced by transformer.Bioinformatics (Oxford, England) · 2025Article
- Modeling critical dosing strategies for stromal-induced resistance to cancer therapy.NPJ systems biology and applications · 2025Article
- Cell Population Growth Kinetics in the Presence of Stochastic Heterogeneity of Cell Phenotype.ArXiv · 2023Article
- Statistical inference of the rates of cell proliferation and phenotypic switching in cancer.Journal of theoretical biology · 2023Article
- Inference on autoregulation in gene expression with variance-to-mean ratio.Journal of mathematical biology · 2023Article
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Intratumor cellular heterogeneity and non-genetic cell plasticity in tumors pose a recently recognized challenge to cancer treatment. Because of the dispersion of initial cell states within a clonal tumor cell population, a perturbation imparted by a cytocidal drug only kills a fraction of cells. Due to dynamic instability of cellular states the cells not killed are pushed by the treatment into a variety of functional states, including a "stem-like state" that confers resistance to treatment and regenerative capacity. This immanent stress-induced stemness competes against cell death in response to the same perturbation and may explain the near-inevitable recurrence after any treatment. This double-edged-sword mechanism of treatment complements the selection of preexisting resistant cells in explaining post-treatment progression. Unlike selection, the induction of a resistant state has not been systematically analyzed as an immanent cause of relapse. Here, we present a generic elementary model and analytical examination of this intrinsic limitation to therapy. We show how the relative proclivity towards cell death versus transition into a stem-like state, as a function of drug dose, establishes either a window of opportunity for containing tumors or the inevitability of progression following therapy. The model considers measurable cell behaviors independent of specific molecular pathways and provides a new theoretical framework for optimizing therapy dosing and scheduling as cancer treatment paradigms move from "maximal tolerated dose," which may promote therapy induced-stemness, to repeated "minimally effective doses" (as in adaptive therapies), which contain the tumor and avoid therapy-induced progression.
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