ArticleJCO clinical cancer informatics2019
Mathematical Approach to Differentiate Spontaneous and Induced Evolution to Drug Resistance During Cancer Treatment.
Article in JCO clinical cancer informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- 75 Years of Mathematical Oncology.bioRxiv : the preprint server for biology · 2026Article
- Optimal dosing of anti-cancer treatment under drug-induced plasticity.NPJ systems biology and applications · 2025Article
- The HDAC inhibitor romidepsin renders liver cancer vulnerable to RTK targeting and immunologically active.Nature communications · 2025Article
- Multiscale mathematical model-informed reinforcement learning optimizes combination treatment scheduling in glioblastoma evolution.Science advances · 2025Article
- A statistical framework for detecting therapy-induced resistance from drug screens.NPJ systems biology and applications · 2025Article
- Personalized cancer treatment strategies incorporating irreversible and reversible drug resistance mechanisms.NPJ systems biology and applications · 2025Article
- Understanding therapeutic tolerance through a mathematical model of drug-induced resistance.NPJ systems biology and applications · 2025Article
- Modeling critical dosing strategies for stromal-induced resistance to cancer therapy.NPJ systems biology and applications · 2025Article
- A mathematical framework for comparison of intermittent versus continuous adaptive chemotherapy dosing in cancer.NPJ systems biology and applications · 2024Article
- Understanding tumour growth variability in breast cancer xenograft models identifies PARP inhibition resistance biomarkers.NPJ precision oncology · 2024Article
- Threshold-awareness in adaptive cancer therapy.PLoS computational biology · 2024Article
- Statistical inference of the rates of cell proliferation and phenotypic switching in cancer.Journal of theoretical biology · 2023Article
- A survey of open questions in adaptive therapy: Bridging mathematics and clinical translation.eLife · 2023Article
- Model-informed experimental design recommendations for distinguishing intrinsic and acquired targeted therapeutic resistance in head and neck cancer.NPJ systems biology and applications · 2022Article
- NETISCE: a network-based tool for cell fate reprogramming.NPJ systems biology and applications · 2022Article
- Optimal Strategy and Benefit of Pulsed Therapy Depend On Tumor Heterogeneity and Aggressiveness at Time of Treatment Initiation.Molecular cancer therapeutics · 2022Article
- Roadmap on plasticity and epigenetics in cancer.Physical biology · 2022Review
- Mathematical characterization of population dynamics in breast cancer cells treated with doxorubicin.Frontiers in molecular biosciences · 2022Article
- Drug-induced resistance evolution necessitates less aggressive treatment.PLoS computational biology · 2021Article
- A theoretical analysis of tumour containment.Nature ecology & evolution · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeDrug resistance is a major impediment to the success of cancer treatment. Resistance is typically thought to arise from random genetic mutations, after which mutated cells expand via Darwinian selection. However, recent experimental evidence suggests that progression to drug resistance need not occur randomly, but instead may be induced by the treatment itself via either genetic changes or epigenetic alterations. This relatively novel notion of resistance complicates the already challenging task of designing effective treatment protocols. MATERIALS AND
methodsTo better understand resistance, we have developed a mathematical modeling framework that incorporates both spontaneous and drug-induced resistance.
resultsOur model demonstrates that the ability of a drug to induce resistance can result in qualitatively different responses to the same drug dose and delivery schedule. We have also proven that the induction parameter in our model is theoretically identifiable and propose an in vitro protocol that could be used to determine a treatment's propensity to induce resistance.
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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.