ArticlePLoS computational biology2009
Evolution of resistance to targeted anti-cancer therapies during continuous and pulsed administration strategies.
Article in PLoS computational biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 71 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
71 citing papers in PubMed, 127 citations in OpenAlex.
- Longitudinal In Vivo Imaging at Single-Lesion Resolution Identifies Allele-Associated Response and Resistance Dynamics in EGFR-Mutant Lung Cancer.International journal of molecular sciences · 2026Article
- Comprehensive overview of AI methodologies in nano-drug delivery Optimization and Design.NPJ precision oncology · 2026Review
- Can evolutionary therapy be applied in non-small cell lung cancer?Scientific reports · 2026Article
- Mathematical Oncology: How Modeling Is Transforming Clinical Decision-Making.Cancer research · 2025Review
- The HDAC inhibitor romidepsin renders liver cancer vulnerable to RTK targeting and immunologically active.Nature communications · 2025Article
- The adaptive state determines the impact of mutations on evolving populations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Quantitative measurement of phenotype dynamics during cancer drug resistance evolution using genetic barcoding.Nature communications · 2025Article
- A Model of Intratumor and Interpatient Heterogeneity Explains Clinical Trials of Curative Combination Therapy for Lymphoma.Blood cancer discovery · 2025Article
- Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapy.Signal transduction and targeted therapy · 2024Review
- The pharmacokinetic-pharmacodynamic modelling framework as a tool to predict drug resistance evolution.Microbiology (Reading, England) · 2023Article
- Mutators can drive the evolution of multi-resistance to antibiotics.PLoS genetics · 2023Article
- Article
- Therapeutic Effects of Coumarins with Different Substitution Patterns.Molecules (Basel, Switzerland) · 2023Review
- Multiscale modeling of drug resistance in glioblastoma with gene mutations and angiogenesis.Computational and structural biotechnology journal · 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
- A Broad-Based Characterization of a Cell-Penetrating, Single Domain Camelid Bi-Specific Antibody Monomer That Targets STAT3 and KRAS Dependent Cancers.International journal of molecular sciences · 2022Article
- Article
- Establishment of Acquired Cisplatin Resistance in Ovarian Cancer Cell Lines Characterized by Enriched Metastatic Properties with Increased Twist Expression.International journal of molecular sciences · 2020Article
- Pharmacokinetic Profiles Determine Optimal Combination Treatment Schedules in Computational Models of Drug Resistance.Cancer research · 2020Article
- Towards Multidrug Adaptive Therapy.Cancer research · 2020Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
The discovery of small molecules targeted to specific oncogenic pathways has revolutionized anti-cancer therapy. However, such therapy often fails due to the evolution of acquired resistance. One long-standing question in clinical cancer research is the identification of optimum therapeutic administration strategies so that the risk of resistance is minimized. In this paper, we investigate optimal drug dosing schedules to prevent, or at least delay, the emergence of resistance. We design and analyze a stochastic mathematical model describing the evolutionary dynamics of a tumor cell population during therapy. We consider drug resistance emerging due to a single (epi)genetic alteration and calculate the probability of resistance arising during specific dosing strategies. We then optimize treatment protocols such that the risk of resistance is minimal while considering drug toxicity and side effects as constraints. Our methodology can be used to identify optimum drug administration schedules to avoid resistance conferred by one (epi)genetic alteration for any cancer and treatment type.
Indexed as
Identifiers
What OpenQuestion holds
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.