ArticleJournal of theoretical biology2014
The formation of tight tumor clusters affects the efficacy of cell cycle inhibitors: a hybrid model study.
Article in Journal of theoretical biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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Who cites it
9 citing papers in PubMed, 28 citations in OpenAlex.
- Histology-guided mathematical model of tumor oxygenation: sensitivity analysis of physical and computational parameters.bioRxiv : the preprint server for biology · 2024Article
- Dynamics of Fibril Collagen Remodeling by Tumor Cells: A Model of Tumor-Associated Collagen Signatures.Cells · 2023Article
- Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations.PLoS computational biology · 2021Article
- Collective Cell Migration in a Fibrous Environment: A Hybrid Multiscale Modelling Approach.Frontiers in applied mathematics and statistics · 2021Article
- Morphophenotypic classification of tumor organoids as an indicator of drug exposure and penetration potential.PLoS computational biology · 2019Article
- Cell signaling heterogeneity is modulated by both cell-intrinsic and -extrinsic mechanisms: An integrated approach to understanding targeted therapy.PLoS biology · 2018Article
- Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues.Journal of the Royal Society, Interface · 2018Review
- Diagnostic assessment of osteosarcoma chemoresistance based on Virtual Clinical Trials.Medical hypotheses · 2015Article
- Dosage and Dose Schedule Screening of Drug Combinations in Agent-Based Models Reveals Hidden Synergies.Frontiers in physiology · 2015Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Cyclin-dependent kinases (CDKs) are vital in regulating cell cycle progression, and, thus, in highly proliferating tumor cells CDK inhibitors are gaining interest as potential anticancer agents. Clonogenic assay experiments are frequently used to determine drug efficacy against the survival and proliferation of cancer cells. While the anticancer mechanisms of drugs are usually described at the intracellular single-cell level, the experimental measurements are sampled from the entire cancer cell population. This approach may lead to discrepancies between the experimental observations and theoretical explanations of anticipated drug mechanisms. To determine how individual cell responses to drugs that inhibit CDKs affect the growth of cancer cell populations, we developed a spatially explicit hybrid agent-based model. In this model, each cell is equipped with internal cell cycle regulation mechanisms, but it is also able to interact physically with its neighbors. We model cell cycle progression, focusing on the G1 and G2/M cell cycle checkpoints, as well as on related essential components, such as CDK1, CDK2, cell size, and DNA damage. We present detailed studies of how the emergent properties (e.g., cluster formation) of an entire cell population depend on altered physical and physiological parameters. We analyze the effects of CDK1 and CKD2 inhibitors on population growth, time-dependent changes in cell cycle distributions, and the dynamic evolution of spatial cell patterns. We show that cell cycle inhibitors that cause cell arrest at different cell cycle phases are not necessarily synergistically super-additive. Finally, we demonstrate that the physical aspects of cell population growth, such as the formation of tight cell clusters versus dispersed colonies, alter the efficacy of cell cycle inhibitors, both in 2D and 3D simulations. This finding may have implications for interpreting the treatment efficacy results of in vitro experiments, in which treatment is applied before the cells can grow to produce clusters, especially because in vivo tumors, in contrast, form large masses before they are detected and treated.
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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.