ArticleMathematical models & methods in applied sciences : M3AS2018
A HYBRID THREE-SCALE MODEL OF TUMOR GROWTH.
Article in Mathematical models & methods in applied sciences : M3AS, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 44 citations in OpenAlex.
- Exploring the relationship between vascular remodelling and tumour growth using agent-based modelling.PLoS computational biology · 2026Article
- Experimentally calibrated multiscale model predicts schedule dependent drug combination effects.NPJ systems biology and applications · 2026Article
- Validating the predictions of mathematical models describing tumor growth and treatment response.ArXiv · 2025Article
- Bridging Scales: a Hybrid Model to Simulate Vascular Tumor Growth and Treatment Response.ArXiv · 2023Article
- Multiscale modeling of collective cell migration elucidates the mechanism underlying tumor-stromal interactions in different spatiotemporal scales.Scientific reports · 2022Article
- Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology.Biophysics reviews · 2022Review
- A multi-layered hybrid model for cancer cell invasion.Medical & biological engineering & computing · 2022Article
- A continuum mechanical framework for modeling tumor growth and treatment in two- and three-phase systems.Archive of applied mechanics = Ingenieur-Archiv · 2022Article
- Bayesian calibration of a stochastic, multiscale agent-based model for predicting in vitro tumor growth.PLoS computational biology · 2021Article
- A persistent invasive phenotype in post-hypoxic tumor cells is revealed by fate mapping and computational modeling.iScience · 2021Article
- Drug delivery: Experiments, mathematical modelling and machine learning.Computers in biology and medicine · 2020Article
- A Coupled Mass Transport and Deformation Theory of Multi-constituent Tumor Growth.Journal of the mechanics and physics of solids · 2020Article
- Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities.Journal of clinical medicine · 2020Review
- Article
- Coupling tumor growth and bio distribution models.Biomedical microdevices · 2019Article
- Mathematical models of tumor cell proliferation: A review of the literature.Expert review of anticancer therapy · 2018Review
- Calibration of Multi-Parameter Models of Avascular Tumor Growth Using Time Resolved Microscopy Data.Scientific reports · 2018Article
- Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: theory and preliminary clinical results.Physics in medicine and biology · 2018Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
Cancer results from a complex interplay of different biological, chemical, and physical phenomena that span a wide range of time and length scales. Computational modeling may help to unfold the role of multiple evolving factors that exist and interact in the tumor microenvironment. Understanding these complex multiscale interactions is a crucial step towards predicting cancer growth and in developing effective therapies. We integrate different modeling approaches in a multiscale, avascular, hybrid tumor growth model encompassing tissue, cell, and sub-cell scales. At the tissue level, we consider the dispersion of nutrients and growth factors in the tumor microenvironment, which are modeled through reaction-diffusion equations. At the cell level, we use an agent based model (ABM) to describe normal and tumor cell dynamics, with normal cells kept in homeostasis and cancer cells differentiated apoptotic, hypoxic, and necrotic states. Cell movement is driven by the balance of a variety of forces according to Newton's second law, including those related to growth-induced stresses. Phenotypic transitions are defined by specific rule of behaviors that depend on microenvironment stimuli. We integrate in each cell/agent a branch of the epidermal growth factor receptor (EGFR) pathway. This pathway is modeled by a system of coupled nonlinear differential equations involving the mass laws of 20 molecules. The rates of change in the concentration of some key molecules trigger proliferation or migration advantage response. The bridge between cell and tissue scales is built through the reaction and source terms of the partial differential equations. Our hybrid model is built in a modular way, enabling the investigation of the role of different mechanisms at multiple scales on tumor progression. This strategy allows representating both the collective behavior due to cell assembly as well as microscopic intracellular phenomena described by signal transduction pathways. Here, we investigate the impact of some mechanisms associated with sustained proliferation on cancer progression. Specifically, we focus on the intracellular proliferation/migration-advantage-response driven by the EGFR pathway and on proliferation inhibition due to accumulation of growth-induced stresses. Simulations demonstrate that the model can adequately describe some complex mechanisms of tumor dynamics, including growth arrest in avascular tumors. Both the sub-cell model and growth-induced stresses give rise to heterogeneity in the tumor expansion and a rich variety of tumor behaviors.
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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.