ArticleMathematical and computer modelling2009
Simulating Brain Tumor Heterogeneity with a Multiscale Agent-Based Model: Linking Molecular Signatures, Phenotypes and Expansion Rate.
Article in Mathematical and computer modelling, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 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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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.
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Who cites it
43 citing papers in PubMed.
- A Review of the Application of Spatial Transcriptomics in Neuroscience.Interdisciplinary sciences, computational life sciences · 2024Review
- Data-driven spatio-temporal modelling of glioblastoma.Royal Society open science · 2023Review
- 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
- MUC21 induces the viability and migration of glioblastoma via the STAT3/AKT pathway.Experimental and therapeutic medicine · 2022Article
- Multiscale Computational Modeling of Vascular Adaptation: A Systems Biology Approach Using Agent-Based Models.Frontiers in bioengineering and biotechnology · 2021Review
- Data-driven analysis of a mechanistic model of CAR T cell signaling predicts effects of cell-to-cell heterogeneity.Journal of theoretical biology · 2020Article
- A systems approach to clinical oncology uses deep phenotyping to deliver personalized care.Nature reviews. Clinical oncology · 2020Review
- The double-edged sword role of fibroblasts in the interaction with cancer cells; an agent-based modeling approach.PloS one · 2020Article
- A Review of Cell-Based Computational Modeling in Cancer Biology.JCO clinical cancer informatics · 2019Review
- Dynamic Targeting in Cancer Treatment.Frontiers in physiology · 2019Article
- Microvascular bioengineering: a focus on pericytes.Journal of biological engineering · 2019Review
- Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI.NeuroImage. Clinical · 2018Article
- A simple and accurate rule-based modeling framework for simulation of autocrine/paracrine stimulation of glioblastoma cell motility and proliferation by L1CAM in 2-D culture.BMC systems biology · 2017Article
- The biology and mathematical modelling of glioma invasion: a review.Journal of the Royal Society, Interface · 2017Review
- Chemoprotection Across the Tumor Border: Cancer Cell Response to Doxorubicin Depends on Stromal Fibroblast Ratios and Interstitial Therapeutic Transport.Cellular and molecular bioengineering · 2017Article
- Tumor evolution: Linear, branching, neutral or punctuated?Biochimica et biophysica acta. Reviews on cancer · 2017Review
- Article
- Agent-Based Modeling in Systems Pharmacology.CPT: pharmacometrics & systems pharmacology · 2015Article
- Coarse-grained analysis of stochastically simulated cell populations with a positive feedback genetic network architecture.Journal of mathematical biology · 2015Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
We have extended our previously developed 3D multi-scale agent-based brain tumor model to simulate cancer heterogeneity and to analyze its impact across the scales of interest. While our algorithm continues to employ an epidermal growth factor receptor (EGFR) gene-protein interaction network to determine the cells' phenotype, it now adds an implicit treatment of tumor cell adhesion related to the model's biochemical microenvironment. We simulate a simplified tumor progression pathway that leads to the emergence of five distinct glioma cell clones with different EGFR density and cell 'search precisions'. The in silico results show that microscopic tumor heterogeneity can impact the tumor system's multicellular growth patterns. Our findings further confirm that EGFR density results in the more aggressive clonal populations switching earlier from proliferation-dominated to a more migratory phenotype. Moreover, analyzing the dynamic molecular profile that triggers the phenotypic switch between proliferation and migration, our in silico oncogenomics data display spatial and temporal diversity in documenting the regional impact of tumorigenesis, and thus support the added value of multi-site and repeated assessments in vitro and in vivo. Potential implications from this in silico work for experimental and computational studies are discussed.
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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.