ArticleBMC bioinformatics2012
Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: incorporating EGFR signaling pathway and angiogenesis.
Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 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
36 citing papers in PubMed, 65 citations in OpenAlex.
- Advancing Tumor Treatment Through Artificial Intelligence and Mathematical Modeling: A Comprehensive Review.Health science reports · 2026Article
- Multiscale mathematical model-informed reinforcement learning optimizes combination treatment scheduling in glioblastoma evolution.Science advances · 2025Article
- scProAtlas: an atlas of multiplexed single-cell spatial proteomics imaging in human tissues.Nucleic acids research · 2025Article
- Wireless sequential dual light delivery for programmed PDT in vivo.Light, science & applications · 2024Article
- Metabolic symbiosis between oxygenated and hypoxic tumour cells: An agent-based modelling study.PLoS computational biology · 2024Article
- Glutamine metabolic microenvironment drives M2 macrophage polarization to mediate trastuzumab resistance in HER2-positive gastric cancer.Cancer communications (London, England) · 2023Article
- Article
- Multiscale modeling of drug resistance in glioblastoma with gene mutations and angiogenesis.Computational and structural biotechnology journal · 2023Article
- A global method for fast simulations of molecular dynamics in multiscale agent-based models of biological tissues.iScience · 2022Article
- PhysiPKPD: A pharmacokinetics and pharmacodynamics module for PhysiCell.GigaByte (Hong Kong, China) · 2022Article
- Bayesian calibration of a stochastic, multiscale agent-based model for predicting in vitro tumor growth.PLoS computational biology · 2021Article
- Multiscale computational modeling of cancer growth using features derived from microCT images.Scientific reports · 2021Article
- Biologically-Based Mathematical Modeling of Tumor Vasculature and Angiogenesis via Time-Resolved Imaging Data.Cancers · 2021Review
- A validated mathematical model of FGFR3-mediated tumor growth reveals pathways to harness the benefits of combination targeted therapy and immunotherapy in bladder cancer.Computational and systems oncology · 2021Article
- Multiscale modeling of tumor response to vascular endothelial growth factor (VEGF) inhibitor.In silico biology · 2021Article
- Hybrid modeling frameworks of tumor development and treatment.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Article
- Interplay of Darwinian Selection, Lamarckian Induction and Microvesicle Transfer on Drug Resistance in Cancer.Scientific reports · 2019Article
- Multicellular gene network analysis identifies a macrophage-related gene signature predictive of therapeutic response and prognosis of gliomas.Journal of translational medicine · 2019Article
- Multiscale modeling reveals angiogenesis-induced drug resistance in brain tumors and predicts a synergistic drug combination targeting EGFR and VEGFR pathways.BMC bioinformatics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 3 countries.
Funding
Abstract
backgroundThe epidermal growth factor receptor (EGFR) signaling pathway and angiogenesis in brain cancer act as an engine for tumor initiation, expansion and response to therapy. Since the existing literature does not have any models that investigate the impact of both angiogenesis and molecular signaling pathways on treatment, we propose a novel multi-scale, agent-based computational model that includes both angiogenesis and EGFR modules to study the response of brain cancer under tyrosine kinase inhibitors (TKIs) treatment.
resultsThe novel angiogenesis module integrated into the agent-based tumor model is based on a set of reaction-diffusion equations that describe the spatio-temporal evolution of the distributions of micro-environmental factors such as glucose, oxygen, TGFα, VEGF and fibronectin. These molecular species regulate tumor growth during angiogenesis. Each tumor cell is equipped with an EGFR signaling pathway linked to a cell-cycle pathway to determine its phenotype. EGFR TKIs are delivered through the blood vessels of tumor microvasculature and the response to treatment is studied.
conclusionsOur simulations demonstrated that entire tumor growth profile is a collective behaviour of cells regulated by the EGFR signaling pathway and the cell cycle. We also found that angiogenesis has a dual effect under TKI treatment: on one hand, through neo-vasculature TKIs are delivered to decrease tumor invasion; on the other hand, the neo-vasculature can transport glucose and oxygen to tumor cells to maintain their metabolism, which results in an increase of cell survival rate in the late simulation stages.
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.