Mathematical Biology Tumor Growth

Eco-Evolutionary Dynamics of Proliferation Heterogeneity: A Phenotype-Structured Model for Tumor Growth and Treatment Response

This paper develops a phenotype-structured model to study how proliferation heterogeneity affects tumor growth and treatment response, showing that optimal proliferation rates shift with tumor size and treatment regimes.

A mathematical investigation of the interplay between vasculature and intratumoral cellular heterogeneity during tumor progression

This paper develops a mathematical model to study how tumor vasculature and cellular heterogeneity interact during progression, showing angiogenesis increases growth rate and hypoxic cells strongly influence phenotypic switching.

Evolutionary implications of phenotype switching for growth and survival of tumors in stochastic environments.

This study shows that tumor cells adapt to changing environments through phenotypic switching, with optimal survival achieved by blocking mesenchymal to epithelial transition.

Emergence of travelling wave patterns in resource-mediated tissue competition

This paper studies resource-mediated tissue competition using mathematical models and simulations, showing the emergence of travelling wave patterns that depend on population fitness and resource dynamics.

Mixed effects modeling of the synergy between immune checkpoint and thrombin inhibitors in a preclinical mouse model of colon cancer

The paper uses nonlinear mixed-effects modeling to study synergy between immune checkpoint and thrombin inhibitors in a mouse colon cancer model, identifying mechanisms like CD8+ T cell expansion.

Thermodynamic continuum tumour modelling recovers multicompartment spheroid structure and supports drug-response screening

This paper develops a thermodynamic continuum model of tumour spheroid growth that recovers multicompartment structure and supports drug-response screening without prescribing compartments.

UQ-PhysiCell: An extensible Python framework for uncertainty quantification and model analysis in PhysiCell

UQ-PhysiCell provides a Python framework for uncertainty quantification, calibration, and model analysis in PhysiCell simulations, enabling scalable and reproducible uncertainty-aware analysis of agent-based models.

Modelling phenotypic plasticity in cancer invasion and metastasis: from microscopic interactions to macroscopic dynamics

This study develops macroscopic models to simulate cancer cell invasion and metastasis by bridging microscopic cell dynamics with continuum descriptions, showing accurate reproduction of phenotypic and spatial patterns.

Quantitative Calibration of a Spatial QSP Model Identifies Fibroblast Impact on HCC Immunotherapy

The paper calibrates a spatial QSP model using CODEX data to predict TME states and identify biomarkers for HCC immunotherapy response.

Spectral fingerprints distinguish buckling from angiogenesis in tortuous blood vessels

The paper distinguishes between buckling and angiogenesis in blood vessel tortuosity using spectral analysis of vessel morphology.

Cell Cluster Geometry and Fluidity Control the Transition from Single-Cell Chemorepulsion to Collective Chemotaxis

This study shows that cell cluster geometry and fluidity control the transition from single-cell chemorepulsion to collective chemotaxis through receptor trafficking and critical concentration thresholds.

Traveling Wave Analysis of a Go-or-Grow Invasion Model with ECM-Regulated Phenotypic Switching

The paper analyzes a go-or-grow invasion model with ECM-regulated phenotypic switching, showing that the reduced model captures the dynamics and deriving the minimum traveling wave speed.

Deciphering population-level response under spatial drug heterogeneity on microhabitat structures

The paper develops a model to predict population responses to spatially heterogeneous drug treatments by analyzing growth, migration, and microhabitat structures.

Personalized Immunotherapy via Multiscale Tumor-Immune Modeling and Optimal Control

This paper develops a multiscale tumor-immune model with optimal control for personalized immunotherapy, achieving 78% tumor reduction in simulations compared to standard-of-care.

MISSTE: a multiscale integrative spatial simulator for understanding the mechanisms underlying tissue ecosystems

MISSTE simulates multiscale tissue ecosystems to improve CAR-T therapy by identifying spatial access as a key bottleneck for immune persistence and tumor control.

A new cancer progression model: from synthetic tumors to real data and back

This paper introduces a stochastic model of tumor evolution that integrates genetic and environmental factors to simulate clonal dynamics and demonstrates how ecological feedbacks shape cancer progression.

Informing agent-based models with spatial data using convolutional autoencoders

This paper presents a framework to optimize agent-based models using spatial data by comparing imaging data and model outputs in a shared latent space, showing improved reproduction of spatial features.

Coupled SDE-ODE Modeling of Tumor-Immune Dynamics to Infer Biomarker Release

This paper develops a coupled SDE-ODE model to infer tumor burden from biomarker signals by linking tumor-immune dynamics to ctDNA release.

Phenotypic Plasticity and Competition Shape Therapy Sequencing in HER2+/HER2- Breast Cancer: A Mathematical Framework

The paper develops a mathematical model to study how phenotypic plasticity and competition between HER2+ and HER2- cells affect treatment outcomes in breast cancer, showing that treatment order and intensity influence long-term tumour composition.

140 Years of mathematical modeling in oncology through AI-assisted curation

This paper curates a large corpus of mathematical oncology literature using AI, revealing its evolution from cancer biology to therapeutic modeling over 140 years.

Stability Transitions in Discrete Tumor-Immune Dynamics under Immune Suppression

This study uses a discrete-time tumor-immune model to analyze stability transitions and bifurcations under immune suppression, showing how parameter changes affect tumor control and immune escape.

Receptor-structured modelling of EGFR-driven tumor initiation: from spatially resolved cell-based simulations to reduced population dynamics

The paper develops multiscale models linking EGFR receptor dynamics to tumor growth thresholds, showing how receptor abundance and ligand binding affect sustained tumor initiation.

Endocytosis suppresses stochastic collapse in fibroblast-macrophage circuits under shared resource competition

The paper models fibroblast-macrophage circuits to show endocytosis stabilizes coexistence under resource competition by suppressing stochastic failure, with macrophage CSF uptake being critical.

Which evolutionary game-theoretic model best captures non-small cell lung cancer dynamics?

The paper fits evolutionary game-theoretic models to NSCLC in-vitro data to identify the best model for capturing tumor growth and treatment response dynamics.

Exploring the relationship between vascular remodelling and tumour growth using agent-based modelling

This paper develops an agent-based model to simulate vascular remodelling and its impact on tumour growth and response to radiotherapy, showing that friction forces significantly influence vessel compression and tumour regrowth.

Ecological Dynamics of Pro-tumor and Anti-tumor Teams in the Tumor Microenvironment

The paper models tumor-immune interactions as a two-team ecosystem using a generalized Lotka-Volterra framework to predict ecological outcomes in the tumor microenvironment.

A computational model reveals that spatial localization of cancer stem cells increases radioresistance in tumorspheres

This paper shows that cancer stem cells in tumorspheres are more radioresistant due to their spatial localization in hypoxic regions, which protects them from radiation.

Model-supported patient stratification using multi-objective synergy optimization in combination therapy

This paper develops a method to stratify patients for combination therapy by optimizing synergy across efficacy and potency, using a preclinical mouse dataset to demonstrate subgroup-specific treatment responses.

A Hallmark-Integrated, Agent-Based Framework for Intratumor Heterogeneity in Melanoma Evolution

This paper introduces a computational model to study intratumor heterogeneity in melanoma by integrating cancer hallmarks and simulating genetic, immune, and spatial pressures.

Asymmetric drug effects drive near-extinction cancer cell oscillations in transgenic oncolytic virotherapy: A modelling study

This paper models oncolytic virotherapy with and without a prodrug-activating transgene, showing that asymmetric drug effects can drive oscillations in cancer cell populations.