A HYBRID THREE-SCALE MODEL OF TUMOR GROWTH.

Area of Science:

• Computational Biology
• Cancer Research
• Mathematical Modeling

Background:

• Cancer arises from complex interactions across biological, chemical, and physical scales within the tumor microenvironment.
• Understanding these multiscale dynamics is crucial for predicting cancer growth and developing effective therapies.
• Existing models often lack the integration of multiple scales and intracellular signaling pathways.

Purpose of the Study:

• To develop and utilize a multiscale, avascular, hybrid tumor growth model integrating tissue, cell, and sub-cell levels.
• To investigate the impact of sustained proliferation mechanisms, specifically the epidermal growth factor receptor (EGFR) pathway and growth-induced stresses, on cancer progression.
• To explore how intracellular phenomena and microenvironmental factors contribute to tumor heterogeneity and behavior.

Main Methods:

• Developed a hybrid model incorporating reaction-diffusion equations for tissue-level nutrient dispersion.
• Employed an agent-based model (ABM) for cell-level dynamics, including normal and cancer cell states (apoptotic, hypoxic, necrotic).
• Integrated a detailed model of the epidermal growth factor receptor (EGFR) pathway using coupled nonlinear differential equations within each cell agent.

Main Results:

• The model successfully simulated complex tumor dynamics, including growth arrest in avascular tumors.
• Simulations demonstrated that intracellular signaling via the EGFR pathway drives proliferation and migration advantages.
• Accumulation of growth-induced stresses was shown to inhibit proliferation, contributing to tumor heterogeneity and diverse behaviors.

Conclusions:

• The multiscale hybrid model provides a robust framework for investigating tumor progression by integrating diverse biological scales.
• Intracellular signaling pathways and physical forces play significant roles in shaping tumor growth, heterogeneity, and response to stimuli.
• This modeling approach aids in understanding complex cancer mechanisms and can inform the development of targeted therapeutic strategies.