Oxygen-Driven Tumour Growth Model: A Pathology-Relevant Mathematical Approach

Area of Science:

• Mathematical Oncology
• Tumor Microenvironment
• Preclinical Cancer Models

Background:

• Xenograft models, commonly used in cancer research, exhibit significant differences in vasculature and stromal architecture compared to human tumors.
• These physiological discrepancies complicate the translation of mathematical model-based predictions from animal studies to clinical outcomes.
• Understanding tumor progression and physiology differences between animal models and clinical settings is crucial for accurate predictive modeling.

Purpose of the Study:

• To develop and validate a mathematical model that accounts for tumor pathophysiology, focusing on oxygen dynamics.
• To investigate how oxygen transport and cellular proliferation rates influence tumor growth and characteristics in preclinical models.
• To identify distinct physiological profiles of tumors based on key parameters derived from the model.

Main Methods:

• Proposed the Oxygen-Driven Model (ODM), utilizing oxygen diffusion equations to simulate tumor growth, hypoxia, and necrosis.
• Defined two key physiological parameters: apparent oxygen uptake rate (k'R) and proliferation rate (kp).
• Retrospectively analyzed longitudinal tumor volume data from 38 xenografted cell lines and 5 patient-derived xenograft-like models.

Main Results:

• Identified two distinct groups of cell lines based on parameter space exploration: Group 1 (low k'R, low kp) indicating poor perfusion and slow growth; Group 2 (consistent k'R, variable kp) suggesting similar oxygen transport but intrinsic growth variability.
• The ODM successfully described tumor growth, hypoxia, and necrosis dynamics.
• The model's limitations were noted in explant-like animal models due to complex tumor-stromal morphology not fully captured.

Conclusions:

• The Oxygen-Driven Model (ODM) provides a versatile framework for analyzing tumor physiology and distinguishing between different tumor growth characteristics in preclinical models.
• The model highlights the importance of oxygen transport (k'R) and proliferation rates (kp) in defining tumor behavior.
• Future enhancements incorporating stromal interactions are recommended to improve model accuracy for complex preclinical systems and enhance predictions for clinical translation.