A multilevel approach to cancer growth modeling

Area of Science:

• Computational Biology
• Mathematical Oncology
• Biophysics

Background:

• Cancer growth is modeled macroscopically (single entity) or microscopically (cell dynamics).
• Mesoscopic models, like the Local Interaction Simulation Approach, study cell cluster interactions at intermediate scales.
• Existing models are developed independently, limiting cross-correlation and a holistic understanding.

Purpose of the Study:

• To develop an intermediate model bridging macroscopic and mesoscopic cancer growth formulations.
• To establish direct correspondences between parameters across different spatial and temporal scales.
• To analyze the influence of extracellular matrix pressure on tumor growth.

Main Methods:

• Utilized multicellular tumor spheroids as biological reference systems.
• Proposed a novel intermediate model integrating macroscopic and mesoscopic perspectives.
• Analyzed parameter dependence on extracellular matrix pressure.

Main Results:

• Established a direct correspondence between parameters characterizing processes at different scales.
• Demonstrated consistency between macroscopic (e.g., energy conservation) and mesoscopic (cell dynamics) models.
• Showed the proposed formalism aligns with universal growth law conjectures.

Conclusions:

• The developed intermediate model effectively bridges macroscopic and mesoscopic cancer growth descriptions.
• The model provides a unified framework for understanding tumor growth mechanisms.
• Cross-validation of macro and mesoscopic models enhances their reliability and applicability.