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

Area of Science:

• Computational Biology
• Systems Biology
• Immunology

Background:

• Multiscale tissue ecosystems involve complex interactions often studied in isolation.
• Understanding these interactions is crucial for developing effective cellular therapies.

Purpose of the Study:

• To introduce MISSTE, a novel computational framework integrating multiple scales for tissue ecosystem simulation.
• To apply MISSTE to model CAR-T therapy in solid tumors and identify key determinants of efficacy.

Main Methods:

• Developed MISSTE, a modular framework combining Boolean logic, agent-based modeling, and partial differential equations.
• Simulated CAR-T therapy within a solid tumor microenvironment using the MISSTE framework.

Main Results:

• The model accurately recapitulated CAR-T behaviors like limited penetration, exhaustion, and microenvironmental constraints.
• Optimizing CAR-T interaction range, migration, and cytotoxicity improved immune persistence.
• Spatial access emerged as a more significant bottleneck than killing strength.

Conclusions:

• MISSTE provides a generalizable multiscale approach for studying tissue ecosystems.
• The findings highlight spatial access as a critical factor in CAR-T therapy efficacy.
• Mechanistically informed, sequential intervention strategies can outperform static optimization for engineered cellular therapies.