MAST

MAST simulates tumor-immune spatio-temporal dynamics by combining agent-based models with partial differential equations (PDEs) to produce data-informed representations of the tumor microenvironment.

Key Features:

• Hybrid Modeling Approach: Integrates discrete agent-based modeling with continuous partial differential equations to capture spatial and temporal evolution of the tumor microenvironment.
• Data-Driven Informing: Incorporates high-throughput sequencing data to parameterize simulations reflecting unique tumor subtypes.
• Application to Real Data: Applied to human colorectal cancer tissue data to simulate spatio-temporal dynamics across different simulated cancer subtypes.
• Validation with Biological Outcomes: Demonstrates agreement with established biological insights and patient cohort outcomes to support model validity.

Scientific Applications:

• Oncology Research: Enables study of tumor microenvironment dynamics relevant to cancer biology and progression.
• Tumor–Immune Interaction Studies: Supports analysis of interactions between immune cells and tumor cells over space and time.
• Personalized Simulation Studies: Facilitates individualized simulations based on patient-specific high-throughput sequencing data to explore potential treatment scenarios.

Methodology:

Combines agent-based modeling with partial differential equations and is informed by high-throughput sequencing data, with applications demonstrated on human colorectal cancer tissue data to simulate spatio-temporal tumor-immune dynamics.