Multiscale models of breast cancer progression

Area of Science:

• Computational biology
• Mathematical oncology
• Biophysics

Background:

• Breast cancer progression involves complex interactions across multiple length and time scales, from molecular events to systemic metastasis.
• Understanding these processes requires integrating cellular and subcellular signaling with microenvironmental factors.

Purpose of the Study:

• To review the state-of-the-art in multiscale cancer modeling, focusing on integrating intracellular signaling with microenvironmental cues.
• To highlight the role of tissue engineering in developing experimental models for validating multiscale simulations.

Main Methods:

• Review of biomolecular origins of breast cancer, emphasizing angiogenesis.
• Summary of tissue engineering platforms for ex vivo experimental models.
• Analysis of top-down and bottom-up multiscale modeling strategies.

Main Results:

• Integration of intracellular signal transduction with chemical and mechanical microenvironmental cues is crucial.
• Tissue engineering platforms offer high-fidelity models for simulation validation.
• Multiscale and agent-based models are advancing basic scientific discovery in cancer.

Conclusions:

• Multiscale modeling, particularly agent-based approaches, is becoming vital for cancer research.
• These models facilitate the identification and validation of novel therapeutic targets for various cancers, including breast cancer.