Live-cell tissue models
Whole-tissue and tissue-like systems make it possible to watch tumor cells interact with host cells, extracellular matrix, and treatment in context.
Tumor ecosystem dynamics
Tumors are living ecosystems.
The Davies Cancer Lab develops living tissue models, time-lapse imaging, and computational approaches to understand how cancer cells respond to their surroundings across space and time.
Live tissue imaging reveals tumor cells and host environments as dynamic ecosystems.
Therapy response in context
Watch drug response and adaptive tumor survival in real time.
Using our Serial Imaging of Tumor and microEnvironment (SITE) ex vivo tissue culture, imaging, and in silico predictive modeling platform, we directly observe how tumor cells die, persist, and rewire signaling after treatment.
Directly measure response. Follow tumor death and persistence over hours to days in intact tissue environments.
Resolve adaptation. Link signaling dynamics and microenvironmental position to survival under therapy.
Design better therapies. Use real-time ecosystem measurements to identify vulnerabilities in adaptive tumor states.
Tumor death after cytotoxic drug addition, revealing dynamic response and adaptive survival in tissue context.
We study cancer as a living system.
Tumors are not static collections of cells. They are changing ecosystems shaped by signaling, physical contacts, tissue architecture, treatment, and time. Our work combines experimental tumor-host models with quantitative analysis to measure these processes directly.
Computational dynamics
Image-derived models connect single-cell behavior, tissue organization, and fate decisions to predict how tumor ecosystems evolve.
Osteosarcoma and metastatic response
We use osteosarcoma as a powerful system to study metastatic survival, tumor-host signaling, and how therapies can be improved in the lung microenvironment.
Our long-term goal is to define the rules that govern tumor progression and use them to identify better points of intervention.
Map cell state in context. Quantify signaling, position, contacts, and fate at single-cell resolution.
Measure tumor-host interactions. Determine how cells and tissue niches promote survival, death, invasion, and resistance.
Build predictive models. Translate longitudinal imaging into executable models of tumor ecosystem behavior.
Design control strategies. Use dynamics to reveal when, where, and how therapies can redirect tumor cell fate.