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Initial 3D Cell Cluster Control in a Hybrid Gel Cube Device for Repeatable Pattern Formations

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Progress Towards Computational 3-D Multicellular Systems Biology.

Paul Macklin¹, Hermann B Frieboes², Jessica L Sparks³

¹Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, CA, USA. Paul.Macklin@MathCancer.org.

Advances in Experimental Medicine and Biology

|October 15, 2016

Summary

This summary is machine-generated.

Computational cancer biology requires integrated models of tumor microenvironments. Our work advances simulation platforms for complex, multicellular tumor systems, integrating mechanics, flow, and heterogeneity for better reproducibility and discovery.

Keywords:

Cancer microenvironment Computational modeling Multicellular systems biology Tissue engineering

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Area of Science:

Computational biology
Cancer research
Systems biology

Background:

Tumors are complex systems influenced by their microenvironment.
Tumor and stromal cells dynamically interact with and remodel their surroundings.
Understanding cancer necessitates investigating it as an adaptive, multicellular system.

Purpose of the Study:

To review advances in computational modeling of tumor microenvironments.
To highlight the need for integrated modeling platforms.
To discuss the development of open-source tools and data standards for cancer systems biology.

Main Methods:

Advanced modeling of tissue mechanics and interstitial flow.
Development of open-source simulation software.
High-throughput phenotypic screening and multicellular data standards.

Main Results:

Progress in modeling key aspects of tumor microenvironment dynamics.
Creation of integrated computational platforms for cancer research.
Establishment of open data standards for enhanced reproducibility.

Conclusions:

Computational cancer biology is shifting towards integrated, multi-coalition approaches.
Future research will focus on simulating 3-D multicellular systems biology of cancer.
This approach promises a transformative impact on understanding and treating cancer.