Digitize your Biology! Modeling multicellular systems through interpretable cell behavior

Date:	5 November 2023
PMID:	PMC10516032
Category:	N/A
Authors:	Jeanette A I Johnson, Genevieve L Stein-O'Brien, Max Booth, Randy Heiland, Furkan Kurtoglu, Daniel R Bergman, Elmar Bucher, Atul Deshpande, André Forjaz, Michael Getz, Ines Godet, Melissa Lyman, John Metzcar, Jacob Mitchell, Andrew Raddatz, Heber Rocha, Jacobo Solorzano, Aneequa Sundus, Yafei Wang, Danielle Gilkes, Luciane T Kagohara, Ashley L Kiemen, Elizabeth D Thompson, Denis Wirtz, Pei-Hsun Wu, Neeha Zaidi, Lei Zheng, Jacquelyn W Zimmerman, Elizabeth M Jaffee, Young Hwan Chang, Lisa M Coussens, Joe W Gray, Laura M Heiser, Elana J Fertig, Paul Macklin
Abstract:

Cells are fundamental units of life, constantly interacting and evolving as dynamical systems. While recent spatial multi-omics can quantitate individual cells' characteristics and regulatory programs, forecasting their evolution ultimately requires mathematical modeling. We develop a conceptual framework-a cell behavior hypothesis grammar-that uses natural language statements (cell rules) to create mathematical models. This allows us to systematically integrate biological knowledge and multi-omics data to make them computable. We can then perform virtual "thought experiments" that challenge and extend our understanding of multicellular systems, and ultimately generate new testable hypotheses. In this paper, we motivate and describe the grammar, provide a reference implementation, and demonstrate its potential through a series of examples in tumor biology and immunotherapy. Altogether, this approach provides a bridge between biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale, allowing the community to extrapolate from single-cell characterization to emergent multicellular behavior.

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Acknowledgements:

The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute, or the National Institute of Health.

The Translational and Basic Science Research in Early Lesions (TBEL) Research Consortia is supported and funded by grants from the National Cancer Institute and the National Institutes of Health under the following award numbers:

Project Number:	Awardee Organization
U54CA274374	Fred Hutchinson Cancer Center
U54CA274375	Houston Methodist Research Institute
U54CA274370	Johns Hopkins University
U54CA274371	UT MD Anderson Cancer Center
U54CA274367	Vanderbilt University Medical Center