Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023And generous funding to support our work from the NCI, NCI Systems Biology, lLustgarten Foundation, the NSF, the JKTG Foundation, and others. Thank you for following along! 19/19 000
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Thanks to contributions from all of our collaborators at JHU, IU, OHSU and beyond-- Dr. Ines Godet, Dr. Laura Heiser, and the Jaffee lab just to name a few 18/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023This has been a true dream team science project led by @mathcancer.bsky.social @fertiglab.bsky.social and Dr. Genevieve Stein-O'Brien 17/19 110
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Another nice benefit of our approach is that we can combine the model grammar with graphical interfaces to easily write and test new models without writing code. This opens the world of simulation modeling to new communities. (Preprint by @rheiland soon!) 16/19 132
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Altogether, this approach shows a powerful new strategy to predict emergent cell behaviors and test the impact of hypotheses of the impact of cell-cell interactions defined either from literature or genomics that are broadly applicable across biological systems. 15/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023In this work, we found that applying combination immunotherapy to our model improved clearance of virtual tumors. 14/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Example 5 extends our model to simulate combination immunotherapy strategies in pancreatic cancer based on these genomics-derived rules of immune cell interactions in immunotherapy response to provide a platform for virtual clinical trials. 13/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Genomics data can also be used to define novel cell-cell interactions of tumor-immune interactions during immunotherapy response and propose candidate therapeutic targets to overcome immunosuppressive signaling (e.g., www.cell.com/cancer-cell/... 12/19cell.comPage not found: Cancer Cell 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023This example demonstrates the power of the simulation to model emergent cell behaviors, as a population of protective M2-like macrophages emerges as the simulation progresses and protects the remaining tumor from destruction. 11/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023With the immune cells in place, example 4 uses extensive literature-derived rules of tumor-immune interactions to simulate T cell activation in response to tumor contact. 10/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Example 3 extends this tumor model to incorporate the regulation of tumor growth in immune cells 9/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023This model allowed us to forecast PDAC microenvironment dynamics from RNA and imaging information. We saw isolated tumor cells transition predominantly to the mesenchymal phenotype and then formulate nests of epithelial tumor cells invade during carcinogenesis. 8/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Example 2 models human pancreatic tumor progression to invasion by initializing mathematical agents from spatial transcriptomics coordinates of epithelial cells and fibroblasts the hypothesis grammar to encode our genomics-inferred rules of their cell-cell interactions. 7/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Recently, integrating single-cell data from human pancreatic cancer tumors and organoid co-culture demonstrated a trade-off between tumor cell proliferation and fibroblast-associated EMT in epithelial cells. 6/19 doi.org/10.1101/2022... 110
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Example 1 simulates unchecked cell growth in cancer, which exhausts oxygen in non-vascularized tumors. Modeling this resource consumption problem has provided a foundation for mathematical modeling of tumors, and this serves as the base example of tumor cell behavior. 5/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023To allow for human-readable encoding of equations, we define a new concept of hypothesis grammar and demonstrate its use in 5 real-world biological examples. 4/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Here, we extend PhysiCell to model cellular systems that translates human-readable text into mathematical equations of cell behavior for broad accessibility of these complex mathematical models. 3/19 100
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Agent-based modeling is particularly well-suited to studying communities of interacting cells, as it is intuitive to map a single cell to a single agent and is readily empowered through the PhysiCell software ecosystem. 2/19 journals.plos.org/ploscompbiol...journals.plos.orgPhysiCell: An open source physics-based cell simulator for 3-D multicellular systemsAuthor summary This paper introduces PhysiCell: an open source, agent-based modeling framework for 3-D multicellular simulations. It includes a standard library of sub-models for cell fluid and solid ... 120
Jeanette Johnson @jeanettejohnson.bsky.social · 22/09/2023Thrilled to announce a new preprint developing a new grammar in @PhysiCell to bridge biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale including integration of single-cell multi-omics data. 1/19 www.biorxiv.org/content/10.1...biorxiv.orgDigitize your Biology! Modeling multicellular systems through interpretable cell behaviorbioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution 2135
