Speaker
Description
Cancer-associated fibroblasts (CAFs) are key components of the tumor microenvironment (TME) and exhibit highly heterogeneous phenotypes that can either promote or suppress tumor growth. While clinical evidence increasingly links CAF composition to patient survival and drug response, a quantitative framework that predicts treatment outcomes from CAF phenotypic profiles has been lacking.
Here we present an ordinary differential equation (ODE) model that captures the interactions among cancer cells, effector and regulatory T cells, and four functionally distinct CAF phenotypes — anti-immune, pro-immune, anti-cancer, and pro-cancer. CAF fractions enter as direct modulators of PD-1/PD-L1 binding kinetics, PI3K/AKT signaling, and Treg recruitment. Simulations demonstrate that CAF composition profoundly shapes cancer growth and immunotherapy outcomes: the same PD-L1, Treg, or PI3K inhibitor can succeed in one CAF regime and fail in another. A model-guided treatment map identifies CAF profiles for which monotherapy is as effective as combination therapy, profiles requiring combination, and a minority resistant even to triple therapy. Kaplan–Meier simulations across 500 virtual patients show order-of-magnitude survival differences arising purely from CAF composition \cite{1}.
Building on this framework, our ongoing work extends the model into a hybrid agent-based / PDE / ODE system that additionally represents the spatial arrangement of CAFs and the PD-1/PD-L1 dynamics of individual T cells. Preliminary results suggest that spatial layout is a distinct, complementary axis of TME heterogeneity, offering a path toward CAF-informed, spatially resolved precision oncology.
Bibliography
@article{1,
title = {Ordinary differential equation model of cancer-associated fibroblast heterogeneity predicts treatment outcomes},
volume = {11},
issn = {2056-7189},
url = {https://www.nature.com/articles/s41540-025-00578-y},
doi = {10.1038/s41540-025-00578-y},
language = {en},
number = {1},
urldate = {2026-07-08},
journal = {npj Systems Biology and Applications},
author = {Lee, Junho and Kim, Eunjung},
month = aug,
year = {2025},
pages = {96},
}
