EDAR-Mediated Cell Fate Determination via the PGTM Network: A Potential Landscape Analysis.

INTRODUCTION: Skin cell fate determination is a core issue in wound repair and regenerative medicine. The multistability of the PGTM gene regulatory network, comprising ΔNp63α, GRHL2, TFAP2A, and MYC, provides a structural basis for cell fate plasticity. However, the mechanism by which the key microenvironmental signal EDAR regulates the PGTM network remains unclear. METHODS: We first constructed a coupled network model of the PGTM network with EDAR interference and further established a corresponding differential dynamic system model. We then inferred model parameters via a stable-state fitting method and analyzed the mechanism by combining potential landscape quantification and bifurcation analysis. For convenience, we mathematically defined three states: the M‑state, P‑state, and GT‑state. These states have expression profiles similar to those of the mesenchymal stem cell, epidermal progenitor cell, and early keratinocyte states, respectively, while satisfying the specified constraints. RESULTS: In the absence of EDAR interference, the PGTM network exhibits three stable states corresponding to the M‑state, P‑state, and GT‑state, respectively. As a key regulatory parameter, Se modulates the system, and its variation induces a staged transition from tristability to bistability to GT-state dominance. When Se is in the range [0, 1], three stable states coexist, accompanied by the reconfiguration of the attractor basin structure. When Se > 1, the M-state completely vanishes, and the system enters the bistable regime. Specifically, when Se > 2.7, the system evolves toward a final phase characterized by GT-state dominance, mirroring the trend of cellfate transition from mesenchymal cells through skin progenitor cells to early keratinocytes. DISCUSSION: In order to quantitatively decipher the intrinsic mechanism, we performed a bifurcation analysis with respect to Se. The increase in Se first triggers a saddle-node bifurcation in the system, which is the primary reason for the disappearance of the M-state at Se≈1.0. Thereafter, the system retains only the P-state and GT-state. As Se rises further, the stability of the P-state decreases, while the GT-state remains stable and gradually becomes dominant. This underlies the system's staged fate transition. CONCLUSION: This study provides a quantitative dynamical framework for investigating the regulatory effects of EDAR signaling on the PGTM network, offering model-derived theoretical insights for EDAR-targeted skin cell reprogramming and regenerative therapy.