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<p>The extracellular matrix undergoes a transformation from soft, stable, and uniform to stiff, dynamic, and heterogeneous as disease progresses, facilitating the transformation of cells such as macrophages into malignant entities even in the absence of biochemical signals. Despite this crucial role, models elucidating the impact of matrix properties on cell phenotypic transitions, particularly those incorporating stochastic effects, are markedly limited. Here, we present a stochastic phenotypic transition model incorporating matrix-related term and parameters derived from the clutch-like model to investigate how physical changes affect macrophage functions. Our findings reveal that stiff matrices induce a chronic state of macrophages within the model, analogous to the concomitant emergence of fibrosis and chronic inflammation. The phenotypic transition of macrophages from chronic inflammation to disordered state (tumor-associated) is driven by the noise in matrix stiffness. The portrayal of macrophages within tumors, characterized by mixed phenotypes, is depicted by a bimodal distribution observed in the stationary probability density and a partial escape from the chronic state basin predicted by the conditional reliability function. Moreover, the observation of non-monotonic changes in the first passage time coupled with increased noise, alongside semi-relative sensitivity, not only underscores the potential delay between the exacerbation of macrophage phenotypes and matrix deterioration but also signals that minor perturbations might precipitate rapid phenotypic alterations necessitating clinical intervention. Through another absorbing boundary, noise in matrix stiffness serves as a cautionary indicator of the heightened susceptibility of individuals with chronic inflammation to an over-inflammatory state, which is underestimated in the analysis of stationary probability density. Overall, this model serves as a novel and efficient mechanism to simulate disease progression for diagnostic purposes and to formulate hypotheses regarding macrophage phenotypes in response to matrix stiffening, thereby providing a theoretical foundation for therapeutic interventions targeting the mechanical microenvironment.</p>

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The modeling of macrophage phenotypic states in diseases regulated by physical properties of extracellular matrix

  • 期刊论文

  • 发表日期：

    2025年1月16日

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  • Yuwei Zhou,
  • Yu Wu

摘要

The extracellular matrix undergoes a transformation from soft, stable, and uniform to stiff, dynamic, and heterogeneous as disease progresses, facilitating the transformation of cells such as macrophages into malignant entities even in the absence of biochemical signals. Despite this crucial role, models elucidating the impact of matrix properties on cell phenotypic transitions, particularly those incorporating stochastic effects, are markedly limited. Here, we present a stochastic phenotypic transition model incorporating matrix-related term and parameters derived from the clutch-like model to investigate how physical changes affect macrophage functions. Our findings reveal that stiff matrices induce a chronic state of macrophages within the model, analogous to the concomitant emergence of fibrosis and chronic inflammation. The phenotypic transition of macrophages from chronic inflammation to disordered state (tumor-associated) is driven by the noise in matrix stiffness. The portrayal of macrophages within tumors, characterized by mixed phenotypes, is depicted by a bimodal distribution observed in the stationary probability density and a partial escape from the chronic state basin predicted by the conditional reliability function. Moreover, the observation of non-monotonic changes in the first passage time coupled with increased noise, alongside semi-relative sensitivity, not only underscores the potential delay between the exacerbation of macrophage phenotypes and matrix deterioration but also signals that minor perturbations might precipitate rapid phenotypic alterations necessitating clinical intervention. Through another absorbing boundary, noise in matrix stiffness serves as a cautionary indicator of the heightened susceptibility of individuals with chronic inflammation to an over-inflammatory state, which is underestimated in the analysis of stationary probability density. Overall, this model serves as a novel and efficient mechanism to simulate disease progression for diagnostic purposes and to formulate hypotheses regarding macrophage phenotypes in response to matrix stiffening, thereby providing a theoretical foundation for therapeutic interventions targeting the mechanical microenvironment.