Bougueon, M. | Search bioRxiv

bioRxiv2026

Dynamics of the B-Cell gene regulatory network in differentiation determine evolutionary trajectories of childhood leukaemogenesis

B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) is the most frequent paediatric malignancy. Despite extensive molecular and cellular characterization a mechanistic model of leukaemogenesis has not yet been developed. Here we present a multi-valued logical model of B-cell differentiation, centred on a core pentad of transcription factors whose dysregulation results in the developmental arrest characteristic of BCP-ALL. Whilst B-cell maturation follows a fixed and sequential differentiation process, leukaemic transformation is driven by stochastic genetic insults. Integrating BCR-ABL1 as the initiating event, we model alternative evolutionary trajectories by introducing secondary mutations at different time points within synchronous simulations. We demonstrate that the combination, order and timing of secondary mutations dictate maturation arrest points and fitness, explaining how different patterns of mutations seen in patients may arise and in turn influence disease severity. This platform provides a generalisable framework to model driver mutations in their developmental context to predict evolutionary trajectories in cancer.

cancer biology↗

bioRxiv2024

A rule-based multiscale model of hepatic stellate cell plasticity: critical role of the inactivation loop in fibrosis progression

Hepatic stellate cells (HSC) are the source of extracellular matrix (ECM) whose overproduction leads to fibrosis, a condition that impairs liver functions in chronic liver diseases. Understanding the dynamics of HSCs will provide insights needed to develop new therapeutic approaches. Few models of hepatic fibrosis have been proposed, and none of them include the heterogeneity of HSC phenotypes recently highlighted by single-cell RNA sequencing analyses. Here, we developed rule-based models to study HSC dynamics during fibrosis progression and reversion. We used the Kappa graph rewriting language, for which we used tokens and counters to overcome temporal explosion. HSCs are modeled as agents that present seven physiological cellular states and that interact with (TGF{beta}1) molecules which regulate HSC activation and the secretion of type I collagen, the main component of the ECM. Simulation studies revealed the critical role of the HSC inactivation process during fibrosis progression and reversion. While inactivation allows elimination of activated HSCs during reversion steps, reactivation loops of inactivated HSCs (iHSCs) are required to sustain fibrosis. Furthermore, we demonstrated the models sensitivity to (TGF{beta}1) parameters, suggesting its adaptability to a variety of pathophysiological conditions for which levels of (TGF{beta}1) production associated with the inflammatory response differ. Using new experimental data from a mouse model of CCl4-induced liver fibrosis, we validated the predicted ECM dynamics. Our model also predicts the accumulation of iHSCs during chronic liver disease. By analyzing RNA sequencing data from patients with non-alcoholic steatohepatitis (NASH) associated with liver fibrosis, we confirmed this accumulation, identifying iHSCs as novel markers of fibrosis progression. Overall, our study provides the first model of HSC dynamics in chronic liver disease that can be used to explore the regulatory role of iHSCs in liver homeostasis. Moreover, our model can also be generalized to fibroblasts during repair and fibrosis in other tissues. Author summaryChronic liver diseases (CLDs) are associated with the development of fibrosis which is characterized by an abnormal deposition of extracellular matrix (ECM) leading to severe liver dysfunction. Hepatic stellate cells (HSCs) are key players in liver fibrosis driving ECM remodeling. However numerous biological processes are involved including HSC activation, proliferation, differentiation and inactivation and novel computational modeling is necessary to integrate such complex dynamics. Here, we used the Kappa graph rewriting language to develop the first rule-based model describing the HSCs dynamics during liver fibrosis and its reversion. Simulation analyses enabled us to demonstrate the critical role of the HSC inactivation loop in the development of liver fibrosis, and to identify inactivated HSCs as potential new markers of fibrosis progression.

systems biology↗