Modeling intra- and inter-cellular networks for TRPC6-dependent cardiac fibrosis

Summary Heart disease remains the leading cause of death worldwide with a major contributor being coronary artery blockage and myocardial infarction (MI, affecting ~800K/year in US). As a result, a substantial fraction of cardiac muscle is permanently replaced with fibrotic scar. Fibrosis affects not just the heart but all organs, with no available efficacious antifibrotic therapies due to the field's limited understanding. Most experimental studies have pursued reductionist approaches to identify individual targets against fibrosis, such as the promising target TRPC6. Yet as with other targets, how TRPC6 mechanistically drives myofibroblast transition remains poorly characterized, limiting clinical translation. Here, we seek to define the multi-scale intra- and inter-cellular signaling networks mediating TRPC6-dependent cardiac fibrosis. This leverages our preliminary data characterizing the TRPC6 interactome, as well as our new computational methods and models that map pathways from novel protein interactions into the fibroblast intracellular-intercellular signaling network. To meet this challenge, we introduce a new computational method, Logic-Based Network Expansion with Protein Interactomes (LogNEPRI). LogNEPRI maps pathways from novel interactions to a validated network model, which bolsters subsequent experimental validation. By integrating multi-scale computational models and experiments ranging from genetic and proteomic screens to mice, we test the overall hypothesis that the TRPC6- interactome induces myofibroblast transformation and fibrosis in response to both cardiac and dermal wounds. In Specific Aim 1, we develop LogNEPRI to integrate multi-omic data (overexpression screens, proteomic screen for TRPC6 partners) to automatically expand a mechanistic network model to predict and experimentally validate TRPC6-dependent drivers of myofibroblast transformation. In Specific Aim 2, we integrate the LogNEPRI- expanded model of intracellular fibroblast signaling with a model of intercellular inflammation-fibrosis signaling post-myocardial infarction, which we validate by global knockout and fibroblast-specific overexpression of TRPC6/ARHGEF2 in vivo. The generality of predicted roles for TRPC6/ARHGEF2 will be further validated in dermal fibroblasts and dermal wounds. Overall, these studies will establish a new computational approach LogNEPRI for automated expansion of network models that integrates multi-omic data with highly-validated network models. This approach and a new multi-scale computational model of intra-intercellular signaling of fibrosis will identify and validate novel pathways that explain how a high-priority target (TRPC6) modulates fibrosis after myocardial infarction and dermal wounds. Project Number: 1R01HL176700-01A1 | Fiscal Year: 2025 | NIH Institute/Center: National Heart Lung and Blood Institute (NHLBI) | Principal Investigator: Jeffrey Saucerman (+1 co-PI) | Institution: UNIVERSITY OF VIRGINIA, CHARLOTTESVILLE, VA | Award Amount: $726,452 | Activity Code: R01 | Study Section: Modeling and Analysis of Biological Systems Study Section[MABS] View on NIH RePORTER: https://reporter.nih.gov/project-details/1R01HL17670001A1