Dual inhibition of EGR1/STAT3 transcriptional hubs suppresses macrophage-driven liver fibrosis: A multi-omics-guided drug repurposing strategy

Liver fibrosis (LF), driven by dysregulated macrophage polarization and extracellular matrix remodeling, represents a critical and unmet therapeutic challenge in chronic liver diseases. Despite decades of research, the lack of agents targeting core transcriptional regulators of fibrogenesis underscores the urgent need for mechanism-based interventions. An integrative analysis of three single-cell transcriptomic atlases identified Early Growth Response 1 (EGR1) and Signal Transducer and Activator of Transcription 3 (STAT3) as central transcriptional regulators that orchestrate pro-fibrotic macrophage polarization and the downstream activation of fibrogenic effectors such as Arginase 1 (Arg1), Fibronectin 1 (Fn1), Osteopontin (Spp1), and Thrombospondin 1 (Thbs1). By leveraging computer-aided drug design (CADD), multi-precision virtual screening of both the FDA-approved drug library and the TCMSP drug database identified Cidofovir and Pioglitazone as novel inhibitors selectively targeting EGR1 and STAT3, respectively. Molecular dynamics simulations confirmed stable binding interactions at their DNA-binding domains. Functional validation in macrophages showed that Cidofovir suppressed EGR1 signaling and downstream fibrotic gene expression, while Pioglitazone inhibited STAT3 activity and M2 macrophage polarization. In a murine LF model, dual therapy synergistically reduced Collagen deposition and hepatic stellate cell activation, exhibiting superior efficacy compared to monotherapy. This study pioneers the therapeutic repositioning of Cidofovir and Pioglitazone as dual-target transcriptional inhibitors, disrupting the EGR1/STAT3-Fn1/Spp1/Thbs1 axis to attenuate fibrotic niche formation. Our "multi-omics to bedside" framework, empowered by computer-aided drug design, not only deciphers macrophage-centric fibrogenic networks but also delivers clinically translatable candidates, bridging the gap between computational drug discovery and precision antifibrotic therapy.

EGR1; Liver fibrosis; M2 macrophages; STAT3; Virtual screening.