AI-based Predictive Signaling Pathway Profiling in Cardiac Fibrosis Suggests a Novel Combinatorial Treatment Strategy
Here we employed the wealth of past signaling pathway data underlying cardiac fibrosis to train an AI model, which suggested an optimized approach of inhibiting 2 nodal signaling pathways but with differential timing as a more effective therapeutic strategy that reduces pathologic cardiac fibrosis without negatively impacting compensatory fibrotic activity with acute MI injury. The therapeutic approach involves altering the timing of JAK-STAT signaling blockade with ruxolitinib (RUX) in combination with delayed and temporary TGF-β signaling inhibition post MI injury with pirfenidone (PFD).
Authors
- Ningxin Gao
- Qinghang Meng (ORCID: https://orcid.org/0000-0002-2253-1641)
- Jeffery D. Molkentin (ORCID: https://orcid.org/0000-0002-3558-6529)
- Qing‐Sheng Mi (ORCID: https://orcid.org/0000-0002-1411-6827)
- Jiuzhou Huo (ORCID: https://orcid.org/0000-0003-3242-568X)
- Jie Chen (ORCID: https://orcid.org/0000-0001-9375-7210)
- Xinhua Lin (ORCID: https://orcid.org/0000-0002-1063-749X)
- Bo Yang (ORCID: https://orcid.org/0000-0001-5586-3186)
Institutions
- Cincinnati Children's Hospital Medical Center (US)
- Fudan University (CN)
- Precision for Medicine (United States) (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2025-12-04
- DOI
- https://doi.org/10.64898/2025.12.04.692460
- Primary Topic
- Cardiac Fibrosis and Remodeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00