Abstract
Background: Without the availability of disease-modifying drugs, there is an unmet therapeutic need for osteoarthritic patients. During osteoarthritis, the homeostasis of articular chondrocytes is dysregulated and a phenotypical transition called hypertrophy occurs, leading to cartilage degeneration. Targeting this phenotypic transition has emerged as a potential therapeutic strategy. Chondrocyte phenotype maintenance and switch are controlled by an intricate network of intracellular factors, each influenced by a myriad of feedback mechanisms, making it challenging to intuitively predict treatment outcomes, while in silico modeling can help unravel that complexity. In this study, we aim to develop a virtual articular chondrocyte to guide experiments in order to rationalize the identification of potential drug targets via screening of combination therapies through computational modeling and simulations.Results: We developed a signal transduction network model using knowledge-based and data-driven (machine learning) modeling technologies. The in silico high-throughput screening of (pairwise) perturbations operated with that network model highlighted conditions potentially affecting the hypertrophic switch. A selection of promising combinations was further tested in a murine cell line and primary human chondrocytes, which notably highlighted a previously unreported synergistic effect between the protein kinase A and the fibroblast growth factor receptor 1.Conclusions: Here, we provide a virtual articular chondrocyte in the form of a signal transduction interactive knowledge base and of an executable computational model. Our in silico-in vitro strategy opens new routes for developing osteoarthritis targeting therapies by refining the early stages of drug target discovery.
Original language | English |
---|---|
Article number | 253 |
Number of pages | 25 |
Journal | Bmc Biology |
Volume | 20 |
Issue number | 1 |
DOIs | |
Publication status | Published - 9 Nov 2022 |
Keywords
- Network of signal transduction
- Computational modeling
- Drug targets
- Osteoarthritis
- Chondrocyte hypertrophy
- In vitro validation
- Regulatory network inference
- Virtual cell
- ARTICULAR-CARTILAGE
- INDIAN HEDGEHOG
- REGULATORY NETWORKS
- SYSTEMS BIOLOGY
- ONCOSTATIN-M
- X COLLAGEN
- TGF-BETA
- EXPRESSION
- DIFFERENTIATION
- PROGRESSION