Poster #22: Julie Nguyen MS

Cartilage Explant-Based High-Throughput Screening Identifies Matrix-Protective Compounds and Supports Candidate Prioritization for Osteoarthritis Drug Repurposing

Julie Nguyen, MS, University of Delaware; Annie Porter, MS, University of Delaware; Saeideh Valipour, MS, University of Delaware; Zugui Zhang, PhD, ChristianaCare; Joseph Fox, PhD, University of Delaware; Ilya Safro, PhD, University of Delaware; Michael Axe, MD, University of Delaware; X. Lucas Lu, PhD, University of Delaware.

Osteoarthritis (OA) is characterized by progressive cartilage extracellular matrix degradation, yet no approved disease-modifying therapy prevents disease progression. Drug repurposing may accelerate therapeutic development, but large-scale screening can yield numerous hits without a systematic basis for candidate selection. We integrated cartilage explant-based high-throughput screening (HTS) with literature- and database-derived evidence to prioritize candidates for OA drug repurposing. METHODS: Juvenile bovine cartilage explants were metabolically labeled using bioorthogonal click chemistry to longitudinally quantify glycosaminoglycan (GAG) and collagen loss. Explants were co-treated with IL-1β (2-10 ng/mL) and library compounds (10 µM) across two independent plates. Protection relative to IL-1β controls was calculated, with ≥ 50% protection defining hits. MEDLINE abstracts were mined using AGATHA to identify associations between protective compounds and cartilage-related genes and molecular functions. Experimental protection and literature-derived evidence were integrated into preliminary composite priority scores, while route-of-administration information from DrugBank provided additional translational context. RESULTS: Interim data included 395 compounds evaluated for GAG protection, including 80 with preliminary collagen data. Screening identified 117 GAG-protective and 32 preliminary collagen-protective hits, representing 140 matrix-protective compounds. Nine compounds provisionally demonstrated dual GAG and collagen protection. Literature mining identified STAT3, MAPK1, VEGFA, TGFB1, and PTK2 among the strongest aggregated gene associations, with highly represented molecular functions including JUN kinase activity, signal transduction, protein biosynthesis, collagen biosynthesis, and adipogenesis. Integration of experimental and literature-derived evidence preliminarily prioritized atorvastatin, deoxycholic acid, mitoxantrone, fostamatinib disodium, and desonide as leading candidates, with DrugBank-derived administration routes providing additional context for candidate evaluation. CONCLUSION: Combining native-cartilage HTS with literature mining and drug database information provides an informed approach for translating large-scale screening results into candidate priorities supported by experimental and literature-derived evidence and contextualized with existing drug information for OA repurposing.