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Published on: February 25, 2014
Disulfidptosis in osteoarthritis: Role of SLC2A3 downregulation and potential therapeutic implications
Ruoyang Feng1, Xiadiye Tuerhong2, Yongsong Cai3
1Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China; Key Laboratory of Pathogenesis and Precision Treatment of Arthritis, Xi'an, ShaanXi Province, China.
Objective:
Disulfidptosis is a newly recognized form of regulated cell death characterized by actin cytoskeleton collapse under disulfide stress. Recent studies suggest it may significantly contribute to osteoarthritis (OA), though its exact role in OA development remains unclear. This study aims to analyze the expression of disulfidptosis-related genes in OA, identifying potential biomarkers and candidate therapeutic leads.
Methods:
Transcriptomic data from six datasets related to OA and single-cell RNA sequencing data were sourced from the GEO database. To identify differentially expressed genes (DEGs) associated with disulfidptosis, we employed robust rank aggregation. We then utilized functional enrichment analysis, constructed a protein-protein interaction network, and applied machine learning models to prioritize key genes of interest. A single-cell analysis was conducted to evaluate gene expression within specific subsets of chondrocytes. Additionally, we predicted drug-target binding affinity using the GraphDTA model and performed molecular docking studies to assess drug-to-target binding affinity. Finally, immunohistochemistry, RT-qPCR, and Western blotting were performed for experimental validation.
Results:
We identified several DEGs related to disulfidptosis, including SLC2A3, PDLIM1, and SLC3A2, which were found to be downregulated in OA tissues, particularly in pre-fibrocartilage chondrocyte subtypes. Our functional analysis indicated that these genes were enriched in pathways associated with cytoskeleton organization and the oxidative stress response. Furthermore, machine learning models demonstrated that these genes have significant diagnostic potential across various datasets. Using GraphDTA for drug prediction and molecular docking, we discovered that talaroflavone exhibits a strong binding affinity to SLC2A3, with highest predicted affinity (13.98) and a binding energy of -8.8 kcal/mol. Experimental validation confirmed the downregulation of SLC2A3 in OA-affected cartilage. Functional assays indicated that modulating SLC2A3 could alleviate cartilage matrix degradation and oxidative stress, suggesting a potential functional association between SLC2A3 and OA progression.
Conclusion:
This study providing functional evidence for a potential association between disulfidptosis-related genes and OA, while highlighting SLC2A3 as a potential functional regulator for further investigation. Additionally, was identified talaroflavone as a computationally predicted lead compound that warrants future experimental validation. These findings not only enhance our understanding of the molecular pathways underlying OA but also lay the groundwork for potential development of targeted therapeutic strategies.
Insights
Disulfidptosis, a cell death process, is linked to osteoarthritis (OA). This study identifies SLC2A3 as a key gene in OA, with talaroflavone showing potential as a therapeutic agent for OA.
Area of Science:
- Molecular Biology
- Cell Death Mechanisms
- Osteoarthritis Research
Background:
- Disulfidptosis is a regulated cell death pathway involving actin cytoskeleton collapse under disulfide stress.
- Emerging evidence suggests a role for disulfidptosis in osteoarthritis (OA) pathogenesis, but its specific contribution is not well understood.
Purpose of the Study:
- To investigate the expression of disulfidptosis-related genes in OA.
- To identify potential diagnostic biomarkers and therapeutic targets for OA.
Main Methods:
- Analysis of transcriptomic and single-cell RNA sequencing data from OA datasets.
- Identification of differentially expressed genes (DEGs) using robust rank aggregation.
- Functional enrichment, protein-protein interaction network, and machine learning analyses.
- Drug-target interaction prediction (GraphDTA) and molecular docking.
- Experimental validation using immunohistochemistry, RT-qPCR, and Western blotting.
Main Results:
- Several disulfidptosis-related DEGs, including SLC2A3, PDLIM1, and SLC3A2, were downregulated in OA tissues, particularly in chondrocyte subtypes.
- These genes are enriched in cytoskeleton organization and oxidative stress response pathways.
- Machine learning models indicated significant diagnostic potential for these genes.
- Talaroflavone demonstrated strong predicted binding affinity to SLC2A3.
- Experimental validation confirmed SLC2A3 downregulation in OA cartilage and suggested its role in mitigating cartilage degradation and oxidative stress.
Conclusions:
- Disulfidptosis-related genes are associated with OA, with SLC2A3 identified as a potential functional regulator.
- Talaroflavone emerged as a computationally predicted therapeutic lead compound for OA.
- These findings offer insights into OA molecular mechanisms and potential targeted therapies.
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