Bioinformatics-Based Analysis of Ferroptosis-Related Biomarkers and the Prediction of Drugs Affecting the Adipogenic Differentiation of MSCs

<b>Background</b>: The imbalance between the osteogenic and adipogenic differentiation of mesenchymal stem cells (MSCs) is a key factor in the progression of osteoporosis; therefore, it is crucial to study the regulatory mechanisms that maintain this balance. Ferroptosis is a form of regulated cell death caused by the accumulation of lipid peroxides and is closely associated with various diseases. Changes in intracellular oxidative stress levels can affect the lineage allocation of MSCs. However, it remains unclear whether the disruption of intracellular oxidative stress levels caused by ferroptosis can influence the osteogenic-adipogenic differentiation balance of MSCs, and the mechanism underlying this influence in osteoporosis has not been fully elucidated. This study is the first to demonstrate through in vitro cell experiments that inhibiting ferroptosis can decrease the adipogenic differentiation of MSCs. <b>Methods and Results:</b> Through bioinformatics analysis, differentially expressed genes (DEGs) associated with the adipogenic differentiation of MSCs were identified from the GEO database. We then intersected these differentially expressed genes with a ferroptosis-related gene dataset and identified 118 ferroptosis-related differentially expressed genes (FRDEGs). Additionally, we explored the functional roles of FRDEGs through GO and KEGG analyses and found that these genes significantly impacted intracellular oxidative stress. Furthermore, we identified 10 key FRDEGs via protein-protein interaction (PPI) analysis. The diagnostic performance of these genes was evaluated by plotting receiver operating characteristic (ROC) curves, and the reliability of the diagmodel was validated using data from osteoporosis patients. We then constructed a mouse osteoporosis model and validated the mRNA expression levels of key FRDEGs via qRT-PCR, which revealed significant differences in expression in the osteoporosis group. Finally, molecular docking technology was used to identify two small molecules from the DrugBank database that are able to negatively regulate MSC adipogenic differentiation by inhibiting ferroptosis. <b>Conclusions:</b> The identified FRDEGs and small molecules offer novel diagnostic markers and therapeutic candidates for osteoporosis.

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Journal
Biomedicines
Published
2025-04-11
DOI
https://doi.org/10.3390/biomedicines13040940
Primary Topic
Cancer-related molecular mechanisms research
Type
article
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article

Bioinformatics-Based Analysis of Ferroptosis-Related Biomarkers and the Prediction of Drugs Affecting the Adipogenic Differentiation of MSCs

Pengfei Ji, Zihao Yuan, Xinglang Wang, Jiahao Jin et al.
Biomedicines
Cancer-related molecular mechanisms research
article

Bioinformatics-Based Analysis of Ferroptosis-Related Biomarkers and the Prediction of Drugs Affecting the Adipogenic Differentiation of MSCs

Pengfei Ji, Zihao Yuan, Xinglang Wang, Jiahao Jin, Wenjie Liu, Yunhui Zhang, Yibin Zhang, Yanfeng Wu, Quanfeng Li, Peng Wang
article en

Abstract

<b>Background</b>: The imbalance between the osteogenic and adipogenic differentiation of mesenchymal stem cells (MSCs) is a key factor in the progression of osteoporosis; therefore, it is crucial to study the regulatory mechanisms that maintain this balance. Ferroptosis is a form of regulated cell death caused by the accumulation of lipid peroxides and is closely associated with various diseases. Changes in intracellular oxidative stress levels can affect the lineage allocation of MSCs. However, it remains unclear whether the disruption of intracellular oxidative stress levels caused by ferroptosis can influence the osteogenic-adipogenic differentiation balance of MSCs, and the mechanism underlying this influence in osteoporosis has not been fully elucidated. This study is the first to demonstrate through in vitro cell experiments that inhibiting ferroptosis can decrease the adipogenic differentiation of MSCs. <b>Methods and Results:</b> Through bioinformatics analysis, differentially expressed genes (DEGs) associated with the adipogenic differentiation of MSCs were identified from the GEO database. We then intersected these differentially expressed genes with a ferroptosis-related gene dataset and identified 118 ferroptosis-related differentially expressed genes (FRDEGs). Additionally, we explored the functional roles of FRDEGs through GO and KEGG analyses and found that these genes significantly impacted intracellular oxidative stress. Furthermore, we identified 10 key FRDEGs via protein-protein interaction (PPI) analysis. The diagnostic performance of these genes was evaluated by plotting receiver operating characteristic (ROC) curves, and the reliability of the diagmodel was validated using data from osteoporosis patients. We then constructed a mouse osteoporosis model and validated the mRNA expression levels of key FRDEGs via qRT-PCR, which revealed significant differences in expression in the osteoporosis group. Finally, molecular docking technology was used to identify two small molecules from the DrugBank database that are able to negatively regulate MSC adipogenic differentiation by inhibiting ferroptosis. <b>Conclusions:</b> The identified FRDEGs and small molecules offer novel diagnostic markers and therapeutic candidates for osteoporosis.

BiomedicinesVol. 13(4)
Sun Yat-sen University (CN), Eighth Affiliated Hospital of Sun Yat-sen University
Good health and well-being
Openalex Percentile: Top 91%
Cancer-related molecular mechanisms research
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