Expression and Regulatory Network Analysis of BICC1 for Aged Sca-1-Positive Bone Narrow Mesenchymal Stem Cells.

Background: The impaired osteoblastic differentiation of bone marrow mesenchymal stem cells (BMSCs) is a major cause of bone remodeling imbalance and osteoporosis. The bicaudal C homologue 1 (BICC1) gene is a genetic regulator of bone mineral density (BMD) and promotes osteoblast differentiation. The purpose of this study is to explore the probable function of BICC1 in osteoporosis and osteogenic differentiation of aged BMSCs. Methods: We examined the GSE116925 microarray dataset obtained from the Gene Expression Omnibus (GEO) database. The GEO2R algorithm identified differentially expressed genes (DEGs) in Sca-1+ BMSCs from young (3 months old) and old (18 months old) mice. Then, to identify the most crucial genes, we used pathway enrichment analysis and a protein-protein interaction (PPI) network. Furthermore, starBase v2.0 was used to generate the regulatory networks between BICC1 and related competing endogenous RNAs (ceRNAs). NetworkAnalyst was used to construct TF-gene networks and TF-miRNA-gene networks of BICC1 and ceRNA. Furthermore, we investigated the Bicc1 expression in aged Sca-1-positive BMSCs. Result: We detected 923 DEGs and discovered that epidermal growth factor receptor (EGFR) was the top hub gene with a high degree of linkage. According to the findings of the PPI module analysis, EGFR was mostly engaged in cytokine signaling in immune system and inflammation-related signaling pathways. 282 ceRNAs were found to interact with the BICC1 gene. EGFR was not only identified as a hub gene but also as a BICC1-related ceRNA. Then, we predicted 11 common TF-genes and 7 miRNAs between BICC1 and EGFR. Finally, we found that BICC1 mRNA and EGFR mRNA were significantly overexpressed in aged Sca-1-positive BMSCs. Conclusion: As a genetic gene that affects bone mineral density, BICC1 may be a new target for clinical treatment of senile osteoporosis by influencing osteogenic differentiation of BMSCs through EGFR-related signaling. However, the application of the results requires support from more experimental data.