Identification of key microRNAs and target genes for the diagnosis of bone nonunion

Xiong, Yuan; Cao, Faqi; Chen, Lang; Yan, Chenchen; Zhou, Wu; Chen, Yanyan; Endo, Yori; Leng, Xingzhu; Mi, Bobin; Liu, Guohui

doi:10.3892/mmr.2020.10996

Cited by 11 publications

(19 citation statements)

References 42 publications

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“…The rate of bone defects, fracture nonunion, and osteoporosis incidence continues to rise, and available therapeutic options remain limited. These diseases, closely related to the osteogenic differentiation of bone marrow-derived mesenchymal stem cells (BMSCs), have been confirmed by numerous studies (Marongiu et al, 2020;Xiao et al, 2020;Xiong et al, 2020;Jiang et al, 2021).…”

Section: Introductionmentioning

confidence: 83%

Bioinformatics-Guided Analysis Uncovers AOX1 as an Osteogenic Differentiation-Relevant Gene of Human Mesenchymal Stem Cells

Sun

Cheng

et al. 2022

Front. Mol. Biosci.

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Background: The available therapeutic options of bone defects, fracture nonunion, and osteoporosis remain limited, which are closely related to the osteogenic differentiation of bone marrow–derived mesenchymal stem cells (BMSCs). Thus, there remains an urgent demand to develop a prediction method to infer osteogenic differentiation–related genes in BMSCs.Method: We performed differential expression analysis between hBMSCs and osteogenically induced samples. Association analysis, co-expression analysis, and PPI analysis are then carried out to identify potential osteogenesis-related regulators. GO enrichment analysis and GSEA are performed to identify significantly enriched pathways associated with AOX1. qRT-PCR and Western blotting were employed to investigate the expression of genes on osteogenic differentiation, and plasmid transfection was used to overexpress the gene AOX1 in hBMSCs.Result: We identified 25 upregulated genes and 17 downregulated genes. Association analysis and PPI network analysis among these differentially expressed genes show that AOX1 is a potential regulator of osteogenic differentiation. GO enrichment analysis and GSEA show that AOX1 is significantly associated with osteoblast-related pathways. The experiments revealed that AOX1 level was higher and increased gradually in differentiated BMSCs compared with undifferentiated BMSCs, and AOX1 overexpression significantly increased the expression of osteo-specific genes, thereby clearly indicating that AOX1 plays an important role in osteogenic differentiation. Moreover, our method has ability in discriminating genes with osteogenic differentiation properties and can facilitate the process of discovery of new osteogenic differentiation–related genes.Conclusion: These findings collectively demonstrate that AOX1 is an osteogenic differentiation-relevant gene and provide a novel method established with a good performance for osteogenic differentiation-relevant genes prediction.

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Section: Introductionmentioning

confidence: 83%

Bioinformatics-Guided Analysis Uncovers AOX1 as an Osteogenic Differentiation-Relevant Gene of Human Mesenchymal Stem Cells

Sun

Cheng

et al. 2022

Front. Mol. Biosci.

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“…Bioinformatics analysis has been widely used to unravel molecular and cellular mechanisms of several human diseases [ 9 – 11 ]. Therefore, in this study, we performed comprehensive bioinformatics analysis and in vitro experiments in the cellular model of glucocorticoid-induced osteoporosis (GIO) to identify molecular mechanisms underlying the therapeutic effects of BN in osteoporosis.…”

Section: Introductionmentioning

confidence: 99%

Baicalein ameliorates osteoporosis via AKT/FOXO1 signaling

Cai

Yin

et al. 2021

Aging

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In this study, we used bioinformatics and an in vitro cellular model of glucocorticoid-induced osteoporosis to investigate mechanisms underlying the beneficial effects of baicalein (BN) against osteoporosis. STITCH database analysis revealed 30 BN-targeted genes, including AKT1, CCND1, MTOR , and PTEN . Functional enrichment analysis demonstrated that BN-targeted genes were enriched in 49 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. MIRWALK2.0 database analysis identified 110 enriched KEGG pathways related to osteoporosis. A Venn diagram demonstrated that 26 KEGG pathways were common between osteoporosis and BN-targeted genes. The top 5 common KEGG pathways were prostate cancer, bladder cancer, glioma, pathways in cancer, and melanoma. BN-targeted genes in the top 5 shared KEGG pathways were involved in PI3K-AKT, MAPK, p53, ErbB, and mTOR signaling pathways. In addition, glucocorticoid-induced osteoporosis in MC3T3-E1 cells was partially reversed by BN through inhibition of AKT, which, by upregulating FOXO1, enhanced expression of bone turnover markers (ALP, OCN, Runx2, and Col 1) and extracellular matrix mineralization. These findings demonstrate that BN suppresses osteoporosis via an AKT/FOXO1 signaling pathway.

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“…Bioinformatics is an interdisciplinary field incorporating biology and computer science in order to analyze and synthesize related data ( 7 ). Several bioinformatics tools are currently used to screen for potential genes associated with a variety of pathological processes in vivo ( 8 , 9 ). Similarly, microarrays have been used to elucidate underlying pathological mechanisms and identify novel biological markers ( 10 ).…”

Section: Introductionmentioning

confidence: 99%