Identification of key gene networks associated with fracture healing using αSMA‑labeled progenitor cells

Molecular Medicine Reports
Hua WangJingcheng Wang

Abstract

The aim of the present study was to investigate the key gene network in fracture healing. The dataset GSE45156 was downloaded from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified using the linear models for microarray data package of Bioconductor. Subsequently, Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted for DEGs in day 2 and 6 fractured samples via the Database for Annotation, Visualization and Integrated Discovery. Furthermore, protein‑protein interactions (PPIs) of DEGs were analyzed and a PPI network was constructed. A total of 774 and 1,172 DEGs were identified in day 2 and 6 fractured samples, respectively, compared with unfractured controls. Of the DEGs in day 2 and 6 fractured samples, various upregulated DEGs, including protein kinase C α (Prkca) and B‑cell lymphoma antagonist/killer 1 were significantly enriched in GO terms associated with cell death, and certain downregulated DEGs, including fms‑related tyrosine kinase 1 (Flt1), nitric oxide synthase 3 (Nos3), bone morphogenetic protein 4 (Bmp4) and Notch1 were enriched in GO terms associated with angiogenesis. Furthermore, a series of downregulated DEGs were e...Continue Reading

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Datasets Mentioned

BETA
GSE45156

Methods Mentioned

BETA
GTPase

Software Mentioned

Cytoscape
Bioconductor
LIMMA
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