Seeking for correlative genes and signaling pathways with bone metastasis from breast cancer by integrated analysis

Abstract

Background: Bone metastasis frequently occurs in advanced breast cancer patients, and it is one of major causes of breast cancer associated mortality. The aim of the current study is to identify potential genes and related signaling pathways in the pathophysiology of breast cancer bone metastasis. Methods: Three mRNA expression datasets for breast cancer bone metastasis were obtained from Gene Expression Omnibus (GEO) dataset. The differentially expressed genes (DEGs) were obtained. Functional analyses, protein-protein interaction (PPI) network, and transcription factors (TFs)-target genes network was constructed. Realtime PCR using clinical specimens was conducted to justify the results from integrated analysis. Results: A 749 DEGs were obtained. Osteoclast differentiation and rheumatoid arthritis were two significantly enriched signaling pathways for DEGs in the bone metastasis of breast cancer. SMAD7 (degree = 10), TGFBR2 (degree = 9), VIM (degree = 8), FOS (degree = 8), PDGFRB (degree = 7), COL5A1 (degree = 6), ARRB2 (degree = 6), and ITGAV (degree = 6) were high degree genes in the PPI network. ETS1 (degree = 12), SPI1 (degree = 12), FOS (degree = 10), FLI1 (degree = 5), KLF4 (degree = 4), JUNB (degree = 4), NR3C1 (degree = 4) were high degree genes in the TFs-target genes network. Validated by QRT-PCR, the expression levels of IBSP, MMP9, MMP13, TNFAIP6, CD200, DHRS3, ASS1, RIPK4, VIM, and PROM1 were roughly consistent with our integrated analysis. Except PROM1, the other genes had a diagnose value for breast cancer bone metastasis. Conclusions: The identified DEGs and signaling pathways may make contribution for understanding the pathological mechanism of bone metastasis from breast cancer.