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Down-regulation of S100A9 inhibits osteosarcoma cell growth through inactivating MAPK and NF-κB signaling pathways

Overview of attention for article published in BMC Cancer, March 2016
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Title
Down-regulation of S100A9 inhibits osteosarcoma cell growth through inactivating MAPK and NF-κB signaling pathways
Published in
BMC Cancer, March 2016
DOI 10.1186/s12885-016-2294-1
Pubmed ID
Authors

Si Cheng, Xi Zhang, Ning Huang, Quanhe Qiu, Ying Jin, Dianming Jiang

Abstract

Osteosarcoma (OS) is well-known for poor prognosis due to its high incidence of proliferation and metastasis. Researches have provided valuable insights into the tumorigenesis of S100A9 in some cancers. We aimed to understand the expression level, functions and mechanisms of S100A9 in human osteosarcoma for the first time. The expression of S100A9 protein was detected in 120 human osteosarcoma tissues and 40 normal human bone tissues using tissue microarrays analysis. The knockdown of S100A9 induced by RNA interference (RNAi) method in three osteosarcoma cell lines (U2OS, 143B, MG63) was applied to analyze the effects of S100A9 on cell proliferation, cell cycle distribution, migration, invasion and xenotransplanted tumors. Moreover, MAPK-ERK1/2, MAPK-p38, NF-κB-p65, NF-κB-p50, p21, p27, CDK2 and CDK4 were tested. The expression of S100A9 was increased in human osteosarcoma issues and was positively correlated with clinical classification and survival rate. Down-regulation of S100A9 inhibited OS cellular proliferation, migration, invasion and cell cycle S phase in vitro and suppressed tumor formation in vivo with the reduction on PCNA and Ki67 proliferation index. Our data also demonstrated that knockdown of S100A9 repressed the protein levels of phospho-ERK1/2, phospho-p50, phospho-p65 except phospho-p38, and prompted up-regulation of p21 and p27 leading to inactivation of cyclin dependent kinase 2(CDK2) and cyclin dependent kinase 4(CDK4). S100A9 might be a significant role for predicting osteosarcoma prognosis and down-regulation of S100A9 could be used as a potential target for gene therapy.

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Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 5 20%
Student > Ph. D. Student 4 16%
Researcher 3 12%
Student > Master 3 12%
Professor > Associate Professor 2 8%
Other 3 12%
Unknown 5 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 16%
Pharmacology, Toxicology and Pharmaceutical Science 4 16%
Medicine and Dentistry 4 16%
Biochemistry, Genetics and Molecular Biology 2 8%
Neuroscience 2 8%
Other 4 16%
Unknown 5 20%