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STAT1 inhibits human hepatocellular carcinoma cell growth through induction of p53 and Fbxw7

Overview of attention for article published in Cancer Cell International, November 2015
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Title
STAT1 inhibits human hepatocellular carcinoma cell growth through induction of p53 and Fbxw7
Published in
Cancer Cell International, November 2015
DOI 10.1186/s12935-015-0253-6
Pubmed ID
Authors

Jiayu Chen, Haihe Wang, Jing Wang, Shishun Huang, Wei Zhang

Abstract

Aberrant STAT1 signaling is observed in human hepatocellular carcinoma (HCC) and has been associated with the modulation of cell proliferation and survival. However, the role of STAT1 signaling in HCC and its underlying mechanism remain elusive. We transiently transfected pcDNA3.1-STAT1 and STAT1 siRNA into SMMC7721 and HepG2 cells. Western blot and qRT-PCR examined the expression of protein and RNA of target genes. Cell viability was assessed using MTT assay, and cell cycle and apoptosis were analyzed by flow cytometry. We found that STAT1 overexpression increased protein expression of p53 and Fbxw7, and downregulated the expression of cyclin A, cyclin D1, cyclin E, CDK2, Hes-1 and NF-κB p65. These changes led to growth inhibition and induced G0/G1 cell cycle arrest and apoptosis in SMMC7721 and HepG2 cells. Conversely, ablation of STAT1 had the opposite effect on p53, Fbxw7, Hes-1, NF-κB p65, cyclin A, cyclin D1, cyclin E and CDK2, and improved the viability of SMMC7721 and HepG2 cells. Our data indicate that STAT1 exerts tumor-suppressive effects in hepatocarcinogenesis through induction of G0/G1 cell cycle arrest and apoptosis, and may provide a basis for the design of new therapies for the intervention of HCC in the clinic.

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Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer > Senior Lecturer 1 13%
Student > Ph. D. Student 1 13%
Student > Master 1 13%
Researcher 1 13%
Student > Postgraduate 1 13%
Other 0 0%
Unknown 3 38%
Readers by discipline Count As %
Immunology and Microbiology 2 25%
Biochemistry, Genetics and Molecular Biology 1 13%
Agricultural and Biological Sciences 1 13%
Computer Science 1 13%
Unknown 3 38%