Literature DB >> 26132704

Evaluation of the Antitumor Efficacy of RNAi-Mediated Inhibition of CDC20 and Heparanase in an Orthotopic Liver Tumor Model.

Meizhou Liu1, Yangde Zhang1, Yunjun Liao2, Yixing Chen2, Yifeng Pan1, Hu Tian3, Yongqiang Zhan2, Dongjing Liu1.   

Abstract

Over 90% of patients with hepatocellular carcinoma (HCC) are diagnosed at an advanced stage. This study investigated the antitumor efficacy of the inhibition of cell division cycle protein 20 (CDC20) and heparanase (HPSE) expression in Hepa1-6 mouse hepatoma cells. Cell viability was measured by the MTT assay. Cell cycle was analyzed by cytometry. The invasion assay was performed using the Transwell chamber. The orthotopic liver tumor model was established by inoculating the livers of immunocompetent Kunming mice with Hepa1-6 cells. The MTT assay showed that 50 and 100 nM CDC20 siRNA-1 and HPSE siRNA-2 significantly reduced Hepa1-6 cell viability with the combination of CDC20 and HPSE siRNA being the most effective. Silencing of CDC20 or both CDC20 and HPSE expression significantly induced G2/M phase cell cycle arrest in Hepa1-6 HCC cells. Silencing HPSE expression significantly inhibited the invasion ability of Hepa1-6 cells with the combination of CDC20 and HPSE silencing being more effective than HPSE alone. Silencing CDC20 and HPSE expression significantly inhibited HCC tumor growth in the orthotopic liver tumor model, but the combination was most effective. Silencing CDC20 and HPSE expression activated cell apoptosis and autophagy. In conclusion, targeting inhibition of both CDC20 and HPSE expression is an ideal strategy for HCC therapy.

Entities:  

Keywords:  CDC20; RNA interference; animal model; heparanase; liver cancer

Mesh:

Substances:

Year:  2015        PMID: 26132704     DOI: 10.1089/cbr.2014.1799

Source DB:  PubMed          Journal:  Cancer Biother Radiopharm        ISSN: 1084-9785            Impact factor:   3.099


  9 in total

Review 1.  Mechanisms of heparanase inhibitors in cancer therapy.

Authors:  Benjamin Heyman; Yiping Yang
Journal:  Exp Hematol       Date:  2016-08-26       Impact factor: 3.084

2.  Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis.

Authors:  Ziqi Meng; Jiarui Wu; Xinkui Liu; Wei Zhou; Mengwei Ni; Shuyu Liu; Siyu Guo; Shanshan Jia; Jingyuan Zhang
Journal:  J Int Med Res       Date:  2020-07       Impact factor: 1.671

3.  Transcriptome Analysis Revealed a Highly Connected Gene Module Associated With Cirrhosis to Hepatocellular Carcinoma Development.

Authors:  Shan Shan; Wei Chen; Ji-Dong Jia
Journal:  Front Genet       Date:  2019-04-02       Impact factor: 4.599

4.  A gene module identification algorithm and its applications to identify gene modules and key genes of hepatocellular carcinoma.

Authors:  Yan Zhang; Zhengkui Lin; Xiaofeng Lin; Xue Zhang; Qian Zhao; Yeqing Sun
Journal:  Sci Rep       Date:  2021-03-09       Impact factor: 4.379

5.  Identification of a five-gene signature in association with overall survival for hepatocellular carcinoma.

Authors:  Lei Yang; Weilong Yin; Xuechen Liu; Fangcun Li; Li Ma; Dong Wang; Hongxing Li
Journal:  PeerJ       Date:  2021-04-28       Impact factor: 2.984

6.  Identification of hub genes and biological pathways in hepatocellular carcinoma by integrated bioinformatics analysis.

Authors:  Qian Zhao; Yan Zhang; Shichun Shao; Yeqing Sun; Zhengkui Lin
Journal:  PeerJ       Date:  2021-01-19       Impact factor: 2.984

7.  Risk Predictive Model Based on Three DDR-Related Genes for Predicting Prognosis, Therapeutic Sensitivity, and Tumor Microenvironment in Hepatocellular Carcinoma.

Authors:  Renzhi Hu; Xiping Liang; Qiying Li; Yao Liu
Journal:  J Oncol       Date:  2022-09-30       Impact factor: 4.501

8.  Comprehensive analysis of key genes, microRNAs and long non-coding RNAs in hepatocellular carcinoma.

Authors:  Baoqi Shi; Xuejun Zhang; Lumeng Chao; Yu Zheng; Yongsheng Tan; Liang Wang; Wei Zhang
Journal:  FEBS Open Bio       Date:  2018-07-31       Impact factor: 2.693

9.  Characterization of diagnostic and prognostic significance of cell cycle-linked genes in hepatocellular carcinoma.

Authors:  Jukun Wang; Yu Li; Chao Zhang; Xin Chen; Linzhong Zhu; Tao Luo
Journal:  Transl Cancer Res       Date:  2021-11       Impact factor: 1.241

  9 in total

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