Title |
Effect of targeted ovarian cancer immunotherapy using ovarian cancer stem cell vaccine
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Published in |
Journal of Ovarian Research, October 2015
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DOI | 10.1186/s13048-015-0196-5 |
Pubmed ID | |
Authors |
Di Wu, Jing Wang, Yunlang Cai, Mulan Ren, Yuxia Zhang, Fangfang Shi, Fengshu Zhao, Xiangfeng He, Meng Pan, Chunguang Yan, Jun Dou |
Abstract |
Accumulating evidence has shown that different immunotherapies for ovarian cancer might overcome barriers to resistance to standard chemotherapy. The vaccine immunotherapy may be a useful one addition to conditional chemotherapy regimens. The present study investigated the use of vaccine of ovarian cancer stem cells (CSCs) to inhibit ovarian cancer growth. CD117(+)CD44(+)CSCs were isolated from human epithelial ovarian cancer (EOC) SKOV3 cell line by using a magnetic-activated cell sorting system. Pre-inactivated CD117(+)CD44(+)CSC vaccine was vacccinated into athymic nude mice three times, and then the mice were challenged subcutaneously with SKOV3 cells. The anti-tumor efficacy of CSC vaccine was envaluated by in vivo tumorigenicity, immune efficient analysis by flow cytometer, and enzyme-linked immunosorbent assays, respectively. The CD117(+) CD44(+)CSC vaccine increased anti-ovarian cancer efficacy in that it depressed ovarian cancer growth in the athymic nude mice. Vaccination resulted in enhanced serum IFN-γ, decreased TGF-β levels, and increased cytotoxic activity of natural killer cells in the CD117(+) CD44(+)CSC vaccine immunized mice. Moreover, the CSC-based vaccine significantly reduced the CD117(+)CD44(+)CSC as well as the aldehyde dehydrogenase 1 positive cell populations in the ovarian cancer tissues in the xenograft mice. The present study provided the first evidence that human SKOV3 CD117(+) CD44(+)CSC-based vaccine may induce the anti-ovarian cancer immunity against tumor growth by reducing the CD117(+)CD44(+)CSC population. |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Bachelor | 8 | 22% |
Student > Master | 6 | 16% |
Researcher | 5 | 14% |
Student > Ph. D. Student | 4 | 11% |
Student > Doctoral Student | 2 | 5% |
Other | 2 | 5% |
Unknown | 10 | 27% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 7 | 19% |
Agricultural and Biological Sciences | 6 | 16% |
Medicine and Dentistry | 6 | 16% |
Immunology and Microbiology | 2 | 5% |
Psychology | 2 | 5% |
Other | 4 | 11% |
Unknown | 10 | 27% |