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Texosome-anchored superantigen triggers apoptosis in original ovarian cancer cells

Overview of attention for article published in Medical Oncology, December 2014
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Title
Texosome-anchored superantigen triggers apoptosis in original ovarian cancer cells
Published in
Medical Oncology, December 2014
DOI 10.1007/s12032-014-0409-6
Pubmed ID
Authors

Hamideh Mahmoodzadeh Hosseini, Jafar Soleimanirad, Elnaz Mehdizadeh Aghdam, Mohsen Amin, Abbas Ali Imani Fooladi

Abstract

Texosomes, nano-endosomal vesicles, are candidates for cancer immunotherapy due to their immunostimulating properties. We designed a new structure based on texosome and staphylococcal enterotoxin B (SEB) and assessed its cytotoxic impact on an ovarian cell line. Texosomes were isolated from tumor cells, and SEB was anchored onto by protein transfer method. MTT assay and Hoechst staining were used to identify the cytotoxic and apoptotic effects of this compound on treated cells with different concentrations of texosome-SEB (TEX-SEB). Moreover, the expression rate of bcl-2, bax, bak, bcl-xl and the activity of caspase-3 and caspase-9 were investigated. Treatments of the cells with 0.5, 2.5 and 10 μg/100 μl TEX-SEB were significantly cytotoxic within 24 h (p < 0.001). Hoechst staining revealed that all tested concentrations caused apoptosis after 24 h compared with the control cells (p < 0.001). Furthermore, it was found that treatment with all examined concentrations of TEX-SEB enhanced caspase-9 activity after 24 and 48 h, while caspase-3 activity was increased upon treatment with only 0.5 and 2.5 μg/100 μl of TEX-SEB after 24 h (p < 0.001). None of the concentrations of TEX-SEB affected the expression of the cancer-promoting genes. Our construct, the TEX-SEB, is a new model being able to create cytostatic properties on cancer cells.

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Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 27%
Professor > Associate Professor 2 18%
Researcher 1 9%
Unknown 5 45%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 18%
Environmental Science 1 9%
Engineering 1 9%
Unknown 7 64%