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Integrated glycomic analysis of ovarian cancer side population cells.

Authors :
Ran Zhao
Xiaoxia Liu
Yisheng Wang
Xiaoxiang Jie
Ruihuan Qin
Wenjun Qin
Mengyu Zhang
Haiyan Tai
Caiting Yang
Lili Li
Peike Peng
Miaomiao Shao
Xingwang Zhang
Hao Wu
Yuanyuan Ruan
Congjian Xu
Shifang Ren
Jianxin Gu
Source :
Clinical Proteomics; 11/10/2016, Vol. 13, p1-14, 14p
Publication Year :
2016

Abstract

Background: Ovarian cancer is the most lethal gynecological malignancy due to its frequent recurrence and drug resistance even after successful initial treatment. Accumulating scientific evidence indicates that subpopulations of cancer cells with stem cell-like properties, such as so-called side population (SP) cells, are primarily responsible for these recurrences. A better understanding of SP cells may provide new clues for detecting and targeting these cancer-initiating cells and ultimately help to eradicate cancer. Changes in glycosylation patterns are remarkable features of SP cells. Here, we isolated SP cells from ovarian cancer cell lines and analyzed their glycosylation patterns using multiple glycomic strategies. Methods: Six high-grade serous ovarian cancer cell lines were used for SP cell isolation. Among them, HO8910 pm, which contained the highest proportion of SP cells, was used for glycomic analysis of SP cells. Cell lysate of SP cells and main population cells was applied to lectin microarray and mass spectrometry for glycan profiling. Differently expressed glycan structures were further verified by lectin blot, flow cytometry, and real-time PCR analysis of their relevant enzymes. Results: Expression of core fucosylated N-glycan and tumor-associated Tn, T and sT antigens were increased in SP cells. By contrast, SP cells exhibited decreased hybrid glycan, α2,3-linked sialic glycan and multivalent sialyl-glycan. Conclusions: Glycan structures, such as Tn, T, sT antigens, and core fucosylation may serve as biomarkers of ovarian cancer stem cells. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15426416
Volume :
13
Database :
Complementary Index
Journal :
Clinical Proteomics
Publication Type :
Academic Journal
Accession number :
119714544
Full Text :
https://doi.org/10.1186/s12014-016-9131-z