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Gliomasphere marker combinatorics: multidimensional flow cytometry detects CD44+/CD133+/ITGA6+/CD36+ signature.
- Source :
-
Journal of cellular and molecular medicine [J Cell Mol Med] 2019 Jan; Vol. 23 (1), pp. 281-292. Date of Electronic Publication: 2018 Nov 22. - Publication Year :
- 2019
-
Abstract
- Glioblastoma is the most dangerous brain cancer. One reason for glioblastoma's aggressiveness are glioblastoma stem-like cells. To target them, a number of markers have been proposed (CD133, CD44, CD15, A2B5, CD36, CXCR4, IL6R, L1CAM, and ITGA6). A comprehensive study of co-expression patterns of them has, however, not been performed so far. Here, we mapped the multidimensional co-expression profile of these stemness-associated molecules. Gliomaspheres - an established model of glioblastoma stem-like cells - were used. Seven different gliomasphere systems were subjected to multicolor flow cytometry measuring the nine markers CD133, CD44, CD15, A2B5, CD36, CXCR4, IL6R, L1CAM, and ITGA6 all simultaneously based on a novel 9-marker multicolor panel developed for this study. The viSNE dimensionality reduction algorithm was applied for analysis. All gliomaspheres were found to express at least five different glioblastoma stem-like cell markers. Multi-dimensional analysis showed that all studied gliomaspheres consistently harbored a cell population positive for the molecular signature CD44+/CD133+/ITGA6+/CD36+. Glioblastoma patients with an enrichment of this combination had a significantly worse survival outcome when analyzing the two largest available The Cancer Genome Atlas datasets (MIT/Harvard Affymetrix: P = 0.0015, University of North Carolina Agilent: P = 0.0322). In sum, we detected a previously unknown marker combination - demonstrating feasibility, usefulness, and importance of high-dimensional gliomasphere marker combinatorics.<br /> (© 2018 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.)
- Subjects :
- AC133 Antigen analysis
Algorithms
Biomarkers, Tumor metabolism
Brain Neoplasms metabolism
Brain Neoplasms mortality
CD36 Antigens analysis
Cell Adhesion physiology
Cell Line, Tumor
Computer Simulation
Glioblastoma metabolism
Glioblastoma mortality
Humans
Hyaluronan Receptors analysis
Integrin alpha6 analysis
Kaplan-Meier Estimate
Neoplastic Stem Cells metabolism
Biomarkers, Tumor analysis
Brain Neoplasms pathology
Flow Cytometry methods
Glioblastoma pathology
Subjects
Details
- Language :
- English
- ISSN :
- 1582-4934
- Volume :
- 23
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Journal of cellular and molecular medicine
- Publication Type :
- Academic Journal
- Accession number :
- 30467961
- Full Text :
- https://doi.org/10.1111/jcmm.13927