Secondary Data Analytics of Aquaporin Expression Levels in Glioblastoma Stem-Like Cells

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Secondary Data Analytics of Aquaporin Expression Levels in Glioblastoma Stem-Like Cells

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Title: Secondary Data Analytics of Aquaporin Expression Levels in Glioblastoma Stem-Like Cells
Author: Isokpehi, Raphael D; Wollenberg Valero, Katharina C; Graham, Barbara E; Pacurari, Maricica; Sims, Jennifer N; Udensi, Udensi K; Ndebele, Kenneth

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Citation: Isokpehi, Raphael D, Katharina C Wollenberg Valero, Barbara E Graham, Maricica Pacurari, Jennifer N Sims, Udensi K Udensi, and Kenneth Ndebele. 2015. “Secondary Data Analytics of Aquaporin Expression Levels in Glioblastoma Stem-Like Cells.” Cancer Informatics 14 (1): 95-103. doi:10.4137/CIN.S22058. http://dx.doi.org/10.4137/CIN.S22058.
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Abstract: Glioblastoma is the most common brain tumor in adults in which recurrence has been attributed to the presence of cancer stem cells in a hypoxic microenvironment. On the basis of tumor formation in vivo and growth type in vitro, two published microarray gene expression profiling studies grouped nine glioblastoma stem-like (GS) cell lines into one of two groups: full (GSf) or restricted (GSr) stem-like phenotypes. Aquaporin-1 (AQP1) and aquaporin-4 (AQP4) are water transport proteins that are highly expressed in primary glial-derived tumors. However, the expression levels of AQP1 and AQP4 have not been previously described in a panel of 92 glioma samples. Therefore, we designed secondary data analytics methods to determine the expression levels of AQP1 and AQP4 in GS cell lines and glioblastoma neurospheres. Our investigation also included a total of 2,566 expression levels from 28 Affymetrix microarray probe sets encoding 13 human aquaporins (AQP0–AQP12); CXCR4 (the receptor for stromal cell derived factor-1 [SDF-1], a potential glioma stem cell therapeutic target]); and PROM1 (gene encoding CD133, the widely used glioma stem cell marker). Interactive visual representation designs for integrating phenotypic features and expression levels revealed that inverse expression levels of AQP1 and AQP4 correlate with distinct phenotypes in a set of cell lines grouped into full and restricted stem-like phenotypes. Discriminant function analysis further revealed that AQP1 and AQP4 expression are better predictors for tumor formation and growth types in glioblastoma stem-like cells than are CXCR4 and PROM1. Future investigations are needed to characterize the molecular mechanisms for inverse expression levels of AQP1 and AQP4 in the glioblastoma stem-like neurospheres.
Published Version: doi:10.4137/CIN.S22058
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4524166/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:21462356
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