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Secondary Data Analytics of Aquaporin Expression Levels in Glioblastoma Stem-Like Cells.
Isokpehi, Raphael D; Wollenberg Valero, Katharina C; Graham, Barbara E; Pacurari, Maricica; Sims, Jennifer N; Udensi, Udensi K; Ndebele, Kenneth.
Afiliação
  • Isokpehi RD; College of Science, Engineering, and Mathematics, Bethune-Cookman University, Daytona Beach, FL, USA.
  • Wollenberg Valero KC; College of Science, Engineering, and Mathematics, Bethune-Cookman University, Daytona Beach, FL, USA.
  • Graham BE; Laboratory of Cancer Immunology, Target Identification and Validation, Department of Biology, Jackson State University, MS, USA. ; NIH RCMI-Center for Environmental Health, College of Science, Engineering, and Technology, Jackson State University, Jackson, MS, USA.
  • Pacurari M; Department of Biology, Jackson State University, MS, USA.
  • Sims JN; Laboratory of Cancer Immunology, Target Identification and Validation, Department of Biology, Jackson State University, MS, USA.
  • Udensi UK; NIH RCMI-Center for Environmental Health, College of Science, Engineering, and Technology, Jackson State University, Jackson, MS, USA.
  • Ndebele K; Laboratory of Cancer Immunology, Target Identification and Validation, Department of Biology, Jackson State University, MS, USA. ; NIH RCMI-Center for Environmental Health, College of Science, Engineering, and Technology, Jackson State University, Jackson, MS, USA. ; Department of Pathology, Harvard
Cancer Inform ; 14: 95-103, 2015.
Article em En | MEDLINE | ID: mdl-26279619
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.
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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Cancer Inform Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Cancer Inform Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Estados Unidos