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

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.

The value of multi ultra high-b-value DWI in grading cerebral astrocytomas and its association with aquaporin-4

“…This suggests the involvement of AQP4 in inducing tumorigenic changes, particularly those affecting cell migration and cytoskeleton organization. 20,21 Further, our study showed that ADC value (r = −0.357; p = 0.024) had a little negative correlation with AQP4 expression, which is consistent with literature reported elsewhere. 22,23 But in our research, UHBV-ADC generated by five multi UHBVs (2000-5000 s mm -2 ) showed a positive correlation with AQP4 expression (r = 0.646; p < 0.01).…”

Ubiquitin carboxyl-terminal esterase L1 (UCHL1) is associated with stem-like cancer cell functions in pediatric high-grade glioma

“…For instance aberrant expression of the brain aquaporin 1 (AQ1) and 4 (AQ4), which regulate water flow in and out of the cells, have been found in glioblastoma sphere cultures and their role in this tumor has just started to be elucidated [39, 40]. Of note, AQ4 was the second most downregulated gene in the UCHL1 KDs (~37-fold reduction compared to controls), thus consistent with a possible function of UCHL1 in glioma CSCs.…”

“…Additional mechanisms mediating self-renewal and invasion in our model system such as activation of Akt and Erk1/2 pathways [ 30 , 36 ], or stabilization of the oxidase NOX4 and of membrane receptors like the cell adhesion protein NCAM among other yet to uncover targets [ 37 , 38 ] should not be ruled out. For instance aberrant expression of the brain aquaporin 1 (AQ1) and 4 (AQ4), which regulate water flow in and out of the cells, have been found in glioblastoma sphere cultures and their role in this tumor has just started to be elucidated [ 39 , 40 ]. Of note, AQ4 was the second most downregulated gene in the UCHL1 KDs (~37-fold reduction compared to controls), thus consistent with a possible function of UCHL1 in glioma CSCs.…”

Genomic and phenotypic signatures of climate adaptation in anAnolislizard

“…Expression data for human were again more exhaustive than data for other vertebrates, on which we consequently focus our interpretation. Human gene expression data measured on Affymetrix chip U133 were obtained for a list of 31 candidate genes plus 14 outlier genes from BioGPS (Wu et al., ) and imported into TABLEAU (V.9.0, Seattle, WA, USA) after data transformation (Isokpehi et al., ), and standardization to mean and standard deviation. Probe sets were compared for expression outlier values in different tissues.…”