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Mechanobiology of Disease
Poster Abstracts
67
70-POS
Board 70
Mining Genome Expression Omnibus (GEO) Datasets for Analysis of TRP Channels in
Glioma Cell Lines
Taylor M. Nunn, Taylor W. Uselman,
Elba E. Serrano
.
New Mexico State University, Las Cruces, NM, USA.
Gliomas are aggressive primary brain tumors that develop from glial cells and are characterized
by a low survival prognosis. Recent literature points to a potential role for TRP channels in
glioma proliferation and tumor progression. As a prelude to experiments exploring the role of
mechanosensation in glioma cell culture systems, we aimed to determine the prevalence of TRP
channels across multiple glioma cell lines using bioinformatics approaches. Our strategy
benefited from the emergence of open source metadata repositories that facilitate experimental
design which incorporates
in silico
inquiry as a complementary approach to
in vitro
and
in
vivo
methodologies. Through literature review we identified a subset of 13 TRP channel genes as
candidates for expression analysis in glioma cell lines (TRPA, 1; TRPC, 3; TRPV, 3; TRPM, 5;
TRPP, 1). Genes were selected based on their reported role in mechanotransduction and/or
evidence that they are involved in glioma brain tumor progression. We queried the GEO
repository for glioma high throughput datasets and selected a GEO Dataset Record
comprising
GeneChip® Human Genome U133 Plus 2.0
microarray data from 60 cancer cell lines
for analysis (GDS4296). Evaluation of normalized expression values for the 13 exploratory TRP
channels uncovered the highest expression for TRPC1, TRPM7, and TRPP2 in all six glioma cell
lines included in the dataset. Future studies will use qPCR to confirm TRP channel expression in
glioma cell lines as part of ongoing experiments that examine glioma proliferation in matrix
environnments. We conclude that outcomes from analysis of cell line expression metadata can
inform research that investigates the role of TRP channels in brain cancer. Supported by
undergraduate research awards: NMSU Discovery Scholars (TMN); NIH R25NS080685 (TWU).