The proteomic landscape of glioma stem-like cells

Abstract

Glioma stem-like cells (GSCs) are hypothesized to provide a repository of cells in tumors that can self-replicate and are radio- and chemo-resistant. GSC lines, representing several glioma subtypes, have been isolated and characterized at the transcript level. We sought to characterize 35 GSC lines at the protein level using label-free quantitative proteomics. Resulting relative fold changes were used to drive unsupervised hierarchical clustering for the purpose of classifying the cell lines based on proteomic profiles. Bioinformatics analysis identified synoviolin, serine/arginine-rich splicing factor 2, symplekin, and IL-5 as molecules of interest in progression and/or treatment of glioma.

Keywords

• Glioblastoma
• Glioma stem cells
• Label-free quantitative proteomics
• Ingenuity Pathway Analysis
• DAVID
• Unsupervised hierarchical clustering