Identification of Novel Cancer Stem Cell Markers in Glioblastoma by Comparing Tumor Cells with Stem-cell-like Cell Lines

Abstract

Aim. The aim of this study is to identify differential gene expression for glioblastoma tumor cells, normoxic and hypoxic glioblastoma stem-like cell lines. Finding the upregulated and downregulated gene and pathway interactions. Analysis to find the differential expression genes and pathway interactions. Materials and methods. The gene expression profiling data from the microarray dataset GSE45117 from the Gene Expression Omnibus (GEO) database, as well as differentially expressed genes (DEGs) between the 2 categories, are used in this analysis. 4 Samples of Glioblastoma tumors were considered as group 1 and 4 samples of normoxic and Hypoxic glioblastoma stem-like cell lines were considered as group 2 in the GEO2R web tool that has been used to screen them. Results. The gene-gene interactions among the DEGs and the GGI network with 37 nodes and 13 edges. The stem-cell-like cell lines showed lower expression of endothelin-related genes such as EDN3 and EDNRA along with dysregulation of enzymes such as PDK1, PGK1 which points to dysregulation of cellular respiratory pathways. This effect in consensus with under expression of cell attachment genes such as COL2A1, COL5A2, COL15A1 denotes a strong shift toward metastasis. Conclusion. Thus, a computational pipeline for identifying the significant genes and pathways involved in the glioblastoma tumors and glioblastoma stem-like cell lines. This study provides a path towards discovering potential leads for the treatment of glioblastoma and aids in comprehending the underlying novel molecular mechanisms.