Evaluation and Selection of MiRNAs as Diagnostic and Therapeutic Biomarkers Related to Glioblastoma Cancer Stem Cells Through Bioinformatics Analysis

Background: Glioblastoma is one of the most common and malignant cancers of the brain that despite all the treatments, the survival rate of patients with glioblastoma is still low(1). Cancer stem cells have a potential role in disease recurrence, and the molecules involved in the progression of glioblastoma by cancer stem cells are still unclear(2,3). This study aimed to find a cure for glioblastoma cancer stem cells to fight these cells. Methods and materials: This study uses integrated bioinformatics analysis from the GEO database. We selected the appropriate datasets. We then separated the signal paths using theEnrichr database and the KEGG library. We used the Enrichr database cellular components library to examine cellular components. Finally, we used the targetscan database to select miRNAs.Results: 3280 genes with high expression and 3100 genes with low expression were classified as glioblastoma cancer stem cells. Metabolism pathways, cell adhesion, extracellular matrix, TNF were observed in overexpressed genes and axon guidance, cell division, and cellular senescencein low expression genes. 40 proteins were observed from the top 10 signaling pathways in extracellular involved in glioblastoma cancer progression by cancer stem cells in the extracellular matrix. Among these proteins, hsa-miR-3669, hsa-miR-147b, and hsa-miR-621 were significantly associated with more genes.Conclusion: Finally, through integrated bioinformatics analysis and selection of proteins in the extracellular matrix and their target miRNAs, by taking patients' blood, cancer stem cells' function can be more accurately measured, and appropriate diagnostic and therapeutic platforms can be used.

Keywords:

Glioblastoma Multiform , Bioinformatics Analysis , micro RNAs , Biomarkers , Cancer Stem Cells