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Identification and Analysis of Molecular Pathways and Key Candidate Biomarkers in Glioblastoma Multiforme

Aditi Stuti Kumari

Glioblastoma Multiforme (GBM) is a Grade IV malignant primary tumor present in the central nervous system. Despite advancements in treatments, it has a poor prognosis as the median survival is 14 months-15 months. The goal of this study was to identify the candidate biomarkers as well as the functional pathways regulated in GBM. The dataset (GSE100675) accessed included 3 glioblastoma tissues, 3 paired tissues, and 3 normal tissues. The Differentially Expressed Genes (DEGs) were identified using GEO2R, which found a total of 1,609 DEGs (916 downregulated and 693 upregulated). A gene ontology and KEGG pathway analysis was done with the DEGs. The KEGG pathway analysis was then utilized in constructing a Protein Protein Interaction (PPI) network, identifying the genes of interest. The interaction network was then put into cytoscape and 10 hub genes were identified. To ensure reliability of the research, those hub genes were put in GEPIA, and the data was compared for consistency of the research, with the regulation of all 10 hub genes matching that of a larger dataset. Kaplan-Meier analysis was done on the hub genes, which demonstrated that an upregulation in Signal Transducer and Activator of Transcription 3 (STAT3) was associated with lower survival. Study shows that STAT3 gene may be a key factor in the progression of GBM, being crucial in cell proliferation. In conclusion, STAT3, along with the molecular pathways identified, may be used as a potential prognostic and diagnostic biomarker and can be used to further our understanding of GBM.