Master's Theses or Doctor of Nursing Practice

Department

Biology

Degree Name

Master of Science (MS)

Abstract

Despite significant advances in cancer research and treatment, Glioblastoma multiforme (GBM) remains one of the most difficult cancers to treat effectively, with minimal improvement in long-term survival rates over the past few decades. This is largely attributed to tumor heterogeneity and the ability of tumor cells to develop adaptive resistance mechanisms supported by the tumor microenvironment (TME). Although the TME is recognized as a key contributor to tumor progression and therapeutic resistance, the underlying molecular pathways and regulatory genes remain incompletely understood. This study investigated the role of the tumor microenvironment in GBM therapeutic resistance using a bioinformatics approach. Single-cell RNA sequencing (scRNA-seq) data were obtained from the Broad Institute’s Single Cell Portal (SCP393), comprising approximately 24,000 cells derived primarily from IDH-wildtype GBM. Data preprocessing, including quality control, normalization, dimensionality reduction, and cell clustering was performed using CLC Genomics Workbench. Differential expression analysis was conducted to identify genes associated with resistant and sensitive tumor states. Protein–protein interaction (PPI) networks were constructed using the STRING database and further analyzed in Cytoscape to identify key network features and hub genes. Functional and pathway enrichment analysis were then performed to determine the biological processes associated with the identified genes. Visualization techniques, including volcano plots and heatmaps, were used to illustrate gene expression patterns and statistical significance. The findings demonstrate that the tumor microenvironment contributes to therapeutic resistance through coordinated interactions involving immune signaling, extracellular matrix remodeling, and survival pathways. Notably, TLR4 was identified as a central hub gene, suggesting a key role for innate immune signaling in shaping the resistant tumor phenotype. These results highlight potential molecular targets and support further experimental validation using gene expression-based approaches.

Keywords

hub gene analysis, immune signaling pathways, protein-protein interaction networks, T-cell exhaustion, extracellular matrix remodeling

Advisor

Dr. Ifelayo Adefuye

Date of Award

Spring 2026

Document Type

Thesis

Rights

© The Author

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