Glioblastoma (GB) is the most common and most aggressive primary brain tumor in adults, characterized by a poor prognosis, with a five-year survival rate of approximately 5%. Diagnosis is based on histopathological and molecular features, with molecular characteristics becoming increasingly important for disease classification, treatment selection, and prognosis. Despite advances in understanding the molecular biology of GB, therapeutic approaches have remained largely unchanged in recent years. Immunotherapy has emerged as a promising area of research; however, its effectiveness in GB is limited by a highly immunosuppressive tumor microenvironment. Among the most promising approaches are cancer vaccines, which rely on various platforms, including dendritic cells, viral vectors, nucleic acids, and peptide-based strategies. Peptide-based approaches depend on the identification of tumor antigens, which can be classified according to their origin into tumor-specific antigens (TSA) and tumor-associated antigens (TAA). TSA arise from somatic genetic alterations and are typically patient-specific, enabling high selectivity, although their number is often limited in tumors with low mutational burden. In contrast, TAA result from aberrant gene expression and may be shared across patients, albeit with lower tumor specificity. A specific subgroup includes cancer-testis antigens (CTA), which are normally expressed only in germ cells and therefore represent potentially safer therapeutic targets. Human leukocyte antigen (HLA) molecules play a crucial role in antigen presentation, enabling peptide binding and presentation on the surface of tumor cells. Only a subset of identified peptides induces an effective T-cell response, making the prediction of immunogenic antigens a complex process requiring the integration of biological and bioinformatics approaches. Within this doctoral research, a dataset was generated comprising transcriptomic data of glioblastoma (IDH-wildtype, grade IV), obtained from retrospectively collected archival tumor samples. The aim of the study was to identify potential tumor antigens, compare different sources of tumor antigens (TSA, TAA, CNV, gene fusions), and evaluate their potential for use in personalized immunotherapy.
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