Background/Objectives: Glioblastoma multiforme (GBM) is an aggressive primary brain tumor with limited therapeutic options. Neoantigen-based immunotherapy offers a promising avenue, but its efficacy primarily depends on the ability of somatic mutations to generate immunogenic peptides effectively presented by HLA class I molecules and recognized by cytotoxic T cells, in concert with innate immune mechanisms such as NK-cell activation and DAMP/PAMP signaling. This study aimed to characterize the MHC-I binding diversity of peptides derived from GBM-associated somatic variants, with a particular focus on interactions involving HLA-A68:01 and HLA-B15:01 alleles. These alleles were selected based on their ethnic prevalence and potential structural compatibility with neoepitopes. Methods: Somatic missense variants from TCGA-GBM were filtered using high-confidence genomic databases, including dbSNP, COSMIC, and MANE. Neoepitope prediction was performed across multiple HLA class I alleles using binding affinity algorithms (MHCflurry2). Peptide–HLA interactions were characterized through motif analysis and anchor residue enrichment. Structural modeling of peptide–HLA complexes was conducted using ColabFold (AlphaFold2-multimer v3) to evaluate conformational stability. The population frequency of selected HLA alleles was examined through epidemiological comparisons. Results: Canonical GBM driver mutations (e.g., EGFR, TP53, PIK3R1) are recurrent and biologically relevant, although pharmacological inhibition of EGFR alone has not consistently improved patient outcomes, underscoring the complex signaling redundancy in glioblastoma. HLA-A68:01 exhibited high binding affinity and favorable motif compatibility, supporting its potential for effective neoantigen presentation. HLA-B15:01 was identified as a viable presenter for the EGFR p.Arg108Lys variant. Structural modeling confirmed stable peptide insertion into the MHC-I binding groove, with high-confidence folding and preserved interface integrity. Ethnic distribution analysis revealed varying GBM incidence across populations expressing these alleles. Conclusions: This integrative analysis identified structurally validated, immunogenically promising neoantigens derived from GBM mutations, particularly for HLA-A68:01 and HLA-B15:01. These findings support allele-informed neoepitope prioritization in personalized immunotherapy, especially for patient populations with corresponding HLA genotypes and MHC-I presentation capacity.

Background: Medulloblastoma is an aggressive pediatric brain tumor characterized by marked molecular heterogeneity, which significantly impacts prognosis. The low frequency of genomic mutations in medulloblastoma suggests that alternative mechanisms, such as epigenetic regulation, may play a critical role in its pathogenesis. Methods: Using the EpiFactors database, we investigated the expression of epigenetic regulators in two independent RNA sequencing cohorts [Pediatric Brain Tumor Atlas (PBTA) and Williamson], stratified by molecular subgroups and clinical outcomes. We further analyzed expression heterogeneity at the single-cell level in malignant medulloblastoma cells using single-cell RNA sequencing. Results: Members of the SWI/SNF superfamily were dysregulated across all four molecular subtypes of medulloblastoma. Subtype-specific alterations were also observed: the acetyltransferase complex was shared between Group 3 (with SMARCD3 as a potential marker) and Group 4 (with RBM24 as a potential marker); SWR1, β-catenin/TCF, and protein–DNA complexes were specifically enriched in SHH-MB (with EYA1 and SATB2 as SHH markers); and RSC-type, PRC1, DNA polymerase complexes, and X-chromosome-related factors were enriched in WNT-MB (with FOXA1 and PIWIL4 as WNT markers). An epigenetic score (epi-score), linked to RNA metabolism and S-adenosyl-L-methionine pathways, was developed and identified as an independent adverse prognostic factor. High epi-scores were associated with proliferative, stem-like SHH malignant cells (characterized by G2/M phase, low pseudotime, and high entropy), exhibiting alterations in RNA splicing, DNA recombination, and nuclear division. Conclusions: Expression heterogeneity of epigenetic regulators is closely associated with molecular subgroups and clinical outcomes in medulloblastoma. These findings highlight the role of epigenetic dysregulation in RNA metabolism and tumor progression, particularly in SHH-driven proliferative cells.