Medulloblastoma (MB) is the most common malignant brain tumor in children, typically arising during infancy and childhood. Despite multimodal therapies achieving a response rate of 70% in children older than 3 years, treatment remains challenging. Ferroptosis, a form of regulated cell death, can be induced in medulloblastoma cells in vitro using erastin or RSL3. Using two independent medulloblastoma RNA-sequencing cohorts (MB-PBTA and MTAB-10767), we investigated the expression of ferroptosis-related molecules through multiple approaches, including Weighted Gene Co-Expression Network Analysis (WGCNA), molecular subtype stratification, protein–protein interaction (PPI) networks, and univariable and multivariable overall survival analyses. A prognostic expression score was computed based on a cross-validated ferroptosis signature. In training and validation cohorts, the regulation of the ferroptosis transcriptional program distinguished the four molecular subtypes of medulloblastoma. WGCNA identified nine gene modules in the MB tumor transcriptome; five correlated with molecular subtypes, implicating pathways related to oxidative stress, hypoxia, and trans-synaptic signaling. One module, associated with disease recurrence, included epigenetic regulators and nucleosome organizers. Univariable survival analyses identified a 45-gene ferroptosis prognostic signature associated with nutrient sensing, cysteine and methionine metabolism, and trans-sulfuration within a one-carbon metabolism. The top ten unfavorable ferroptosis genes included CCT3, SNX5, SQOR, G3BP1, CARS1, SLC39A14, FAM98A, FXR1, TFAP2C, and ATF4. Patients with a high ferroptosis score showed a worse prognosis, particularly in the G3 and SHH subtypes. The PPI network highlighted IL6 and CBS as unfavorable hub genes. In a multivariable overall survival model, which included gender, age, and the molecular subtype classification, the ferroptosis expression score was validated as an independent adverse prognostic marker (hazard ratio: 5.8; p-value = 1.04 × 10⁻⁹). This study demonstrates that the regulation of the ferroptosis transcriptional program is linked to medulloblastoma molecular subtypes and patient prognosis. A cross-validated ferroptosis signature was identified in two independent RNA-sequencing cohorts, and the ferroptosis score was confirmed as an independent and adverse prognostic factor in medulloblastoma.

Background/Objectives: Hepatic cancers, including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are major global health concerns due to rising incidence and limited therapeutic success. While traditional risk factors include chronic liver disease and environmental exposures, recent evidence underscores the significance of genetic alterations and gut microbiota in liver cancer development and progression. This review aims to integrate emerging knowledge on the interplay between host genomic changes and gut microbial dynamics in the pathogenesis and treatment of hepatic cancers. Methods: We conducted a comprehensive review of current literature on genetic and epigenetic drivers of HCC and CCA, focusing on commonly mutated genes such as TP53, CTNNB1, TERT, IDH1/2, and FGFR2. In parallel, we evaluated studies addressing the gut–liver axis, including the roles of dysbiosis, microbial metabolites, and immune modulation. Key clinical and preclinical findings were synthesized to explore how host–microbe interactions influence tumorigenesis and therapeutic response. Results: HCC and CCA exhibit distinct but overlapping genomic landscapes marked by recurrent mutations and epigenetic reprogramming. Alterations in the gut microbiota contribute to hepatic inflammation, genomic instability, and immune evasion, potentially enhancing oncogenic signaling pathways. Furthermore, microbiota composition appears to affect responses to immune checkpoint inhibitors. Emerging therapeutic strategies such as probiotics, fecal microbiota transplantation, and precision oncology based on mutational profiling demonstrate potential for personalized interventions. Conclusions: The integration of host genomics with microbial ecology provides a promising paradigm for advancing diagnostics and therapies in liver cancer. Targeting the gut–liver axis may complement genome-informed strategies to improve outcomes for patients with HCC and CCA.

(1) Background: Hepatoblastoma and medulloblastoma are two types of pediatric tumors with embryonic origins. Both tumor types can exhibit genetic alterations that affect the β-catenin and Wnt pathways; (2) Materials and Methods: This study used bioinformatics and integrative analysis of multi-omics data at both the tumor and single-cell levels to investigate two distinct pediatric tumors: medulloblastoma and hepatoblastoma; (3) Results: The cross-transcriptome analysis revealed a commonly regulated expression signature between hepatoblastoma and medulloblastoma tumors. Among the commonly upregulated genes, the transcription factor LEF1 was significantly expressed in both tumor types. In medulloblastoma, LEF1 upregulation is associated with the WNT-subtype. The analysis of LEF1 genome binding occupancy in H1 embryonic stem cells identified 141 LEF1 proximal targets activated in WNT medulloblastoma, 13 of which are involved in Wnt pathway regulation: RNF43, LEF1, NKD1, AXIN2, DKK4, DKK1, LGR6, FGFR2, NXN, TCF7L1, STK3, YAP1, and NFATC4. The ROC curve analysis of the combined expression of these 13 WNT-related LEF1 targets yielded an area under the curve (AUC) of 1.00, indicating 100% specificity and sensitivity for predicting the WNT subtype in the PBTA medulloblastoma cohort. An expression score based on these 13 WNT-LEF1 targets accurately predicted the WNT subtype in two independent medulloblastoma transcriptome cohorts. At the single-cell level, the WNT-LEF1 expression score was exclusively positive in WNT-medulloblastoma tumor cells. This WNT-LEF1-dependent signature was also confirmed as activated in the hepatoblastoma tumor transcriptome. At the single-cell level, the WNT-LEF1 expression score was higher in tumor cells from both human hepatoblastoma samples and a hepatoblastoma patient-derived xenotransplant model; (4) Discussion: This study uncovered a shared transcriptional activation of a LEF1-dependent embryonic program, which orchestrates the regulation of the Wnt signaling pathway in tumor cells from both hepatoblastoma and medulloblastoma.

Background/Objectives: Medulloblastoma is the most common malignant brain tumor in children and comprises four molecular subtypes—WNT, SHH, Group 3, and Group 4—each with distinct genetic, epigenetic, and metabolic features. Increasing evidence highlights the critical role of metabolic reprogramming and epigenetic alterations in driving tumor progression, therapy resistance, and clinical outcomes. This review aims to explore the interplay between metabolic and epigenetic mechanisms in medulloblastoma, with a focus on their functional roles and therapeutic implications. Methods: A comprehensive literature review was conducted using PubMed and relevant databases, focusing on recent studies examining metabolic pathways and epigenetic regulation in medulloblastoma subtypes. Particular attention was given to experimental findings from in vitro and in vivo models, as well as emerging preclinical therapeutic strategies targeting these pathways. Results: Medulloblastoma exhibits metabolic adaptations such as increased glycolysis, lipid biosynthesis, and altered amino acid metabolism. These changes support rapid cell proliferation and interact with the tumor microenvironment. Concurrently, epigenetic mechanisms—including DNA methylation, histone modification, chromatin remodeling, and non-coding RNA regulation—contribute to tumor aggressiveness and treatment resistance. Notably, metabolic intermediates often serve as cofactors for epigenetic enzymes, creating feedback loops that reinforce oncogenic states. Preclinical studies suggest that targeting metabolic vulnerabilities or epigenetic regulators—and particularly their combination—can suppress tumor growth and overcome resistance mechanisms. Conclusions: The metabolic–epigenetic crosstalk in medulloblastoma represents a promising area for therapeutic innovation. Understanding subtype-specific dependencies and integrating biomarkers for patient stratification could facilitate the development of precision medicine approaches that improve outcomes and reduce long-term treatment-related toxicity in pediatric patients.

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.

Medulloblastoma (MB) is the most common malignant brain tumor in children, typically arising during infancy and childhood. Despite multimodal therapies achieving a response rate of 70% in children older than 3 years, treatment remains challenging. Ferroptosis, a form of regulated cell death, can be induced in medulloblastoma cells in vitro using erastin or RSL3. Using two independent medulloblastoma RNA-sequencing cohorts (MB-PBTA and MTAB-10767), we investigated the expression of ferroptosis-related molecules through multiple approaches, including Weighted Gene Co-Expression Network Analysis (WGCNA), molecular subtype stratification, protein-protein interaction (PPI) networks, and univariable and multivariable overall survival analyses. A prognostic expression score was computed based on a cross-validated ferroptosis signature. In training and validation cohorts, regulation of the ferroptosis transcriptional program distinguished the four molecular subtypes of medulloblastoma. WGCNA identified nine gene modules in the MB tumor transcriptome; five correlated with molecular subtypes, implicating pathways related to oxidative stress, hypoxia, and trans-synaptic signaling. One module, associated with disease recurrence, included epigenetic regulators and nucleosome organizers. Univariable survival analyses identified a 45-gene ferroptosis prognostic signature associated with nutrient sensing, cysteine and methionine metabolism, and trans-sulfuration within one-carbon metabolism. The top ten unfavorable ferroptosis genes included: CCT3, SNX5, SQOR, G3BP1, CARS1, SLC39A14, FAM98A, FXR1, TFAP2C, and ATF4. Patients with a high ferroptosis score showed worse prognosis, particularly in G3 and SHH subtypes. The PPI network highlighted IL6 and CBS as unfavorable hub genes. In a multivariable overall survival model, which included gender, age, and molecular subtype classification, the ferroptosis expression score was validated as an independent adverse prognostic marker (hazard ratio: 5.8; p-value = 1.04 × 10⁻⁹). This study demonstrates that regulation of the ferroptosis transcriptional program is linked to medulloblastoma molecular subtypes and patient prognosis. A cross-validated ferroptosis signature was identified in two independent RNA-sequencing cohorts, and the ferroptosis score was confirmed as an independent and adverse prognostic factor in medulloblastoma.