Immuno, Volume 6, Issue 2 (June 2026) – 2 articles

Melanoma is characterized by a high mutational burden making it an established model for studying tumor neoantigens and developing strategies for personalized immunotherapy. In this study, a reproducible bioinformatics pipeline was developed and implemented for the identification and prioritization of candidate neoantigens derived from non-synonymous somatic mutations in melanoma, using genomic data from the MSK-IMPACT cohort (mel-mskimpact-2020; n = 696) and comparative reference information from TCGA-SKCM. From the somatic mutation annotation file (MAF), 16,311 non-synonymous mutations were filtered, from which 50,480 mutant 8–11-mer peptides were generated using a sliding-window approach centered on the mutated position. Peptide–HLA class I binding affinity was predicted using MHCflurry 2.0 across six representative alleles (HLA-A*02:01, HLA-A*24:02, HLA-B*35:01, HLA-B*39:05, HLA-C*04:01, and HLA-C*07:02). Candidate prioritization was initially based on predicted binding percentile (rank ≤ 2), identifying 12,209 peptide–HLA combinations with high predicted binding affinity. To refine candidate selection, additional computational analyses were incorporated, including proteasomal cleavage prediction using NetChop 3.1 and estimation of T-cell epitope immunogenicity using the Immune Epitope Database (IEDB) immunogenicity predictor. Furthermore, a direct comparison between mutant (MUT) and corresponding wild-type (WT) peptides was performed using Δaffinity and Δrank metrics to evaluate the predicted impact of somatic mutations on HLA binding. The analysis revealed a predominance of peptides associated with the HLA-B locus, particularly the allele HLA-B*35:01, among the interactions with the lowest predicted binding percentiles. Several high-ranking peptide candidates were derived from genes with known roles in melanoma biology, including PLCG2, GATA3, AKT1, PTEN, PTCH1, and SMO. Overall, the integrative computational framework implemented in this study enables the systematic prioritization of candidate neoantigens derived from non-synonymous mutations in melanoma. This pipeline provides a reproducible strategy for exploring tumor neoantigen repertoires and may serve as a foundation for subsequent experimental validation and for studies related to neoantigen-based immunotherapies and immunopeptidomics. Full article

Nanomaterials (NMs) are increasingly utilized in drug delivery, diagnostic imaging, and therapeutic applications. However, their widespread use raises concerns regarding potential neurotoxicity, particularly for metal and metal oxide nanoparticles. Accumulating evidence indicates that these nanoparticles induce neurotoxicity through interconnected mechanisms, including excessive reactive oxygen species generation, activation of neuroinflammatory pathways, mitochondrial dysfunction, and disruption of blood–brain barrier integrity. These molecular events collectively lead to synaptic impairment, neuronal apoptosis, and progressive cognitive and behavioral deficits, with toxicity severity influenced by dose, exposure duration, and age. Given that in vitro models often fail to capture complex systemic interactions such as nanoparticle biodistribution, blood–brain barrier dynamics, and neuroimmune responses, this review places particular emphasis on in vivo studies to provide a more physiologically relevant understanding of nanoparticle-induced neurotoxicity. Importantly, a growing body of in vivo evidence demonstrates that natural bioactive compounds can mitigate these effects by targeting key pathogenic pathways, including oxidative stress, inflammation, and mitochondrial dysfunction, while preserving neuronal integrity. These findings highlight the therapeutic potential of natural bioactives as protective agents against nanoparticle-induced neurotoxicity and as candidates for broader neuroprotective strategies. This review summarizes the mechanistic basis of metal and metal oxide nanoparticle neurotoxicity and critically evaluates the protective role of natural bioactive compounds, with a focus on evidence derived from animal models. Full article