2026-06-09 医薬基盤・健康・栄養研究所
＜関連情報＞
- https://www.nibn.go.jp/pr/press/20260609.html
- https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2026.1829509/full
がん患者における個別化ネオアンチゲンワクチンによって誘導される免疫原性ネオアンチゲンペプチドのプロファイリング Profiling immunogenic neoantigen peptides elicited by personalized neoantigen vaccine in cancer patients
Peng Zhao ,Clara Effenberger,Saki Matsumoto,Takafumi Morisaki,Yu Ishii,Masayo Umebayashi,Hiroto Tanaka,Norihiro Koya,+ 4 more,Kazuma Kiyotani
Frontiers in Immunology Published:09 June 2026
DOI:https://doi.org/10.3389/fimmu.2026.1829509
Abstract
Introduction:
Personalized neoantigen vaccines can induce antitumor T cell responses, but only 10-20% of selected peptides have induced immune responses in patients, underscoring the limitations of current prediction strategies.
Methods:
We analyzed a clinically annotated dataset from 352 cancer patients who received personalized neoantigen peptide-pulsed dendritic cell vaccines. We focused on 2,317 short peptides derived from single nucleotide variants for which post-vaccination T cell responses were evaluated by IFN-γ ELISPOT assay. Immunogenic neoantigen peptides were defined as those inducing a ≥2.0-fold increase in IFN-γ ELISPOT responses after vaccination. We systematically examined peptide intrinsic characteristics and physicochemical properties, as well as predicted scores related to antigen-processing machinery.
Results and discussion:
Immunogenicity was not associated with specific mutation positions or sequence patterns but was significantly correlated with higher hydrophobicity (P = 5.2 × 10-4). Among several predictive scores, peptides with higher binding affinity to HLA molecules (P = 0.0014 for NetMHC3, P = 0.028 for MHCflurry-affinity), higher binding stability (P = 0.043 for NetMHCstab) or better peptide presentation scores (P = 0.012 for mixmhcPred3, P = 0.0085 for MHCflurry-presentation) were significantly enriched among immunogenic neoantigen peptides. Composite models integrating peptide physicochemical features, particularly hydrophobicity, with prediction scores improved the area under the receiver operating characteristic curve and balanced accuracy compared with individual tools alone. Together, these findings highlight the multifactorial determinants of neoantigen immunogenicity and support the integration of complementary peptide features to refine neoantigen prioritization for personalized vaccines and T cell-based immunotherapies.
