PROTAC 工程化蛋白/DNA 纳米抗原是癌症免疫治疗中树突状细胞疫苗的有效增强剂
PROTAC-Engineered Protein/DNA Nanoantigen is a Potent Booster for Dendritic Cell Vaccines in Cancer Immunotherapy.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Profiling immunogenic neoantigen peptides elicited by personalized neoantigen vaccine in cancer patients.
Profiling immunogenic neoantigen peptides elicited by personalized neoantigen vaccine in cancer patients.
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个体化新抗原疫苗可诱导抗肿瘤T细胞反应,但仅10-20%的所选肽在患者中诱导了免疫反应,凸显了当前预测策略的局限性。
我们分析了一个包含352名接受个体化新抗原肽脉冲树突状细胞疫苗治疗的癌症患者的临床注释数据集。我们聚焦于源自单核苷酸变异的2,317条短肽,通过IFN-γ ELISPOT试验评估其疫苗接种后的T细胞反应。免疫原性新抗原肽定义为疫苗接种后诱导IFN-γ ELISPOT反应增加≥2.0倍的肽。我们系统检查了肽的内在特征和理化性质,以及与抗原加工机制相关的预测评分。结果与讨论:免疫原性与特定突变位置或序列模式无关,但与较高的疏水性显著相关(P = 5.2 × 10⁻⁴)。在若干预测评分中,对HLA分子具有较高结合亲和力的肽(NetMHC3 P = 0.0014,MHCflurry-affinity P = 0.028)、较高结合稳定性的肽(NetMHCstab P = 0.043)或较好肽呈递评分的肽(mixmhcPred3 P = 0.012,MHCflurry-presentation P = 0.0085)在免疫原性新抗原肽中显著富集。将肽理化特征(尤其是疏水性)与预测评分整合的复合模型,相比单独使用各工具,提高了受试者工作特征曲线下面积和平衡准确度。总之,这些发现突出了新抗原免疫原性的多因素决定因素,并支持整合互补的肽特征以优化个体化疫苗和T细胞免疫治疗的新抗原优先级排序。
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.
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