Neoantigens can function as actual antigens to facilitate tumor rejection, which play a crucial role in cancer immunology and immunotherapy. Emerging evidence revealed that neoantigens can be used to develop personalized, cancer-specific vaccines. To date, large numbers of immunogenomic peptides have been computationally predicted to be potential neoantigens. However, experimental validation remains the gold standard for potential clinical application. Experimentally validated neoantigens are rare and mostly appear scattered among scientific papers and various databases. Here, we constructed dbPepNeo, a specific database for human leukocyte antigen class I (HLA-I) binding neoantigen peptides based on mass spectrometry (MS) validation or immunoassay in human tumors. According to the verification methods of these neoantigens, the collection of peptides was classified as 295 high confidence, 247 medium confidence and 407 794 low confidence neoantigens, respectively. This can serve as a valuable resource to aid further screening for effective neoantigens, optimize a neoantigen prediction pipeline and study T-cell receptor (TCR) recognition. Three applications of dbPepNeo are shown. In summary, this work resulted in a platform to promote the screening and confirmation of potential neoantigens in cancer immunotherapy. Database URL: www.biostatistics.online/dbPepNeo/.

中文翻译：

---

dbPepNeo：人肿瘤新抗原肽的手动管理数据库。

新抗原可以用作促进肿瘤排斥的实际抗原，这在癌症免疫学和免疫疗法中起着至关重要的作用。新兴证据表明，新抗原可用于开发个性化的癌症特异性疫苗。迄今为止，已通过计算预测大量免疫基因组肽是潜在的新抗原。但是，实验验证仍然是潜在临床应用的金标准。经过实验验证的新抗原很少见，并且大多散布在科学论文和各种数据库中。在这里，我们基于质谱（MS）验证或人体肿瘤中的免疫测定，构建了dbPepNeo，这是一个针对人白细胞抗原I类（HLA-1）结合新抗原肽的特定数据库。根据这些新抗原的验证方法，肽的收集分别分类为295个高信度，247个中信度和407794个低信度新抗原。这可以作为宝贵的资源，以帮助进一步筛选有效的新抗原，优化新抗原预测流程以及研究T细胞受体（TCR）的识别。显示了dbPepNeo的三个应用程序。总之，这项工作建立了一个平台，以促进癌症免疫治疗中潜在新抗原的筛选和确认。数据库URL：www.biostatistics.online/dbPepNeo/。显示了dbPepNeo的三个应用程序。总之，这项工作建立了一个平台，以促进癌症免疫治疗中潜在新抗原的筛选和确认。数据库URL：www.biostatistics.online/dbPepNeo/。显示了dbPepNeo的三个应用程序。总之，这项工作建立了一个平台，以促进癌症免疫治疗中潜在新抗原的筛选和确认。数据库URL：www.biostatistics.online/dbPepNeo/。