Neoantigens can be differentially recognized by T cell receptor (TCR) as these sequences are derived from mutant proteins and are unique to the tumor. The discovery of neoantigens is the first key step for tumor-specific antigen (TSA) based immunotherapy. Based on high-throughput tumor genomic analysis, each missense mutation can potentially give rise to multiple neopeptides, resulting in a vast total number, but only a small percentage of these peptides may achieve immune-dominant status with a given major histocompatibility complex (MHC) class I allele. Specific identification of immunogenic candidate neoantigens is consequently a major challenge. Currently almost all neoantigen prediction tools are based on genomics data. Here we report the construction of proteogenomics prediction of neoantigen (ProGeo-neo) pipeline, which incorporates the following modules: mining tumor specific antigens from next-generation sequencing genomic and mRNA expression data, predicting the binding mutant peptides to class I MHC molecules by latest netMHCpan (v.4.0), verifying MHC-peptides by MaxQuant with mass spectrometry proteomics data searched against customized protein database, and checking potential immunogenicity of T-cell-recognization by additional screening methods. ProGeo-neo pipeline achieves proteogenomics strategy and the neopeptides identified were of much higher quality as compared to those identified using genomic data only. The pipeline was constructed based on the genomics and proteomics data of Jurkat leukemia cell line but is generally applicable to other solid cancer research. With massively parallel sequencing and proteomics profiling increasing, this proteogenomics workflow should be useful for neoantigen oriented research and immunotherapy.

中文翻译：

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ProGeo-neo：用于新抗原预测和选择的定制蛋白质组学工作流程

新抗原可以被T细胞受体（TCR）区别识别，因为这些序列均来自突变蛋白，并且是肿瘤特有的。新抗原的发现是基于肿瘤特异性抗原（TSA）的免疫疗法的第一步。根据高通量肿瘤基因组分析，每个错义突变都可能产生多个新肽，导致总数庞大，但是在给定的主要组织相容性复合物（MHC）的情况下，这些肽中只有一小部分可以达到免疫显性状态我是等位基因。因此，特异性鉴定免疫原性候选新抗原是一项重大挑战。当前，几乎所有的新抗原预测工具都基于基因组数据。在这里，我们报告了新抗原（ProGeo-neo）管道的蛋白质组学预测的构建，它包含以下模块：从下一代测序基因组和mRNA表达数据中挖掘肿瘤特异性抗原，通过最新的netMHCpan（v.4.0）预测与I类MHC分子结合的突变肽，通过MaxQuant与质谱蛋白质组学验证MHC肽数据针对定制的蛋白质数据库进行搜索，并通过其他筛选方法检查T细胞识别的潜在免疫原性。ProGeo-neo管线实现了蛋白质组学策略，与仅使用基因组数据鉴定的肽相比，鉴定出的新肽的质量高得多。该管道是根据Jurkat白血病细胞系的基因组学和蛋白质组学数据构建的，但通常可用于其他实体癌症研究。随着大规模并行测序和蛋白质组学分析的发展，