背景:癌症免疫治疗是通过识别在癌细胞的细胞表面上呈递的抗原和非法的T细胞反应来实现的(Schumacher和Schreiber,科学348:69-74,2015;Waldman等人。,NatRevImmunol20:651-668,2020;Zhang等人。,前免疫醇12:672,356,2021b)。这种抗原的经典候选物是由遗传改变产生的肽,被命名为“新抗原”(舒马赫和施雷伯,科学348:69-74,2015)。新抗原已在几种人类癌症类型中广泛分类(Tan等人。,数据库(牛津)2020;2020b;Vigneron等人。,癌症Immun13:15,2013;Yi等人。,iScience24:103,107,2021;Zhang等人。,BMC生物信息学22:40,2021a)。最近,一类新的可诱导抗原已被鉴定,即替代品,是由于异常蛋白质翻译而产生的(Pataskar等人。,自然603:721-727,2022)。主要:人类癌症类型的替代表达目录,它们的特异性和与基因表达特征的关联对于科学界来说仍然难以捉摸。作为解决方案,我们介绍ABPEPserver,一个在线数据库和分析平台,可以可视化来自CPTAC数据库的八种肿瘤类型的替代表达的大规模肿瘤蛋白质组学分析(Edwards等人。,J蛋白质组研究14:2707-2713,2015)。功能上,ABPEPserver提供了取代肽的基因关联特征分析,比较肿瘤和肿瘤附近正常组织之间的富集,以及作为免疫治疗设计候选肽的列表。ABPEPserver将显著增强人类癌症中异常蛋白质产生的探索,如案例研究所示。
结论:ABPEPserver是在RSHINY平台上设计的,用于编目人类癌症中的取代肽。该应用程序可在https://rhpc。nkinl/网站/闪亮/ABPEP/。该代码可在GitHub(https://github.com/jasminesmn/ABPEPserver)的GNU通用公共许可证下获得。
BACKGROUND: Cancer immunotherapy is implemented by identifying antigens that are presented on the cell surface of cancer cells and illicit T-cell response (Schumacher and Schreiber, Science 348:69-74, 2015; Waldman et al., Nat Rev Immunol 20:651-668, 2020; Zhang et al., Front Immunol 12:672,356, 2021b). Classical candidates of such antigens are the peptides resulting from genetic alterations and are named \"neoantigen\" (Schumacher and Schreiber, Science 348:69-74, 2015). Neoantigens have been widely catalogued across several human cancer types (Tan et al., Database (Oxford) 2020;2020b; Vigneron et al., Cancer Immun 13:15, 2013; Yi et al., iScience 24:103,107, 2021; Zhang et al., BMC Bioinformatics 22:40, 2021a). Recently, a new class of inducible antigens has been identified, namely
Substitutants, that are produced as a result of aberrant protein translation (Pataskar et al., Nature 603:721-727, 2022). MAIN: Catalogues of Substitutant expression across human cancer types, their specificity and association to gene expression signatures remain elusive for the scientific community\'s access. As a solution, we present ABPEPserver, an online database and analytical platform that can visualize a large-scale tumour proteomics analysis of Substitutant expression across eight tumour types sourced from the CPTAC database (Edwards et al., J Proteome Res 14:2707-2713, 2015). Functionally, ABPEPserver offers the analysis of gene-association signatures of Substitutant peptides, a comparison of enrichment between tumour and tumour-adjacent normal tissues, and a list of peptides that serve as candidates for immunotherapy design. ABPEPserver will significantly enhance the exploration of aberrant protein production in human cancer, as exemplified in a case study.
CONCLUSIONS: ABPEPserver is designed on an R SHINY platform to catalogue Substitutant peptides in human cancer. The application is available at https://rhpc.nki.nl/sites/shiny/ABPEP/ . The code is available under GNU General public license from GitHub ( https://github.com/jasminesmn/ABPEPserver ).