TRON-Translationale Onkologie an der Universitätsmedizin der Johannes Gutenberg-Universität Mainz gemeinnützige GmbH, Freiligrathstraße, Mainz, Germany.
Methods Mol Biol. 2020;2120:1-9. doi: 10.1007/978-1-0716-0327-7_1.
Our immune system plays a key role in health and disease as it is capable of responding to foreign antigens as well as acquired antigens from cancer cells. Latter are caused by somatic mutations, the so-called neoepitopes, and might be recognized by T cells if they are presented by HLA molecules on the surface of cancer cells. Personalized mutanome vaccines are a class of customized immunotherapies, which is dependent on the detection of individual cancer-specific tumor mutations and neoepitope (i.e., prediction, followed by a rational vaccine design, before on-demand production. The development of next generation sequencing (NGS) technologies and bioinformatic tools allows a large-scale analysis of each parameter involved in this process. Here, we provide an overview of the bioinformatic aspects involved in the design of personalized, neoantigen-based vaccines, including the detection of mutations and the subsequent prediction of potential epitopes, as well as methods for associated biomarker research, such as high-throughput sequencing of T-cell receptors (TCRs), followed by data analysis and the bioinformatics quantification of immune cell infiltration in cancer samples.
我们的免疫系统在健康和疾病中起着关键作用，因为它能够对来自癌细胞的外来抗原和获得性抗原做出反应。后者是由体细胞突变引起的，即所谓的新抗原，并且如果它们由 HLA 分子在癌细胞表面呈现，可能被 T 细胞识别。个性化突变体疫苗是一类定制的免疫疗法，它依赖于检测个体癌症特异性肿瘤突变和新抗原（即预测，然后进行合理的疫苗设计，然后按需生产。下一代测序（NGS）技术和生物信息学工具的发展允许对这个过程中涉及的每个参数进行大规模分析。在这里，我们提供了个性化、基于新抗原的疫苗设计中涉及的生物信息学方面的概述，包括突变的检测和随后对潜在表位的预测，以及相关生物标志物研究的方法，例如 T 细胞受体（TCRs）的高通量测序，然后进行数据分析和癌症样本中免疫细胞浸润的生物信息学定量。
