Mardis Elaine R
From the Institute for Genomic Medicine, Nationwide Children's Hospital, and The Ohio State University College of Medicine, Columbus, OH.
Cancer J. 2017 Mar/Apr;23(2):97-101. doi: 10.1097/PPO.0000000000000248.
Cancer is caused by alterations to DNA that ultimately are translated into altered proteins with unique amino acid sequences when compared with their counterparts in normal cells. By inference, these altered proteins have the potential to elicit immune responses such as T-cell recognition, if properly presented by the immune system following protein degradation and major histocompatibility complex binding. Historically, identifying tumor-specific mutant antigens was painstaking work that involved molecular cloning and immune screening. This scenario has changed dramatically in the last few years as new sequencing technology combined with computational data analysis can identify the unique tumor peptide sequences, and algorithmic evaluation of these novel peptides can estimate their binding affinity to the major histocompatibility complex haplotypes encoded by each genome. This process can identify unique neoantigens in each cancer, either as a means of characterizing the overall neoantigen load or as a precursor to designing a personalized cancer vaccine. An overview of the data and analysis methods used to identify cancer neoantigens will be presented along with an in-depth consideration of the nuances of each step.
癌症是由DNA改变引起的,与正常细胞中的对应物相比,这些改变最终会转化为具有独特氨基酸序列的改变的蛋白质。由此推断,如果这些改变的蛋白质在蛋白质降解和主要组织相容性复合体结合后由免疫系统正确呈递,它们就有可能引发免疫反应,如T细胞识别。从历史上看,鉴定肿瘤特异性突变抗原是一项艰苦的工作,涉及分子克隆和免疫筛选。在过去几年中,这种情况发生了巨大变化,因为新的测序技术与计算数据分析相结合,可以识别独特的肿瘤肽序列,并且对这些新型肽的算法评估可以估计它们与每个基因组编码的主要组织相容性复合体单倍型的结合亲和力。这个过程可以识别每种癌症中的独特新抗原,既可以作为表征总体新抗原负荷的一种手段,也可以作为设计个性化癌症疫苗的前体。本文将概述用于识别癌症新抗原的数据和分析方法,并深入考虑每个步骤的细微差别。