Deluca D S, Blasczyk R
Institute for Transfusion Medicine, Hannover Medical School, Carl-Neuberg-Street 1, 30625 Hannover, Germany.
Tissue Antigens. 2007 Oct;70(4):265-71. doi: 10.1111/j.1399-0039.2007.00914.x.
We review here the developments in the field of immunoinformatics and their present and potential applications to the immunotherapeutic treatment of cancer. Antigen presentation plays a central role in the immune response, and as a result in immunotherapeutic methods such as adoptive T-cell transfer and antitumor vaccination. We therefore extensively review the current technologies of antigen presentation prediction, including the next generation predictors, which combine proteasomal processing, transporter associated with antigen processing and major histocompatibility complex (MHC)-binding prediction. Minor histocompatibility antigens are also relevant targets for immunotherapy, and we review the current systems available, SNEP and SiPep. Here, antigen presentation plays a key role, but additional types of data are also incorporated, such as single nucleotide polymorphism data and tissue/cell-type expression data. Current systems are not capable of handling the concept of immunodominance, which is critical to immunotherapy, but efforts have been made to model general aspects of the immune system. Although tough challenges lie ahead, when measuring the field of immunoinformatics on its contributions thus far, one can expect fruitful developments in the future.
我们在此回顾免疫信息学领域的发展及其在癌症免疫治疗中的当前和潜在应用。抗原呈递在免疫反应中起着核心作用，因此在诸如过继性T细胞转移和抗肿瘤疫苗接种等免疫治疗方法中也起着核心作用。因此，我们广泛回顾了当前抗原呈递预测技术，包括结合蛋白酶体加工、抗原加工相关转运体和主要组织相容性复合体（MHC）结合预测的新一代预测器。次要组织相容性抗原也是免疫治疗的相关靶点，我们回顾了现有的系统，即SNEP和SiPep。在此，抗原呈递起着关键作用，但也纳入了其他类型的数据，如单核苷酸多态性数据和组织/细胞类型表达数据。当前的系统无法处理对免疫治疗至关重要的免疫优势概念，但已努力对免疫系统的一般方面进行建模。尽管未来面临严峻挑战，但从免疫信息学领域迄今为止的贡献来看，人们可以期待未来会有丰硕的发展成果。
