Faculty of Pharmacy, Medical University of Sofia, 2 Dunav st, 1000, Sofia, Bulgaria.
School of Life and Health Sciences, Aston University, Aston Triangle, Birmingham, B4 7ET, UK.
BMC Immunol. 2018 Mar 15;19(1):11. doi: 10.1186/s12865-018-0248-x.
Cancer kills 8 million annually worldwide. Although survival rates in prevalent cancers continue to increase, many cancers have no effective treatment, prompting the search for new and improved protocols. Immunotherapy is a new and exciting addition to the anti-cancer arsenal. The successful and accurate identification of aberrant host proteins acting as antigens for vaccination and immunotherapy is a key aspiration for both experimental and computational research. Here we describe key elements of in silico prediction, including databases of cancer antigens and bleeding-edge methodology for their prediction. We also highlight the role dendritic cell vaccines can play and how they can act as delivery mechanisms for epitope ensemble vaccines. Immunoinformatics can help streamline the discovery and utility of Cancer Immunogens.
癌症每年在全球导致 800 万人死亡。虽然常见癌症的存活率持续上升，但许多癌症仍缺乏有效治疗方法，促使人们寻求新的、改进的方案。免疫疗法是抗癌武器库中的一项新的令人兴奋的补充。成功和准确地识别作为疫苗接种和免疫治疗抗原的异常宿主蛋白是实验和计算研究的关键目标。在这里，我们描述了计算机预测的关键要素，包括癌症抗原数据库和用于其预测的最先进方法。我们还强调了树突状细胞疫苗可以发挥的作用，以及它们如何作为表位组合疫苗的递送机制。免疫信息学可以帮助简化癌症免疫原的发现和应用。
