THE CANCER EPITOPE DATABASE AND ANALYSIS RESOURCE

摘要 近年来，人们对癌症表位和新表位的兴趣急剧上升。 这包括在特定的肿瘤中产生的突变。目前的研究路线考察了 特定肿瘤中的表位负载关系到检查点阻断治疗的成功，以及如何利用 基于表位的疫苗和用于个性化治疗的表位特异性T细胞的过继转移。为了这些 目的，在不同个体中反复识别的新表位特别令人感兴趣，这具有 也重新点燃了人们对经典肿瘤相关抗原表位的兴趣。伴随着对 癌症表位，也有兴趣的TCR和BCR专门识别它们，因为它们有 有可能用于治疗方法，它们可以帮助基础研究推断T细胞的特异性 或在单细胞测序数据中表征的B细胞。对表位的兴趣的复苏创造了一个 需要编目并向科学界提供所有表位数据，也与生物学、 免疫学和临床背景。最终的目标是让表位识别和连接成一个完整的循环。 临床结果和治疗策略的免疫学读数。同时，还有一种迫切需要 为表位预测和分析工具开发资源，这些工具提供访问预测策略和 在相关的生物学、免疫学和临床背景下对他们的表现进行客观评估。 近年来，也见证了多种原创方法的出版，这些方法有时会报告 癌症表位预测方面取得了令人印象深刻的进展。然而，这些研究中有几项很难 评估，因为方法和/或数据集不是完全可用的格式 可执行文件。因此，他们的表现不能在独立的数据集上进行适当的基准测试。这是 还因为对独立数据集进行有效的基准测试需要组装 足够的规模和多样性。为了克服所有这些信息技术挑战，我们建议设计 并实现了癌症表位数据库和分析资源(CEDAR)，它将提供一个免费的 从文献中收集可访问的、全面的癌症表位和受体数据，并提供 易于获取的表位和TCR/BCR靶标预测和分析工具。因为癌症表位数据是 经过精心策划，它们将被用作预测工具表现如何的透明基准，还将用于开发 雪松分析资源成分的新预测工具。雪松将利用我们的专业知识从 全面运行、广泛应用的免疫表位数据库与分析资源(IEDB)的开发 全球研究人员都在使用。雪松将直接补充目前由美国国立卫生研究院资助的其他项目 ITCR计划，提供与癌症组学数据相关的资源和工具。最后，我们将进行外展 改进功能、用户界面和与其他ITCR工具的互操作性的活动，并促进 雪松在癌症研究中的地位。

ABSTRACT Recent years have witnessed a dramatic rise in interest towards cancer epitopes in general, and neoepitopes that encompass mutations arising in a given tumor in particular. Current lines of research examine how the epitope load in a given tumor relates to the success of checkpoint blockade treatments, and how to utilize epitope-based vaccines and adoptive transfer of epitope-specific T cells for personalized therapies. For these purposes, neoepitopes that are recurrently recognized in different individuals are of particular interest, which has also re-ignited interest in epitopes identified in classic tumor-associated antigens. Along with the interest in cancer epitopes, there is also interest in the TCRs and BCRs specifically recognizing them, as these have the potential to be used in therapeutic approaches, and they can aid in basic studies to infer the specificity of T cells or B cells characterized in single cell sequencing data. This resurgence of interest in epitopes has created a need to catalog and make accessible to the scientific community all epitope data, also linked to the biological, immunological, and clinical contexts. The ultimate goal is to come “full circle” and link epitope recognition and immunological readouts to clinical outcomes and treatment strategies alike. In parallel, there is an urgent need to develop resources for epitope prediction and analysis tools that provide access to predictive strategies and provide objective evaluations of their performance in the relevant biological, immunological, and clinical contexts. Recent years have also witnessed the publication of multiple original methodologies that reported sometimes impressive gains in the predictions of cancer epitopes. However, several of these studies were difficult to evaluate, because the methodologies and/or datasets were not fully available in a format that was readily executable. As a result, their performance could not be properly benchmarked on independent datasets. This is also because effective benchmarking on independent datasets requires the assembly of novel datasets of sufficient size and diversity. To overcome all of these information technology challenges, we propose to design and implement the Cancer Epitope Database and Analysis Resource (CEDAR), which will provide a freely accessible, comprehensive collection of cancer epitope and receptor data curated from the literature, and provide easily accessible epitope and TCR/BCR target prediction and analysis tools. As the cancer epitope data are curated, they will be used as a transparent benchmark of how well prediction tools perform, and also to develop new prediction tools for the analysis resource component of CEDAR. CEDAR will leverage our expertise from developing the Immune Epitope Database and Analysis Resource (IEDB), which is fully operational and widely used by researchers globally. CEDAR will directly complement other projects currently funded through the NIH ITCR program that provide resources and tools related to cancer omics data. Finally, we will engage in outreach activities to improve functions, user interfaces, and interoperability with other ITCR tools and promote the use of CEDAR in cancer research.