PCI-DB: a novel primary tissue immunopeptidome database to guide next-generation peptide-based immunotherapy development.

IF 10.3 1区 医学 Q1 IMMUNOLOGY
Steffen Lemke, Marissa L Dubbelaar, Patrick Zimmermann, Jens Bauer, Annika Nelde, Naomi Hoenisch Gravel, Jonas Scheid, Marcel Wacker, Susanne Jung, Anna Dengler, Yacine Maringer, Hans-Georg Rammensee, Cecile Gouttefangeas, Sven Fillinger, Tatjana Bilich, Jonas S Heitmann, Sven Nahnsen, Juliane S Walz
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引用次数: 0

Abstract

Background: Various cancer immunotherapies rely on the T cell-mediated recognition of peptide antigens presented on human leukocyte antigens (HLA). However, the identification and selection of naturally presented peptide targets for the development of personalized as well as off-the-shelf immunotherapy approaches remain challenging.

Methods: Over 10,000 raw mass spectrometry (MS) files from over 3,000 tissue samples were analyzed, summing to approximately seven terabytes of data. The raw MS data were processed using the standardized and open-source nf-core pipelines MHCquant2 and epitopeprediction, providing a uniform procedure for data handling. A global false discovery rate was applied to minimize false-positive identifications.

Results: Here, we introduce the open-access Peptides for Cancer Immunotherapy Database (PCI-DB, https://pci-db.org/), a comprehensive resource of immunopeptidome data originating from various malignant and benign primary tissues that provides the research community with a convenient tool to facilitate the identification of peptide targets for immunotherapy development. The PCI-DB includes >6.6 million HLA class I and >3.4 million HLA class II peptides from over 40 tissue types and cancer entities. First application of the database provided insights into the representation of cancer-testis antigens across malignant and benign tissues, enabling the identification and characterization of cross-tumor entity and entity-specific tumor-associated antigens (TAAs) as well as naturally presented neoepitopes from frequent cancer mutations. Further, we used the PCI-DB to design personalized peptide vaccines for two patients suffering from metastatic cancer. In a retrospective analysis, PCI-DB enabled the composition of both a multi-peptide vaccine comprising non-mutated, highly frequent TAAs matching the immunopeptidome of the individual patient's tumor and a neoepitope-based vaccine matching the mutational profile of a patient with cancer. Both vaccine approaches induced potent and long-lasting T-cell responses, accompanied by long-term survival of these patients with advanced cancer.

Conclusion: The PCI-DB provides a highly versatile tool to broaden the understanding of cancer-related antigen presentation and, ultimately, supports the development of novel immunotherapies.

PCI-DB:一个新的原代组织免疫肽球数据库,指导下一代基于肽的免疫治疗的发展。
背景:各种癌症免疫治疗依赖于T细胞介导的人类白细胞抗原(HLA)上肽抗原的识别。然而,鉴定和选择天然存在的肽靶点用于个性化和现成的免疫治疗方法的发展仍然具有挑战性。方法:分析了来自3000多个组织样本的10000多个原始质谱(MS)文件,总计约7tb的数据。原始MS数据使用标准化和开源的nf-core管道MHCquant2和表位预测进行处理,为数据处理提供了统一的程序。采用全局错误发现率来最大限度地减少假阳性识别。结果:在这里,我们介绍了开放获取的多肽用于癌症免疫治疗数据库(PCI-DB, https://pci-db.org/),这是一个来自各种恶性和良性原发组织的免疫肽球数据的综合资源,为研究社区提供了一个方便的工具,以方便识别免疫治疗开发的肽靶点。PCI-DB包括来自40多种组织类型和癌症实体的660万HLA I类肽和340万HLA II类肽。该数据库的首次应用为癌症-睾丸抗原在恶性和良性组织中的表现提供了见解,使跨肿瘤实体和实体特异性肿瘤相关抗原(TAAs)的识别和表征以及来自频繁癌症突变的自然呈现的新表位成为可能。此外,我们使用PCI-DB为两名患有转移性癌症的患者设计个性化肽疫苗。在一项回顾性分析中,PCI-DB能够组合一种多肽疫苗,包括与个体患者肿瘤的免疫肽球相匹配的非突变、高频率的taa,以及与癌症患者的突变谱相匹配的基于新表位的疫苗。这两种疫苗方法都诱导了强效和持久的t细胞反应,并伴随着这些晚期癌症患者的长期生存。结论:PCI-DB提供了一个高度通用的工具,以扩大对癌症相关抗原呈递的理解,并最终支持新型免疫疗法的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal for Immunotherapy of Cancer
Journal for Immunotherapy of Cancer Biochemistry, Genetics and Molecular Biology-Molecular Medicine
CiteScore
17.70
自引率
4.60%
发文量
522
审稿时长
18 weeks
期刊介绍: The Journal for ImmunoTherapy of Cancer (JITC) is a peer-reviewed publication that promotes scientific exchange and deepens knowledge in the constantly evolving fields of tumor immunology and cancer immunotherapy. With an open access format, JITC encourages widespread access to its findings. The journal covers a wide range of topics, spanning from basic science to translational and clinical research. Key areas of interest include tumor-host interactions, the intricate tumor microenvironment, animal models, the identification of predictive and prognostic immune biomarkers, groundbreaking pharmaceutical and cellular therapies, innovative vaccines, combination immune-based treatments, and the study of immune-related toxicity.
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