Ran Zhi, Mu Meilin, Lin Shaofeng, Wang Tao, Zeng Jing, Kuang Lan, Chen Kunqi, Suo Shengbao, Yuan Kai, Xu Haodong
Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.
School of Life Science, Central South University, Changsha, Hunan 410011, China.
Brief Bioinform. 2025 Jul 2;26(4). doi: 10.1093/bib/bbaf314.
A fundamental principle of immunotherapy is that T cells are capable of detecting tumor epitopes presented on cancer cell surfaces. Immunopeptidomic strategies empowered by liquid chromatography-tandem mass spectrometry have transformed tumor epitopes identification and provided novel insights into tumor immunology. It enables in-depth profiling of major histocompatibility complex (MHC) presented ligands, thereby offering valuable perspectives on the molecular dialog among tumor and T cells. Here, we developed an immune-ligand identification and analysis pipeline from large-scale immunopeptidomics data. Through an extensive collection and processing of 5821 immunopeptidomic samples, which amounted to 305.7 million MS2 spectra, we identified 24 380 595 peptide-spectrum matches from these samples and further detected a total of 1 017 731 unique MHC immune ligands. These ligands were deconvolved and classified to specific HLA alleles. In total, we detected 582 852 HLA-I peptides and 434 879 HLA-II peptides that can bind to 292 HLA alleles, thereby greatly expanding the cancer immunopeptidome. Additionally, we identified and annotated 372 720 tumor-associated post-translational modification (PTM) peptides, revealing the comprehensive landscape of PTM antigens. All ligands and annotations were aggregated into Ligand.MHC Atlas, a comprehensive repository dedicated to tumor-derived HLA-presented ligands across 26 major human cancers (54 subtypes). Overall, our study uniquely integrates batch-effect correction, leverages the optimized software with novel deconvolution approach for immunopeptidomics analysis and ligand identification, and provides a public web portal with a comprehensive HLA ligand repository. Ligand.MHC Atlas functions as an invaluable resource, offering crucial understandings into immunology investigations. It will accelerate the advancement of cancer vaccines and immunotherapies. Ligand.MHC Atlas is available at http://modinfor.com/Ligand.MHC-Atlas/.
免疫疗法的一个基本原则是T细胞能够检测癌细胞表面呈现的肿瘤表位。液相色谱-串联质谱技术支持的免疫肽组学策略改变了肿瘤表位的识别，并为肿瘤免疫学提供了新的见解。它能够对主要组织相容性复合体（MHC）呈现的配体进行深入分析，从而为肿瘤与T细胞之间的分子对话提供有价值的观点。在此，我们从大规模免疫肽组学数据中开发了一种免疫配体识别与分析流程。通过广泛收集和处理5821个免疫肽组学样本（总计3.057亿个MS2谱图），我们从这些样本中鉴定出24380595个肽-谱匹配，并进一步检测到总共1017731个独特的MHC免疫配体。这些配体被解卷积并归类到特定的HLA等位基因。我们总共检测到582852个HLA-I肽和434879个HLA-II肽，它们能够与292个HLA等位基因结合，从而极大地扩展了癌症免疫肽组。此外，我们鉴定并注释了372720个肿瘤相关的翻译后修饰（PTM）肽，揭示了PTM抗原的全面情况。所有配体和注释都汇总到Ligand.MHC Atlas中，这是一个全面的数据库，专门收录26种主要人类癌症（54个亚型）中肿瘤来源的HLA呈现的配体。总体而言，我们的研究独特地整合了批次效应校正，利用优化的软件和新颖的解卷积方法进行免疫肽组学分析和配体识别，并提供了一个带有全面HLA配体数据库的公共网站门户。Ligand.MHC Atlas作为一种宝贵的资源，为免疫学研究提供了关键的见解。它将加速癌症疫苗和免疫疗法的发展。Ligand.MHC Atlas可在http://modinfor.com/Ligand.MHC-Atlas/获取。
