optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material.
Mogjiborahman Salek, Jonas D Förster, Jonas P Becker, Marten Meyer, Pornpimol Charoentong, Yanhong Lyu, Katharina Lindner, Catharina Lotsch, Michael Volkmar, Frank Momburg, Isabel Poschke, Stefan Fröhling, Marc Schmitz, Rienk Offringa, Michael Platten, Dirk Jäger, Inka Zörnig, Angelika B Riemer
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引用次数: 0
Abstract
Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for the improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft from as little as 2.5 × 106 cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.
治疗性疫苗和 T 细胞受体(TCR)转基因 T 细胞的采纳性转移等个性化癌症免疫疗法依赖于人类白细胞抗原(HLA)Ⅰ类分子向细胞毒性 T 细胞呈递肿瘤特异性多肽。例如,这种新表位可由体细胞突变产生,识别它们对于合理设计新的治疗干预措施至关重要。基于液相色谱质谱(LC-MS)的免疫肽组学是直接证明实际肽呈现的唯一方法,我们开发了一种参数优化工作流程来调整靶向检测,以实现每条肽的最大检测灵敏度,称为 optiPRM。利用 optiPRM 优化碰撞能量,可以提高对低含量多肽的检测灵敏度,而使用标准参数很难检测到这些多肽。将这一方法应用于免疫肽组学,我们从仅输入 2.5×106 个细胞的病人异种移植(PDX)中检测到了一个新表位。在小型患者肿瘤样本中应用该工作流程,在三名患者中检测到了五个突变衍生的新表位。其中一个新表位被证实能被患者的 T 细胞识别。总之,optiPRM 是一种靶向质谱工作流程,通过对每个肽段参数的优化达到了超高灵敏度,这使得从临床上通常可用的样本量中鉴定可操作的新表位成为可能。
期刊介绍:
The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action.
The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data.
Scope:
-Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights
-Novel experimental and computational technologies
-Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes
-Pathway and network analyses of signaling that focus on the roles of post-translational modifications
-Studies of proteome dynamics and quality controls, and their roles in disease
-Studies of evolutionary processes effecting proteome dynamics, quality and regulation
-Chemical proteomics, including mechanisms of drug action
-Proteomics of the immune system and antigen presentation/recognition
-Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease
-Clinical and translational studies of human diseases
-Metabolomics to understand functional connections between genes, proteins and phenotypes