机构地区:[1]Fudan University Shanghai Cancer Center,Shanghai 200032,China [2]Bio-Med Big Data Center,CAS Key Laboratory of Computational Biology,Shanghai Institute of Nutrition and Health,Chinese Academy of Sciences,Shanghai 200031,China [3]University of Chinese Academy of Sciences,Beijing 100049,China [4]School of Life Science and Technology,ShanghaiTech University,Shanghai 201210,China [5]State Key Laboratory of Pharmaceutical Biotechnology&Model Animal Research Center of Nanjing University and MOE Key Laboratory of Model Animal for Disease Study,Nanjing University,Nanjing 210061,China [6]School of Medicine,Nanjing University,Nanjing 210093,China [7]The International Cooperation Laboratory on Signal Transduction,Eastern Hepatobiliary Surgery Hospital,Second Military Medical University,Shanghai 200438,China [8]National Center for Liver Cancer,Shanghai 200441,China [9]Institute of Metabolism and Integrative Biology,Fudan University,Shanghai 200433,China [10]State Key Laboratory of Cell Biology&Shanghai Key Laboratory of Molecular Andrology,Center for Excellence in Molecular Cell Science,Chinese Academy of Sciences,Shanghai 200031,China [11]Institute for Stem Cell and Regeneration,Chinese Academy of Sciences,Beijing 100101,China [12]Faculty of Health Sciences,University of Macao,Macao 999078,China [13]Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer(SMMU),Ministry of Education&Shanghai Key Laboratory of Hepatobiliary Tumor Biology(EHBH),Eastern Hepatobiliary Surgery Hospital,Second Military Medical University,Shanghai 200438,China
出 处:《Engineering》2023年第3期159-170,共12页工程(英文)
基 金:the National Natural Science Foundation of China(U21A20376,82102871,81988101,81903184,81790633,and 81830054);the Innovation Program of Shanghai Municipal Education Commission(2019-01-07-00-07E00065);the National Science Foundation of Shanghai(21XD1404600,21JC1406600,and 22140901000);the China Postdoctoral Science Foundation(2020M671007).
摘 要:基于肿瘤抗原的免疫治疗的应用受到验证免疫原性肽稀缺性的阻碍。本研究旨在研究环状RNA(circRNA)在肝胆肿瘤类器官中作为肿瘤抗原肽新来源的潜力。使用RNA测序(RNA-seq)和基于算法的评分工具,预测3950个翻译的肿瘤特异性环状RNA在27个类器官中产生18971个抗原肽。从抗原格局来看,11个氨基酸长度(mer)肽和人白细胞抗原(HLA)-A结合肽具有最高的免疫原性相关评分。在分析的3/5类器官中,有13个预测抗原肽通过质谱(MS)免疫肽组学被直接确认为HLA-A、HLA-B和HLA-C(HLA-ABC)结合肽。在流式细胞术和酶联免疫吸附试验(ELISA)中,由HLA-ABC分子呈递的circRNA衍生的肿瘤特异性肽刺激CD8(CD8)T细胞,显示CD107a干扰素γ(IFNγ)共表达和IFNγ分泌增加。免疫原性环状RNA衍生肽诱导的靶向类器官的细胞毒性T细胞活性在杀伤实验中得到验证。值得注意的是,来自circTBC1D15的抗原肽YGFNEILKK不仅被认为是类器官的HLA-ABC呈递肽,而且还显著降低了肿瘤类器官的存活率。本研究的发现强调了产生肿瘤抗原的一个关键亚群,这对靶向肿瘤特异性circRNA具有重要意义。The application of tumor antigen-based immunotherapy is hindered by the rarity of validated immunogenic peptides.In this study,we aimed to investigate the potential of circular RNAs(circRNAs)as a novel source of tumor antigen peptides in hepatobiliary tumor organoids.Using RNA-sequencing(RNA-seq)with an algorithm-based score tool,3950 translated tumor-specific circRNAs were predicted to generate 18971 antigen peptides in 27 organoids.In view of the antigen landscape,11 amino acid length(mer)peptides and human leukocyte antigen(HLA)-A binding peptides harbored the highest immunogenicity-related scores.In three out of five analyzed organoids,13 predicted antigen peptides were directly confirmed as HLA-A,-B,and-C(HLA-ABC)binding peptides with mass spectrometry(MS)-based immunopeptidomics.CircRNA-derived tumor-specific peptides presented by the HLA-ABC molecules stimulated cluster of differentiation 8(CD8)T cells to exhibit increased CD107a interferonγ(IFNγ)co-expressions and IFNγsecretion in flow cytometry and enzyme-linked immunosorbent assay(ELISA).Cytotoxic T cell activity targeting the organoids,induced by the immunogenic circRNA-derived peptides,was verified in a killing assay.Notably,the antigen peptide YGFNEILKK from circTBC1D15 was not only recognized as an HLA-ABC-presented peptide of the organoids but also drastically reduced the tumor organoid survival rate.Our findings highlight a crucial subset for generating tumor antigens,which has implications for targeting tumor-specific circRNAs in cancers.
关 键 词:Tumor antigen Patient-derived hepatobiliary tumor organoid Circular RNA Mass-spectrometry-based immunopeptidomics
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