点评 | Gregoire Lauvau（爱因斯坦医学院）、周旭（哈佛大学医学院）
责编 | 兮
以免疫检查点抑制剂（Immune Checkpoint Inhibitors,ICI）和过继细胞疗法（Adoptive Cell Transfer,ACT）为代表的肿瘤免疫治疗手段颠覆了人们对于肿瘤治疗的认知，并于2018年获得诺贝尔生理医学奖。【4】通常认为，肿瘤浸润淋巴细胞（Tumor-infiltrating Lymphocytes ,TILs）中的肿瘤特异抗原(Tumor Specific Antigen,TSA)反应性T细胞（TSA-reactive T cells）的再激活和克隆扩增是ICI疗法成功的基础【5】，而TILs中同时存在TSA反应性T细胞和“旁观者”T细胞（bystander T cells）【6】。目前还没有简单可靠的细胞表面标志物来特异性地识别TSA反应性T细胞，从而精确地研究它们的表型与功能。因此，发展一种快速、直接的方法来鉴定和分离癌症病人体内的TSA反应性T细胞将有助于加深对肿瘤免疫微环境的生物学理解同时加速相关的转化研究。
2020年10月22日，美国Scripps研究所吴鹏教授实验室在Cell杂志上发表了题为“Detecting Tumor Antigen-Specific T Cells via Interaction-Dependent Fucosyl-Biotinylation”的研究论文。该研究开发了一种基于细胞-细胞相互作用的邻近标记方法，成功地将TSA反应性T细胞与旁观者T细胞在TILs中区分开来，并进一步分析了TSA反应性T细胞与旁观者T细胞在功能和转录水平的差异，分离鉴定了一种新的PD-1阳性的旁观者T细胞亚群，为TILs的基础研究提供了全新的方法，也为更加精准的TILs疗法提供了经济快速的分离手段。
在之前的TILs研究中，研究人员通过逆向免疫学的方法，结合全外显子测序，生物信息学分析，机器学习等手段预测肿瘤中的TSA，再利用对应的荧光标记的主要组织相容性复合体（MHC）的多聚体对单一抗原的特异T细胞进行染色【7】，这样的策略耗资巨大，周期长，且无法获得所有的TSA反应性T细胞。
吴鹏教授团队利用DC细胞能够吞噬、分解、呈递肿瘤抗原的特性，发展了基于活细胞的标记策略（类比多聚体染色），通过细胞间相互作用介导的邻近标记（生物素标签）来实现多数TSA反应性T细胞的“染色”，直接绕过了TSA的鉴定。该工具基于李劼博士在吴鹏课题组进行博士后研究期间的意外发现：一种细菌中的岩藻糖基转移酶（H. pylori a(1,3)Fucosyltransferase,FT）具有极强的底物兼容能力，可以快速将其供体底物（鸟苷二磷酸岩藻糖，GF）与蛋白质的偶联物作为整体快速转移至其另外一个受体底物LacNAc上【8】，而LacNAc作为一个二糖单元广泛存在于多种细胞表面。通过构建FT酶与其底物的自催化复合物（GF-FT），可以在多种原代免疫细胞上安装能够实现细胞间邻近标记的酶FT。
作者将DC细胞作为诱饵细胞（bait cell），通过与预先化学合成的GF-FT复合物孵育20分钟，即可构建出DC-FT细胞偶联物。若诱饵细胞在体系中与猎物细胞（prey cell）发生相互作用，FT即可将其生物素化的供体底物（GF-Biotin）转移至猎物细胞表面的LacNAc上，从而实现猎物细胞的标记，该方法被命名为FucoID技术（图1）。
图1. FucoID技术示意图
在完成体系验证后，作者将FucoID运用于捕捉和鉴定TILs中TSA反应性T细胞（图2）。在小鼠黑色素瘤模型（B16），三阴性乳腺癌模型（E0771）和结肠癌模型（MC38）中均捕获了相应的CD8+TSA反应性T细胞，并通过对比PD-1+Bio+亚群，PD-1+Bio-亚群或PD-1-亚群的抗原识别能力，肿瘤杀伤能力和TCR克隆多样性等确定PD-1+Bio+亚群为“真正的”CD8+ TSA反应性T细胞，而PD-1+Bio-则是一类新的CD8+旁观者T细胞（图3）。CD8+ TSA反应性T细胞在体外扩增后相比其它旁观者T细胞在活体模型中表现出更强的抗肿瘤能力。
进一步的转录组测序发现，CD8+ TSA反应性T细胞（PD-1+Bio+）和CD8+旁观者T细胞中的PD-1+Bio-亚群虽然表型相近但仍有差别，CD8+ TSA反应性T细胞的TCR克隆多样性分数低，表现出类似于激活/功能紊乱（activation/dysfunction）的表型，且显著上调了类固醇生物合成的相关基因。此外，CD8+ TSA反应性T细胞和CD8+旁观者T细胞的TCR克隆型重叠度很低，说明通过FucoID技术可以捕获绝大多数的CD8+ TSA反应性T细胞，不会出现“漏网之鱼”。
图2. FucoID在肿瘤中筛选TSA反应性T细胞的流程
最后，为了分析CD4+ TSA反应性T细胞在肿瘤免疫治疗中的调节作用，作者在Pan02小鼠胰腺导管腺癌模型中进行FucoID实验捕获CD4+ TSA反应性T细胞，发现在肿瘤微环境中存在抗原抑制性和抗原反应性CD4+ T细胞，发挥调节CD8+ T细胞的抗肿瘤免疫功能。这也说明相较于预测抗原肽的多聚体染色技术，FucoID技术能够很好地兼容I型和II型MHC分子，具有更广的应用前景。
图3. 文章整体设计思路
总结一下，本研究开发了一种称为FucoID的细胞-细胞相互作用的邻近标记方法，能够快速地将地将TSA反应性T细胞与旁观者T细胞在TILs中区分开来，进而可以深入研究其生物学特征。FucoID不需要依赖于基因操作手段，适用于原代细胞的研究，并且操作流程相对简单，周期短，具有进一步临床应用的潜力，为加速TILs疗法的发展，助力肿瘤免疫疗法的个性化治疗提供了有力工具。
据悉，美国Scripps研究所的刘子雷博士，李劼博士，陈明宽博士为本文的共同第一作者，吴鹏教授和李劼博士为文章的共同通讯作者。吴梦瑶、石玉洁等也在研究中做出了突出贡献。John Teijaro教授提供了LCMV 模型和免疫学权威建议。李劼博士在Scripps研究所吴鹏教授和诺奖得主K. Barry Sharpless教授实验室完成博士后研究，现为南京大学化学化工学院教授。据悉，吴鹏教授和李劼博士团队将基于FucoID开展一系列合作。
专家点评
Gregoire Lauvau（爱因斯坦医学院，免疫学教授）
This work from Dr. Peng Wu's laboratory represents a major advance in tumor Immunology and beyond, that is very likely to impact the field durably. Defining which antigenic peptides are recognized by T lymphocytes in tumors, but also in other pathologies (autoimmunity, infections), represents the ultimate quest, and requires systematic, cumbersome and tedious work. The clever use of a rather simple glyco-enzymatic procedure that label T cells that interact closely enough with their antigen because they recognize it, now enables to reliably isolate and study these T cells prior to even knowing which antigen they see.This method will open many new avenues of investigations to quickly characterize tumor-, pathogen- or even self-antigen-specific T cells isolated from patients.
专家点评
周旭（哈佛大学医学院、波士顿儿童医院、助理教授）
Peng Wu and colleagues are revolutionizing the field of system immunology, with their genius invention of a cell-interaction dependent labeling technique named FucoID. In their latest work, published on this latest issue of Cell, they reported a method to attach an enzymatic labeling tool to dendric cells without genetic manipulation, and subsequently used these cells as bait to identify physical interactions with tumor infiltration lymphocytes. Functional dissection of these interacting T cells revealed cellular features that distinguish antigen-specific T cells and by-stander T cells. The surprising complexity of regulatory functions among antigen-specific T cells further emphasizes the need of such targeted approach to understand tumor immunology.
Mammalian tissues consist different types of cells. Tumor, as a specialized organ, displays extreme complex composition and organization of immune cells. Recently studies begin to unveil the spatial organization of immune cells and their critical role in tumor immunotherapy. Decoding the spatial information in tumors have become the forefront for tumor immunology and system immunology research. Technologies such as spatial transcriptomics, have been developed over the past two to three years to couple single cell expression with proximity among cells. They provide exquisite spatial information at single-cell or near single-cell resolution, but are rather limited in distinguishing the functional interactions and causal encounters. Existing technology that identifies functional interactions, such as LIPSTIC developed by Gabriel Victora at Rockefeller University, requires prior knowledge about the cells of interest and genetic manipulation to introduce the specific labels. These limitations hinder its broad application in exploratory research as well as clinical settings. Identifying functional interacting patterners in an accessible way has been one of the most challenging tasks. Peng’s team, led by Zilei Liu, Jie Li, and Mingkuan Chen provides an almost perfect solution to this problem.Their methods demonstrated several significant advantages: first, no genetic manipulation is required.Introducing genetic elements into human cells, such as dendric cells or macrophages, often change their cellular functions. Most of previous approaches thus become unfeasible in clinical applications.Second, no prior knowledge is required.The enzyme used in the study induces proximity-based transfer of fucosylated biotin (Fuc-Bio) tags to the surface of interacting cell, regardless of the specific cell type. The opens an avenue to survey cell-cell interactions in an unbiased way.Third, FucoID labeling seems to correlate with the strength and duration of the interaction, providing quantitative information related to the cellular functions.Overall, this work unleashes the potential to create an interacting map in tissues. It is an enormous step forward towards the new era of tumor interactomes.
招聘信息
李劼博士于2019年初加入南京大学化学生物学学科并任南京大学化学和生物医药创新研究院PI（双聘），目前主要从事肿瘤化学免疫学前沿研究，致力于描绘肿瘤免疫微环境的细胞相互作用谱并开发新型的肿瘤免疫大分子药物，已在Cell,Nat. Chem.,Nat. Chem. Biol.等国际顶尖杂志上以第一作者或通讯作者发表多篇文章，课题组欢迎对肿瘤免疫和化学生物学感兴趣的科研人员加入（详见：年薪可达40万：南京大学化学生物学学科李劼课题组2020年招聘免疫学、分子生物学方向博士后）。
目前课题组已依托南京大学化学和生物医药创新研究院建立了流式分析、单细胞测序等平台，并与郭子建院士课题组联合招聘单细胞生物信息学方向副研究员1名，具体情况参（详见：南京大学化学化工学院郭子建院士团队公开招聘肿瘤免疫方向博士后或副研究员）。简历可直接发送至邮箱jieli@nju.edu.cn。
https://doi.org/10.1016/j.cell.2020.09.048
制版人：嘉
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