Cell | 吳鵬團隊發明酶化學方法捕捉腫瘤抗原特異T細胞

編者按

鄰近化學標記技術已廣泛用於研究蛋白質相互作用及空間蛋白質組學，但在細胞相互作用領域的實際應用仍不多【1-3】。該工作在發明了一種全新的鄰近酶化學標記技術的基礎上成功展示了該類化學生物學工具在腫瘤免疫領域的重要應用，為利用鄰近標記技術研究細胞相互作用提供了全新的思路。

點評 | Gregoire Lauvau（愛因斯坦醫學院）、周旭（哈佛大學醫學院）

責編 | 兮

以免疫檢查點抑制劑（Immune Checkpoint Inhibitors, ICI）和過繼細胞療法（Adoptive Cell Transfer, ACT）為代表的腫瘤免疫治療手段顛覆了人們對於腫瘤治療的認知，並於2018年獲得諾貝爾生理醫學獎。【4】 通常認為，腫瘤浸潤淋巴細胞（Tumor-infiltrating Lymphocytes , TILs）中的腫瘤特異抗原(Tumor Specific Antigen, TSA)反應性T細胞（TSA-reactive T cells）的再激活和克隆擴增是ICI療法成功的基礎【5】，而TILs中同時存在TSA反應性T細胞和「旁觀者」T細胞（bystander T cells）【6】。目前還沒有簡單可靠的細胞表面標誌物來特異性地識別TSA反應性T細胞，從而精確地研究它們的表型與功能。因此，發展一種快速、直接的方法來鑑定和分離癌症病人體內的TSA反應性T細胞將有助於加深對腫瘤免疫微環境的生物學理解同時加速相關的轉化研究。

2020年10月22日，美國Scripps研究所吳鵬教授實驗室在Cell雜誌上發表了題為「Detecting Tumor Antigen-Specific T Cells via Interaction-Dependent Fucosyl-Biotinylation」 的研究論文。該研究開發了一種基於細胞-細胞相互作用的鄰近標記方法，成功地將TSA反應性T細胞與旁觀者T細胞在TILs中區分開來，並進一步分析了TSA反應性T細胞與旁觀者T細胞在功能和轉錄水平的差異，分離鑑定了一種新的PD-1陽性的旁觀者T細胞亞群，為TILs的基礎研究提供了全新的方法，也為更加精準的TILs療法提供了經濟快速的分離手段。

在之前的TILs研究中，研究人員通過逆向免疫學的方法，結合全外顯子測序，生物信息學分析，機器學習等手段預測腫瘤中的TSA，再利用對應的螢光標記的主要組織相容性複合體（MHC）的多聚體對單一抗原的特異T細胞進行染色【7】，這樣的策略耗資巨大，周期長，且無法獲得所有的TSA反應性T細胞。

吳鵬教授團隊利用DC細胞能夠吞噬、分解、呈遞腫瘤抗原的特性，發展了基於活細胞的標記策略（類比多聚體染色），通過細胞間相互作用介導的鄰近標記（生物素標籤）來實現多數TSA反應性T細胞的「染色」，直接繞過了TSA的鑑定。該工具基於李劼博士在吳鵬課題組進行博士後研究期間的意外發現：一種細菌中的巖藻糖基轉移酶（H. pylori a(1,3)Fucosyltransferase,FT）具有極強的底物兼容能力，可以快速將其供體底物（鳥苷二磷酸巖藻糖，GF）與蛋白質的偶聯物作為整體快速轉移至其另外一個受體底物LacNAc上【8】，而LacNAc作為一個二糖單元廣泛存在於多種細胞表面。通過構建FT酶與其底物的自催化複合物（GF-FT），可以在多種原代免疫細胞上安裝能夠實現細胞間鄰近標記的酶FT。

作者將DC細胞作為誘餌細胞（bait cell），通過與預先化學合成的GF-FT複合物孵育20分鐘，即可構建出DC-FT細胞偶聯物。若誘餌細胞在體系中與獵物細胞（prey cell）發生相互作用，FT即可將其生物素化的供體底物（GF-Biotin）轉移至獵物細胞表面的LacNAc上，從而實現獵物細胞的標記，該方法被命名為FucoID技術（圖1）。

圖1. FucoID技術示意圖

在完成體系驗證後，作者將FucoID運用於捕捉和鑑定TILs中TSA反應性T細胞（圖2）。在小鼠黑色素瘤模型（B16），三陰性乳腺癌模型（E0771）和結腸癌模型（MC38）中均捕獲了相應的CD8+TSA反應性T細胞，並通過對比PD-1+Bio+亞群，PD-1+Bio-亞群或PD-1-亞群的抗原識別能力，腫瘤殺傷能力和TCR克隆多樣性等確定PD-1+Bio+亞群為「真正的」CD8+ TSA反應性T細胞，而PD-1+Bio-則是一類新的CD8+旁觀者T細胞（圖3）。CD8+ TSA反應性T細胞在體外擴增後相比其它旁觀者T細胞在活體模型中表現出更強的抗腫瘤能力。

進一步的轉錄組測序發現，CD8+ TSA反應性T細胞（PD-1+Bio+）和CD8+旁觀者T細胞中的PD-1+Bio-亞群雖然表型相近但仍有差別，CD8+TSA反應性T細胞的TCR克隆多樣性分數低，表現出類似於激活/功能紊亂（activation/dysfunction）的表型，且顯著上調了類固醇生物合成的相關基因。此外，CD8+ TSA反應性T細胞和CD8+旁觀者T細胞的TCR克隆型重疊度很低，說明通過FucoID技術可以捕獲絕大多數的CD8+ TSA反應性T細胞，不會出現「漏網之魚」。

圖2. FucoID在腫瘤中篩選TSA反應性T細胞的流程

最後，為了分析CD4+ TSA反應性T細胞在腫瘤免疫治療中的調節作用，作者在Pan02小鼠胰腺導管腺癌模型中進行FucoID實驗捕獲CD4+ TSA反應性T細胞，發現在腫瘤微環境中存在抗原抑制性和抗原反應性CD4+ T細胞，發揮調節CD8+ T細胞的抗腫瘤免疫功能。這也說明相較於預測抗原肽的多聚體染色技術，FucoID技術能夠很好地兼容I型和II型MHC分子，具有更廣的應用前景。

圖3. 文章整體設計思路

總結一下，本研究開發了一種稱為FucoID的細胞-細胞相互作用的鄰近標記方法，能夠快速地將地將TSA反應性T細胞與旁觀者T細胞在TILs中區分開來，進而可以深入研究其生物學特徵。FucoID不需要依賴於基因操作手段，適用於原代細胞的研究，並且操作流程相對簡單，周期短，具有進一步臨床應用的潛力，為加速TILs療法的發展，助力腫瘤免疫療法的個性化治療提供了有力工具。

據悉，美國Scripps研究所的劉子雷博士，李劼博士，陳明寬博士為本文的共同第一作者，吳鵬教授和李劼博士為文章的共同通訊作者。吳夢瑤、石玉潔等也在研究中做出了突出貢獻。John Teijaro教授提供了LCMV 模型和免疫學權威建議。李劼博士在Scripps研究所吳鵬教授和諾獎得主K. Barry Sharpless教授實驗室完成博士後研究，現為南京大學化學化工學院教授。據悉，吳鵬教授和李劼博士團隊將基於FucoID開展一系列合作。

專家點評

Gregoire Lauvau（愛因斯坦醫學院，免疫學教授）

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.

專家點評

周旭（哈佛大學醫學院、波士頓兒童醫院、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

李劼博士於2019年初加入南京大學化學生物學學科並任南京大學化學和生物醫藥創新研究院PI（雙聘），目前主要從事腫瘤化學免疫學前沿研究，致力於描繪腫瘤免疫微環境的細胞相互作用譜並開發新型的腫瘤免疫大分子藥物，已在Cell, Nat. Chem., Nat. Chem. Biol.等國際頂尖雜誌上以第一作者或通訊作者發表多篇文章，課題組歡迎對腫瘤免疫和化學生物學感興趣的科研人員加入（詳見：年薪可達40萬：南京大學化學生物學學科李劼課題組2020年招聘免疫學、分子生物學方向博士後）。

目前課題組已依託南京大學化學和生物醫藥創新研究院建立了流式分析、單細胞測序等平臺，並與郭子建院士課題組聯合招聘單細胞生物信息學方向副研究員1名，具體情況參（詳見：南京大學化學化工學院郭子建院士團隊公開招聘腫瘤免疫方向博士後或副研究員）。簡歷可直接發送至郵箱[e-mail]。

原文連結：

https://doi.org/10.1016/j.cell.2020.09.048

製版人：sc

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