Temporal single-cell tracing reveals clonal revival and expansion of precursor exhausted T cells during anti-PD-1 therapy in lung cancer

簡介

腫瘤浸潤T細(xì)胞既包含能夠識別腫瘤抗原并殺傷癌細(xì)胞的腫瘤特異性T細(xì)胞伟件，也包含專門識別非腫瘤抗原例如流感病毒的T細(xì)胞纳猪，而且在腫瘤中非腫瘤特異性T細(xì)胞占了很大一部分比例[1]享钞。因此在分析過程中如何排除非腫瘤特異性T細(xì)胞的潛在影響找岖，精準(zhǔn)地研究腫瘤特異性T細(xì)胞的動態(tài)變化是一個挑戰(zhàn)。之前的多個研究表明，由于腫瘤抗原的持續(xù)刺激，腫瘤中的腫瘤特異性CD8 T細(xì)胞克隆會同時高表達(dá)T細(xì)胞殺傷和“耗竭”相關(guān)基因，而非腫瘤特異性CD8 T細(xì)胞則不會表達(dá)“耗竭”相關(guān)基因[2-4]婚惫。因此在腫瘤中，耗竭CD8 T細(xì)胞可以當(dāng)作腫瘤特異T細(xì)胞的一個替代[5]

研究人員開發(fā)了一套新的分析思路魂爪，首先通過聚類分析鑒定了耗竭CD8 T細(xì)胞類群先舷，進(jìn)而以耗竭CD8 T細(xì)胞克隆的TCR序列為基礎(chǔ)，將所有的CD8 T細(xì)胞分為腫瘤特異性CD8 T細(xì)胞和非腫瘤特異性CD8 T細(xì)胞：根據(jù)上面提到的結(jié)論和假設(shè)滓侍，與耗竭CD8 T細(xì)胞有完全相同TCR序列的細(xì)胞為腫瘤特異性T細(xì)胞蒋川，剩下的為非腫瘤特異性T細(xì)胞。研究發(fā)現(xiàn)在有響應(yīng)的腫瘤當(dāng)中撩笆，治療顯著提高了耗竭信號低的腫瘤特異T細(xì)胞前體細(xì)胞的比例捺球，表明了PD-1抗體可能阻斷了腫瘤特異T細(xì)胞向耗竭狀態(tài)的分化缸浦。相反，這一趨勢在治療前和治療后無響應(yīng)的腫瘤中并沒有觀察到氮兵。

有效治療后腫瘤特異T細(xì)胞前體細(xì)胞的增加有三種可能：1. 耗竭T細(xì)胞的逆轉(zhuǎn)裂逐；2. 腫瘤中之前存在的前體細(xì)胞的擴(kuò)增；3. 來自腫瘤外例如外周血中的T細(xì)胞的補(bǔ)充泣栈。研究者通過相關(guān)分析排除了第一種可能卜高，強(qiáng)調(diào)了后面兩種模式的重要性。耗竭T細(xì)胞的逆轉(zhuǎn)是領(lǐng)域內(nèi)長期存在的一種假設(shè)南片，但是之前的小鼠研究表明耗竭T細(xì)胞的表觀修飾和特征是穩(wěn)定的掺涛，很難改變[6]。研究者對人類腫瘤的分析進(jìn)一步支持了這一觀點铃绒。

此外鸽照，之前斯坦福大學(xué)Howard Chang研究組提出了克隆替代（clonal replacement）的概念螺捐，認(rèn)為治療后腫瘤中的腫瘤特異T細(xì)胞的克隆型都是新出現(xiàn)的[7]颠悬。而該研究發(fā)現(xiàn)，在肺癌治療的過程中定血，新的克隆和之前存在的克隆都會被招募到腫瘤中進(jìn)而發(fā)揮功能赔癌。針對這一現(xiàn)象，研究人員提出了克隆復(fù)興（clonal revival）的概念澜沟，拓展了clonal replacement的模式灾票。

方法要點

1. To remove batch effects between patients we performed the BBKNN pipeline[8] to obtain the batch-corrected space, and further used the Leiden clustering approach implemented in scanpy to identify each cell cluster.
2. Clusters of T and natural killer (NK) cells were identified by unsupervised clustering following the strategy described above, characterized by high expression of CD3D, CD3E and NKG7. A second round of unsupervised clustering was further performed to identify NK, CD4+ and CD8+ T?cells based on the expression of signature genes including CD8A, CD8B, CD4, IL7R and NKG7。（細(xì)胞注釋不是一步完成茫虽，而是several rounds)
3. scTCR-seq data processing:The TCR sequence data from 10X Genomics were processed using Cell Ranger software (v.3.1) with the manufacturer-supplied human VDJ reference genome. For each sample, the output file filtered_contig_annotations.csv, containing TCR α- and β-chain CDR3 nucleotide sequences, was used for downstream analysis. Only those assembled chains that were productive, highly confident, full length, with a valid cell barcode and an unambiguous chain type (for example, alpha) assignment were retained. If a cell had two or more qualified chains of the same type, only that chain with the highest UMI count was qualified and retained. For each patient, cells with an identical α/β-chain pair were considered as having originated from the same clonotype and were therefore identified as clonal cells.
4. Bulk TCR-seq data processing and analysis:To identify the expansion patterns of Tex clonotypes in peripheral blood, we performed bulk TCR-seq using pre- and post-treatment blood samples from P010, P013, P019 and P030.Sequences were processed and analyzed using the MiXCR method. Bulk TCR-seq clonotypes were linked to intratumoral Tex clonotypes by matching the TCR β-chain to any TCR β-chain from a clonotype in the scTCR-seq data.
5. 他們做proportion analysis的時候也不是僅僅只用了t-test刊苍，而是包括the Dirichlet-multinomial regression model, Fisher’s exact test and t-test.
6. RNA velocity: scVelo, dynamical model
7. 對人類樣本耗竭T細(xì)胞的認(rèn)定：CXCL13 has been shown to be exclusively expressed by terminal Tex cells in treatment-na?ve tumors[9-11] and its expression has now also been observed in post-treatment Texp but not in Tex-irrelevant cells。We included only high-confidence Tex clones in subsequent analysis, with two additional filters: (1) clone size at least five?cells and (2) cells from a certain clone expressing CXCL13—that is, normalized average CXCL13 expression of a certain clone >0.1. The identities of Tex cells from the remaining samples were determined by supervised cell-type classification using SciBet[12]
8. Metacell analysis[13]
9. Because our calculation of exhaustion score was based on metacells, which addresses the potential bias introduced by dropout events, we used only four well-defined exhaustion markers (HAVCR2, ENTPD1, LAYN and LAG3) to improve the accuracy of terminal Tex cell identification. Exhaustion score was defined as the sum of the expression of these four genes. In addition, proliferation score was defined as the sum of the expression of STMN1 and TUBB (top two highly expressed genes in proliferative cells).
   10.An important question here is whether the new Tex clonotypes detected by scTCR-seq were really absent before treatment or were missed in the first biopsy. Here we considered bulk TCR-seq data(PB) as ground truth.We observed that the false-positive rate of new Tex clonotypes could be reduced to 17% by filtering out those clonotypes detected in pretreatment blood濒析。如果要看T細(xì)胞亞克隆是否真的是新增的正什，很重要的一點就是和外周血bulk TCR-seq 的結(jié)果進(jìn)行比較。

文章知識要點：

1. 4-1BB (TNFRSF9), a known Treg activation marker号杏；with immunosuppressive functions (IL1R2, REL and LAYN)
2. 對CD4+ T和CD8+ T分開分析
3. CD8+ T-cell infiltration into tumors could predict survival [14,15] and response to immunotherapy[16]
4. Emerging evidence demonstrates that terminal Tex cells in tumors are specifically derived from tumor-specific Tcells, whereas Tcells responsible for acute infections do not give rise to Tex cells. Thus, a terminal Tex subset could be used as a proxy for a tumor-reactive T-cell compartment. To further support this notion, we analyzed previously reported signature genes of tumor antigen-specific T cells—ENTPD1 and ITGAE—and found that they were specifically expressed in the terminal Tex subset

5. Terminal Tex cells were characterized by high expression of exhaustion signatures, including PDCD1, CTLA4 and HAVCR2

   
   

6. 如何找到Tex precursor?常規(guī)方法：細(xì)胞聚類后找與終末耗竭T有最多相同TCR序列的細(xì)胞亞群婴氮。問題：such clusters may contain TCRs independently connected with terminal Tex and blood effector cells, implying that non-exhausted tumor-reactive T?cells and potential bystander cells may fall into the same cluster due to similar transcriptional phenotypes.所以直接基于TCR尋找Texp更為可靠

   
   
7. Co-expression of CD39 and CD103 identifies tumor-reactive CD8 T cells in human solid tumors[17]

8. 發(fā)現(xiàn)本文章中RNA velocity的圖并不是放的整合的圖，而是放的一個人的一部分細(xì)胞盾致。應(yīng)該提取目的細(xì)胞主经，在diffusion map上面embed velocity stream。這真是一種很好的方法庭惜！

   
   
   RNA velocities visualized on diffusion map of cells from the largest Tex clone from pre- and post-treatment P019 tumor biopsies, color coded by cluster.
9. Previous mouse studies have defined detailed developmental frameworks for Tex cells[18-20]罩驻。 Stem, transitory and terminal Tex cells（human):
   
10. Together, using a TCR-based selection approach, we showed that GZMK+NR4A2–, GZMK+NR4A2+, terminal and proliferative Tex cells are four transcriptionally distinct Tex populations present in human lung tumors. For clarity, GZMK+NR4A2–/+ subsets are referred to here as Texp1 (GZMK+NR4A2–) and Texp2 (GZMK+NR4A2+) cells.（輔助：SciBet（好吧，就是他們自己團(tuán)隊開發(fā)的自動注釋包）,MetaCell---Metacell-based in silico FACS
    
11. CXCL13 is upregulated only when cells are in the tumor microenvironment
12. STARTRAC,之后應(yīng)該會看到這篇文獻(xiàn)

本文章用到的方法：

1. scRNA-seq
2. scTCR-seq
3. bulk TCR-seq
4. IHC--驗證

參考文獻(xiàn)：
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