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2024_06_01_fee39e36fafdf56e38abg

TargetingJMJD1C to selectively disrupt tumor cell fitness enhances antitumor immunity
以JMJD1C为靶点选择性地破坏肿瘤 ,增强抗肿瘤免疫力

Received: 9 March 2023
收到:2023 年 3 月 9 日
Accepted: 9 January 2024
接受:2024 年 1 月 9 日
Published online: 14 February 2024
在线出版:2024 年 2 月 14 日
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Abstract 摘要

Xuehui Long , Sulin Zhang (1) , Yuliang Wang , Jingjing Chen (D , Yanlai Lu , Hui Hou , Bichun Lin , Xutong Li( , Chang Shen , Ruirui Yang , Huamin Zhu1, Rongrong Cui , Duanhua , Geng Chen , Dan Wang , Yun Chen , Sulan Zhai , Zhiqin Zeng , Shusheng Wu , Mengting Lou , Junhong Chen , Jian Zou , Mingyue Zheng (1) , Jun Qin Xiaoming Wang
龙学辉 , 张素林(1) , 王玉良 , 陈晶晶(D , 卢燕来 , 侯慧 , 林碧春 , 李旭彤( , 沈畅 , 杨瑞瑞 , 朱华敏1, 崔蓉蓉 、段华 , 陈庚 , 王丹 , 陈云 , 翟素兰 , 曾志勤 , 吴树生 , 楼梦婷 , 陈俊红 , 邹健 , 郑明月 (1) , 秦俊 王晓明

Regulatory ) cells are critical for immune tolerance but also form a barrier to antitumor immunity. As therapeutic strategies involving cell depletion are limited by concurrent autoimmune disorders, identification of intratumoral cell-specific regulatory mechanisms is needed for selective targeting. Epigenetic modulators can be targeted with small compounds, but intratumoral cell-specific epigenetic regulators have been unexplored. Here, we show that JMJD1C, a histone demethylase upregulated by cytokines in the tumor microenvironment, is essential for tumor cell fitness but dispensable for systemic immune homeostasis. JMJD1C deletion enhanced AKT signals in a manner dependent on histone H3 lysine 9 dimethylation (H3K9me2) demethylase and STAT3 signals independently of demethylase, leading to robust interferon production and tumor cell fragility. We have also developed an oral JMJD1C inhibitor that suppresses tumor growth by targeting intratumoral cells. Overall, this study identifies JMJD1C as an epigenetic hub that can integrate signals to establish tumor cell fitness, and we present a specific JMJD1C inhibitor that can target tumor cells without affecting systemic immune homeostasis.
调节性 ) 细胞对免疫耐受至关重要,但也是抗肿瘤免疫的屏障。由于 细胞耗竭的治疗策略受到并发自身免疫性疾病的限制,因此需要确定瘤内 细胞特异性的调控机制,以进行选择性靶向治疗。表观遗传调节剂可通过小分子化合物进行靶向治疗,但瘤内 细胞特异性表观遗传调节剂尚未得到研究。在这里,我们发现JMJD1C是一种由肿瘤微环境中的细胞因子上调的组蛋白去甲基化酶,它对肿瘤 细胞的健康至关重要,但对全身免疫稳态却无足轻重。JMJD1C缺失以依赖组蛋白H3赖氨酸9二甲基化(H3K9me2)去甲基化酶和STAT3信号的方式增强了AKT信号,而不依赖于 去甲基化酶,从而导致干扰素 ,并使肿瘤 细胞变得脆弱。我们还开发了一种口服JMJD1C抑制剂,通过靶向瘤内 细胞抑制肿瘤生长。总之,这项研究发现JMJD1C是一个表观遗传中枢,它可以整合信号以建立肿瘤 细胞的适应性,我们还提出了一种特异性JMJD1C抑制剂,它可以靶向肿瘤 细胞而不影响全身免疫平衡。

Foxp cells are essential for maintaining immune tolerance and preventing autoimmune diseases; they also infiltrate tumor tissues and suppress antitumor immunity . Targeting cells could improve the immune-suppressive tumor microenvironment (TME) and elicit effective antitumor immunity . However, systemic depletion of cells disturbs immune homeostasis and can lead to autoimmune complications . Therefore, it is important to identify regulatory molecules that can be used to selectively target intratumoral cells without affecting systemic or peripheral cells. In this regard, several molecules or pathways have been shown to be specific to intratumoral cells. For examples, lipid metabolism is particularly important for cell maintenance and function in tumors but not under inflammatory settings . NRP1, PD1 and IL-33 signals suppress interferon (IFN ) expression to prevent cell fragility in tumors . Targeting chemokine receptor CCR8 has been shown to specifically remove clonally expanded cells in tumors . The TME creates a specialized niche that is distinct from steady or inflammatory settings. Further investigation is required to determine whether cells acquire new features to enable 'fitness' and maintain the capability to survive, expand and function properly following infiltration into the TME.
Foxp 细胞对维持免疫耐受和预防自身免疫性疾病至关重要;它们也会浸润肿瘤组织并抑制抗肿瘤免疫 。以 细胞为靶点可以改善免疫抑制性肿瘤微环境(TME),激发有效的抗肿瘤免疫 。然而,系统性消耗 细胞会扰乱免疫稳态,并可能导致自身免疫并发症 。因此,确定可用于选择性靶向瘤内 细胞而不影响全身或外周 细胞的调控分子非常重要。在这方面,有几种分子或途径已被证明对瘤内 细胞具有特异性。例如,脂质代谢对 细胞在肿瘤中的维持和功能尤为重要,但在炎症环境下则不然 。NRP1、PD1和IL-33信号可抑制干扰素 (IFN )的表达,从而防止肿瘤 细胞的脆弱性 。靶向趋化因子受体 CCR8 可特异性清除肿瘤中克隆扩增的 细胞 。TME创造了一种有别于稳定或炎症环境的特化生态位。还需要进一步研究,以确定 细胞是否获得了新的特征,使其能够 "适应 "并在渗入 TME 后保持生存、扩增和正常功能的能力。
Epigenetic regulation has proven to be essential for cellular differentiation and function, including for cells . Appropriate DNA methylation at CNS2 loci is critical for Foxp3 expression and cell identity . MLL4 regulates Foxp3 induction via chromatin looping . Ezh2 has been reported to be required for maintenance of cell identity during cellular activation . However, it is unclear whether there are epigenetic regulatory mechanisms that are important for intratumoral cells but not for peripheral cells. Given that epigenetic regulators-especially enzymes, including writers and erasers-can be feasibly targeted with small compounds, it is important to identify tumor cell-specific epigenetic regulators.
表观遗传调控已被证明对细胞分化和功能至关重要,包括对 细胞 。CNS2 基因座上适当的 DNA 甲基化对 Foxp3 的表达和 细胞特性至关重要 。MLL4 通过染色质循环调节 Foxp3 的诱导 。据报道,在细胞活化过程中,Ezh2 是维持 细胞特性所必需的 。然而,目前尚不清楚是否存在对瘤内 细胞重要而对外周 细胞不重要的表观遗传调控机制。鉴于表观遗传调控因子--尤其是酶,包括写入器和擦除器--可以用小化合物作为靶标,因此确定肿瘤 细胞特异性表观遗传调控因子非常重要。

Results 成果

Upregulation of JMJD1C in tumor cells
肿瘤 细胞中 JMJD1C 的上调

We compared the chromatin accessibility of tumor cells with that of their counterparts in peripheral lymphoid organs by assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and observed a substantial difference between these two cell populations (Fig. 1a). The observed disparities in chromatin accessibility prompted us to investigate whether the two cell populations had distinct epigenetic regulatory mechanisms. We therefore re-analyzed published transcriptome data comparing tumor and splenic cells. Focusing on the genes encoding epigenetic enzymes , we found that Jmjd1c, the gene encoding H3K9me2 demethylase, was the most significantly upregulated gene in tumor cells (Fig. 1b). Increased expression of Jmjd1c in tumor cells compared with their peripheral counterparts was also observed in multiple human cancer types including colorectal cancer (CRC), hepatocellular carcinoma (HCC) and nonsmall-cell lung cancer (NSCLC) (Fig.1c). By contrast, the expression of Jmjd1c in tumor conventional CD4 T cells compared with peripheral blood mononuclear cell (PBMC) CD4 T cells was not consistently upregulated across different tumor types. Specifically, whereas Jmjd1c was upregulated in tumor-infiltrating CD4 T cells in CRC, its expression remained unchanged in HCC and NSCLC (Fig. 1c). cells from HCC patients were further analyzed to track the dynamic profile of Jmjd1c. Unsupervised -distributed stochastic neighbor
我们通过高通量测序(ATAC-seq)检测转座酶可及染色质,比较了肿瘤 细胞与外周淋巴器官中相应细胞的染色质可及性,并观察到这两种 细胞群之间存在巨大差异(图 1a)。观察到的染色质可及性差异促使我们研究这两个 细胞群是否具有不同的表观遗传调控机制。因此,我们重新分析了已发表的转录组数据 ,比较了肿瘤细胞和脾 。以编码表观遗传酶的基因 为重点,我们发现编码 H3K9me2 去甲基化酶的基因 Jmjd1c 是肿瘤 细胞中最显著上调的基因(图 1b)。在包括结肠直肠癌(CRC)、肝细胞癌(HCC)和非小细胞肺癌(NSCLC)在内的多种人类癌症 ,也观察到肿瘤 细胞中Jmjd1c的表达量较其外周对应基因有所增加(图1c)。相比之下,与外周血单核细胞(PBMC)CD4 T细胞相比,Jmjd1c在肿瘤常规CD4 T细胞中的表达在不同肿瘤类型中并没有一致的上调。 ,以追踪 Jmjd1c 的动态变化。无监督 -分布式随机邻接法

Fig. 1|Expression of Jmjd1c is upregulated in tumor cells by a combination
图 1|Jmjd1c在肿瘤 细胞中的表达上调

of cytokines. a, Heatmap of ATAC-seq peaks with splenic and tumor cells from B16-OVA tumor. , Comparison of mRNA expression of genes encoding epigenetic enzymes (from the dbEM database) between splenic and tumor cells (GSE139325).c, Box plot showing Jmjd1c expression in cells and cells from scRNA-seq(GSE108989, GSE98638 and GSE99254). Center line shows median, box limits indicate first and third quartiles, and whiskers extend to the smallest and largest data values. as indicated within the image. -SNE visualization of cell clusters from HCC patients (GSE98638, left);right:Jmjd1c expression projected onto the clusters. e,f, Dot plot showing Jmjd1c expression in seven separate clusters (e) or three combined clusters (f).g, Monocle-based pseudotimes were derived for the three cell populations. , Western blotting analysis of JMJD1C expression in splenic naive cells, effector cells and tumor cells from MCA205-tumorbearing Foxp3-YFP mice. , Splenic cells or cells were cultured with B16 tumor supernatant (i), MCA205 tumor supernatant (j) left) or MCA205 cell culture medium (j, right) for 3 days.JMJD1C levels were then detected by western blotting. embedding ( -SNE) analysis identified a total of seven clusters (one for peripheral cells and six for tumor cells), among which (representing cells) expressed very low levels of Jmjd1c (Jmjd1c cells); c1, c2, c5 and c6 tumor cells expressed medium levels; and c3 and c4 tumor cells expressed high levels (Fig.1d,e). We therefore combined c1, c2, c5 and c6 to be defined as Jmjd1c tumor cells, and and asJmjd1 tumor cells (Fig. 1f), and analyzed their developmental trajectories. As shown in Fig. 1g and Extended Data Fig. 1, a trajectory from PMBC cells (Jmjd1c cells) to Jmjd1c tumor cells and then to Jmjd1c tumor cells emerged along the pseudotime, indicating a gradual transition from PMBC cells to Jmjd1c tumor cells. This suggests thatJmjd1c expression increases over the course of cells fitting into the TME.
Furthermore, immunoblotting confirmed that at the protein level, JMJD1C was more abundant in tumor cells than in splenic cells obtained from MCA205-tumor-bearing mice (Fig. ). Consistent with previous studies, we observed tumor cells to also express higher levels of Foxp3 compared with splenic cells (Fig. 1h). We next directly tested whetherJMJD1C expression in cells could be induced by exposure to the TME. Treating splenic cells in vitro with supernatant from B16 melanoma tumor tissue for 3 days indeed increased JMJD1C expression (Fig. 1i). However, tumor supernatant could not induce JMJD1C expression in conventional CD4 T cells (Fig. 1i), indicating a cell-type-specific regulation of JMJD1C. Similar induction of JMJD1C was observed in cells treated with supernatant from MCA205 fibrosarcoma tumor (Fig. 1j).
此外,免疫印迹证实,在蛋白质水平上,肿瘤 细胞中的 JMJD1C 比 MCA205 肿瘤小鼠脾脏 细胞中的含量更高(图 )。与之前的研究一致,我们观察到肿瘤 细胞也比脾脏 细胞表达更高水平的 Foxp3 (图 1h)。接下来,我们直接检测了 细胞中的 JMJD1C 表达是否会因暴露于 TME 而被诱导。用 B16 黑色素瘤肿瘤组织的上清液体外处理脾脏 细胞 3 天确实会增加 JMJD1C 的表达(图 1i)。然而,肿瘤上清不能诱导常规CD4 T细胞中JMJD1C的表达(图1i),这表明JMJD1C受细胞类型特异性调控。在用 MCA205 纤维肉瘤肿瘤上清液处理的 细胞中也观察到了类似的 JMJD1C 诱导(图 1j)。
Notably, when we treated splenic cells with culture media of MCA205 tumor cells, noJMJD1C induction was observed (Fig.1j), suggesting that factors present in the in vivo TME, rather than products directly generated by tumor cells, are responsible for JMJD1C induction. To further investigate this, we analyzed the signaling pathways specifically enriched in tumor cells compared with cells, using single-cell RNA sequencing (scRNA-seq) data from patients with tumors. Applying gene set enrichment analysis (GSEA), we identified the top 30 enriched signaling pathways in tumor cells from each type of tumor (CRC, HCC and NSCLC). These pathways included well-known TME-associated signals such as hypoxia, along with several HALLMARK and REACTOME pathways (Fig. 1k). Integrative analysis of these 90 enriched pathways revealed 12 pathways shared by all three tumor types, one of which was hypoxia (Fig.1k).JMJD1C induction by tumor supernatant occurred even under regular normoxic culture conditions (Fig. 1i,j), indicating that hypoxia signaling is not required for JMJD1C expression in tumor cells.
值得注意的是,当我们用MCA205肿瘤细胞的培养基处理脾脏 细胞时,没有观察到JMJD1C诱导(图1j),这表明体内TME中存在的因素而不是肿瘤细胞直接产生的产物是JMJD1C诱导的原因。为了进一步研究这一点,我们利用肿瘤患者的单细胞 RNA 测序(scRNA-seq)数据分析了肿瘤 细胞与 细胞相比特异性富集的信号通路。通过基因组富集分析(GSEA),我们确定了每种类型肿瘤(CRC、HCC 和 NSCLC)的肿瘤 细胞中富集的前 30 条信号通路。这些通路包括众所周知的TME相关信号,如缺氧,以及一些HALLMARK和REACTOME通路(图1k)。对这90条富集通路的整合分析显示,所有三种肿瘤类型共有12条通路,其中之一是缺氧(图1k)。即使在常规常氧培养条件下,肿瘤上清液也会诱导JMJD1C(图1i,j),这表明缺氧信号传导并非肿瘤
Among the 12 overlapping pathways, multiple inflammatory cytokine-related signaling pathways were notable, including the HALLMARK inflammatory response and REACTOME cytokine signaling in the immune system (Fig. ). Specific cytokine signals including IFN , TNF, IL-1 and IL-6-STAT3, which are commonly found in the TME, were
在 12 条重叠的通路中,与炎症细胞因子相关的多条信号通路引人注目,包括 HALLMARK 炎症反应和免疫系统中的 REACTOME 细胞因子信号(图 )。特定的细胞因子信号包括 IFN 、TNF、IL-1 和 IL-6-STAT3,这些信号通常存在于 TME 中。
, Venn diagram showing overlap of enriched pathways in tumor cells versus cells in three types of tumors (top 30 pathways for each). , Splenic cells were treated with individual ( or combined ( ) cytokines as indicated ( ) for 3 days, and JMJD1C levels were analyzed by western blotting. , Splenic cells were treated with MCA205 tumor supernatant or supernatant plus blocking antibody cocktails of anti-TNF + anti-IL-1 anti-IL-6 . o, IgV snapshot of ATAC-seq at Jmjd1c gene locus. F1 and F2 are the fragments for chromatin immunoprecipitation with quantitative PCR (ChIP-qPCR) analysis. p, Luciferase reporter assays showing that STAT3 and NF- KB regulate Jmjd1c promoter activity. , Splenic cells were treated with IL-1 plus IL-6 for 3 days and subjected to ChIP-qPCR analysis with STAT3 and NF-кB antibodies; independent experiments in and ; bar graph shows mean values. Data represent two (h, and ) or three (i i and ) independent experiments. Two-sided Wald test without adjustment in Deseq2(b); two-tailed Wilcoxon rank-sum test without adjustment (c).PC, peak center;Ctrl., control;EV, empty vector;sup., supernatant; TSS, transcriptional start site; unstimu., unstimulated.
, 维恩图显示了三种类型肿瘤 细胞与 细胞中富集通路的重叠情况(每种类型的前 30 条通路)。 , 用单独的 ( 或联合的 ( ) 细胞因子处理脾脏 细胞 3 天( ),并通过免疫印迹分析 JMJD1C 的水平。 用 MCA205 肿瘤上清或上清加抗肿瘤坏死因子 + 抗 IL-1 抗 IL-6 的阻断抗体鸡尾酒处理脾 细胞。 o, Jmjd1c 基因座 ATAC-seq 的 IgV 快照。F1 和 F2 是染色质免疫共沉淀与定量 PCR(ChIP-qPCR)分析的片段。 p, 荧光素酶报告实验显示 STAT3 和 NF- KB 调节 Jmjd1c 启动子的活性。 , 脾 细胞用 IL-1 加 IL-6 处理 3 天,并用 STAT3 和 NF-кB 抗体进行 ChIP-qPCR 分析; 独立实验, 和 ;条形图显示平均值。数据代表两次(h、 和 )或三次(i i 和 )独立实验。PC,峰中心;Ctrl.,对照;EV,空载体;sup.,上清液;TSS,转录起始位点;unstimu.,未刺激。

identified . However, when we treated splenic cells with these cytokines individually, we did not observe induction of JMJD1C expression (Fig. 11). We subsequently investigated whether a combination of these cytokines could induce JMJD1C. Treatment with TNF plus IL-1 resulted in a slight increase inJMJD1C expression (Fig. 1m). Moreover, when cells were treated with either TNF plus IL-6 or IL-1 plus IL-6, a dramatic upregulation of JMJD1C expression was observed, reaching a level comparable with that induced by tumor supernatant treatment (Fig. 1m). By contrast, blocking the activity of these three cytokines completely abolished the induction of JMJD1C by tumor supernatant (Fig. 1 n). Both TNF and IL-1 signaling pathways are known to activate signaling. It is plausible that TNF plus IL-1 treatment results in stronger -кB activity compared with treatment with either cytokine alone. Therefore, it appears that NF- кB signaling is responsible for initiatingJMJD1C expression, whereas IL-6-STAT3 signaling synergizes with the NF-kB pathway to further enhance and fully induce JMJD1C.
。然而,当我们用这些细胞因子单独处理脾脏 细胞时,并没有观察到 JMJD1C 的诱导表达(图 11)。我们随后研究了这些细胞因子的组合是否能诱导 JMJD1C。TNF 加 IL-1 处理后,JMJD1C 的表达略有增加(图 1m)。此外,当 细胞用 TNF 加 IL-6 或 IL-1 加 IL-6 处理时,观察到 JMJD1C 表达急剧上调,达到与肿瘤上清液处理诱导的水平相当(图 1m)。相比之下,阻断这三种细胞因子的活性可完全消除肿瘤上清液对 JMJD1C 的诱导(图 1 n)。已知 TNF 和 IL-1 信号通路都能激活 信号。与单独使用其中一种细胞因子相比,TNF 加 IL-1 处理会导致更强的 -кB 活性。因此,NF- кB信号似乎负责启动JMJD1C的表达,而IL-6-STAT3信号与NF-kB通路协同作用,进一步增强并完全诱导JMJD1C。
Previous studies have shown that STAT3 can interact with NF-кB in tumor cells to dramatically enhance NF-kB-mediated downstream gene expression, whereas STAT3 alone fails to do . We hypothesized that a similar phenomenon occurs in tumor cells. To validate this hypothesis, we examined the sequence of the Jmjd1c gene promoter near the transcriptional start site, in which region tumor a
先前的研究表明,STAT3 可与肿瘤细胞中的 NF-кB 相互作用,显著增强 NF-kB 介导的下游基因表达,而 STAT3 本身则无法做到这一点 。我们假设肿瘤 细胞中也会出现类似现象。为了验证这一假设,我们研究了Jmjd1c基因启动子靠近转录起始位点的序列,在这一区域肿瘤细胞的NF-kB介导的基因表达与STAT3无关。
d
b
e
h

Hypoxia Inflammatory response Cytokine signaling IFNy signal response TNF signal via NF- IL6-STAT3 signaling IL1 signaling
缺氧 炎症反应 细胞因子信号转导 IFNy 信号转导 TNF 信号通过 NF- IL6-STAT3 信号转导 IL1 信号转导
Top 30 in each tumor
每个肿瘤的前 30 名
O
j
Luciferase signal 荧光素酶信号

cells exhibited stronger ATAC-seq signals than splenic cells, and identified four canonical NF-кB binding sites (N1-N4) (Fig. 1o). In accordance with our hypothesis, a luciferase assay showed that NF-кB rather than STAT3CA (constitutive active form) transduction could slightly increase JMJD1C expression (Fig. 1p). Moreover, when both STAT3CA and NF-кB were present, there was a dramatic boost inJMJD1C expression (Fig. 1p). Mutation analysis revealed that and were necessary for JMJD1C induction (Fig. 1p). Near the N3 and N4 sites, we identified two canonical STAT3-binding sites (S1 and S2), and deletion of these two motifs abolished the boosting effect of STAT3 onJMJD1C expression (Fig.1p). This suggests that STAT3 requires its binding sites to be in proximity to the NF-кB sites to enhance JMJD1C expression. Finally, we performed chromatin immunoprecipitation with quantitative PCR analysis and found increased NF-кB and STAT3 binding to the N3-N4 and S1-S2 regions upon treatment of cells with IL-1 plus IL-6 (Fig. 1q).
细胞比脾脏 细胞表现出更强的 ATAC-seq 信号,并确定了四个典型的 NF-кB 结合位点(N1-N4)(图 1o)。与我们的假设相符的是,荧光素酶试验表明,NF-кB 而非 STAT3CA(组成型活性形式)转导可轻微增加 JMJD1C 的表达(图 1p)。此外,当 STAT3CA 和 NF-кB 同时存在时,JMJD1C 的表达也会急剧增加(图 1p)。突变分析表明 和 是诱导 JMJD1C 的必要条件(图 1p)。在 N3 和 N4 位点附近,我们发现了两个典型的 STAT3 结合位点(S1 和 S2),删除这两个基团可消除 STAT3 对 JMJD1C 表达的促进作用(图 1p)。这表明 STAT3 需要其结合位点靠近 NF-кB 位点才能增强 JMJD1C 的表达。最后,我们进行了染色质免疫共沉淀和定量 PCR 分析,发现用 IL-1 加 IL-6 处理 细胞后,N3-N4 和 S1-S2 区域的 NF-кB 和 STAT3 结合增加(图 1q)。
Overall, these findings suggest that a combination of TNF, IL-6 and IL-1 drives robustJMJD1C expression in tumor cells. Downstream of these cytokines, NF-кB initiatesJMJD1C expression in tumor cells, and STAT3 plays a key part in enhancing this expression.
总之,这些研究结果表明,TNF、IL-6 和 IL-1 在肿瘤 细胞中的联合作用可促进 JMJD1C 的强有力表达。在这些细胞因子的下游,NF-кB 在肿瘤 细胞中启动了 JMJD1C 的表达,而 STAT3 在增强这种表达中起着关键作用。

JMJD1C is essential for tumor cell fitness
JMJD1C 对肿瘤 细胞的健康至关重要

To dissect the role of JMJD1C in cells, we crossedJmjd1c floxed mice to Foxp3 and obtained cell-specificJmjd1c conditional knockout
为了剖析JMJD1C在 细胞中的作用,我们将Jmjd1c基因缺失小鼠与Foxp3 杂交,获得了 细胞特异性Jmjd1c条件性基因敲除小鼠。

Jmjd11 ).Jmjd11 Foxp or Jmjd1c Foxp mice were used as controls (Jmjd1c ).JMJD1C expression was efficiently ablated
Jmjd11 )。Jmjd11 Foxp 或 Jmjd1c Foxp 小鼠作为对照组(Jmjd1c )。JMJD1C 的表达被有效消减。

with the relatively low expression level of JMJD1C in peripheral cells, the development of cells in peripheral immune organs was unaltered byJMJD1C deletion (Extended Data Fig. 2b). Overall immune homeostasis also seemed to be intact, as assessed by both effector and
由于 JMJD1C 在外周 细胞中的表达水平相对较低,JMJD1C 基因缺失不会改变外周免疫器官 细胞的发育(扩展数据图 2b)。整体免疫稳态似乎也没有受到影响,这可以从效应细胞和免疫细胞的评估中看出。

of multiple organs from aged mice (Extended Data Fig. 2c,d). cell frequencies in peripheral organs were unaltered in aged Jmjd1 ко mice (Extended Data Fig. 2e). Moreover, when the mice were induced with experimental autoimmune encephalomyelitis (EAE), there were no alterations in disease scores, central nervous system cell frequency or T cell cytokine production (Supplementary Fig.1a-c). Thus,JMJD1C is dispensable for systemic cell development and function, under either steady or inflammatory state.
老龄 Jmjd1 ко 小鼠外周器官的 细胞频率没有变化(扩展数据图 2e)。此外,当小鼠被诱发实验性自身免疫性脑脊髓炎(EAE)时,疾病评分、中枢神经系统 细胞频率或 T 细胞细胞因子的产生均无变化(补充图 1a-c)。因此,在稳定或炎症状态下,JMJD1C 对全身 细胞的发育和功能都是不可或缺的。
Having found that JMJD1C was not required for cells to maintain systemic immune homeostasis, we next challenged Jmjd1 ко mice with multiple tumor models, including B16-OVA melanoma, MCA205 fibrosarcoma and EL4 lymphoma. JMJD1C deficiency in cells decelerated tumor growth for all these engrafted tumor cell types
在发现 细胞不需要 JMJD1C 来维持全身免疫平衡之后,我们接下来用多种肿瘤模型(包括 B16-OVA 黑色素瘤、MCA205 纤维肉瘤和 EL4 淋巴瘤)来挑战 Jmjd1 ко 小鼠。 细胞中 JMJD1C 的缺乏使所有这些移植肿瘤细胞类型的肿瘤生长速度减慢。

with B16-OVA tumors had a profound loss of cells in the tumor but not in the spleen or draining lymph nodes (Fig. 2b and Extended Data Fig. 3a). This was accompanied by increased numbers of conven-
B16-OVA 肿瘤的 细胞在肿瘤中大量丢失,但在脾脏或引流淋巴结中却没有丢失(图 2b 和扩展数据图 3a)。与此同时,脾脏和淋巴结中的召集细胞数量增加。

Similar phenotypes were observed with MCA205-tumor-bearing mice (Fig. 2d,e). Moreover, these tumor conventional T cells produced more abundant effector-function-related cytokines, whereas cytokine production by draining lymph node T cells was not altered (Fig. 2f). Further characterization showed thatJMJD1C-deleted tumor cells displayed defective proliferation and survival, as revealed by Ki67 and active caspase 3 staining (Extended Data Fig. 3b,c). We then sorted out the cells for an in vitro suppression assay. Compared with wild-type (WT) cells, JMJD1C-deficient tumor cells had a dramatically reduced capability to inhibit T cell proliferation (Extended Data Fig. 3d), suggesting a compromised immunosuppressive function. By contrast, the suppressive function of splenic cells was not altered (Extended Data Fig. 3e). Taken together, these results indicate that JMJD1C is selectively required for cell fitness in tumors and that deficiency of
在携带 MCA205 肿瘤的小鼠身上也观察到了类似的表型(图 2d、e)。此外,这些肿瘤常规 T 细胞产生了更多的效应功能相关细胞因子,而引流淋巴结 T 细胞产生的细胞因子没有改变(图 2f)。进一步的特性分析表明,Ki67 和活性 caspase 3 染色显示,JMJD1C 缺失的肿瘤 细胞显示出增殖和存活缺陷(扩展数据图 3b、c)。然后,我们筛选出 细胞进行体外抑制试验。与野生型(WT) 细胞相比,JMJD1C缺陷的肿瘤 细胞抑制T细胞增殖的能力大大降低(扩展数据图3d),表明其免疫抑制功能受到了影响。相比之下,脾脏 细胞的抑制功能没有改变(扩展数据图 3e)。综上所述,这些结果表明,JMJD1C 是 细胞在肿瘤中适应性的选择性需要,缺乏 JMJD1C 会导致肿瘤细胞的免疫抑制功能受损。

JMJD1C in cells retards tumor growth without discernible adverse inflammatory or autoimmune effects.
细胞中的 JMJD1C 可延缓肿瘤生长,而不会产生明显的不良炎症或自身免疫效应。
To further determine the specific importance of JMJD1C to tumor cells, we also crossed mice to , thereby deleting JMJD1C in total T cells (Jmjd1c ). The development of cells and cells was unaffected (Supplementary Fig. 2a,b). T cell immune homeostasis, as assessed by CD44 and CD62L staining, also remained intact (Supplementary Fig. 2c). Notably, when the mice were subjected to
为了进一步确定 JMJD1C 对肿瘤 细胞的特殊重要性,我们还将 小鼠与 杂交,从而在全部 T 细胞中缺失 JMJD1C(Jmjd1c )。 细胞和 细胞的发育未受影响(补充图 2a,b)。通过 CD44 和 CD62L 染色评估的 T 细胞免疫平衡也保持不变(补充图 2c)。值得注意的是,当小鼠受到

compared with WT mice (Supplementary Fig. 2d), and tumor cells were significantly reduced in number (Supplementary Fig. 2e). Accordingly, conventional cell numbers in tumor tissues were increased, along with upregulated cytokine production (Supplementary Fig. 2f,g), suggesting thatJMJD1C is dispensable for conventional T cell function. Furthermore, tumor cells from Jmjd1c mice exhibited reduced cell proliferation and survival, whereas conventional T cells were unaffected (Supplementary Fig. 2h). Thus, these data further confirm that JMJD1C selectively maintains tumor cells.
与 WT 小鼠相比(补充图 2d),肿瘤 细胞的数量显著减少(补充图 2e)。相应地,肿瘤组织中的传统 细胞数量增加,细胞因子的产生也上调(补充图 2f,g),这表明 JMJD1C 对传统 T 细胞的功能是不可或缺的。此外,来自 Jmjd1c 小鼠的肿瘤 细胞表现出细胞增殖和存活率降低,而常规 T 细胞不受影响(补充图 2h)。因此,这些数据进一步证实了 JMJD1C 可选择性地维持肿瘤 细胞。

JMJD1C suppresses AKT in tumor cells
JMJD1C 抑制肿瘤 细胞中的 AKT

We then sought to determine the molecular basis of the regulation of fitness by JMJD1C in tumors. Tumor cells fromJmjd1c and Jmjd1 mice were sorted out for scRNA-seq analysis. More than three mice per group were pooled to minimize the sample variation. Using -SNE for visualization and clustering, based on previous studies , a total of four cellular clusters were identified (TNFRSF9 , and TNFRSF9 ). The cluster proportions were comparable betweenJmjd1c WT and KO cells (Extended Data Fig. 4a,b), suggesting that upregulation of JMJD1C in tumor cells is not required for the cell differentiation and transition program. Flow cytometry analysis further confirmed that the frequency of the 4-1BB (encoded by Tnfrsf9) cell subpopulation was unaltered by JMJD1C ablation (Extended Data Fig. 4c). We then focused on gene expression and pathway alterations inJmjd1c cells. Consistent with the classical function of JMJD1C as a H3K9me2 demethylase, the overall H3K9me2 level in JMJD1C-deleted tumor cells was increased (Extended Data Fig. 4d), suggesting that loss of JMJD1C probably decreased expression of its target genes. Indeed, 230 downregulated differentially expressed genes were identified in Jmjd1c KO tumor cells (Extended Data Fig. 4e). According to GSEA, fatty acid metabolism was the most downregulated hallmarkgene set inJmjd1c KO tumor cells (Extended Data Fig. 4f). Fatty acid synthesis has been reported to be required for functional maturation of tumor cells , consistent with our observation that the suppressive function of KO cells was impaired (Extended Data Fig. 3d). However, it has also been reported that disruption of fatty acid synthesis by Fasn does not alter cell frequency in tumor , whereas the frequency of tumor cells in the absence of JMJD1C was significantly reduced (Fig. 2b,d), suggesting that JMJD1C could regulate tumor cells by additional mechanisms beyond fatty acid metabolism.
然后,我们试图确定 JMJD1C 在肿瘤中调控 适宜性的分子基础。我们对Jmjd1c 和Jmjd1 小鼠的肿瘤 细胞进行了分类,以进行 scRNA-seq 分析。每组有三只以上的小鼠被集中在一起,以尽量减少样本差异。根据先前的研究 ,使用 -SNE 进行可视化和聚类,共确定了四个细胞群(TNFRSF9 和 TNFRSF9 )。Jmjd1c WT 和 KO 细胞的细胞簇比例相当(扩展数据图 4a,b),表明肿瘤 细胞中 JMJD1C 的上调并非细胞分化和转化程序所必需。流式细胞术分析进一步证实,4-1BB(由Tnfrsf9编码) 细胞亚群的频率不会因JMJD1C消减而改变(扩展数据图4c)。然后,我们重点研究了Jmjd1c 细胞中基因表达和通路的改变。与JMJD1C作为H3K9me2去甲基化酶的经典功能相一致,在JMJD1C缺失的肿瘤 细胞中,整体H3K9me2水平升高(扩展数据图4d),这表明JMJD1C的缺失可能会降低其靶基因的表达。事实上,在 Jmjd1c KO 的肿瘤 细胞中发现了 230 个下调的差异表达基因(扩展数据图 4e)。根据GSEA,脂肪酸代谢是Jmjd1c KO肿瘤 细胞中下调最多的标志基因集(扩展数据图4f)。据报道,脂肪酸合成是肿瘤 细胞 功能成熟所必需的,这与我们观察到的 KO 细胞的抑制功能受损是一致的(扩展数据图 3d)。 然而,也有报道称,Fasn 破坏脂肪酸合成并不会改变肿瘤 ,而在JMJD1C缺失的情况下,肿瘤 细胞的频率显著降低(图2b,d),这表明JMJD1C可以通过脂肪酸代谢以外的机制调节肿瘤 细胞。
Surface molecules have essential roles in cell maintenance and function. Pdcd1 and Nrp1 were among the most strongly downregulated genes encoding surface molecules (Fig. 3a). Flow cytometry confirmed that the expression of PD1 and NRP1 at a protein level was significantly reduced byJMJD1C deficiency in tumor cells (Fig. 3b,c). Importantly, the expression of these two genes was not altered at all in splenic cells (Fig. 3b,c). NRP1 deficiency has been reported to impair tumor cell survival and proliferation , consistent with our observations in Jmjd1c KO tumor cells (Extended Data Fig. 3b,c). To determine whether and were potentially directly regulated by JMJD1C-mediated H3K9me2, CUT&RUN-seq (cleavage under targets and release using nuclease sequencing) was performed with tumor cells from MCA205-tumor-bearing Jmjd1 WT and Jmjd1c Ко mice.Jmjd1c tumor cells had stronger overall peak signal intensity of than WT tumor cells (Fig. 3d); a total of 5,012
表面分子对 细胞的维持和功能起着至关重要的作用。Pdcd1 和 Nrp1 是编码表面分子的基因中下调最强烈的基因之一(图 3a)。流式细胞术证实,在肿瘤 细胞中,PD1 和 NRP1 蛋白水平的表达因 JMJD1C 缺乏而显著降低(图 3b、c)。重要的是,这两个基因的表达在脾脏 细胞中没有任何改变(图 3b,c)。据报道,NRP1缺乏会影响肿瘤 细胞的存活和增殖 ,这与我们在Jmjd1c KO肿瘤 细胞中的观察结果一致(扩展数据图3b,c)。为了确定 是否可能受到 JMJD1C 介导的 H3K9me2 的直接调控,我们对来自 MCA205 肿瘤携带 Jmjd1 WT 和 Jmjd1c Ко 小鼠的肿瘤 细胞进行了 CUT&RUN-seq(使用核酸酶测序的靶标下裂解和释放)分析。与 WT 肿瘤 细胞相比,Jmjd1c 肿瘤 细胞的 整体峰值信号强度更强(图 3d);共有 5,012 个 Jmjd1c 肿瘤 细胞的 峰值信号强度高于 WT 肿瘤 细胞(图 3d)。

b B16-OVA tumor b B16-OVA 肿瘤

d
f
Fig. cellJmjd1c deficiency reduces tumor cell frequency and
细胞 Jmjd1c 缺乏会降低肿瘤 细胞的频率和数量。

inoculated subcutaneously with B16-OVA cells ( for Jmjd1c and for
皮下接种 B16-OVA 细胞 ( for Jmjd1c and for Jmjd1c and )

EL4 cells ( for and for ).b, Representative flow cytometric plots of tumor-infiltrating cells (left). Percentages of Foxp3-YFP cells among cells in the indicated tissues of B16-OVA-tumor-bearing mice are plotted on the right. Spl, spleen; dLN, draining lymph node. for Jmjd1c and for Jmjd1c .c, Cell numbers of Foxp3- CD4 and CD8 T cells per gram of tumor in B16-OVA-tumor-bearing Jmjd1c and Jmjd1 mice. TIL, tumor-infiltrating lymphocyte. d, Representative flow cytometric plots of tumor-infiltrating cells (left). Percentages of Foxp3-YFP cells among CD4 cells in the indicated tissues of MCA205tumor-bearing mice are plotted on the right. for and for Jmjd1c , Cell numbers of Foxp3 and cells per gram of tumor in MCA205-tumor-bearing mice. for Jmjd1 and for о. f, Representative flow cytometric plots of cytokine production in Foxp3 and MCA205-tumor-infiltrating T cells (left). Percentages of cytokineproducing cells in draining lymph node and tumor are plotted on the right. for and for Jmjd1c . Data in a-f were pooled from two independent experiments and are shown as mean s.d. Two-way ANOVA (a) and two-tailed unpaired Student's -test (b-f) were used for data analysis. increased peaks (corresponding to 1,198 genes) were identified in Jmjd1c KO cells compared with cells. By integrating transcriptome data, we identified 18 genes that could be directly regulated by JMJD1C-mediated H3K9me2 (Fig. 3e and Supplementary Table 1), as they showed both increased H3K9me2 deposition and decreased messenger RNA (mRNA) expression, with Pdcd1 in particular showing clearly increased peak intensity inJmjd1c cells(Fig.3f). There was no increased deposition in the Nrp1 locus, suggesting that
EL4细胞( 表示 表示 )。b, 肿瘤浸润 细胞的代表性流式细胞图(左)。右图为 B16-OVA 肿瘤小鼠指定组织中 细胞中 Foxp3-YFP 细胞的百分比。Spl,脾脏;dLN,引流淋巴结。 代表 Jmjd1c 代表 Jmjd1c 。c, B16-OVA 肿瘤携带 Jmjd1c 和 Jmjd1 小鼠每克肿瘤中 Foxp3- CD4 和 CD8 T 细胞数。TIL,肿瘤浸润淋巴细胞。 d,肿瘤浸润 细胞(左)的代表性流式细胞图。右图为 MCA205 肿瘤小鼠指定组织中 Foxp3-YFP 细胞占 CD4 细胞的百分比。 为 Jmjd1c ,MCA205 肿瘤小鼠每克肿瘤中 Foxp3 细胞数。 о f, Foxp3 MCA205 肿瘤浸润 T 细胞细胞因子产生的代表性流式细胞图(左)。 为 Jmjd1c 数据分析采用了双向方差分析(a)和双尾非配对学生 -检验(b-f)。与 细胞相比,在 Jmjd1c KO 细胞中发现了增加的峰值(对应 1,198 个基因)。通过整合转录组数据,我们确定了 18 个可能受 JMJD1C 介导的 H3K9me2 直接调控的基因(图 3e 和补充表 1),因为它们同时显示出 H3K9me2 沉积增加和信使 RNA(mRNA)表达减少,尤其是 Pdcd1 在 Jmjd1c 细胞中的峰强度明显增加(图 3f)。 的沉积在 Nrp1 基因座中没有增加,这表明

effect (Supplementary Table1). These data indicate thatJMJD1C potentially regulates PD1 expression as a canonical demethylase. Previous studies have reported that both NRP1 and PD1 could suppress
效应(补充表 1)。这些数据表明,JMJD1C 有可能作为一种典型的 去甲基化酶调节 PD1 的表达。以前的研究曾报道,NRP1 和 PD1 都可以抑制


H3K9me2 signal H3K9me2 信号

i  i
Fig. 3 |JMJD1C suppresses AKT signaling by promoting NRP1 and PD1 expression to prevent IFNY production. a, Left, heatmap showing mRNA expression of selected surface markers from scRNA-seq data of tumor cells
图 3 |JMJD1C通过促进 NRP1 和 PD1 的表达来抑制 AKT 信号转导,从而阻止 IFNY 的产生。a, 左图,热图显示了肿瘤 细胞 scRNA-seq 数据中选定表面标记物的 mRNA 表达。

showing expression of Pdcd1 and Nrp1. b,c, Flow cytometric analysis of PD1 (b) and NRP1 (c) expression in cells from and mice bearing MCA205 tumors . MFI, mean fluorescence intensity. d, Overall peak signal intensity of in tumor cells from MCA205-tumor-bearing Jmjd1 and Jmjd1 mice by CUT&RUN-seq analysis. e, Venn diagram indicating overlap of genes with reduced expression and increased modification inJmjd1c KO tumor cells. , Snapshot of H3K9me2 deposition on the Pdcd1 gene locus from CUT&RUN-seq data. , Flow cytometric analysis of pAKT (left)
b,c, 流式细胞仪分析 患有 MCA205 肿瘤的小鼠的 细胞中 PD1(b)和 NRP1(c)的表达情况 。MFI,平均荧光强度。 d,通过 CUT&RUN-seq 分析,MCA205 肿瘤携带 Jmjd1 和 Jmjd1 小鼠肿瘤 细胞中 的总体峰值信号强度。 e,表示在 Jmjd1c KO 肿瘤 细胞中表达减少和 修饰增加的基因重叠的维恩图。 , CUT&RUN-seq 数据显示的 Pdcd1 基因位点上的 H3K9me2 沉积快照。 , pAKT(左)的流式细胞分析
and Jmjd1 ко mice, stimulated and stained for IFN by and pS6 (right) levels in tumor cells. FMO, Fluorescence-Minus-One control. flow cytometry. , Tumor cells sorted from mice as in , stimulated with CD3 and CD28 antibodies for 3 days, followed by treatment with PMA (phorbol 12-myristate 13-acetate) + ionomycin. Enzyme-linked immunosorbent assays were then performed to measure IFN levels in the cell culture media. . j, GSEA showing enrichment of the IFN response pathway in Jmjd1c KO tumorinfiltrating cells. k, Violin plot showing expression of Tap1, H2-k1 and Cd274 in tumor cells from scRNA-seq data. Foxp and Foxp mice were inoculated with MCA205 cells, and tumor growth was measured. Data were pooled from two independent experiments in and h. Data are representative of three independent experiments in and . Data are shown as mean s.d. (b, and ) or mean s.e.m. (l). Two-way ANOVA (l), twotailed unpaired Student's -test (b, c, and two-sided Wilcoxon rank-sum test for and for Jmjd1 cells from MCA205 tumors in ( and ) were used to analyze the data. FDR, false discovery rate.
和 Jmjd1 小鼠,通过肿瘤 细胞中的 IFN 和 pS6(右)水平进行刺激和染色。流式细胞术。 用 CD3 和 CD28 抗体刺激小鼠 3 天,然后用 PMA(光稳定剂 12-肉豆蔻酸 13-乙酸酯)+离子霉素处理 。然后进行酶联免疫吸附试验,测量细胞培养基中 IFN 的水平。 j, GSEA 显示 Jmjd1c KO 肿瘤浸润 细胞中 IFN 反应途径的富集。 k, Violin plot 显示来自 scRNA-seq 数据的 Tap1、H2-k1 和 Cd274 在肿瘤 细胞中的表达。 Foxp 和 Foxp 小鼠接种 MCA205 细胞并测量肿瘤生长。数据来自 和 h 的两个独立实验。数据代表 和 的三个独立实验。数据显示为平均值 s.d. (b, 和 ) 或平均值 s.e.m. (l)。采用双向方差分析 (l)、双尾非配对学生 -test (b, c, 和双侧 Wilcoxon 秩和检验 和 来自 MCA205 肿瘤的 Jmjd1 细胞 ( 和 ) 来分析数据。FDR,错误发现率。 ко
AKT signaling to restrain IFN production in tumor cells and prevent tumor cell fragility . Indeed, flow cytometry analysis revealed higher levels of phosphorylated AKT (pAKT) and S6 (pS6) inJmjd1c KO tumor cells (Fig. 3g). As a consequence of upregulated AKT signaling,JMJD1C-deleted tumor cells produced 4-6-fold more IFN than cells (Fig. 3h,i). The extent of the IFN increase was substantial
AKT信号转导抑制肿瘤 细胞中IFN 的产生,防止肿瘤 细胞脆性 。事实上,流式细胞术分析显示,在Jmjd1c KO的肿瘤 细胞中,磷酸化AKT(pAKT)和S6(pS6)的水平更高(图3g)。由于AKT信号的上调,JMJD1C缺失的肿瘤 细胞产生的IFN 细胞的4-6倍(图3h,i)。IFN 增加的幅度很大
d
e f
6
j  j
CD4 and CD8 cells
CD4 和 CD8 细胞

\ m
Fig. 4|JMJD1C demethylates and inhibits STAT3 in tumor cells to prevent IFN production. a, GSEA showing enriched hallmark gene signatures in Jmjd1c KO tumor cells. , Tumor cells were sorted from MCA205-tumor-bearing mice, and STAT3 protein was immunoprecipitated for detection of lysine methylation levels by immunoblotting. c, Flow cytometric analysis of pSTAT3 levels in cells from mice bearing MCA205 tumors. for and for Jmjd1c , Flow cytometric analysis of Foxp3 levels in tumor cells from mice bearing MCA205 tumors. , Violin plot showing expression of Il17a in tumor cells from scRNA-seq data. , Left, Ifng gene locus with predicted STAT3-binding motifs noted. Right, luciferase reporter assays showing that STAT3 regulates Ifng promoter activity. The reporter constructs containing the WT Ifng promoter sequence or a sequence with motifs deleted were cotransfected into 293T cells along with STAT3CA expression constructs or an empty vector control. biologically independent samples. g, Strategy for generating knock-in mice with STAT3 overexpression in cells (Stat3CA ). h, Representative plots of tumor-infiltrating cells (left) and percentages of Foxp3-YFP cells in MCA205-tumor-bearing WT and Stat3CA mice. . i, Tumor growth in WT and Stat3CA mice inoculated with MCA2O5 cells. . cells from MCA205-tumor-bearing WT and Stat3CA mice, stimulated and stained for IFN by flow cytometry. , Experimental design to reconstitute cell immune response and assess tumor cell function in mice. I, Tumor growth curve in Rag1 mice reconstituted as indicated in . , Frequencies of Foxp3-YFP cells in the indicated tissues of MCA205-tumorbearing Rag1 mice. . Data in and are shown as mean s.d. Data in and are shown as mean s.e.m. Data are representative of three (c, and ) or two ( and ) independent experiments. Two-way ANOVA (i, , two-tailed unpaired Student's -test (c, and ), one-way ANOVA with Tukey's multiple comparison test and two-sided Wilcoxon rank-sum test (e) were used to analyze the data. effector cell; i.v., intravenous. and seemed to exceed even that caused by Nrp1 knockout . Consistent with this,Jmjd1c KO tumor cells showed elevated expression of IFN -responsive genes, including antigen-presentation-related genes and Cd274 (Fig. 3j, k). Moreover, similar phenotypes of inhibited tumor growth, reduced numbers of JMJD1C-deficient cells and increased numbers of cytokine-producing cells were observed in female
图4|JMJD1C在肿瘤 细胞中去甲基化并抑制STAT3以阻止IFN 的产生。a, GSEA显示Jmjd1c KO肿瘤 细胞中富集的标志基因特征。 Ⅳ、从 MCA205 肿瘤小鼠中分选肿瘤 细胞,免疫沉淀 STAT3 蛋白,通过免疫印迹检测赖氨酸甲基化水平。c, 流式细胞仪分析来自 MCA205 肿瘤小鼠 细胞中 pSTAT3 的水平。 为 Jmjd1c ,流式细胞仪分析来自 MCA205 肿瘤小鼠 细胞中 Foxp3 的水平。 根据 scRNA-seq 数据绘制的显示肿瘤 细胞中 Il17a 表达的 Violin 图。 左图:Ifng 基因位点,并标注了预测的 STAT3 结合基团。右图:荧光素酶报告实验显示 STAT3 可调控 Ifng 启动子的活性。将含有 WT Ifng 启动子序列或删除了基团的序列的报告构建物与 STAT3CA 表达构建物或空载体对照共转染到 293T 细胞中。 生物学独立样本。g, 在 细胞中过表达 STAT3 的基因敲入小鼠的生成策略(Stat3CA )。 h, MCA205 肿瘤 WT 小鼠和 Stat3CA 小鼠中肿瘤浸润 细胞(左)和 Foxp3-YFP 细胞百分比的代表图。 。 i, 接种 MCA2O5 细胞的 WT 小鼠和 Stat3CA 小鼠的肿瘤生长情况。 . 细胞来自 MCA205 肿瘤携带 WT 和 Stat3CA 小鼠,通过流式细胞术刺激和染色 IFN , 在 小鼠中重建 细胞免疫反应并评估肿瘤 细胞功能的实验设计。I,Rag1 小鼠的肿瘤生长曲线,如 所示。 , MCA205 肿瘤携带 Rag1 小鼠指定组织中 Foxp3-YFP 细胞的频率。 中的数据显示为平均值 s.d.。 中的数据显示为平均值 s.e.m.。数据代表三个(c, )或两个( )独立实验。数据分析采用了双向方差分析(i, ,双尾非配对学生 -检验(c, ),单向方差分析与 Tukey's 多重比较检验 和双侧 Wilcoxon 秩和检验(e)。 效应 细胞;i.v. ,静脉注射。似乎甚至超过了 Nrp1 基因敲除引起的 。 与此相一致,Jmjd1c KO 肿瘤 细胞显示 IFN 反应基因的表达升高,包括抗原递呈相关基因和 Cd274(图 3j,k)。此外,在雌性 细胞中也观察到了类似的表型,即肿瘤生长受到抑制、JMJD1C 缺失的 细胞数量减少以及产生细胞因子的 细胞数量增加。

a
b
d c
Fig. IFN deletion rescues tumor cell fragility in the absence of JMJD1C. a, Experimental design to reconstitute T cell immune response and assess tumor cell function in Rag1 mice. , Tumor growth curve in mice with adoptive transfer of effector cells and cells as indicated in a. mice.
IFN 缺失可在缺乏 JMJD1C 的情况下挽救肿瘤 细胞的脆弱性。a, 在 Rag1 小鼠中重建 T 细胞免疫反应和评估肿瘤 细胞功能的实验设计。 小鼠的肿瘤生长曲线。
c, Representative flow cytometric plots of tumor-infiltrating cells (above) and percentages of Foxp3- cells among cells in the indicated tissues of MCA205-tumor-bearing mice (below). mice. , Bar graph of IFN and IFN cell percentages in Foxp3-YFP cells (above) and cells (below) in the indicated tissues of MCA205-tumor-bearing Rag1 mice. mice. Data are representative of two independent experiments . Data in are shown as mean s.e.m. Data in and are shown as mean s.d. Two-way ANOVA (b) and one-way ANOVA with Tukey's multiple comparison test (c, were used to analyze the data.
c, MCA205-肿瘤携带者 小鼠指定组织中肿瘤浸润 细胞(上图)和 细胞中 Foxp3- 细胞百分比的代表性流式细胞图(下图)。 小鼠。 和 IFN 细胞在 MCA205 肿瘤携带 Rag1 小鼠指定组织中的 Foxp3-YFP 细胞(上图)和 细胞(下图)中的百分比条形图。 小鼠。数据代表两个独立实验的结果 中的数据以平均值 s.e.m.表示。 中的数据以平均值 s.d.表示。数据分析采用双向方差分析(b)和单向方差分析加 Tukey's 多重比较检验(c, )。

Foxp Jmjd1 mosaic mice (Fig. 3l and Supplementary Fig. 3a,b), indicating a dominant effect of JMJD1C-deficient cells in the TME. Notably, the frequency of cells was also slightly reduced in mosaic mice compared with control mice (Supplementary Fig. 3a), possibly owing to a more proinflammatory TME in mosaic mice.
Foxp Jmjd1 镶嵌小鼠(图 3l 和补充图 3a,b),表明 JMJD1C 缺失的 细胞在 TME 中具有显性效应。值得注意的是,与对照组小鼠相比,镶嵌组小鼠中 细胞的频率也略有降低(补充图 3a),这可能是由于镶嵌组小鼠的 TME 更具有促炎性。
Furthermore, we generated mixed bone marrow chimeras containing 50% CD45.1 CD45.2 Foxp3-Cre-YFP WT plus 50% CD45.2 either (WT) or Jmjd1c cells to directly compare WT and JMJD1C-deficient cells derived from the same TME (Supplementary Fig.4a).Upon MCA205tumor inoculation of WT:KO mixed chimeras, we observed that the tumor cell frequency in the CD45.2+ compartment was significantly reduced compared with that in the CD45.1/2 WT compartment in the same tumor tissue (Supplementary Fig. 4b). No such reduction was observed in spleen (Supplementary Fig. 4b). Moreover, JMJD1C-deficient cells exhibited dramatically decreased PD1 and NRP1 expression but increased pSTAT3 signal and IFN expression compared with their WT counterparts in the same tumor tissues (Supplementary Fig. 4c-e). By contrast, conventional T cells from WT and Jmjd1c compartments in WT:KO mixed chimeras showed similarly elevated effector function compared with cells in WT:WT mixed chimeras, as assessed by cytokine staining (Supplementary Fig. 4f). WT tumor cells from WT:KO mixed chimeras were also slightly altered compared with cells from :WT mixed chimeras and exhibited moderately reduced cell frequency and decreased PD1 expression (Supplementary Fig. 4b,c), possibly owing to a more proinflammatory TME in WT:KO chimeras compared with WT:WT mixed chimeras. Overall, the data for mixed bone marrow chimeras suggest thatJMJD1C regulates tumor cells in a cell-intrinsic manner.
此外,我们生成了含有50% CD45.1 CD45.2 Foxp3-Cre-YFP WT和50% CD45.2 (WT)或Jmjd1c 细胞的混合骨髓嵌合体,以直接比较WT和JMJD1C缺陷的 来自同一TME的细胞(补充图4)。a)。接种WT:KO混合嵌合体的MCA205肿瘤后,我们观察到在相同的肿瘤组织中,CD45.2+ 区系的肿瘤 细胞频率与CD45.1/2 WT区系相比显著降低(补充图4b)。在脾脏中没有观察到这种减少(补充图 4b)。此外,与相同肿瘤组织中的 WT 细胞相比,JMJD1C 缺陷 细胞的 PD1 和 NRP1 表达显著减少,但 pSTAT3 信号和 IFN 表达增加(补充图 4c-e)。相比之下,经细胞因子染色评估,WT:KO 混合嵌合体中来自 WT 和 Jmjd1c 区间的传统 T 细胞与 WT:WT 混合嵌合体中的 细胞相比,显示出类似的效应功能增强(补充图 4f)。与来自 :WT 混合嵌合体的 细胞相比,来自 WT:KO 混合嵌合体的 WT 肿瘤 细胞也发生了轻微变化,表现出细胞频率适度降低和 PD1 表达减少(补充图 4b,c),这可能是由于与 WT:WT 混合嵌合体相比,WT:KO 嵌合体的 TME 更具有促炎性。总之,混合骨髓嵌合体的数据表明,JMJD1C 以细胞内在的方式调节肿瘤 细胞。
Collectively, these data show that JMJD1C, as a canonical histone demethylase, promotes PD1 expression to prevent IFN production and tumor cell fragility, thereby exacerbating tumor growth.
这些数据共同表明,JMJD1C 作为一种典型的组蛋白去甲基化酶,会促进 PD1 的表达,从而阻止 IFN 的产生和肿瘤 细胞的脆弱性,从而加剧肿瘤的生长。

JMJD1C suppresses STAT3 in tumor cells
JMJD1C 抑制肿瘤 细胞中的 STAT3

Our previous study in B cells revealed thatJMJD1C could inhibit STAT3 signaling by directly demethylating STAT3 in a noncanonical manner, andJMJD1C deletion led to an upregulated IL-6-STAT3 signal . Here, cell transcriptome analysis identified a large number of upregulated differentially expressed genes inJmjd1c KO tumor cells (Extended Data Fig. 4e), prompting us to assess whether JMJD1C could also demethylate STAT3 in tumor cells. Indeed, the results of our GSEA indicated that IL-6-STAT3 was the most highly upregulated signal pathway among all the 50 hallmark gene sets inJmjd1c KO tumor cells (Fig. 4a), and STAT3 retained higher levels of lysine methylation in Jmjd1c KO tumor cells than in cells (Fig. 4b). Consequently,JMJD1C deficiency led to increased pSTAT3 specifically in tumor cells but not in splenic cells (Fig. 4c). Moreover, by analyzing the mixed chimeras containing Foxp3-Cre-YFP WT plusJmjd1c cells shown in Supplementary Fig. 4, we observed increased pSTAT3 in JMJD1C-deficient tumor
我们之前在B细胞中的研究发现,JMJD1C可以通过非经典方式直接去甲基化STAT3来抑制STAT3信号转导,而且JMJD1C缺失会导致IL-6-STAT3信号上调 。在这里, 细胞转录组分析在Jmjd1c KO肿瘤 细胞中发现了大量上调的差异表达基因(扩展数据图4e),这促使我们评估JMJD1C是否也能在肿瘤 细胞中使STAT3去甲基化。事实上,我们的GSEA结果表明,在Jmjd1c KO肿瘤 细胞中,IL-6-STAT3是所有50个标志性基因集中上调程度最高的信号通路(图4a),而且与 细胞相比,STAT3在Jmjd1c KO肿瘤 细胞中保留了更高水平的赖氨酸甲基化(图4b)。因此,JMJD1C的缺乏导致肿瘤 细胞中的pSTAT3特异性增加,而脾脏 细胞中的pSTAT3则没有增加(图4c)。此外,通过分析补充图 4 中所示的含有 Foxp3-Cre-YFP WT 加 Jmjd1c 细胞的混合嵌合体,我们观察到 JMJD1C 缺乏的肿瘤细胞中 pSTAT3 增加。

cells compared with cells in the same tumor tissues (Supplementary Fig. 4d). Under inflammatory settings, an elevated IL-6-STAT3 signal is believed to impair the stability of cells and convert them into . However, the impact of an increased STAT3 signal on cells in the TME has not previously been directly addressed. Notably, the protein level of Foxp3 was unaltered in the absence of JMJD1C (Fig. 4d), and Jmjd1c KO tumor cells did not show increased Il17a mRNA expression (Fig. 4e), suggesting a context-dependent impact of the STAT3 signal on cells. Given the surprisingly strong upregulation of IFN ү inJmjd1c KO tumor cells (Fig. 3h), we considered whether the elevated STAT3 signal might also contribute to IFN upregulation. In support of this hypothesis, we identified two classical STAT3-binding motifs in the promoter region of the Ifng genomic locus (Fig. 4f). A luciferase assay proved that STAT3 was able to upregulate Ifng promoter activity, and that these two motifs were required for the upregulation (Fig. 4f). These data suggest thatJMJD1C may also repress IFN expression by restraining the STAT3 signal in a noncanonical manner independent of histone modification, in addition to suppressing the AKT signal in a canonical manner.
细胞与相同肿瘤组织中的 细胞相比(补充图 4d)。在炎症环境下,IL-6-STAT3 信号的升高被认为会损害 细胞的稳定性并将其转化为 。然而,STAT3 信号的升高对 细胞在 TME 中的影响以前还没有直接研究过。值得注意的是,在没有 JMJD1C 的情况下,Foxp3 的蛋白水平没有改变(图 4d),而 Jmjd1c KO 肿瘤 细胞也没有显示 Il17a mRNA 表达的增加(图 4e),这表明 STAT3 信号对 细胞的影响与环境有关。鉴于在Jmjd1c KO肿瘤 细胞中IFN ү 的上调出乎意料地强烈(图3h),我们考虑了STAT3信号的升高是否也会导致IFN 的上调。为了支持这一假设,我们在 Ifng 基因组位点的启动子区域发现了两个经典的 STAT3 结合基团(图 4f)。荧光素酶试验证明,STAT3 能够上调 Ifng 启动子的活性,而这两个基团是上调所必需的(图 4f)。这些数据表明,除了以规范方式抑制 AKT 信号外,JMJD1C 还可能以独立于组蛋白修饰的非规范方式抑制 STAT3 信号,从而抑制 IFN 的表达。
To further corroborate these observations and directly address the role of STAT3 in tumor cells, we generated a conditional overexpressing mouse strain by inserting Loxp-STOP-Loxp-Stat3CA (constitutive active form by p.Ala661Cys and p.Asn663Cys mutation) into the Rosa26 locus. By crossing it to Foxp3 mice, we obtained mice with STAT3CA overexpressed in cells (named Stat3CA ) (Fig. 4g). Similar toJmjd1 mice, upon MCA205 tumor inoculation, Stat3CA mice had reduced cell frequency selectively in tumor tissue but not in peripheral lymphoid organs (Fig. 4h). Accordingly, intratumoral effector T cells in Stat3CA mice produced more abundant IFN and TNF cytokines (Extended Data Fig. 5a), and tumor growth was significantly repressed (Fig. 4i). Notably, IL-17A production was not increased in Stat3CA mice, further confirming that elevated STAT3 did not regulate conversion in tumor cells (Extended Data Fig. 5b). Moreover, we detected higher levels of IFN production selectively in tumor cells but not in cells from lymphoid organs (Fig. 4j). We further generated mixed bone marrow chimeric mice to assess the effects of STAT3 overexpression on tumor cells on a per-cell basis (Supplementary Fig. 5a). Upon MAC205 tumor inoculation, tumor cells from the CD45.2 Stat3CA compartment selectively decreased in frequency and expressed higher levels of IFN compared with those from the CD45.1/2+ WT compartment in the same tumor tissue (Supplementary Fig. 5b,c). Consistent with this, conventional T cells from WT:Stat mixed chimera mice produced elevated levels of cytokines compared with WT:WT chimeric mice (Supplementary Fig. 5d). Overall, these data suggest that JMJD1C deficiency can induce IFN production in tumor cells via upregulation of the STAT3 signal.
为了进一步证实这些观察结果并直接探讨 STAT3 在肿瘤 细胞中的作用,我们将 Loxp-STOP-Loxp-Stat3CA(p.Ala661Cys 和 p.Asn663Cys 突变的组成活性形式) 插入 Rosa26 基因座,产生了一个条件性过表达小鼠品系。通过与 Foxp3 小鼠杂交,我们获得了在 细胞中过表达 STAT3CA 的小鼠(命名为 Stat3CA )(图 4g)。与Jmjd1 小鼠类似,接种 MCA205 肿瘤后,Stat3CA 小鼠选择性地减少了肿瘤组织中 细胞的频率,但没有减少外周淋巴器官中 细胞的频率(图 4h)。相应地,Stat3CA 小鼠的瘤内效应 T 细胞产生了更多的 IFN 和 TNF 细胞因子(扩展数据图 5a),肿瘤生长受到显著抑制(图 4i)。值得注意的是,Stat3CA 小鼠的 IL-17A 产量并没有增加,这进一步证实了 STAT3 的升高并没有调节肿瘤 细胞中 的转化(扩展数据图 5b)。此外,我们在肿瘤 细胞中选择性地检测到更高水平的 IFN 产生,而在来自淋巴器官的 细胞中却没有检测到(图 4j)。我们进一步生成了混合骨髓嵌合体小鼠,以评估STAT3过表达对肿瘤 细胞的影响(补充图5a)。MAC205肿瘤接种后,与同一肿瘤组织中来自CD45.2 Stat3CA 区系的细胞相比,来自CD45.1/2+ WT区系的肿瘤 细胞选择性地减少了频率并表达了更高水平的IFN (补充图5b,c)。与此相一致,与 WT:WT 嵌合小鼠相比,WT:Stat 混合嵌合小鼠的常规 T 细胞产生的细胞因子水平升高(补充图 5d)。总之,这些数据表明,JMJD1C 缺乏可通过上调 STAT3 信号诱导肿瘤 细胞产生 IFN
As defects in both H3K9me2 and STAT3 demethylation in the absence of JMJD1C could impair cell fitness in tumors and suppress tumor growth, we next investigated which function of JMJD1C contributed more to the phenotype using Stat mice, which we have previously reported as having a mutation at STAT3 (K140, the demethylation site for JMJD1C). We crossed and generatedJmjd1c Stat3 mice, which allowed JMJD1C to act solely on H3K9me2 but not on STAT3 in cells. We then sorted cells from , Stat3CA КО Stat and Jmjd1c mice and cotransferred them with effector T cells into Rag1 KO recipients, which were subsequently inoculated with MCA205 tumor cells (Fig. 4k). By monitoring tumor size, we observed that mice receiving transfer of Stat cells exhibited less inhibition of tumor growth than those receiving Stat cells (Fig. 4I). Accordingly, numbers of Jmjd1 Stat cells decreased to a greater extent within tumors compared with Stat cells (Fig. ). These findings suggest that the demethylation function of JMJD1C contributes slightly more to the phenotype observed inJMJD1C KO mice compared with the STAT3 demethylation function.
由于缺乏 JMJD1C 时 H3K9me2 和 STAT3 去甲基化的缺陷会损害 细胞在肿瘤中的适存性并抑制肿瘤生长,因此我们接下来利用 Stat 小鼠研究了 JMJD1C 的哪种功能对表型的贡献更大,我们以前曾报道过这种小鼠的 STAT3(K140,JMJD1C 的去甲基化位点)发生了突变。我们杂交产生了 Jmjd1c Stat3 小鼠,这使得 JMJD1C 只作用于 细胞中的 H3K9me2 而不作用于 STAT3。然后,我们从 、Stat3CA КО Stat 和 Jmjd1c 小鼠中分拣出 细胞,并将它们与效应 T 细胞共同转移到 Rag1 KO 受体中,随后接种 MCA205 肿瘤细胞(图 4k)。通过监测肿瘤大小,我们观察到与接受 Stat 细胞的小鼠相比,接受 Stat 细胞转移的小鼠对肿瘤生长的抑制作用较弱(图 4I)。相应地,与Stat 细胞相比,Jmjd1 Stat 细胞数量在肿瘤内的减少程度更大(图 )。这些发现表明,与 STAT3 去甲基化功能相比,JMJD1C 的 去甲基化功能对 JMJD1C KO 小鼠观察到的表型的影响稍大。
Overall, these results show that accumulated H3K9me2 methylation and elevated STAT3 signals by JMJD1C loss jointly drive cell fragility and disrupt tumor cell fitness, in both canonical and noncanonical manners.
总之,这些结果表明,累积的H3K9me2甲基化和因JMJD1C缺失而升高的STAT3信号共同推动了 细胞的脆弱性,并以规范和非规范的方式破坏了肿瘤 细胞的适应性。

cell fragility is rescued by IFN loss
细胞脆性可通过 IFN 的损失得到挽救

To assess whether the tumor growth inhibition in mice was predominantly dependent on IFN overproduction in tumor cells, we intercrossed Jmjd11 mice with Ifng mice. cells isolated
为了评估 小鼠的肿瘤生长抑制作用是否主要依赖于肿瘤 细胞中 IFN 的过度产生,我们将 Jmjd11 小鼠与 Ifng 小鼠杂交。 细胞分离出来。

mice were adoptively cotransferred with cell-depleted CD4 and CD8 effector T cells into Rag1 recipients, which were then inoculated with MCA205 tumors (Fig. 5a). As expected, tumor growth in recipient mice that received Jmjd1c cells was significantly slower than that in mice that receivedJmjd1c WT T reg cells (Fig. 5b).However, tumor growth was comparable in mice that received Jmjd or Jmjd1 Ко cells and similar to that in mice that received Jmjd1c WT T cells (Fig. 5b), suggesting that IFN deletion rescued the tumor cell dysfunction caused by JMJD1C deficiency. Moreover, the reduced tumor cell frequency in mice that received Jmjd1c cells was also rescued by IFN deletion (Fig. 5c). Similar observations were made in terms of cytokine production in effector cells, and the percentages of IFN - and TNF-producing intratumoral CD4 and CD8
细胞贫化的 CD4 和 CD8 效应 T 细胞共转移给 Rag1 受体小鼠,然后接种 MCA205 肿瘤(图 5a)。不出所料,接受 Jmjd1c 细胞的受体小鼠的肿瘤生长速度明显慢于接受 Jmjd1c WT T reg 细胞的受体小鼠(图 5b)。然而,接受Jmjd 或Jmjd1 Ко 细胞的小鼠的肿瘤生长与接受Jmjd1c WT T 细胞的小鼠相似(图5b),这表明IFN 的缺失可挽救因JMJD1C 缺乏引起的肿瘤 细胞功能障碍。此外,接受Jmjd1c 细胞的小鼠肿瘤 细胞频率的降低也被IFN 删除所挽救(图 5c)。在效应 细胞中细胞因子的产生方面也有类似的观察结果,瘤内 CD4 和 CD8 细胞中产生 IFN 和 TNF 的百分比也有类似的观察结果。

cells were comparable and at a similar level to those in mice that receivedJmjd1c cells (Fig. 5d). Collectively, these data suggest thatJMJD1C selectively maintains tumor cell fitness predominantly through repression of IFN expression.
与接受Jmjd1c 细胞治疗的小鼠相比,JMJD1C抑制的肿瘤细胞数量和水平相当(图 5d)。总之,这些数据表明,JMJD1C 主要通过抑制 IFN 的表达来选择性地维持肿瘤 细胞的健康。

JMJD1Cinhibitor suppresses tumor growth
JMJD1抑制剂可抑制肿瘤生长

To find a chemical probe capable of inhibiting the demethylase activity of JMJD1C, we used deep-learning-based scoring function EquiScore for virtual screening. EquiScore was used to score and sort the binding modes of theJMJD1C proteins and their ligands with a well-trained
为了找到能够抑制 JMJD1C 去甲基化酶活性的化学探针,我们使用了基于深度学习的评分函数 EquiScore 进行虚拟筛选。EquiScore 用训练有素的

Fig. 6 |JMJD1C inhibitor suppresses tumor growth by targeting tumor cells. a, Scheme of virtual screening protocol for small-molecule inhibitors of JMJD1C.b,c, Compounds competitively inhibiting H3K9me2 peptide binding to JMJD1C, as measured by HTRF assay. The chemical structure of 193D7 is shown in b. d, In vitro demethylation assay to examine the inhibitory effects of 193D7 on H3K9me2 demethylase activity. , SPR analysis examining the direct binding affinity of 193D7 to JMJD1C. f, Modeled binding pose of 193D7 (orange) inJMJD1C crystal structure (gray, PDB ID:5FZO). g, MCA205-tumor-bearing C57BL/6 mice were i.p. injected once a day with 193D7 ( 10 or ) or a dimethyl sulfoxide (DMSO) vehicle control beginning on day 10 after tumor injection. Tumor growth was measured. , Flow cytometric analysis of cells in tumor tissues. , Numbers of Foxp3-YFP and CD8 cells. mice inoculated with MCA205 cells were orally treated with DMSO or 193D7 ( ) once a day, and tumor progression was monitored. -equivariant graph neural network (for more information, see Methods). Screening was performed against an in-house chemical library containing 19,000 drug-like compounds, and the top 100 candidates were selected for experimental evaluation (Fig. 6a and Supplementary Table 2). Of these candidates, 193D7 showed the highest inhibitory effect at the initial screening concentration, with an (half-maximal inhibitory concentration) value of (Fig. 6b,c), based on an in vitro homogeneous time-resolved fluorescence (HTRF) assay that measured the ability of 193D7 to disrupt the interaction of JMJD1C with
图 6 |JMJD1C抑制剂通过靶向肿瘤 细胞抑制肿瘤生长。a, JMJD1C小分子抑制剂的虚拟筛选方案。b,c, 通过HTRF测定竞争性抑制H3K9me2肽与JMJD1C结合的化合物。b 中显示的是 193D7 的化学结构。d, 体外去甲基化试验以检测 193D7 对 H3K9me2 去甲基化酶活性的抑制作用。 f, 193D7 (橙色)在 JMJD1C 晶体结构(灰色,PDB ID:5FZO)中的模型结合位置。 g, 从肿瘤注射后第 10 天开始,给携带 MCA205 肿瘤的 C57BL/6 小鼠每天注射一次 193D7 ( 10 或 ) 或二甲基亚砜(DMSO)载体对照。测量肿瘤生长情况。 流式细胞仪分析肿瘤组织中的 细胞。 接种 MCA205 细胞的小鼠每天口服一次 DMSO 或 193D7 ( ),并监测肿瘤进展。 -在此基础上,研究人员利用等变图神经网络(更多信息,请参见 "方法")进行了筛选。根据包含 19,000 种类药物的内部化学库进行筛选,选出前 100 种候选化合物进行实验评估(图 6a 和补充表 2)。在这些候选化合物中,193D7 在初始筛选浓度下显示出最高的抑制效果,其 (半最大抑制浓度)值为 (图 6b,c),这是基于体外均相时间分辨荧光(HTRF)测定法,该测定法测量了 193D7 破坏 JMJD1C 与 JMJD1C 之间相互作用的能力。
a
I
d In vitro demethylation assay
d 体外去甲基化试验
h
its peptide substrate. In the in vitro demethylation assay, 193D7 inhibited the demethylation activity of JMJD1C with an value of (Fig. 6d). In addition, 193D7 selectively inhibited the activity of JMJD1C when screened against a panel of 14 other histone demethylases (Supplementary Fig. 6). Surface plasmon resonance (SPR) results showed that 193D7 directly bound to JMJD1C with a kinetic of (Fig. 6e). Based on the putative binding poses selected by EquiScore, 193D7 could fit well into the active site of JMJD1C, forming hydrogen bonds with R2309 and salt bridges with R2309 and R2315 in
肽底物。在体外去甲基化试验中,193D7 抑制了 JMJD1C 的去甲基化活性,其抑制值为 (图 6d)。此外,在与其他 14 种组蛋白去甲基化酶进行筛选时,193D7 还能选择性地抑制 JMJD1C 的活性(附图 6)。表面等离子体共振(SPR)结果表明,193D7 直接与 JMJD1C 结合,其动力学 (图 6e)。根据 EquiScore 筛选出的推定结合位点,193D7 可以很好地进入 JMJD1C 的活性位点,与 R2309 形成氢键,与 R2309 和 R2315 形成盐桥。

the active pocket region of JMJD1C (Fig. 6f). Moreover, a metal coordination bonding interaction was formed between the carbonyl group and the manganese ion, which could make the conformation of 193D7 more stable in the pocket (Fig. 6f).
的活性口袋区域(图 6f)。此外,羰基与锰离子之间形成了金属配位键相互作用,这可能会使 193D7 在口袋中的构象更加稳定(图 6f)。
We next identified the biological function of the 193D7 compound. When mice bearing multiple types of subcutaneous tumors, including MCA205(fibrosarcoma), B16-F10 (melanoma), Hepa1-6 (liver cancer), LLC (lung cancer) and CT26 (colon cancer), were intraperitoneally (i.p.) treated with 193D7 at once a day for 2 weeks, all tumors showed retarded growth (Fig. and Extended Data Fig. 6). Treatment of mice at this dose of 193D7 showed no evidence of toxicity (Extended Data Fig. 7a-c). Moreover, 193D7 treatment inhibited tumor growth in a dose-dependent manner (Fig. 6g). Flow cytometry analysis revealed that cell frequency in tumors was also reduced by 193D7 treatment in a dose-dependent manner (Fig. 6h), accompanied by increased numbers of and tumor-infiltrating effector T cells (Fig. 6i).
我们接下来确定了 193D7 复合物的生物功能。当携带多种类型皮下肿瘤(包括 MCA205(纤维肉瘤)、B16-F10(黑色素瘤)、Hepa1-6(肝癌)、LLC(肺癌)和 CT26(结肠癌))的小鼠腹腔注射(i.p.)193D7 ,每天一次,连续注射 2 周后,所有肿瘤都显示生长迟缓(图 和扩展资料图 6)。用这一剂量的 193D7 治疗小鼠没有显示出毒性(扩展数据图 7a-c)。此外,193D7以剂量依赖的方式抑制了肿瘤的生长(图6g)。流式细胞术分析表明,193D7 以剂量依赖的方式降低了肿瘤中 细胞的频率(图 6h),同时增加了 肿瘤浸润效应 T 细胞的数量(图 6i)。
A pharmacokinetic study was then conducted for 193D7 (Supplementary Fig. 7). Following i.p. or oral (p.o.) administration to BALB/c mice at a dose of , 193D7 displayed high plasma exposure (area under the curve (AUC) , high peak concentration , ) and early peak time ( , ). The half-life values for were (i.p.) and (p.o.), and the mean residence times were (i.p.) and (p.o.).
随后对 193D7 进行了药代动力学研究(附图 7)。以 的剂量给 BALB/c 小鼠静脉注射或口服(p.o.)后,193D7 显示出较高的血浆暴露量(曲线下面积(AUC) 、高峰值浓度 )和较早的峰值时间( )。 的半衰期值为 (体内)和 (口服),平均停留时间为 (体内)和 (口服)。
Given that 193D7 had a similar in vivo half-life when administrated i.p. or p.o., we therefore tested whether it could inhibit tumor growth when administered p.o., as this is a more applicable method of administration than intravenous injection. As expected, the growth of MCA205 tumors was inhibited by p.o.administration of 193D7 at the same dose as that used for i.p. injection (Fig. . cell frequency was also reduced specifically in tumor tissues but not in lymphoid organs (Fig. 6k), accompanied by increased effector cell numbers and cytokine production in tumors (Extended Data Fig. 8a,b). Similar toJMJD1C knockout, p.o. 193D7 treatment downregulated expression of PD1 and NRP1 and increased STAT3 phosphorylation in cells from tumor tissues but not lymphoid organs (Fig. ). Consequently, tumor cells produced dramatically increased IFN upon 193D7 treatment (Fig. 6n).
鉴于 193D7 在体内的半衰期与静脉注射和口服给药相似,因此我们测试了口服给药是否能抑制肿瘤生长,因为这是比静脉注射更适用的给药方法。不出所料,以与静脉注射相同的剂量经腹给药 193D7 可抑制 MCA205 肿瘤的生长(图 )。肿瘤组织中 细胞的频率也特异性地降低了,但淋巴器官中却没有(图 6k),同时肿瘤中效应 细胞的数量和细胞因子的产生也增加了(扩展数据图 8a,b)。与JMJD1C基因敲除相似,p.o. 193D7处理下调了PD1和NRP1的表达,并增加了肿瘤组织而非淋巴器官 细胞中STAT3的磷酸化(图 )。因此,肿瘤 细胞在 193D7 处理后产生的 IFN 显著增加(图 6n)。
To determine whether the antitumor effects of 193D7 rely on its inhibition of JMJD1C in tumor cells, we treated tumor-bearing Rag1 mice with 193D7 and found that this treatment did not inhibit tumor growth (Fig. 60), suggesting that 193D7 inhibits tumor growth via eliciting an antitumor T cell immune response. Furthermore, when tumor-bearing/mjd1c mice were treated with193D7, tumor growth was not suppressed and cell frequency in tumors was not altered (Fig. 6p,q), nor were tumor-infiltrating effector cell numbers and cytokine production by effector T cells (Extended Data Fig. 9a,b). We also treated MCA205-tumor-bearing mixed chimeras containing Foxp3-Cre-YFP WT plusJmjd11 cells with 193D7 (Extended Data
为了确定 193D7 的抗肿瘤作用是否依赖于其对肿瘤 细胞中 JMJD1C 的抑制作用,我们用 193D7 处理了携带 Rag1 的肿瘤小鼠,发现这种处理并没有抑制肿瘤生长(图 60),这表明 193D7 是通过激发抗肿瘤 T 细胞免疫反应来抑制肿瘤生长的。此外,用 193D7 处理罹患肿瘤/mjd1c 的小鼠时,肿瘤的生长没有受到抑制,肿瘤中 细胞的频率没有改变(图 6p,q),肿瘤浸润效应 细胞的数量和效应 T 细胞产生的细胞因子也没有改变(扩展数据图 9a,b)。我们还用 193D7 处理了含 Foxp3-Cre-YFP WT 加 Jmjd11 细胞的 MCA205 肿瘤混合嵌合体(扩展数据图 9a、b)。

JMJD1C-deficient cells in the same tumor tissues, as demonstrated by reduced cell frequency and increased IFN production (Extended Data Fig. 10b,c). These data verify that the effect of 193D7 is on target.
JMJD1C 缺陷的 细胞在相同肿瘤组织中的作用,表现为细胞频率降低和 IFN 产生增加(扩展数据图 10b,c)。这些数据验证了 193D7 的作用是有针对性的。

Discussion 讨论

In the past decade, cancer immunotherapy, especially immune checkpoint blockade (ICB), which boosts antitumor cell response, has led to remarkable clinical advances and become a pillar of cancer therapy. However, the response to this form of therapy is variable, with only a small fraction of patients with tumors able to receive clinical benefit from ICB. It is therefore important to develop new or combination strategies. One factor affecting the efficacy of ICB is the immune-suppressive TME, to which cells make a substantial contribution. Here, we have identified JMJD1C as a tumor cell-specific epigenetic regulator that could be used for selective targeting of tumor cells, provided a potential cell-based tumor immunotherapy strategy and also generated a small compound with high efficacy.
在过去十年中,癌症免疫疗法,尤其是能增强抗肿瘤 细胞反应的免疫检查点阻断疗法(ICB)取得了显著的临床进展,成为癌症疗法的支柱。然而,对这种疗法的反应却不尽相同,只有一小部分肿瘤患者能从 ICB 中获得临床益处。因此,开发新的策略或联合策略非常重要。影响 ICB 疗效的一个因素是免疫抑制 TME,而 细胞在其中发挥了重要作用。在这里,我们发现JMJD1C是一种肿瘤 细胞特异性表观遗传调节因子,可用于选择性靶向肿瘤 细胞,提供了一种潜在的基于 细胞的肿瘤免疫治疗策略,还产生了一种具有高疗效的小化合物。
Epigenetic enzymes are therapeutically targetable via small compounds. Based on the functional essence of JMJD1C for tumor cell fitness, we have developed an inhibitor for JMJD1C, 193D7, which is highly specific for JMJD1C, with no inhibitory activity on intrafamily membersJMJD1A andJMJD1B. Treatment with 193D7 efficiently reduced the frequency of tumor cells with no effect on systemic cells, potentiated an antitumor cell response and led to tumor growth inhibition. Importantly, p.o. administration of 193D7 showed similar efficacy to i.p.injection, which dramatically enhances its applicability and potential for clinical benefit. Mechanistically, JMJD1C controls tumor cell fitness by serving as an integrator for lipid metabolism, AKT signals and STAT3 signals, of which the latter two are both IFN regulators. The ability to coordinating multiple cellular pathways is among the advantages of epigenetic regulation. Activating both AKT and STAT3 signals in the absence of JMJD1C seemed to be able to induce more dramatic IFN production than abrogating one of the pathways alone.
表观遗传酶可通过小化合物进行靶向治疗。基于JMJD1C对肿瘤 细胞健康的功能本质,我们开发了一种JMJD1C抑制剂193D7,它对JMJD1C具有高度特异性,对族内成员JMJD1A和JMJD1B没有抑制活性。用 193D7 治疗可有效降低肿瘤 细胞的频率,但对全身 细胞没有影响,还能增强 细胞的抗肿瘤反应并抑制肿瘤生长。重要的是,193D7口服给药显示出与口服注射相似的疗效,这大大提高了其临床应用性和获益潜力。从机理上讲,JMJD1C通过整合脂质代谢、AKT信号和STAT3信号来控制肿瘤 ,而后两者都是IFN 调节器。能够协调多种细胞通路是表观遗传调控的优势之一。在没有 JMJD1C 的情况下同时激活 AKT 和 STAT3 信号似乎比单独废除其中一个途径能诱导更多的 IFN 产生。
IFN has essential roles in the TME . However, it is currently not possible to modulate IFN as a therapeutic approach, for at least two reasons . First, IFN is a pluripotent cytokine that has both antitumor and protumor activities. Depending on specific settings, it could have opposite effects even on the same type of cell, including cells. In the TME, IFN drives cell fragility and dysfunction, whereas in the draining lymph nodes of lung cancer, IFN enhances the suppressive function of cells . Second, the receptor for IFN is widely expressed on nearly all nucleated cells, and systemic IFN manipulation would result in broad effects. Therefore, to achieve tumor therapy, more mechanistically tailored approaches are needed to selectively manipulate IFN signaling. Here, we showed thatJMJD1C is selectively required for suppressing IFN expression in tumor cells, without affecting other T cell subsets, thus providing a precise IFN manipulation approach for tumor treatment purposes.
IFN 在 TME 中发挥着重要作用。然而,目前还无法将调节 IFN 作为一种治疗方法,原因至少有两个 。首先,IFN 是一种多能细胞因子,具有抗肿瘤和原癌活性。根据具体情况,它甚至可以对同一种细胞(包括 细胞)产生相反的作用。在TME中,IFN 会导致 细胞脆弱和功能障碍,而在肺癌引流淋巴结中,IFN 会增强 细胞的抑制功能 。其次,IFN 的受体在几乎所有有核细胞上都广泛表达,对全身 IFN 的操作会产生广泛的影响。因此,要实现肿瘤治疗,需要更多机制上量身定制的方法来选择性地操纵 IFN 信号。在这里,我们发现JMJD1C选择性地抑制肿瘤 细胞中IFN 的表达,而不影响其他T细胞亚群,从而为肿瘤治疗提供了一种精确的IFN 操纵方法。
By promoting cell fitness in tumors, JMJD1C suppresses the antitumor immune response. Our previous study revealed thatJMJD1C restrains plasma cell differentiation and rheumatoid arthritis, suggesting thatJMJD1C also functions as an immune suppressor in autoimmune settings . Notably, it seems that JMJD1C functions by distinct mechanisms in cells and tumor cells. In B cells, JMJD1C mainly demethylases STAT3 but not H3K9me2, whereas in tumor cells, JMJD1C acts on both substrates. Such a difference could potentially be interpreted in terms of the differential expression levels of JMJD1C in these two cell types, given that tumor cells express very high levels of JMJD1C in response to TME stimulation. Notably, under steady settings, JMJD1C deficiency in B cells did not disrupt B cell immune homeostasis, and even aged mice with Jmjd1cknockout in B cells did not show autoimmune disorders. Therefore, we anticipate that JMJD1C inhibitor treatment would not result in autoantibody-mediated adverse effects. However, for patients with cancer with autoantibody-mediated autoimmune diseases, especially rheumatoid arthritis, JMJD1C-targeting cancer immunotherapy should be carefully evaluated to avoid potential adverse effects.
通过促进肿瘤中 细胞的适存性,JMJD1C 抑制了抗肿瘤免疫反应。我们之前的研究发现JMJD1C抑制浆细胞分化和类风湿性关节炎,这表明JMJD1C在自身免疫环境中也能发挥免疫抑制功能 。值得注意的是,JMJD1C 在 细胞和肿瘤 细胞中似乎通过不同的机制发挥作用。在 B 细胞中,JMJD1C 主要去甲基化 STAT3 而不是 H3K9me2,而在肿瘤 细胞中,JMJD1C 同时作用于这两种底物。鉴于肿瘤 细胞在 TME 刺激下会表达很高水平的 JMJD1C,这种差异有可能被解释为 JMJD1C 在这两种细胞中的不同表达水平。值得注意的是,在稳定的环境下,B细胞中JMJD1C的缺乏并不会破坏B细胞的免疫平衡,甚至B细胞中Jmjd1cknockout的老年小鼠也不会出现自身免疫紊乱。因此,我们预计 JMJD1C 抑制剂治疗不会导致自身抗体介导的不良反应。然而,对于患有自身抗体介导的自身免疫性疾病(尤其是类风湿性关节炎)的癌症患者,JMJD1C靶向癌症免疫疗法应进行仔细评估,以避免潜在的不良反应。

Online content 在线内容

Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41590-024-01746-8 .
任何方法、其他参考文献、《自然》报告摘要、源数据、扩展数据、补充信息、致谢、同行评审信息;作者贡献和竞争利益详情;以及数据和代码可用性声明,均可在 https://doi.org/10.1038/s41590-024-01746-8 上查阅。

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Methods 方法

Mice 小鼠

The Jmjd1 and Stat mice were as described before . To generate Rosa26 mice, a CAG promoter-loxP-PGK-Neo-6*SV40 pA-loxP-Kozak-Mutant-MouseStat3CDS-rBG pA cassette with p.A662C (GCG to TGT) and p.N664C (AAC to TGC) was inserted into the Rosa26 locus using CRISPR-Cas9 by Cyagen Biosciences Inc. Ifng (002287), Foxp3 , Cd4 , Rag1 (002216), B6 (C57BL/6J) and B6-CD45.1(Ptprca Pepcb/BoyJ) mice were obtained from the Jackson Laboratory. All the above mouse strains were maintained on a C57BL/6J background. BALB/c mice were obtained from the Animal Core Facility of Nanjing Medical University. Both male and female mice of 8-12 weeks or 6 months of age were used for analysis. Mice were housed in a specific-pathogen-free environment in the Animal Core Facility of Nanjing Medical University and kept on light/dark cycle; temperature and relative humidity were maintained at and , respectively. Mice were all fed with normal diets ( carbohydrate, protein and fat) purchased from Jiangsu Xietong Pharmaceutical Bio-engineering (no. 1010084). Animal protocols were reviewed and approved by the Institutional Animal Care and Use Committee (IACUC) of Nanjing Medical University (issue no. 2007033) and the IACUC of Shanghai Institute of Materia Medica, Chinese Academy of Sciences (issue no. 2022-06-JHL-28).
Jmjd1 和 Stat 小鼠如前所述 。为了产生 Rosa26 小鼠,Cyagen Biosciences Inc. 使用 CRISPR-Cas9 将带有 p.A662C (GCG 至 TGT) 和 p.N664C (AAC 至 TGC) 的 CAG 启动子-loxP-PGK-Neo-6*SV40 pA-loxP-Kozak-Mutant-MouseStat3CDS-rBG pA 盒插入 Rosa26 基因座。Ifng (002287), Foxp3 , Cd4 , Rag1 (002216), B6 (C57BL/6J) 和 B6-CD45.1(Ptprca Pepcb/BoyJ) 小鼠来自杰克逊实验室。上述所有小鼠品系均以 C57BL/6J 为背景。BALB/c 小鼠来自南京医科大学动物核心实验室。8-12周龄或6个月龄的雌雄小鼠均用于分析。小鼠饲养在南京医科大学动物中心的无特定病原体环境中,光/暗周期为 ,温度和相对湿度分别保持在 。小鼠均饲喂购自江苏协通药业生物工程有限公司(编号:1010084)的普通饲料( 碳水化合物、 蛋白质和 脂肪)。动物实验方案经南京医科大学动物保育和使用委员会(IACUC)(编号:2007033)和中国科学院上海药物研究所动物保育和使用委员会(IACUC)(编号:2022-06-JHL-28)审查批准。

Tumor cell culture and inoculation
肿瘤细胞培养和接种

MCA205 fibrosarcoma cells, B16-F10 and B16-OVA melanoma cells, LLC lung carcinoma cells, EL4 mouse thymic lymphoma cells and Hepa1-6 mouse hepatocellular carcinoma cells were cultured at under in Dulbecco's modified Eagle medium (Gibco) supplemented with fetal bovine serum (FBS; Gibco) and penicillin-streptomycin (Meilunbio). CT26 mouse colorectal carcinoma cells were cultured at under in RPMI-1640 medium (Gibco) supplemented with FBS (Gibco) and penicillin-streptomycin (Meilunbio). All of the cell lines were tested and found to be negative for mycoplasma contamination.
MCA205纤维肉瘤细胞、B16-F10和B16-OVA黑色素瘤细胞、LLC肺癌细胞、EL4小鼠胸腺淋巴瘤细胞和Hepa1-6小鼠肝细胞癌细胞在 ,培养基为Dulbecco改良鹰培养基(Gibco),补充 胎牛血清(FBS;Gibco)和 青霉素-链霉素(Meilunbio)。CT26 小鼠结直肠癌细胞在 ,培养基为 RPMI-1640 培养基(Gibco),添加 FBS(Gibco)和 青霉素-链霉素(美伦生物)。对所有细胞系进行了检测,发现支原体污染均为阴性。
To inoculate recipient mice, MCA205, B16, LLC and EL4 cells and Hepa1-6 cells were subcutaneously injected in the right flanks of mice. Tumors were measured regularly with digital calipers, and tumor volumes were calculated by the following formula: (length width ) (ref. 43). Mice were euthanized before the tumors reached the maximum size permitted by the IACUC .
MCA205、B16、LLC 和 EL4 细胞以及 Hepa1-6 细胞皮下注射到受体小鼠的右腹部。用数字卡尺定期测量肿瘤,并按以下公式计算肿瘤体积:(长 (参考文献 43)。小鼠在肿瘤达到 IACUC 允许的最大尺寸之前被安乐死

In vitro cell stimulation
体外 细胞刺激

MCA205 or B16 tumor tissues were harvested for tumor-bearing mice, minced in RPMI-1640 medium (Gibco) supplemented with FBS (Gibco) through cell strainers and centrifuged for 5 min at . The supernatant was filtered through a filter and adjusted to a concentration of media per gram initial tumor tissue to obtain tumor supernatant for cell culture. To obtain MCA205 cell culture media, confluent MCA205 cells in dishes were replaced with complete growth media, which were gathered 24 h later. The conditioned media were then centrifuged for 5 min at and filtered through a filter. Splenic cells were sorted from Foxp3-YFP reporter mice and cultured with tumor supernatant, cell culture media or cytokines for 3 days on plates coated with anti-CD3 antibody ( ) and anti-CD28 antibody ( ; both from Bio X Cell) in RPMI-1640 medium supplemented with penicillin-streptomycin, nonessential amino acids, sodium pyruvate, L-glutamine, HEPES and -mercaptoethanol. The following antibodies (all from Bio Cell) were used for blocking experiments: anti-IL-1 (B122, ), anti-IL-6(MP5-20F3, ) and anti-TNF (XT3.11, ).
收获肿瘤小鼠的 MCA205 或 B16 肿瘤组织,在补充 FBS(Gibco)的 RPMI-1640 培养基(Gibco)中通过 细胞滤器绞碎,在 下离心 5 分钟。上清液通过 过滤器过滤,并调整至每克初始肿瘤组织含 培养基的浓度,以获得用于细胞培养的肿瘤上清液。为获得 MCA205 细胞培养基, ,将培养皿中汇合的 MCA205 细胞换成完全生长培养基,24 小时后收集。然后将条件培养基在 下离心 5 分钟,并通过 过滤器过滤。从 Foxp3-YFP 报告小鼠脾脏 细胞中分拣出 Foxp3-YFP,并用 肿瘤上清、细胞培养基或细胞因子在涂有抗 CD3 抗体 ( ) 和抗 CD28 抗体 ( .) 的平板上培养 3 天;RPMI-1640 培养基,补充 青霉素-链霉素、 非必需氨基酸、 丙酮酸钠、 L-谷氨酰胺、 HEPES 和 -巯基乙醇。阻断实验使用了以下抗体(均来自 Bio Cell):抗 IL-1 (B122, )、抗 IL-6(MP5-20F3, ) 和抗 TNF (XT3.11, )。

Flow cytometry 流式细胞仪

Spleen and lymph nodes were collected, mashed and then filtered through cell strainers to obtain single-cell suspensions. Tumors were minced into small pieces in RPMI containing FBS, penicillin-streptomycin, DNaseI ( ;Sigma-Aldrich) and collagenase ( ;Sigma-Aldrich) and digested for 60 min at , followed by filtration with a cell strainer. Tumor-infiltrating lymphocytes were then isolated over a Percoll density gradient (GE Healthcare) by centrifugation at for at room temperature.
收集脾脏和淋巴结,捣碎后通过 细胞过滤器过滤,获得单细胞悬浮液。在含有 FBS、 青霉素-链霉素、DNaseI ( ;Sigma-Aldrich) 和胶原酶 ( ;Sigma-Aldrich) 的 RPMI 中将肿瘤切成小块,在 下消化 60 分钟,然后用 细胞过滤器过滤。然后在 下离心,在室温下用 Percoll 密度梯度仪(GE Healthcare)分离出肿瘤浸润淋巴细胞,
For surface staining, cells were collected and incubated in phosphate-buffered saline containing bovine serum albumin with the indicated antibodies for at . For staining of Foxp3, a Foxp3/transcription factor staining buffer set (eBioscience) was used according to the manufacturer's instructions. For staining of intracellular cytokines, cells were stimulated for at using Leukocyte Activation Cocktail (BD Biosciences) and then permeabilized with a Cytofix/Cytoperm fixation/permeabilization kit (BD Biosciences) before intracellular staining. The following fluorescent conjugate-labeled antibodies were used: anti-CD4 (GK1.5;1:400), anti-CD8 (53-6.7;1:100), anti-CD44 (1M7;1:400), anti-CD45 (30-F11; 1:200), anti-CD45.1 (A20; 1:200), anti-CD45.2 (104;1:200), anti-Ki67 (16A8; 1:200), anti-PD1 (RMP1-30;1:200), anti-IFN (XMG1.2;1:100), anti-TNF (MP6-XT22;1:200), anti-Foxp3 (MF-14;1:200) (all from BioLegend); anti-Foxp3 (FJK-16s; 1:400), anti-NRP1 (3DS304M: 1:200), anti-CD62L (MEL-14;1:400) (all from eBioscience) and anti-IL-17A (TC1118H10;1:200) (BD Biosciences). Fluorescence-activated cell sorting data were collected with a BD FACSDIVA v.8.0.2 or Beckman CytExpert v.2.4 and analyzed with FlowJo v.10.
为了进行表面染色,收集细胞并在含 牛血清白蛋白的磷酸盐缓冲液中与指定抗体孵育 。为了对 Foxp3 进行染色,根据生产商的说明使用 Foxp3/转录因子染色缓冲液组(eBioscience)。细胞内细胞因子染色时,使用 Leukocyte Activation Cocktail(BD Biosciences)在 刺激细胞 ,然后用 Cytofix/Cytoperm 固定/透化试剂盒(BD Biosciences)透化细胞,再进行细胞内染色。使用了以下荧光共轭标记抗体:抗-CD4(GK1.5;1:400)、抗-CD8 (53-6.7;1:100)、抗-CD44(1M7;1:400)、抗-CD45(30-F11;1:200)、抗-CD45.1(A20;1:200)、抗-CD45.2(104;1:200)、抗-Ki67(16A8;1:200)、抗-PD1(RMP1-30;1:200)、抗-IFN (XMG1.2;1:100)、抗 TNF(MP6-XT22;1:200)、抗 Foxp3(MF-14;1:200)(均来自 BioLegend);抗 Foxp3(FJK-16s;1:400)、抗 NRP1(3DS304M:1:200)、抗 CD62L(MEL-14;1:400)(均来自 eBioscience)和抗 IL-17A (TC1118H10;1:200)(BD Biosciences)。荧光激活细胞分拣数据用 BD FACSDIVA v.8.0.2 或 Beckman CytExpert v.2.4 采集,并用 FlowJo v.10 进行分析。
For intracellular phosphorylated protein staining, cells were instantly fixed with paraformaldehyde and permeabilized with cold methanol at overnight and then stained with pSTAT3 (phosphorylated at Tyr705;1:100), pAKT (phosphorylated at Thr 308;1:100) and pS6 (phosphorylated at Ser 235 and Ser 236;1:100) (all from Cell Signaling Technology), followed by biotinylated goat anti-rabbit IgG (BD Biosciences) and streptavidin-Alexa 647 (Invitrogen). Fixable viability dye (eBioscience) was used for dead-cell exclusion.
为进行细胞内磷酸化蛋白染色,用 多聚甲醛瞬间固定细胞,并在 下用冷甲醇渗透过夜,然后用 pSTAT3(在 Tyr705 处磷酸化;1:100)、pAKT(在 Thr 308 处磷酸化;1:100)和 pS6(在 Ser 235 和 Ser 236 处磷酸化;1:100)(均来自 Cell Signaling Technology),然后用生物素化山羊抗兔 IgG(BD Biosciences)和链霉亲和素-Alexa 647(Invitrogen)染色。固定活力染料(eBioscience)用于排除死细胞。

Ex vivo suppression assay
体内外抑制试验

cells from the spleens of CD45.1 mice were enriched using a negative selection kit (MojoSort Mouse CD8T Cell Isolation Kit; BioLegend) and labeled with a CellTrace Violet (CTV) Cell Proliferation Kit (Thermo Fisher Scientific) for at . A total of cells were seeded into a 96 -well round-bottomed plate in RPMI medium consisting of . cells (CD45.2) isolated from splenocytes or tumor-infiltrating lymphocytes of Jmjd1c or Jmjd1c mice were added according to the indicated ratios of cells to effector cells in the presence of mitomycin-treated splenocytes and anti-CD3 in round-bottomed 96 -well plates. Cells were incubated at under for , and the proliferation of cells was determined by CellTrace Violet dilution with flow cytometry analysis .
使用阴性选择试剂盒(MojoSort Mouse CD8T Cell Isolation Kit; BioLegend)对来自 CD45.1 小鼠脾脏的细胞进行富集,并用 CellTrace Violet (CTV) 细胞增殖试剂盒(Thermo Fisher Scientific)进行标记, , 。将 细胞播种到 96 孔圆底板中,RPMI 培养基由 组成。 细胞(CD45.2),并在有 丝裂霉素处理的脾细胞和 抗 CD3 存在的情况下,按照 细胞与效应 细胞的指定比例加入 Jmjd1c 或 Jmjd1c 小鼠的脾细胞或肿瘤浸润淋巴细胞,圆底 96 孔板。细胞在 下孵育 ,并通过 CellTrace 紫稀释和流式细胞仪分析测定 细胞的增殖 。

scRNA-seq and data processing
scRNA 序列和数据处理

cells were sorted from MCA205-tumor-bearing and Jmjd1 mice. Immediately after sorting, the cells were run on a 10x Chromium (10x Genomics) and then subjected to library preparation by Capitalbio Technology Inc. following the recommended protocol for the Chromium Single Cell3' Reagent Kit (v.3.1).
从携带 MCA205 肿瘤的 和 Jmjd1 小鼠中分拣出细胞。分选后,细胞立即在 10x Chromium(10x Genomics)上运行,然后由 Capitalbio Technology Inc.按照 Chromium Single Cell3' Reagent Kit (v.3.1) 的推荐方案进行文库制备。
Raw fastq data were processed using CellRanger (v.5.0.1) count with refdata-cellranger-mm10 reference ( ) from Genomics. The barcode file, feature file and matrix file were processed using R package Seurat (v.4.3.0) via RStudio (2022.07.1 Build 554). A WT group with 3,905 cells and group with 4,105 cells were filtered, and we obtained cells with more than 500 genes. Then, the gene expression matrix was normalized using the NormalizeData function. We selected the top 2,000 highly variable genes using the FindVariableFeatures function. Then, two groups of cells were integrated using the FindIntegrationAnchors and IntegrateData functions in Seurat with the first
原始 fastq 数据用 CellRanger(v.5.0.1)计数器处理,并使用 Genomics 提供的 refdata-cellranger-mm10 reference ( )。通过 RStudio (2022.07.1 Build 554) 使用 R 软件包 Seurat (v.4.3.0) 处理条形码文件、特征文件和矩阵文件。筛选出含 3905 个细胞的 WT 组和含 4105 个细胞的 组,并获得含有 500 个以上基因的细胞。然后,使用 NormalizeData 函数对基因表达矩阵进行归一化处理。我们使用 FindVariableFeatures 函数选取了前 2000 个高变异基因。然后,使用 Seurat 中的 FindIntegrationAnchors 和 IntegrateData 函数对两组细胞进行整合,其中第一组为
20 principal components. We obtained 7,925 total tumor cells. In total, 15,388 genes were retained after discarding genes expressed in fewer than five cells. The data were scaled and subjected to principal component analysis. The first 20 principal components were used for -SNE for visualization and graph-based clustering with a resolution of 0.8 . Cell clusters were annotated based on a previous publication , and redimension reduction was performed using linear discriminant analysis with annotated cells. After that, -SNE was reused based on linear discriminant analysis for visualization. Differentially expressed genes were characterized using the FindAllMarkers function with 'RNA' assay. GSEA was performed using GSEA software (v.4.1.0) as the default model.
20 个主成分。我们共获得了 7,925 个肿瘤 细胞。剔除在少于5个细胞中表达的基因后,共保留了15,388个基因。数据经缩放后进行主成分分析。前 20 个主成分用于 -SNE 可视化和基于图形的聚类,分辨率为 0.8。细胞簇是根据之前发表的 进行注释的,并利用注释细胞的线性判别分析进行重维度缩减。之后,基于线性判别分析重新使用 -SNE 进行可视化。使用 FindAllMarkers 功能和 "RNA "检测法对差异表达基因进行表征。使用 GSEA 软件(v.4.1.0)作为默认模型进行 GSEA。
For analysis of public scRNA-seq data (GSE98638), cells in GSE98638 ('C08_CD4-CTLA4' and 'C07_CD4-FOXP3') were reclustered using R package Seurat (v.4.3.0) via RStudio (2022.07.1 Build 554). Briefly, 843 cells were renormalized using the NormalizeData function. We selected the top 2,000 highly variable genes with the FindVariableFeatures function. Then, the data were scaled and subjected to principal component analysis. The first ten principal components were used for -SNE for visualization and graph-based clustering with a resolution of 0.4 . Seven clusters were obtained, and dot plots were constructed using the DotPlot function. Pseudotime analysis was performed via debugged monocle 2.24.1 and slingshot 2.6.0 to characterize the trajectory.
为了分析公开的scRNA-seq数据(GSE98638), GSE98638中的细胞('C08_CD4-CTLA4'和'C07_CD4-FOXP3'),使用R软件包Seurat(v.4.3.0)通过RStudio(2022.07.1 Build 554)重新聚类。简而言之,使用 NormalizeData 函数对 843 个细胞进行了重新归一化。我们使用 FindVariableFeatures 函数选取了前 2000 个高变异基因。然后,对数据进行缩放并进行主成分分析。前十个主成分用于 -SNE 可视化和基于图形的聚类,分辨率为 0.4。得到了七个聚类,并使用 DotPlot 函数绘制了点阵图。通过调试 monocle 2.24.1 和 slingshot 2.6.0 进行伪时间分析,以确定轨迹特征。

CUT&RUN-seq analysis and data processing
CUT&RUN-seq 分析和数据处理

In vitro stimulated cells ( ) were fixed in formaldehyde for the CUT&RUNassay using a Hyperactive pG-MNaseCUT&RUNAssay Kit for Illumina (Vazyme). The cells were collected and bound to ConA beads for at , then washed and incubated with of the indicated antibodies at overnight, followed by a further incubation with -MNase enzyme for at before being digested on ice with for . Then, 10 pg spike-in DNA was added to each sample to calibrate samples in a series. Digestion was stopped using a stop buffer, and cells were incubated at to release digested chromatin. Released DNA was collected with DNA magnetic beads (Vazyme) for library construction according to the manufacturer's instructions.
体外刺激 细胞 ( ) 在 甲醛中固定,使用用于 Illumina 的 Hyperactive pG-MNaseCUT&RUNAssay Kit (Vazyme)进行 CUT&RUN 分析。收集 细胞并与 ConA 珠结合, ,然后洗涤并与 的指定抗体孵育, ,过夜,然后与 -MNase 酶进一步孵育, ,然后在冰上与 消化, 。然后,在每个样品中加入 10 pg 加标 DNA,以校准系列样品。使用停止缓冲液停止消化,然后在 孵育细胞以释放消化的染色质。用 DNA 磁珠(Vazyme)收集释放的 DNA,按照制造商的说明构建文库。
Raw paired-end sequenced reads were first cut for adapter sequences and trimmed using trim_galore (v.0.6.6). Then, cleaned fastq data were mapped to the mm10 reference genome using Bowtie 2 (v.2.4.2). Picard was used for marking and removal of duplication. SAMtools (v.1.11) was used to convert and sort the SAM files into BAM format. Homer (4.11-pl5321h9f5acd7_7) was used for peak calling. Totals of 25,011 and 23,007 STAT3-binding peaks and 30,933 and 28,206 peaks were obtained fromJmjd1c WT and KO tumor cells, respectively. deepTools was used to normalize signals from sorted BAM files via bamCoverage, and computeMatrix was used to calculate the overall signal distribution around the peak center called by Homer using the 'reference-point' model. Data were visualized using plotProfile and plotHeatmap in deepTools.
首先对原始成对端测序读数进行适配序列切割,并使用 trim_galore(v.0.6.6)进行修剪。然后,使用 Bowtie 2(v.2.4.2)将清理后的 fastq 数据映射到 mm10 参考基因组。Picard 用于标记和去除重复。SAMtools (v.1.11) 用于将 SAM 文件转换和分类为 BAM 格式。Homer (4.11-pl5321h9f5acd7_7) 用于峰值调用。从 Jmjd1c WT 和 KO 肿瘤 细胞中分别获得了 25,011 和 23,007 个 STAT3 结合峰以及 30,933 和 28,206 个 峰。deepTools 用于通过 bamCoverage 对分类 BAM 文件中的信号进行归一化处理,computeMatrix 用于使用 "参考点 "模型计算 Homer 调用的峰中心周围的总体信号分布。使用 deepTools 中的 plotProfile 和 plotHeatmap 对数据进行可视化。

ATAC-seq analysis and data processing
ATAC-seq 分析和数据处理

cells were sorted from spleen and tumor tissues in MCA205-tumorbearing Foxp3-YFP WT mice. ATAC-seq was performed by Active Motif. Inc. Briefly, cells were lysed, and nuclei were incubated with tagmentation enzyme. Libraries were purified and sequenced on Illumina's NovaSeq 6000 .
Foxp3-YFP WT 小鼠的脾脏和肿瘤组织中分拣出细胞。ATAC-seq由Active Motif.Inc.公司(Active Motif.Inc.)进行了 ATAC-seq 分析。简而言之,细胞裂解,细胞核与标记酶孵育。纯化文库并在 Illumina 的 NovaSeq 6000 上测序。
Raw paired-end sequenced reads were first cut for adapter sequences and trimmed using trim_galore (v.0.6.6). Then, cleaned fastq data were mapped to the mm10 reference genome using Bowtie 2 (v.2.4.2). Picard was used to mark and remove duplication. SAMtools (v.1.11) was used to convert and sort the SAM files into BAM format. Homer (4.11-pl5321h9f5acd7_7) was used for peak calling. A total of 27,655 and 13,089 peaks were obtained from tumor and spleen cells, respectively. deepTools was used to normalize signals from sorted BAM files via bamCoverage, and computeMatrix was used to calculate the overall signal distribution around the peak center called by Homer using the 'reference-point' model. Data were visualized using plotProfile and plotHeatmap in deepTools.
首先对原始成对端测序读数进行适配序列切割,并使用 trim_galore(v.0.6.6)进行修剪。然后,使用 Bowtie 2(v.2.4.2)将清理后的 fastq 数据映射到 mm10 参考基因组。Picard 用于标记和去除重复。SAMtools (v.1.11) 用于将 SAM 文件转换和分类为 BAM 格式。Homer (4.11-pl5321h9f5acd7_7) 用于峰值调用。从肿瘤细胞和脾脏 细胞中分别获得了 27,655 和 13,089 个峰。deepTools 通过 bamCoverage 对分类 BAM 文件中的信号进行归一化处理,computeMatrix 则用于使用 "参考点 "模型计算 Homer 调用的峰中心周围的总体信号分布。使用 deepTools 中的 plotProfile 和 plotHeatmap 对数据进行可视化。

EAE model EAE 模型

Mice were immunized subcutaneously with l of emulsified complete Freund's adjuvant and MOG35-55 peptide (MEVGWYRSPFSRVVHLYRNGK) and received intravenous injections of pertussis toxin at the time of immunization, repeated later. Mice were assigned scores daily on a scale of in a double-blind manner with the following criteria: 0 , no disease; 1 , tail paralysis; 2 , wobbly gait; 3 , hind limb paralysis; 4 , forelimb paralysis; and 5, moribund or dead. Gradations of 0.5 were assigned to mice exhibiting signs that fell between two of the scores listed above.
l 乳化的完全弗罗因德佐剂和 MOG35-55 肽 (MEVGWYRSPFSRVVHLYRNGK)对小鼠进行皮下注射免疫,并在免疫时静脉注射 百日咳毒素,之后重复注射 。小鼠每天按 的评分标准进行评分,评分采用双盲法,标准如下:0分,无病;1分,尾部麻痹;2分,步态摇摆;3分,后肢麻痹;4分,前肢麻痹;5分,奄奄一息或死亡。如果小鼠的体征介于上述两个评分之间,则将其分为 0.5 级。

Virtual screening of small-molecule JMJD1C inhibitors
虚拟筛选小分子 JMJD1C 抑制剂

An equivariant graph neural-network-based model named EquiScore was established to assess the likelihood of a ligand binding to a target protein of interest. E(3)-equivariant architecture was employed to preserve the known transformation properties of physical systems under changes in ligand coordinates, and thus the model explicitly captures the geometric relationship of protein-ligand complexes, resulting in information-rich representations of ligand-binding environments . A comprehensive dataset containing 344,852 protein-ligand binding complexes was collected as modeling data to train the scoring model, with the objective of discriminating positive (true) from negative (false) ligand-binding complexes. The protein-ligand complex structures collected from the Protein Data Bank were redocked to generate various poses, where the original protein-ligand binding poses and the docking-generated poses with low root mean square deviation from the original were considered to be positive data; the poses of 'decoy' ligands generated by cross-docking and a deep generative model were considered to be negatives. The dataset was split into a training and a validation set at a ratio of 4:1. Agrid search was used to determine hyperparameters of the model, with F1-score on the validation set as the performance metric. In benchmarking on two external sets, DUDE and DEKOIS 2.0 (ref. 49), the final model showed top enrichment rates of 17.67 and 16.83 , respectively, indicating substantially improved virtual screening capability.
我们建立了一个基于等变图神经网络的模型,名为 EquiScore,用于评估配体与目标蛋白质结合的可能性。该模型采用E(3)-等变结构,以保持配体坐标变化时物理系统的已知变换特性,从而明确捕捉蛋白质配体复合物的几何关系,从而获得配体结合环境的丰富信息表征 。为了训练评分模型,我们收集了一个包含 344,852 个蛋白质配体结合复合物的综合数据集作为建模数据,目的是区分阳性(真)和阴性(假)配体结合复合物。对从蛋白质数据库中收集的蛋白质配体复合物结构进行重新对接,生成各种姿势,其中原始蛋白质配体结合姿势和对接生成的姿势与原始姿势均方根偏差较小的被视为阳性数据;交叉对接 和深度生成模型 生成的 "诱饵 "配体姿势被视为阴性数据。数据集按 4:1 的比例分成训练集和验证集。使用阿格里德搜索确定模型的超参数,并以验证集上的 F1 分数作为性能指标。在两个外部集 DUDE 和 DEKOIS 2.0(参考文献 49)上进行的基准测试中,最终模型的最高 富集率分别为 17.67 和 16.83,表明虚拟筛选能力大大提高。
EquiScore was used to screen an in-house lead-like molecule database containing 19,000 compounds (mean molecular weight 368.9 Da; mean Alog ) to discover potential JMJD1C inhibitors. First, the Schrödinger suite of molecular modeling software (Schrödinger LLC) was used to generate putative binding poses of the compounds. The crystal structure of the catalytic domain of human JMJD1C (PDB ID: 5FZO) was prepared with the Protein Preparation Wizard, and Receptor Grid Generation was used to set up a three-dimensional grid box of around the center of the active site of JMJD1C. The compounds were prepared with LigPrep to generate all plausible tautomers and stereoisomers within a range of , which were docked into the grid using Glide (v.8.9) standard precision. Then, all the generated docking poses were scored using EquiScore, and the top 500 hits were clustered into 112 categories based on the Euclidean distance between compounds with 1,024-bit ECFP4 (a Butina module in RDKit in which distThresh was set to 0.26) to obtain an array of structurally diverse compounds. In each category, only the top compound was selected. Finally, the top 100 candidate compounds were evaluated by followed biochemical experiments.
EquiScore 被用来筛选包含 19,000 个化合物(平均分子量 368.9 Da;平均 Alog )的内部类先导分子数据库,以发现潜在的 JMJD1C 抑制剂。首先,使用 Schrödinger 套装分子建模软件(Schrödinger LLC)生成化合物的假定结合位置。使用蛋白质制备向导(Protein Preparation Wizard)制备了人 JMJD1C 催化结构域的晶体结构(PDB ID:5FZO),并使用受体网格生成(Receptor Grid Generation)软件在 JMJD1C 活性位点中心周围设置了一个 的三维网格框。使用 LigPrep 制备化合物,生成 范围内所有可能的同分异构体和立体异构体,并使用 Glide (v.8.9) 标准精度将其对接到网格中。然后,使用 EquiScore 对所有生成的对接姿势进行评分,并根据化合物与 1,024 位 ECFP4(RDKit 中的 Butina 模块,其中 distThresh 设置为 0.26)之间的欧氏距离,将前 500 个命中化合物聚类为 112 个类别,从而获得结构多样的化合物阵列。在每个类别中,只选取排名靠前的化合物。最后,对前 100 个候选化合物进行后续生化实验评估。
Plasmid construction and protein expression and purification The fragment encoding residues 2,147-2,488 of JMJD1C was inserted into a plasmid pET28A vector with His tag. Vector NTI v.11.5.1 was used for DNA sequence analysis. Then, His-tagged JMJD1C plasmids were transformed into BL21 (DE3) gold-competent cells, and
质粒构建、蛋白表达和纯化 将编码 JMJD1C 残基 2,147-2,488 的片段插入带有 His 标记的质粒 pET28A 载体。使用 Vector NTI v.11.5.1 进行 DNA 序列分析。然后,将 His 标记的 JMJD1C 质粒转化到 BL21 (DE3) 金标适配细胞中,并将 JMJD1C 质粒转化到 BL21 (DE3) 金标适配细胞中。

the cells were grown in lysogeny broth medium and induced with isopropyl- -D-galactoside for at . Cells were harvested by centrifugation, resuspended in buffer containing HEPES and imidazole, and lysed by sonication. The supernatant was loaded on a HisTrap HP column (17524802, GE Healthcare) and eluted with buffer containing HEPES , and imidazole. The fractions containingJMJD1C recombinant protein were further purified on a Superdex 200 Increase 10/300 GL column ( 28990944 , GE Healthcare) using 20 mM HEPES as a running buffer. The purified proteins were concentrated and stored at .
在溶菌肉汤培养基中培养细胞,并用 isopropyl- -D-galactoside 进行诱导, 。离心收获细胞,重悬于含 HEPES 亚咪唑的缓冲液中,然后超声裂解。上清液装入 HisTrap HP 柱(17524802,GE Healthcare),用含有 HEPES 亚胺唑的缓冲液洗脱。含有 JMJD1C 重组蛋白的馏分在 Superdex 200 Increase 10/300 GL 色谱柱(28990944 , GE Healthcare)上进一步纯化,使用 20 mM HEPES 作为运行缓冲液。纯化的蛋白质浓缩后储存于

HTRF assay HTRF 检测

A His-tagged JMJD1C recombinant protein and biotin-labeled H3K9me2 peptide (ARTKQTAR-K(Me2)-STGGKAPRKQLA-GGYK (Biotin)-NH2) were used for the HTRF assay. The HTRF assay was carried out in an assay buffer containing HEPES and bovine serum albumin. The total volume of the assay was . sample of the indicated compound was added to an OptiPate-384 assay plate (6007299, PerkinElmer), andJMJD1C recombinant protein (final concentration ) was diluted in the assay buffer and also added to the OptiPate- 384 assay plate in a volume of . After incubation at room temperature, l of biotin-labeled H3K9me2 peptide (final concentration ) was added. After incubation at room temperature, of a solution of monoclonal antibodies (anti-6HIS-Tb cryptate (61HISTLB, Cisbio; dilution ratio 1:200) and anti-streptavidin-XL665 (610SAXLA, Cisbio; dilution ratio 1:200)) diluted with assay buffer was added to each well. After 60 min incubation at room temperature, the HTRF signal was measured on a TECAN Spark with excitation wavelength of and emission wavelengths of 620 and . Data were analyzed using GraphPad Prism software.
His 标记的 JMJD1C 重组蛋白和生物素标记的 H3K9me2 肽(ARTKQTAR-K(Me2)-STGGKAPRKQLA-GGYK (Biotin)-NH2)用于 HTRF 检测。HTRF 检测在含有 HEPES 牛血清白蛋白的检测缓冲液中进行。 所示化合物样品加入 OptiPate-384 检测板(6007299,PerkinElmer 公司),JMJD1C 重组蛋白(最终浓度 )在检测缓冲液中稀释后加入 OptiPate-384 检测板,加入量为 室温孵育后,加入 l 生物素标记的 H3K9me2 肽(最终浓度 )。 室温孵育后,在每个孔中加入用检测缓冲液稀释的单克隆抗体(抗 6HIS-Tb cryptate (61HISTLB, Cisbio; 稀释比 1:200)和抗链霉亲和素-XL665 (610SAXLA, Cisbio; 稀释比 1:200))溶液 。室温孵育 60 分钟后,在 TECAN Spark 上测量 HTRF 信号,激发波长为 ,发射波长为 620 和 。使用 GraphPad Prism 软件分析数据。

SPR assay SPR 检测

SPR experiments were performed on a Biacore instrument (GE Healthcare) at in a running buffer containing , . The purified JMJD1C recombinant protein was covalently immobilized onto a CM5 sensor chip at using a standard amine-coupling procedure in sodium acetate ) with running buffer ( HEPES ). Then, serially diluted compounds were injected individually in a multicycle kinetic mode (contact time , flow rate per min, dissociation time ). The equilibrium dissociation constant ( was obtained by kinetic fitting.
SPR 实验在 Biacore 仪器(GE Healthcare)上进行, ,运行缓冲液中含有 , 。纯化的 JMJD1C 重组蛋白被共价固定在 CM5 传感器芯片上, ,使用标准胺偶联程序,在 乙酸钠 ) 和运行缓冲液 ( HEPES ) 中进行。然后,以多循环动力学模式(接触时间 ,流速 每分钟,解离时间 )分别注入连续稀释的化合物。通过动力学拟合得到平衡解离常数 ( )。

In vitro enzymatic activity assay
体外酶活性测定

The inhibitory profiles of compound 193D7 against a panel of 14 histone demethylases comprisingJMJD2A, JMJD2B,JMJD2C,JMJD2D, JMJD2E, UTX,PHF8,JMJD1A,JMJD1B,JMJD3,LSD1,JARID1A,JARID1B andJARID1C were determined through the enzyme profiling service of Shanghai ChemPartner Co., Ltd.
化合物 193D7 对 14 种组蛋白去甲基化酶(包括 JMJD2A、JMJD2B、JMJD2C、JMJD2D、JMJD2E、UTX、PHF8、JMJD1A、JMJD1B、JMJD3、LSD1、JARID1A、JARID1B 和 JARID1C)的抑制谱是通过上海睿智化学有限公司的酶谱分析服务测定的。

In vitro demethylase assay and western blotting
体外去甲基化酶测定和蛋白质印迹分析

The assay was performed as previously described with slight modifications . The demethylation reaction was performed at for in reaction buffer Tris- -ketoglutarate and ascorbic acid) containing purified JMJD1C and substrate . Then,193D7 was added at a concentration in the range to . Western blot analysis was performed using anti-H3K9me2 (Abcam; ) to detect inhibition effects.
测定方法如前所述,略加修改后进行 。去甲基化反应在 的反应缓冲液 Tris- -ketoglutarate and ascorbic acid)中进行,缓冲液中含有纯化的 JMJD1C 底物 。然后加入 193D7,浓度范围为 。使用抗-H3K9me2 (Abcam; ) 进行 Western 印迹分析以检测抑制作用。
Other antibodies used for western blotting included anti-STAT3 (Cell Signaling; ), anti- -actin (Cell Signaling; ), anti-JMJD1C (MBL International; 1:1,000), anti-methylated lysine (Abcam; 1:500), anti-H3 (Cell Signaling; 1:2,000), anti-H3K9me1 (Cell Signaling;1:2,000) and anti-Foxp3 (Abcam:1:1,000).
用于 Western 印迹的其他抗体包括抗 STAT3(Cell Signaling; )、抗 -actin (Cell Signaling; )、抗 JMJD1C(MBL International;1:1,000)、抗甲基化赖氨酸(Abcam;1:500)、抗 H3(Cell Signaling;1:2,000)、抗 H3K9me1(Cell Signaling;1:2,000)和抗 Foxp3(Abcam:1:1,000)。

Pharmacokinetic study 药代动力学研究

Pharmacokinetic profiles were determined in male BALB/c mice, and the experimental protocol was approved by an institutional animal care and use committee at the Shanghai Institute of Materia Medica, Chinese Academy of Sciences (IACUC issue no. 2022-06-JHL-28). Test compound 193D7 was dissolved in a solution containing dimethyl sulfoxide, PEG400 and hydroxypropyl- -cyclodextrin in water ) and administered via i.p. injection at or p.o. at . Serial blood samples were collected and 24 hafter dosing and centrifuged to obtain the plasma fraction. aliquot of plasma was deproteinized with lacetonitrile:methanol containing an internal standard. After centrifugation, the supernatant was diluted with acetonitrile:water , mixed and centrifuged at for . Finally, the aliquots of the diluted supernatant were injected into a liquid chromatography and tandem mass spectrometry system.
雄性 BALB/c 小鼠的药代动力学曲线由中国科学院上海药物研究所的机构动物保护与使用委员会批准(IACUC 编号:2022-06-JHL-28)。试验化合物 193D7 溶于含二甲基亚砜、PEG400 和 hydroxypropyl- -cyclodextrin 的水溶液中 ),并通过静脉注射 或局部注射 给药。 等分血浆用 含有内标物的乙腈:甲醇 进行去蛋白处理。离心后,上清液用乙腈:水 稀释,混合后在 离心, 。最后,将等分的稀释上清液注入液相色谱和串联质谱系统。

Statistical analysis 统计分析

Prism v. 9 software was used to analyze data. Results are expressed as mean s.e.m. or mean s.d., as indicated, and were analyzed by unpaired two-tailed Student's -test or Wilcoxon rank-sum test. Two-way analysis of variance (ANOVA) was used to compare tumor growth curves and EAE disease scores. For comparisons of multiple groups, one-way ANOVA with Tukey's test was used. was considered to indicate statistical significance. No statistical methods were used to predetermine sample sizes, but our sample sizes were similar to those reported in previous publications . When unpaired two-tailed Student's -tests were used, the data distribution was assumed to be normal, but this was not formally tested. We did not use a randomization protocol, and experimental groups were based on genotype of mice. Data collection and analysis were not performed blind to the conditions of the experiments. No data points were excluded.
使用 Prism v. 9 软件分析数据。结果以平均值 s.e.m.或平均值 s.d.(如有标示)表示,并通过非配对双尾学生 检验或 Wilcoxon 秩和检验进行分析。双向方差分析(ANOVA)用于比较肿瘤生长曲线和EAE疾病评分。对于多组比较,采用单因素方差分析和Tukey's检验。 被认为具有统计学意义。没有使用统计方法来预先确定样本量,但我们的样本量与之前出版物 中报告的样本量相似。在使用非配对双尾学生 检验时,假定数据分布为正态分布,但未进行正式检验。我们没有使用随机化方案,实验组是根据小鼠的基因型划分的。数据收集和分析不在实验条件盲目的情况下进行。没有排除任何数据点。

Reporting summary 报告摘要

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
有关研究设计的更多信息,请参阅本文链接的《自然组合报告摘要》。

Data availability 数据可用性

scRNA-seq data have been deposited in the GEO database under accession code GSE223930. ATAC-seq and CUT&RUN-seq data have been deposited in GEO under accession code GSE224084. Publicly available datasets accessed for use in this manuscript include GSE139325, GSE108989, GSE98638 and GSE99254. Source data are provided with this paper.
scRNA-seq 数据已存入 GEO 数据库,加入代码为 GSE223930。ATAC-seq 和 CUT&RUN-seq 数据已存入 GEO 数据库,登录代码为 GSE224084。本稿件中使用的公开数据集包括 GSE139325、GSE108989、GSE98638 和 GSE99254。本文随附源数据。

Code availability 代码可用性

The codes for scRNA-seq, ATAC-seq and CUT&RUN data analyses reported in this study have been deposited at GitHub (https://github. com/YuliangWang316/JMJD1C_Treg). Any additional information required to re-analyze the data is available from the corresponding authors upon request.
本研究中报告的scRNA-seq、ATAC-seq和CUT&RUN数据分析的代码已存入GitHub ( https://github. com/YuliangWang316/JMJD1C_Treg)。重新分析数据所需的其他信息可向相应作者索取。

References 参考资料

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    Ni, X. et al. YAP 对 Treg 介导的抗肿瘤免疫抑制至关重要。Cancer Discov.8, 1026-1043 (2018).
  2. Zhang, L. et al. Histone methyltransferase Nsd2 ensures maternal-fetal immune tolerance by promoting regulatory T-cell recruitment. Cell. Mol. Immunol. 19, 634-643 (2022).
    组蛋白甲基转移酶 Nsd2 通过促进调节性 T 细胞招募确保母胎免疫耐受。Cell.Mol.Immunol.19, 634-643 (2022).
  3. Batzner, S. et al. E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials. Nat. Commun. 13, 2453 (2022).
    Batzner, S. et al. E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials.Nat.Nat.13, 2453 (2022).
  4. Shen, C. et al. The impact of cross-docked poses on performance of machine learning classifier for protein-ligand binding pose prediction. J. Cheminform. 13, 81 (2021).
    Shen, C. et al. 交叉对接姿势对蛋白质配体结合姿势预测机器学习分类器性能的影响。J. Cheminform.13, 81 (2021).
  5. Imrie, F., Bradley, A. R. & Deane, C. M. Generating propertymatched decoy molecules using deep learning. Bioinformatics 37, 2134-2141 (2021).
    Imrie, F., Bradley, A. R. & Deane, C. M. 使用深度学习生成属性匹配的诱饵分子。Bioinformatics 37, 2134-2141 (2021).
  6. Mysinger, M. M., Carchia, M., Irwin, J. J. & Shoichet, B. K. Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking. J. Med. Chem. 55, 6582-6594 (2012).
    Mysinger, M. M., Carchia, M., Irwin, J. J. & Shoichet, B. K. Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking.J. Med.Chem.55, 6582-6594 (2012).
  7. Bauer, M. R., Ibrahim, T. M., Vogel, S. M. & Boeckler, F. M. Evaluation and optimization of virtual screening workflows with DEKOIS 2.0-a public library of challenging docking benchmark sets. J. Chem. Inf. Model. 53, 1447-1462 (2013).
    Bauer, M. R., Ibrahim, T. M., Vogel, S. M. & Boeckler, F. M. Evaluation and optimization of virtual screening workflows with DEKOIS 2.0-a public library of challenging docking benchmark sets.J. Chem.Inf.Model.53, 1447-1462 (2013).
  8. Luo, D. et al. Deltex 2 represses MyoD expression and inhibits myogenic differentiation by acting as a negative regulator of Jmjd1c. Proc. Natl Acad. Sci. USA 114, E3O71-E3080 (2017).
    Luo, D. 等人 Deltex 2 通过作为 Jmjd1c 的负调控因子抑制 MyoD 的表达并抑制成肌分化。Proc.Natl Acad.USA 114, E3O71-E3080 (2017)。

Acknowledgements 致谢

We thank Z. Qin (Institute of Biophysics, Chinese Academy of Sciences) for providing MCA2O5 cells. This study was supported by the National Natural Science Foundation of China (grant numbers 32330036 to X.W., T222502 to M.Z., 81825018 to J.Q., 82301970 to X. Long, 82130085 to J.Q., 82101827 to Jingjing Chen, 82273855 to M.Z., 82204278 to X. Li and 31970828 to X.W.), National Key Research and Development Program of China (2022YFC3400504 to M.Z.), Youth Innovation Promotion Association CAS (2023296 to S. Zhang), Lingang Laboratory (LG2O210201-O2 to M.Z. and LG-QS-2O2204-01 to S. Zhang), China Postdoctoral Science Foundation (2022M721675 to X. Long, 2020M681665 to Jingjing Chen and 2022M720153 to X. Li), Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX22_1784 to Z.Z. and JX10113833 to S.W.), Postdoc Research Program of Taizhou School of Clinical Medicine (TZBSHKY2O22O3 to X. Long), Major Program of Wuxi Medical Center, Nanjing Medical University (WMCM2O2310 to X.W.), Jiangsu Provincial Key Research Development Program of China (BE2O22770 to Y.C.) and Jiangsu Outstanding Young Investigator Program (BK2O200030 to X.W.).
感谢 Z. Qin(中国科学院生物物理研究所)提供 MCA2O5 细胞。本研究得到了国家自然科学基金(X.W. 32330036,M.Z. T222502,J.Q. 81825018,X. Long 82301970,J.Q. 82130085,陈晶晶 82101827,M.Z. 82273855、82204278 to X. Li and 31970828 to X.W.)、国家重点研发计划(2022YFC3400504 to M.Z.)、中科院青年创新促进会(2023296 to S.Zhang)、临港实验室(LG2O210201-O2 to M.Z.和 LG-QS-2O2204-01 to S.Zhang)、中国博士后科学基金(2022M721675 to X. Long, 2020M681665 to Jingjing Chen and 2022M720153 to X.李)、江苏省研究生科研实践创新计划(KYCX22_1784 给 Z.Z.,JX10113833 给 S.W.)、泰州临床医学院博士后科研项目(TZBSHKY2O22O3 给 X.龙)、南京医科大学无锡医学中心重大项目(WMCM2O2310 给 X.W.)、江苏省重点研发计划(BE2O22770 给 Y.C.)和江苏省杰出青年科学基金(BK2O200030 给 X.W.)。

Author contributions 作者供稿

X.W., J.Q. and M.Z. conceived and directed the study. X. Long, Y.W., Jingjing Chen, Y.L., Y.C. and B.L. performed most of the animal and cellular biology experiments. S. Zhang, H.H., X. Li, C.S., R.Y., D.C., G.C. and D.W. designed and performed the experiments regarding the small compound. R.C. performed the pharmacokinetic study of the inhibitor. Y.W. performed the bioinformatic analysis. H.Z., S. Zhai, Z.Z., S.W., M.L., J.Z. and Junhong Chen helped with mouse care and some in vitro experiments. X.W., J.Q. and M.Z. wrote the manuscript with input from all authors.
X.W.、J.Q.和M.Z.构思并指导了这项研究。X.Long、Y.W.、Jingjing Chen、Y.L.、Y.C.和B.L.完成了大部分动物和细胞生物学实验。S. Zhang、H.H.、X. Li、C.S.、R.Y.、D.C.、G.C.和 D.W. 设计并进行了有关小化合物的实验。R.C. 进行了抑制剂的药代动力学研究。Y.W. 进行了生物信息分析。H.Z.、S. Zhai、Z.Z.、S.W.、M.L.、J.Z.和陈俊宏帮助照顾小鼠和进行一些体外实验。X.W.、J.Q.和M.Z.撰写了手稿,所有作者均提供了意见。

Competing interests 竞争利益

The authors declare no competing interests.
作者声明不存在利益冲突。

Additional information 其他信息

Extended data is available for this paper at https://doi.org/10.1038/s41590-024-01746-8 .
本文的扩展数据见 https://doi.org/10.1038/s41590-024-01746-8。
Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41590-024-01746-8 .
补充信息 在线版本包含补充材料,可从 https://doi.org/10.1038/s41590-024-01746-8 获取。
Correspondence and requests for materials should be addressed to Mingyue Zheng, Jun Qin or Xiaoming Wang.
通讯和资料索取请联系:Mingyue Zheng、Jun Qin 或 Xiaoming Wang。
Peer review information Nature Immunology thanks Axel Kallies and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Primary Handling Editor: N. Bernard, in collaboration with the Nature Immunology team.
同行评议信息 《自然-免疫学》感谢 Axel Kallies 和其他匿名审稿人对这项工作的同行评议所做的贡献。可查阅同行评审报告。主要处理编辑:N. Bernard,与《自然-免疫学》团队合作。
Reprints and permissions information is available at www.nature.com/reprints.
转载和授权信息请访问 www.nature.com/reprints。
Extended Data Fig. 1|Slingshot analysis based pseudotime analysis. Slingshot analysis based pseudotime analysis was derived for the three populations of Treg from Fig. 1g.
扩展数据 图 1|基于弹弓分析的伪时间分析。图 1g 中的三个 Treg 群体得出了基于弹弓分析的伪时间分析。

b
C

d

e

Extended Data Fig. 2 JMJDDIC is dispensable for systemic Treg development
扩展数据 图 2 JMJDDIC 对于全身性 Treg 的发育是不可或缺的

Jmjd1c , treated with TNF plus IL-6 for 3 days, and subject to western blot analysis with anti-JMJD1C. b, Comparison of Treg cell cellularity in spleen and lymph nodes between and mice. pLN, peripheral lymphoid nodes. c, Representative flow cytometric plots of splenic cell subsets (up) or CD8 cell subsets(down): naïve (CD44- CD62L )
b, 小鼠脾脏和淋巴结中 Treg 细胞数量的比较。c, 脾脏 细胞亚群(向上)或 CD8 细胞亚群(向下)的代表性流式细胞图:天真 (CD44- CD62L )
Ко mice. d, Representative images of hematoxylin and eosin
Ко d,苏木精和伊红的代表性图像。

of 6-month-old. Scale bars: spleen , colon , lung , liver , kidney .e, Frequency of Treg cells in different tissues as indicated from 6-month-old mice. Data represent two (a) or three (d) independent experiments. Data were pooled from 2 independent experiments (b, c, e). Data in are shown in means SD. Two-tailed unpaired Student's -test .
6 个月大的小鼠。比例尺:脾脏 ,结肠 ,肺 ,肝 ,肾 。e, 6 月龄小鼠不同组织中 Treg 细胞的频率。数据代表两个(a)或三个(d)独立实验。数据来自 2 个独立实验(b、c、e)。 中的数据以平均值 SD 表示。双尾非配对学生 -test

a
b
Tumor 肿瘤
d
Extended Data Fig. 3 | Characterization of tumor Treg expansion, apoptosis and suppressive function. a, Gating strategy for tumor Treg. b,c, Representative flow cytometric plots of Ki67 (b) and active caspase3 (c) levels in splenic Treg cells or intratumoral Treg cells from MCA205-tumor-bearing and mice. , Ex vivo suppression of CellTrace Violet (CTV)- labeled WT naïve cell proliferation by and Treg cells sorted from tumors (d) or spleens (e) with the annotated co-culture ratios. Teff, T effector cells. biological independent samples. Data represent three independent experiments (b-e). Data in (b-e) are shown in means SD. Two-tailed unpaired Student's -test (b-e).
b,c, MCA205 肿瘤小鼠 脾脏 Treg 细胞或瘤内 Treg 细胞 Ki67 (b) 和活性 caspase3 (c) 水平的代表性流式细胞图。 从肿瘤(d)或脾脏(e)分拣出的 Treg 细胞以注释的共培养比例在体内抑制 CellTrace Violet(CTV)标记的 WT 天真 细胞增殖。Teff, T效应细胞。 生物独立样本。数据代表三个独立实验(b-e)。b-e)中的数据以平均值 SD 表示。双尾非配对学生 -检验(b-e)。

d
e
Extended Data Fig. scRNA-seq analysis of tumor Treg cells from MCA205tumor-bearing mice. a, Unsupervised clustering of tumor-infiltrating Treg cells from MCA205-tumor-bearing ( 4 mice ) and ( 7 mice) mice. b, Dot plot showing the expression of marker genes for each cluster. , Tumor Treg cells from MCA205-tumor-bearing Jmjd1c ( mice) and ко mice ( mice) were stained for BB expression by flow cytometry.
扩展资料 图 MCA205肿瘤小鼠肿瘤Treg细胞的scRNA-seq分析。a, MCA205肿瘤小鼠肿瘤浸润Treg细胞的无监督聚类 ( 4只小鼠) 和 ( 7只小鼠)。b, 点图显示每个聚类的标记基因表达。 用流式细胞术对来自 MCA205-肿瘤携带 Jmjd1c ( 小鼠) 和 ко 小鼠 ( 小鼠) 的肿瘤 Treg 细胞进行 BB 表达染色。
d, Tumor-infiltrating Treg cells cells were sorted from MCA205-tumor-bearing Jmjd1 and Jmjd1c mice, the protein levels of and H3K9me1 were assessed by western blot. e, Volcano plot showing the genes differentially
d, 从携带 Jmjd1 和 Jmjd1c 的 MCA205 肿瘤小鼠中分拣出肿瘤浸润 Treg 细胞,并通过 western blot 评估 和 H3K9me1 的蛋白水平。 e, 火山图显示了差异化的基因。
f
Pathway name 途径名称
HALLMARK_FATTY_ACID_METABOLISM HALLMARK_ANDROGEN_RESPONSE HALLMARK_MITOTIC_SPINDLE HALLMARK_ESTROGEN_RESPONSE_LATE HALLMARK_UNFOLDED_PROTEIN_RESPONSE HALLMARK_ADIPOGENESIS HALLMARK_MYC_TARGETS_V1 HALLMARK_UV_RESPONSE_DN HALLMARK_P53_PATHWAY HALLMARK_ESTROGEN_RESPONSE_EARLY HALLMARK_GLYCOLYSIS HALLMARK_IL2_STAT5_SIGNALING HALLMARK_OXIDATIVE_PHOSPHORYLATION HALLMARK_BILE_ACID_METABOLISM HALLMARK_HEDGEHOG_SIGNALING HALLMARK_SPERMATOGENESIS HALLMARK_PROTEIN_SECRETION HALLMARK_DNA_REPAIR HALLMARK_E2F_TARGETS
脂肪代谢 hallmark_androgen_response hallmark_mitotic_spindle hallmark_estrogen_response_late hallmark_unfolded_protein_response hallmark_adipogenesis hallmark_myc_targets_v1 hallmark_uv_response_dn hallmark_p53_pathwayHallmark_estrogen_response_early hallmark_glycolysis hallmark_il2_stat5_signaling hallmark_oxidative_phosphorylation hallmark_bile_acid_metabolism hallmark_hedgehog_signaling hallmark_spermatogenesis hallmark_protein_secretion hallmark_dna_repair hallmark_e2f_targets
NES NOM p-val FDR q-val
-2.2750268 0 0
-1.9698801 0 0.00567606
-1.8295374 0 0.01901984
-1.6388747 0 0.038183
-1.5952946 0.00203252 0.04016913
-1.6388798 0.00380228 0.04295588
-1.9856513 0.00393701 0.00742658
-1.7461436 0.0056926 0.02628139
-1.4676492 0.0094697 0.06075199
-1.4530864 0.00982318 0.06291576
-1.5410246 0.01113173 0.0435347
-1.6167619 0.01167315 0.03879711
-1.787939 0.01174168 0.0220965
-1.5650495 0.01372549 0.042078
-1.5933923 0.02004008 0.03705965
-1.4833448 0.03326403 0.05865074
-1.4135852 0.04621849 0.07080002
-1.4231943 0.04752066 0.07035238
-1.6786686 0.04819277 0.03591891
expressed inJmjd1c WT and KO tumor Treg cells from the scRNA-seq data. values were computed with two-sided Wilcoxon rank-sum test in Seurat and adjusted with Bonferroni method. f, Gene Set Enrichment Analysis (GSEA) showing the significantly enriched signatures among all the 50 hallmark gene sets inJmjd1c WT versusJmjd1c KO tumor Treg cells. P values were computed with empirical phenotype-based permutation tests (GSEA), and adjusted for multiple comparisons using the Benjamini-Hochberg method (FDR). Data represent two independent experiments . Data are shown in means . Two-tailed unpaired Student's -test (c).
,用 Seurat 中的双侧 Wilcoxon 秩和检验计算,并用 Bonferroni 方法进行调整。 f,基因组富集分析(Gene Set Enrichment Analysis,GSEA)显示了 Jmjd1c WT 与 Jmjd1c KO 肿瘤 Treg 细胞中所有 50 个标志基因组的显著富集特征。P值通过基于经验表型的置换检验(GSEA)计算,并使用Benjamini-Hochberg方法(FDR)进行多重比较调整。数据代表两个独立实验 。数据以均数表示 。双尾非配对学生 -test (c)。
b
Extended Data Fig. Cytokine production in tumor effector cells from WT and Stat3CA OE mice. a, Representative flow cytometric plots of IFN and TNF production in Foxp3 and tumor-infiltrating cells (left). Percentage of cytokine-producing cells in and tumor were plotted on the right.
扩展资料 图 WT 和 Stat3CA OE 小鼠肿瘤效应 细胞中细胞因子的产生。a, Foxp3 肿瘤浸润 细胞中 IFN 和 TNF 产生的代表性流式细胞图(左)。右图为 和肿瘤中产生细胞因子的 细胞的百分比。
mice. , Representative flow cytometric plots of IL-17A production in Foxp3 tumor-infiltrating T cells (left). Percentage of IL-17A-producing T cells were plotted on the right. mice. Data represent two independent experiments. Data in (a, b) are shown in means SD. Two-tailed unpaired Student's -test (a-b).
小鼠。 Foxp3 肿瘤浸润 T 细胞产生 IL-17A 的代表性流式细胞图(左)。 小鼠。数据代表两个独立实验。a、b)中的数据以平均值 SD 表示。双尾非配对学生 -检验(a-b)。
B16-F10
Extended Data Fig. 6|193D7 treatment suppresses tumor growth. C57BL6/J mice were subcutaneously inoculated with B16-F10, LLC or Hepa1-6 tumor cells. BALB/C mice were subcutaneously inoculated with CT26 tumor cells. When tumor grew to measurable size , the tumor bearing mice were
扩展资料图 6|1937D7治疗可抑制肿瘤生长。C57BL6/J小鼠皮下接种B16-F10、LLC或Hepa1-6肿瘤细胞。给 BALB/C 小鼠皮下接种 CT26 肿瘤细胞。当肿瘤生长到可测量的大小 时,将携带肿瘤的小鼠送往医院。

Hepa1-6 赫帕1-6
CT26
intraperitoneally treated with DMSO control or 193D7 at once a day, tumor growth was monitored. mice. Data represent two independent experiments. Data are shown in means SD. Two-way ANOVA was used.
小鼠腹腔注射 DMSO 对照组或 193D7 ,每天一次,监测肿瘤生长情况。数据代表两个独立实验。数据以平均值 SD 表示。采用双向方差分析。
C
Extended Data Fig. 7|193D7 treatment shows no evidence of toxicity in mice. C57BL6/J mice were intraperitoneally treated with DMSO control or 193D7 at once a day for 14 days. mice per group. a, Body weight was monitored over time. b, Quantification of alanine aminotransferase (ALT), alkaline phosphatase (ALP) in the serum at day 14.c, Representative images of hematoxylin and eosin staining for the indicated tissues from DMSO control or 193D7-treated mice at day 14 . Scale bars: colon , lung , liver , kidney . Data represent two independent experiments (a-c). Data are shown in means . Two-way ANOVA (a);two-tailed unpaired Student's -test .
扩展资料图 7|1937D7治疗对小鼠无毒性证据。C57BL6/J 小鼠腹腔注射 DMSO 对照组或 193D7 ,每天一次,连续 14 天。 。a, 随时间监测体重。b, 第 14 天血清中丙氨酸氨基转移酶(ALT)和碱性磷酸酶(ALP)的定量。c, 第 14 天 DMSO 对照组或 193D7 处理的小鼠指定组织的苏木精和伊红染色的代表性图像。比例尺:结肠 ,肺 ,肝 ,肾 。数据代表两个独立实验(a-c)。数据以均数表示 。双向方差分析(a);双尾非配对学生 -检验

a
b
Extended Data Fig. 193D7 treatment increased tumor effector cell number and cytokine production by in wildtype mice. C57BL6/J mice bearing MCA205 tumor were orally treated with DMSO control or 193D7 at once a day for 12 days as in Fig. 6j. DMSO, mice;193D7, mice. a, Cell number of and cells per gram tumor in MCA205-tumor-bearing mice. b, Percentage of cytokine-producing T cells in dLNs and tumors. Data represent two independent experiments. Data are shown in means SD. Two-tailed unpaired Student's -test .
扩展资料 图 193D7 处理可增加野生型小鼠的肿瘤效应 细胞数量和细胞因子的产生。携带 MCA205 肿瘤的 C57BL6/J 小鼠口服 DMSO 对照组或 193D7( ),每天一次,连续 12 天,如图 6j。 a、MCA205 肿瘤小鼠每克肿瘤中 细胞数。b、dLN 和肿瘤中产生细胞因子的 T 细胞百分比。数据代表两个独立实验。数据以平均值 SD 表示。双尾非配对学生 -test

Extended Data Fig. 193D7 treatment did not alter tumor effector cell
扩展数据图 193D7 处理不会改变肿瘤效应 细胞

bearing MCA205 tumor were orally treated with DMSO control or 193D7 at once a day for 12 days as in Fig. 6 p. mice. , Cell number of b
携带 MCA205 肿瘤的 小鼠口服 DMSO 对照组或 193D7 ,每天一次,连续 12 天。 b

and cells per gram tumor in MCA205-tumor-bearing mice. , Percentage of cytokine-producing cells in tumors. Data represent two independent experiments. Data are shown in means . Two-tailed unpaired Student's -test .
细胞。 肿瘤中产生细胞因子的 细胞的百分比。数据代表两个独立实验。数据以均数表示 。双尾非配对学生 -test

a CD45.1/2+WT
b
were isolated from tumor tissues, stimulated and stained for IFN in tumor Treg cells. mice. Data represent two independent experiments. Plotting data in (b, c) are all shown in means SD. Two-tailed unpaired Student's -test (b, c).
小鼠。数据代表两个独立实验。b、c)中的数据均以平均值 SD 表示。双尾非配对学生 -检验(b,c)。
C

Extended Data Fig. 10 |Analysis of the effect of 193D7 treatment on tumor Treg cells in mixed bone marrow chimeras. a, The experimental design of mixed bone marrow chimeras. , The Treg frequency in tumor was analyzed by flow cytometry in tumor-bearing mixed chimeras. mice. , Lymphocytes
扩展资料 图 10 193D7 治疗对混合骨髓嵌合体肿瘤 Treg 细胞的影响分析 a, 混合骨髓嵌合体的实验设计。 小鼠。 淋巴细胞

nature portfolio 自然组合

Reporting Summary 报告摘要

Nature Portfolio wishes to improve the reproducibility of the work that we publish. This form provides structure for consistency and transparency in reporting. For further information on Nature Portfolio policies, see our Editorial Policies and the Editorial Policy Checklist.
自然出版集团希望提高我们所出版作品的可复制性。本表提供了报告的一致性和透明度。有关自然出版集团政策的更多信息,请参阅我们的编辑政策和编辑政策清单。

Statistics 统计资料

For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section. n/a Confirmed
对于所有统计分析,请确认图例、表格图例、正文或 "方法 "部分是否包含以下项目。 n/a 已确认
The exact sample size for each experimental group/condition, given as a discrete number and unit of measurement
每个实验组/条件的确切样本量 ,以离散数和计量单位表示
A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly
说明是对不同样本进行测量,还是对同一样本进行重复测量
The statistical test(s) used AND whether they are one- or two-sided
使用的统计检验,以及是单侧检验还是双侧检验
Only common tests should be described solely by name; describe more complex techniques in the Methods section.
只有常见的测试才应仅用名称进行描述;更复杂的技术应在 "方法 "部分进行描述。
A description of all covariates tested
所有测试协变量的说明
A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons
任何假设或校正的说明,例如正态性检验和多重比较调整
A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals)
完整描述统计参数,包括中心倾向(如平均值)或其他基本估计值(如回归系数)和变异(如标准差)或相关的不确定性估计值(如置信区间)
For null hypothesis testing, the test statistic (e.g. ) with confidence intervals, effect sizes, degrees of freedom and value noted Give values as exact values whenever suitable.
对于零假设检验,检验统计量(如 ),并注明置信区间、效应大小、自由度和 值 在合适的情况下,将 的值作为精确值。
For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings
对于贝叶斯分析,有关先验选择和马尔科夫链蒙特卡罗设置的信息
For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes
对于分层设计和复杂设计,确定测试的适当级别并全面报告结果
Estimates of effect sizes (e.g. Cohen's , Pearson's ), indicating how they were calculated
效应大小估计值(如 Cohen's ,Pearson's ),说明其计算方法
Our web collection on statistics for biologists contains articles on many of the points above.
我们为生物学家收集的统计资料中包含有关上述许多问题的文章。

Software and code 软件和代码

Policy information about availability of computer code
关于计算机代码可用性的政策信息
Data collection 数据收集

FACS 数据用 BD FACSDIVA v8.0.2 或 Beckman CytExpert v2.4 采集。组织学图像使用奥林巴斯显微镜 BX53 采集。高通量测序数据通过 Illumina Novaseq 6000 平台采集。
FACS data were collected with BD FACSDIVA v8.0.2 or Beckman CytExpert v2.4. Histological images were collected with Olympus microscope
BX53. High-throughput sequencing data were collected on Illumina Novaseq 6000 platform.
Data analysis 数据分析

scRNA-seq 数据使用 Cellranger (v5.0.1) 计数和 10x Genomics 的 refdata-cellranger-mm10 reference (mm10-2020-A) 进行处理。条形码文件、特征文件和矩阵文件通过 RStudio(2022.07.1 Build 554)使用 R 软件包 Seurat(v4.3.0)处理。对于CUT&RUN和ATAC-seq数据,首先使用trim_galore(v0.6.6)对原始成对端测序读数进行适配序列切割和修剪。然后,使用 Bowtie 2(v2.4.2)将清理后的 fastq 数据映射到 mm10 参考基因组。Picard 用于标记和去除重复。Samtools (v1.11)用于将 SAM 文件转换和分类为 BAM 格式。Homer (4.11-pl5321h955acd7_7) 用于峰值调用。FACS 数据用 Flowjo v10 进行分析,统计分析用 Prism Graphpad v9 进行。DNA 序列分析使用 Vector NTI v11.5.1。分子对接使用 Schrödinger 的 Glide 模块(v8.9)。本研究中报告的代码已存入 Github https://github.com/YuliangWang316/JMJD1C_Treg。
scRNA-seq data were processed using Cellranger (v5.0.1) count with refdata-cellranger-mm10 reference (mm10-2020-A) from 10x Genomics.
Barcodes file, features file and matrix file were processed using R package Seurat (v4.3.0) via RStudio (2022.07.1 Build 554).
For CUT&RUN and ATAC-seqdata, raw paired-end sequenced reads were first cut for adaptor sequences and trimmed using trim_galore
(v0.6.6). Then, cleaned fastq data were mapped using Bowtie 2 (v2.4.2) to the mm10 reference genome. Picard was used for marking and
removing duplication. Samtools (v1.11) was used for converting and sorting the SAM files into BAM format. Homer (4.11-pl5321h955acd7_7)
was used for peak calling. FACS data were analyzed with Flowjo v10. Statistical analyses were performed with Prism Graphpad v9. Vector NTI
v11.5.1 was used for DNA sequence analysis. For molecular docking, Glide module (v8.9) of Schrödinger was used. The codes reported in this
study have been deposited in Github at https://github.com/YuliangWang316/JMJD1C_Treg.

Policy information about availability of data
有关数据可用性的政策信息

All manuscripts must include a data availability statement. This statement should provide the following information, where applicable:
所有稿件必须包含数据可用性声明。该声明应酌情提供以下信息:
  • Accession codes, unique identifiers, or web links for publicly available datasets
    公开数据集的存取码、唯一标识符或网络链接
  • A description of any restrictions on data availability
    关于数据可用性限制的说明
  • For clinical datasets or third party data, please ensure that the statement adheres to our policy
    对于临床数据集或第三方数据,请确保声明符合我们的政策
scRNA-seq data have been deposited at GEO (GSE223930). ATAC-seq and CUT&RUN-seq data have been deposited at GEO (GSE224084)
scRNA-seq 数据已存入 GEO (GSE223930)。ATAC-seq 和 CUT&RUN-seq 数据已存入 GEO (GSE224084)
Other public available Dataset used in this manuscript include: GSE139325,GSE108989, GSE98638 and GSE99254.
本稿件中使用的其他公开数据集包括:GSE139325、GSE108989、GSE98638 和 GSE99254:GSE139325、GSE108989、GSE98638 和 GSE99254。
There is no restriction on data availability.
对数据的可用性没有限制。

Human research participants
人类研究参与者

Policy information about studies involving human research participants and Sex and Gender in Research.
关于涉及人类研究参与者的研究以及研究中的性别和性别问题的政策信息。
Reporting on sex and gender
关于性和性别的报告
Population characteristics
人口特征
N/A
Recruitment 招聘
N/A
Ethics oversight 道德监督
N/A
Note that full information on the approval of the study protocol must also be provided in the manuscript.
请注意,手稿中还必须提供有关研究方案批准情况的完整信息。

Field-specific reporting
针对具体领域的报告

Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.
请选择以下最适合您研究的一项。如果您不确定,请在选择前阅读相应章节。
Life sciences Behavioural & social sciences Ecological, evolutionary & environmental sciences
生命科学 行为与社会科学 生态、进化与环境科学
For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf
如需参考文件的所有章节,请参见 nature.com/documents/nr-reporting-summary-flat.pdf

Life sciences study design
生命科学研究设计

All studies must disclose on these points even when the disclosure is negative.
所有研究都必须披露这几点,即使披露的是负面信息。
Sample size 样本量

我们没有使用统计方法来预先确定样本量,但我们的样本量与以往出版物(《自然》,2021 年 3 月;591(7849:306-311; 《自然免疫学》,2021 年 3 月;591(7849:306-311)2021 Mar;591(7849):306-311; Nat Immunol.2023年1月;24(1):148-161)。实验变异性是决定样本大小的因素之一。在动物研究中,至少使用了 5 对小鼠。所有实验至少独立重复两次,关键实验由独立研究人员重复。
No statistical methods were used to pre-determine sample sizes but our sample sizes are similar to those reported in previous publications
(Nature. 2021 Mar;591(7849):306-311; Nat Immunol. 2023 Jan;24(1):148-161). The experimental variability is one of the factors determining
sample size. For animal studies, at least 5 pairs of mice were used. all the experiments were independently repeated at least twice and key
experiments were repeated by independent researchers.
Replication 复制 Replications were used in all experiments as noted in figure legends and methods. Experimental findings were reliably reproduced.
如图例和方法所示,所有实验都使用了重复实验。实验结果得到了可靠的再现。
Blinding 致盲

由于测量是客观的,因此数据收集和分析并不是在实验条件盲目的情况下进行的。此外,大部分实验设计都需要事先了解小鼠的基因型,以便进行分组。
Data collection and analysis were not performed blind to the conditions of the experiments because the measurements were objective. In
addition, most of the experiment design requires a priori knowledge of mouse genotype for group allocating.

Reporting for specific materials, systems and methods
特定材料、系统和方法的报告

Materials & experimental systems
材料与实验系统
n/a Involved in the study
参与研究
Antibodies  抗体
Eukaryotic cell lines
真核细胞系
Palaeontology and archaeology
古生物学和考古学
Animals and other organisms
动物和其他生物
Clinical data  临床数据
Dual use research of concern
值得关注的双重用途研究

Methods 方法
n/a Involved in the study
参与研究
Х ChIP-seq
Flow cytometry  流式细胞仪
Х MRI-based neuroimaging
基于磁共振成像的神经成像

Antibodies 抗体

Antibodies used 使用的抗体
Anti-STAT3 Cell Signaling Technology Cat#4904 Clone:79D7 Lot:7; 1:2000 for Immunoblot ; 1:50 for ChIP Anti-Phospho-Stat3 (Tyr705) Cell Signaling Technology Cat#9145 Clone: D3A7 Lot:43; 1:100 for Flow Cytometry Anti-Phospho-S6 Ribosomal Protein (Ser235/236) Cell Signaling Technology Cat#4858 Clone: D57.2.2E Lot:16; 1:100 for Flow Cytometry
抗 STAT3 细胞信号技术 Cat#4904 克隆:79D7 Lot:7; 1:2000 用于免疫印迹;1:50 用于 ChIP 抗磷-Stat3 (Tyr705) 细胞信号技术 Cat#9145 克隆:D3A7 Lot:43; 1:100 用于流式细胞仪 抗磷-S6 核糖体蛋白 (Ser235/236) 细胞信号技术 Cat#4858 克隆:D3A7 Lot:43; 1:100 用于流式细胞仪D3A7 Lot:43; 1:100 用于流式细胞仪 抗磷酸-S6 核糖体蛋白 (Ser235/236) Cell Signaling Technology Cat#4858 Clone:D57.2.2E Lot:16; 1:100 用于流式细胞术
Anti-Phospho-Akt (Thr308) Cell Signaling Technology Cat#13038 Clone: D25E6 Lot:7; 1:100 for Flow Cytometry Anti- -Actin Cell Signaling Technology Cat#4967 Lot:12; 1:2000 for Immunoblot Anti-Histone H3 Cell Signaling Technology Cat#9715 Lot:20; 1:2000 for Immunoblot Anti-Mono-Methyl-Histone H3 (Lys9) Cell Signaling Technology Cat#14186 Clone: D1P5R Lot:1; 1:2000 for Immunoblot Anti-Histone H3 (di methyl K9) Abcam Cat#ab1220 Lot:GR285802-1; 1:2000 for Immunoblot; 1:50 for CUT&RUN. Anti-Jmjd1c MBL International Cat#D356-3 Clone:13B Lot:001; 1:1000 for Immunoblot Anti-Methylated Lysine Abcam Cat#ab23366 Lot: GR211274-15; 1:500 for Immunoblot Anti-Foxp3 Abcam Cat#AB215206 Lot:1001076-6; 1:1000 for Immunoblot streptavidin, Alexa Fluor conjugate Invitrogen Cat#S21374 Lot:2308260; 1:400 for Flow Cytometry Biotin Goat Anti-Rabbit IgG BD Biosciences Cat#550338 Lot:81956; 1:100 for Flow Cytometry Biotin Rabbit Anti- Active Caspase-3 BD Biosciences Cat#550557 Clone:C92-605 Lot:5219831; test for Flow Cytometry APC Anti-mouse CD62L eBioscience Cat#17-0621-82 Clone: MEL-14 Lot:4338519; 1:400 for Flow Cytometry APC Anti-mouse CD4 BioLegend Cat#100412 Clone: GK1.5 Lot:B356962; 1:400 for Flow Cytometry APC/Cyanine7 anti-mouse CD4 BD Biosciences Cat#552051 Clone: GK1.5 Lot:8205982; 1:400 for Flow Cytometry PerCP/Cyanine5.5 Anti-mouse CD8a BioLegend Cat#100734 Clone: 53-6.7 Lot:B330251; 1:100 for Flow Cytometry PE Anti-mouse CD44 BioLegend Cat# 103008 Clone: IM7 Lot:B359213; 1:400 for Flow Cytometry FITC Anti-mouse CD44 BioLegend Cat# 103006 Clone: IM7 Lot:B228504; 1:400 for Flow Cytometry Brilliant Violet 605 Anti-mouse CD45 BioLegend Cat# 103140 Clone: 30-F11 Lot:B375996; 1:200 for Flow Cytometry Brilliant Violet 605 Anti-mouse CD45.1 BioLegend Cat# 110738 Clone: A20 Lot:B303397; 1:200 for Flow Cytometry Brilliant Violet 605 Anti-mouse CD45.2 BioLegend Cat# 109841 Clone: 104 Lot:B358097; 1:200 for Flow Cytometry PE Anti-Mouse IL-17A BD Biosciences Cat#559502 Clone:TC11-18H10 Lot:8018692; 1:200 for Flow Cytometry APC Anti-mouse IFN- BioLegend Cat#505810 Clone: XMG1.2 Lot: B249122; 1:200 for Flow Cytometry PerCP/Cyanine5.5 Anti-mouse IFN- eBioscience Cat#45-7311-82 Clone: XMG1.2 Lot: 1911415; 1:100 for Flow Cytometry PE anti-mouse Ki-67 BioLegend Cat#652403 Clone: 16A8 Lot:B293052; 1:200 for Flow Cytometry
抗磷酸-Akt (Thr308) 细胞信号技术 Cat#13038 克隆:D25E6 Lot:7; 1:100 for Flow Cytometry Anti -Actin Cell Signaling Technology Cat#4967 Lot:12; 1:2000 for Immunoblot Anti-Histone H3 Cell Signaling Technology Cat#9715 Lot:20; 1:2000 for Immunoblot AntiMono-Methyl-Histone H3 (Lys9) Cell Signaling Technology Cat#14186 Clone:D1P5R Lot:1; 1:2000 用于免疫印迹 抗组蛋白 H3 (di methyl K9) Abcam Cat#ab1220 Lot:GR285802-1; 1:2000 用于免疫印迹; 1:50 用于 CUT&RUN.抗 Jmjd1c MBL International Cat#D356-3 Clone:13B Lot:001; 1:1000 用于免疫印迹 抗甲基化赖氨酸 Abcam Cat#ab23366 Lot:GR211274-15; 1:500 用于免疫印迹抗 Foxp3 Abcam Cat#AB215206 Lot:1001076-6; 1:1000 用于免疫印迹链霉亲和素,Alexa Fluor conjugate Invitrogen Cat#S21374 Lot:2308260; 1:400 用于流式细胞仪生物素山羊抗兔 IgG BD Biosciences Cat#550338 Lot:81956; 1:100 用于流式细胞仪生物素兔抗活性 Caspase-3 BD Biosciences Cat#550557 克隆:C92-605 Lot:5219831; test for Flow Cytometry APC Anti-mouse CD62L eBioscience Cat#17-0621-82 Clone:MEL-14 Lot:4338519; 1:400 for Flow Cytometry APC Anti-mouse CD4 BioLegend Cat#100412 Clone:GK1.5 Lot:B356962; 1:400 for Flow Cytometry APC/Cyanine7 anti-mouse CD4 BD Biosciences Cat#552051 Clone:GK1.5 Lot:8205982; 1:400 for Flow Cytometry PerCP/Cyanine5.5 Anti-mouse CD8a BioLegend Cat#100734 Clone: 53-6.7 Lot:B330251; 1:100 for Flow Cytometry PE Anti-mouse CD44 BioLegend Cat#103008 Clone:IM7 Lot:B359213; 1:400 for Flow Cytometry FITC Anti-mouse CD44 BioLegend Cat# 103006 Clone:BioLegend Cat# 103140 Clone: 30-F11 Lot:B375996; 1:200 for Flow Cytometry Brilliant Violet 605 Anti-mouse CD45.1 BioLegend Cat# 110738 Clone:A20 Lot:B303397; 1:200 for Flow Cytometry Brilliant Violet 605 Anti-mouse CD45.2 BioLegend Cat# 109841 Clone: 104 Lot:B358097; 1:200 for Flow Cytometry PE Anti-Mouse IL-17A BD Biosciences Cat#559502 Clone:TC11-18H10 Lot:8018692; 1:200 for Flow Cytometry APC Anti-mouse IFN- BioLegend Cat#505810 Clone:XMG1.2 Lot: B249122; 1:200 for Flow Cytometry PerCP/Cyanine5.5 Anti-mouse IFN- eBioscience Cat#45-7311-82 Clone:XMG1.2 Lot: 1911415; 1:100 用于流式细胞仪 PE anti-mouse Ki-67 BioLegend Cat#652403 Clone: 16A8 Lot:B293052; 1:200 用于流式细胞仪
PE/Cyanine7 anti-mouse CD279 (PD-1) BioLegend Cat#109110 Clone: RMP1-30 Lot:B245159; 1:200 for Flow Cytometry PE Anti-Mouse CD304 (Neuropilin-1) eBioscience Cat#12-3041-82 Clone: 3DS304M Lot:2263162; 1:200 for Flow Cytometry PE anti-mouse TNF BioLegend Cat#506306 Clone: MP6-XT22 Lot:B327717; 1:200 for Flow Cytometry PE Anti-Mouse Foxp3 eBioscience Cat#12-5773-82 Clone: FJK-16s Lot:1970222; 1:400 for Flow Cytometry APC Anti-Mouse Foxp3 eBioscience Cat#17-5773-82 Clone: FJK-16s Lot:4303649; 1:400 for Flow Cytometry Alexa Fluor anti-mouse FOXP3 BioLegend Cat#126406 Clone: MF-14 Lot:B353442; 1:200 for Flow Cytometry PE anti-mouse CD45.2 BioLegend Cat# 109808 Clone: 104 Lot:B298925; 1:400 for Flow Cytometry PE anti-mouse CD45.1 eBioscience Cat#12-0453-82 Clone: A20 Lot:4312189; 1:400 for Flow Cytometry Alexa Fluor anti-mouse CD45.2 BioLegend Cat# 109822 Clone: 104 Lot:B354903; 1:200 for Flow Cytometry Alexa Fluor anti-mouse CD45.1 BioLegend Cat# 110724 Clone: A20 Lot:B345907; 1:200 for Flow Cytometry Anti-mouse/rat IL-1b Bio X Cell Cat# BE0246 Clone:B122 Lot:808822J1; for Cell Culture Anti-mouse TNF Bio X Cell Cat#BE0058 Clone:XT3.11 Lot:728222J1; for Cell Culture Anti-mouse/rat IL-6 Bio X Cell Cat#BE0046 Clone:MP5-20F3 Lot:811721N1; for Cell Culture Anti-mouse CD3e Bio X Cell Cat#BE0001 Clone:145-2C11 Lot:677612M2; 5 ug/ml for Cell Culture Anti-mouse CD28 Bio X Cell Cat#BE0015 Clone:37.51 Lot:639918N1; for Cell Culture
PE/Cyanine7 anti-mouse CD279 (PD-1) BioLegend Cat#109110 Clone:RMP1-30 Lot:B245159; 1:200 for Flow Cytometry PE 抗小鼠 CD304 (Neuropilin-1) eBioscience Cat#12-3041-82 Clone: 3DS304M Lot:2263162; 1:200 for Flow Cytometry PE 抗小鼠 TNF BioLegend Cat#506306 Clone:MP6-XT22 Lot:B327717; 1:200 for Flow Cytometry PE anti-mouse Foxp3 eBioscience Cat#12-5773-82 Clone:FJK-16s Lot:1970222; 1:400 for Flow Cytometry APC Anti-Mouse Foxp3 eBioscience Cat#17-5773-82 Clone:FJK-16s Lot:4303649; 1:400 for Flow Cytometry Alexa Fluor anti-mouse FOXP3 BioLegend Cat#126406 Clone:MF-14 Lot:B353442; 1:200 用于流式细胞仪 PE anti-mouse CD45.2 BioLegend Cat# 109808 Clone: 104 Lot:B298925; 1:400 用于流式细胞仪 PE anti-mouse CD45.1 eBioscience Cat#12-0453-82 Clone:A20 Lot:4312189; 1:400 for Flow Cytometry Alexa Fluor anti-mouse CD45.2 BioLegend Cat# 109822 Clone: 104 Lot:B354903; 1:200 for Flow Cytometry Alexa Fluor anti-mouse CD45.1 BioLegend Cat# 110724 Clone:A20 Lot:B345907; 1:200 for Flow Cytometry 抗小鼠/大鼠 IL-1b Bio X Cell Cat# BE0246 Clone:B122 Lot:808822J1; for Cell Culture 抗小鼠 TNF Bio X Cell Cat#BE0058 Clone:XT3.11 Lot:728222J1; 用于细胞培养 抗小鼠/大鼠 IL-6 Bio X Cell Cat#BE0046 克隆:MP5-20F3 Lot:811721N1; 用于细胞培养 抗小鼠 CD3e Bio X Cell Cat#BE0001 克隆:145-2C11 Lot:677612M2; 5 ug/ml 用于细胞培养 抗小鼠 CD28 Bio X Cell Cat#BE0015 克隆:37.51 Lot:639918N1; 用于细胞培养
Antibodies for WB 用于 WB 的抗体
Anti-Stat3 React: human, mouse, rat, monkey; https://www.cellsignal.cn/products/primary-antibodies/stat3-79d7-rabbit-mab/4904? site-search-type=Products&N=4294956287&Ntt=4904&fromPage=plp&_requestid=249457
抗Stat3反应:人、小鼠、大鼠、猴;https://www.cellsignal.cn/products/primary-antibodies/stat3-79d7-rabbit-mab/4904? site-search-type=Products&N=4294956287&Ntt=4904&fromPage=plp&_requestid=249457
Anti- -Actin React: human, mouse, rat, monkey, hamster, mink, drosophila melanogaster, zebrafish, bovine; https:// www.cellsignal.cn/products/primary-antibodies/b-actin-antibody/4967?site-search-
-Actin 反应:人、小鼠、大鼠、猴、仓鼠、水貂、黑腹果蝇、斑马鱼、牛;https:// www.cellsignal.cn/products/primary-antibodies/b-actin-antibody/4967?site-search-
type=Products&N=4294956287&Ntt=4967&fromPage=plp&_requestid
Anti-Histone H3 React: human, mouse, rat, monkey, zebrafish, bovine, pig; https://www.cellsignal.com/products/primaryantibodies/histone-h3-antibody/9715
抗组蛋白 H3 反应:人、小鼠、大鼠、猴、斑马鱼、牛、猪;https://www.cellsignal.com/products/primaryantibodies/histone-h3-antibody/9715
Anti-Mono-Methyl-Histone H3 (Lys9) React: human, mouse, rat, monkey; https://www.cellsignal.com/products/primary-antibodies/ mono-methyl-histone-h3-lys9-d1p5r-rabbit-mab/14186
抗单甲基组蛋白 H3(Lys9)反应:人、小鼠、大鼠、猴;https://www.cellsignal.com/products/primary-antibodies/ mono-methyl-histone-h3-lys9-d1p5r-rabbit-mab/14186
Anti-Histone H3 (di methyl K9) React: cow, human, arabidopsis thaliana, drosophila melanogaster, rice, recombinant fragment; https://www.abcam.cn/histone-h3-di-methyl-k9-antibody-mabcam-1220-chip-grade-ab1220.html
抗组蛋白 H3(二甲基 K9)反应:牛、人、拟南芥、黑腹果蝇、水稻、重组片段;https://www.abcam.cn/histone-h3-di-methyl-k9-antibody-mabcam-1220-chip-grade-ab1220.html
Anti-Jmjd1c React: mouse http://www.mbl-chinawide.cn/uploads/pdf/D356-3-v1.pdf
抗 Jmjd1c 反应:小鼠 http://www.mbl-chinawide.cn/uploads/pdf/D356-3-v1.pdf
Anti-Methylated Lysine React: Species independent; https://www.abcam.cn/methylated-lysine-di-methyl--mono-methyl--antibodyab23366.html
抗甲基化赖氨酸反应:与物种无关;https://www.abcam.cn/methylated-lysine-di-methyl--mono-methyl--antibodyab23366.html
Anti-Foxp3 React: mouse, rat, human; https://www.abcam.cn/products/primary-antibodies/foxp3-antibody-epr22102-37ab215206.html
抗 Foxp3 反应:小鼠、大鼠、人类;https://www.abcam.cn/products/primary-antibodies/foxp3-antibody-epr22102-37ab215206.html
Other antibodies: 其他抗体
Anti-Phospho-Stat3 (Tyr705) App: Flow Cytometry React: human, mouse, rat, monkey; https://www.cellsignal.com/products/ primary-antibodies/phospho-stat3-tyr705-d3a7-xp-rabbit-mab/9145
抗磷酸-Stat3(Tyr705)应用:流式细胞仪 反应:人、小鼠、大鼠、猴;https://www.cellsignal.com/products/ primary-antibodies/phospho-stat3-tyr705-d3a7-xp-rabbit-mab/9145
Anti-Phospho-S6 Ribosomal Protein (Ser235/236) App: Flow Cytometry React: human, mouse, rat, monkey, S. cerevisiae; https:// www.cellsignal.cn/products/primary-antibodies/phospho-s6-ribosomal-protein-ser235-236-antibody/2211
抗磷酸-S6 核糖体蛋白(Ser235/236) 应用: 流式细胞术流式细胞仪 反应:人、小鼠、大鼠、猴、S. cerevisiae; https:// www.cellsignal.cn/products/primary-antibodies/phospho-s6-ribosomal-protein-ser235-236-antibody/2211
Anti-Phospho-Akt (Thr308) App: Flow Cytometry React: human, mouse, rat, monkey; https://www.cellsignal.com/products/primaryantibodies/phospho-akt-thr308-d25e6-xp-rabbit-mab/13038
抗磷酸-Akt (Thr308) 应用程序:流式细胞仪 反应:人、小鼠、大鼠、猴;https://www.cellsignal.com/products/primaryantibodies/phospho-akt-thr308-d25e6-xp-rabbit-mab/13038
streptavidin, Alexa Fluor conjugate App: Flow cytometry; https://www.thermofisher.cn/order/catalog/product/S21374? SID=srch-hj-S21374
链霉亲和素,Alexa Fluor 共轭化合物 App:流式细胞仪;https://www.thermofisher.cn/order/catalog/product/S21374?SID=srch-hj-S21374
Biotin Goat Anti-Rabbit IgG App: Flow cytometry React: rabbit; https://www.bdbiosciences.com/zh-cn/products/reagents/flowcytometry-reagents/research-reagents/single-color-antibodies-ruo/biotin-goat-anti-rabbit-igg. 550338
生物素山羊抗兔 IgG 应用程序:流式细胞仪 反应:兔;https://www.bdbiosciences.com/zh-cn/products/reagents/flowcytometry-reagents/research-reagents/single-color-antibodies-ruo/biotin-goat-anti-rabbit-igg.550338
Biotin Rabbit Anti- Active Caspase-3 App: Flow cytometry React: human, mouse; https://www.bdbiosciences.com/zh-cn/products/ reagents/flow-cytometry-reagents/research-reagents/single-color-antibodies-ruo/biotin-rabbit-anti-active-caspase-3.550557 APC Anti-mouse CD62L App: Flow cytometry React: mouse; https://www.thermofisher.cn/cn/zh/antibody/product/CD62L-L-SelectinAntibody-clone-MEL-14-Monoclonal/17-0621-82
生物素兔抗活性 Caspase-3 应用:流式细胞仪 反应:人、小鼠;https://www.bdbiosciences.com/zh-cn/products/ reagents/flow-cytometry-reagents/research-reagents/single-color-antibodies-ruo/biotin-rabbit-anti-active-caspase-3.550557 APC Anti-mouse CD62L App:流式细胞仪 反应:小鼠;https://www.thermofisher.cn/cn/zh/antibody/product/CD62L-L-SelectinAntibody-clone-MEL-14-Monoclonal/17-0621-82
APC Anti-mouse CD4 App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/apc-anti-mouse-cd4antibody-245?GroupID=BLG4745
APC 抗小鼠 CD4 应用程序:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/apc-anti-mouse-cd4antibody-245?GroupID=BLG4745
APC/Cyanine7 anti-mouse CD4 App: Flow cytometry React: mouse; https://www.bdbiosciences.com/zh-cn/products/reagents/flowcytometry-reagents/research-reagents/single-color-antibodies-ruo/apc-cy-7-rat-anti-mouse-cd4.552051
APC/Cyanine7 anti-mouse CD4 App:流式细胞仪 反应:小鼠;https://www.bdbiosciences.com/zh-cn/products/reagents/flowcytometry-reagents/research-reagents/single-color-antibodies-ruo/apc-cy-7-rat-anti-mouse-cd4.552051
PerCP/Cyanine5.5 Anti-mouse CD8a App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/percpcyanine5-5-anti-mouse-cd8a-antibody-4255?GroupID=BLG2559
PerCP/Cyanine5.5 抗小鼠 CD8a 应用:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/percpcyanine5-5-anti-mouse-cd8a-antibody-4255?GroupID=BLG2559
PE Anti-mouse CD44 App: Flow cytometry React: mouse, human; https://www.biolegend.com/en-us/products/pe-anti-mousehuman-cd44-antibody-2206?GroupID=BLG10511
PE 抗小鼠 CD44 应用:流式细胞仪 反应:小鼠、人类;https://www.biolegend.com/en-us/products/pe-anti-mousehuman-cd44-antibody-2206?GroupID=BLG10511
FITC Anti-mouse CD44 App: Flow cytometry React: mouse, human; https://www.biolegend.com/en-us/products/fitc-anti-mousehuman-cd44-antibody-314?GroupID=BLG10248
FITC 抗小鼠 CD44 应用:流式细胞仪 反应:小鼠、人类;https://www.biolegend.com/en-us/products/fitc-anti-mousehuman-cd44-antibody-314?GroupID=BLG10248
Brilliant Violet 605 Anti-mouse CD45 App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/brilliantviolet-605-anti-mouse-cd45-antibody-8721?GroupID=BLG6831
亮紫 605 抗小鼠 CD45 应用程序:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/brilliantviolet-605-anti-mouse-cd45-antibody-8721?GroupID=BLG6831
Brilliant Violet 605 Anti-mouse CD45.1 App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/brilliantviolet-605-anti-mouse-cd45-1-antibody-7850?GroupID=BLG1933
亮紫 605 抗小鼠 CD45.1 应用:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/brilliantviolet-605-anti-mouse-cd45-1-antibody-7850?GroupID=BLG1933
Brilliant Violet 605 Anti-mouse CD45.2 App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/brilliantviolet-605-anti-mouse-cd45-2-antibody-9695?GroupID=BLG7009
亮紫 605 抗小鼠 CD45.2 应用:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/brilliantviolet-605-anti-mouse-cd45-2-antibody-9695?GroupID=BLG7009
PE Anti-Mouse IL-17A App: Flow cytometry React: mouse; https://www.bdbiosciences.com/zh-cn/products/reagents/flowcytometry-reagents/research-reagents/single-color-antibodies-ruo/pe-rat-anti-mouse-il-17a.559502
PE 抗小鼠 IL-17A 应用程序:流式细胞仪 反应:小鼠; https://www.bdbiosciences.com/zh-cn/products/reagents/flowcytometry-reagents/research-reagents/single-color-antibodies-ruo/pe-rat-anti-mouse-il-17a.559502
APC Anti-mouse IFN- App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/apc-anti-mouse-ifn-gammaantibody-993
APC 抗小鼠 IFN- 应用:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/apc-anti-mouse-ifn-gammaantibody-993
PerCP/Cyanine5.5 Anti-mouse IFN- App: Flow cytometry React:mouse; https://www.thermofisher.cn/cn/zh/antibody/product/IFNgamma-Antibody-clone-XMG1-2-Monoclonal/45-7311-82
PerCP/Cyanine5.5 Anti-mouse IFN- App:流式细胞仪 反应:小鼠; https://www.thermofisher.cn/cn/zh/antibody/product/IFNgamma-Antibody-clone-XMG1-2-Monoclonal/45-7311-82
PE anti-mouse Ki-67 App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/pe-anti-mouse-ki-67antibody-8134?GroupID=GROUP26
PE 抗小鼠 Ki-67 应用:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/pe-anti-mouse-ki-67antibody-8134?GroupID=GROUP26
PE/Cyanine7 anti-mouse CD279 (PD-1) App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/pecyanine7-anti-mouse-cd279-pd-1-antibody-3612?GroupID=BLG4702
PE/Cyanine7 anti-mouse CD279 (PD-1) App:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/pecyanine7-anti-mouse-cd279-pd-1-antibody-3612?GroupID=BLG4702
PE Anti-Mouse CD304 (Neuropilin-1) App: Flow cytometry React: mouse; https://www.thermofisher.cn/cn/zh/antibody/product/ CD304-Neuropilin-1-Antibody-clone-3DS304M-Monoclonal/12-3041-82
PE 抗小鼠 CD304(神经纤蛋白-1)应用:流式细胞仪 反应:小鼠; https://www.thermofisher.cn/cn/zh/antibody/product/ CD304-神经蛋白-1-抗体-克隆-3DS304M-单克隆/12-3041-82
PE anti-mouse TNF- App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/pe-anti-mouse-tnf-alphaantibody-978?GroupID=GROUP24
PE anti-mouse TNF- App:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/pe-anti-mouse-tnf-alphaantibody-978?GroupID=GROUP24
PE Anti-Mouse Foxp3 App: Flow cytometry React: Bovine, Dog, Cat, Mouse, Pig, Rat; https://www.thermofisher.cn/cn/zh/antibody/ product/FOXP3-Antibody-clone-FJK-16s-Monoclonal/12-5773-82
PE 抗小鼠 Foxp3 应用:流式细胞仪 反应:牛、狗、猫、小鼠、猪、大鼠;https://www.thermofisher.cn/cn/zh/antibody/ product/FOXP3-Antibody-clone-FJK-16s-Monoclonal/12-5773-82
APC Anti-Mouse Foxp3 App: Flow cytometry React: Bovine, Dog, Cat, Mouse, Pig, Rat; https://www.thermofisher.cn/cn/zh/antibody/ product/FOXP3-Antibody-clone-FJK-16s-Monoclonal/17-5773-82
APC 抗小鼠 Foxp3 应用程序:流式细胞仪 反应:牛、狗、猫、小鼠、猪、大鼠;https://www.thermofisher.cn/cn/zh/antibody/ product/FOXP3-Antibody-clone-FJK-16s-Monoclonal/17-5773-82
Alexa Fluor anti-mouse FOXP3 App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/alexafluor-488-anti-mouse-foxp3-antibody-4661?GroupID=BLG5706
Alexa Fluor anti-mouse FOXP3 App:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/alexafluor-488-anti-mouse-foxp3-antibody-4661?GroupID=BLG5706
PE anti-mouse CD45.2 App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/pe-anti-mouse-cd45-2antibody-7?GroupID=BLG7007
PE anti-mouse CD45.2 App:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/pe-anti-mouse-cd45-2antibody-7?GroupID=BLG7007
PE anti-mouse CD45.1 App: Flow cytometry React: mouse; https://www.thermofisher.cn/cn/zh/antibody/product/CD45-1-Antibodyclone-A20-Monoclonal/12-0453-82
PE anti-mouse CD45.1 App:流式细胞仪 反应:小鼠;https://www.thermofisher.cn/cn/zh/antibody/product/CD45-1-Antibodyclone-A20-Monoclonal/12-0453-82
Alexa Fluor anti-mouse CD45.2 App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/alexafluor-700-anti-mouse-cd45-2-antibody-3393?GroupID=BLG1934
Alexa Fluor anti-mouse CD45.2 App:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/alexafluor-700-anti-mouse-cd45-2-antibody-3393?GroupID=BLG1934
Alexa Fluor anti-mouse App: Flow cytometry React: mouse; https://www.biolegend.com/en-us/products/alexa-fluor-700-antimouse-cd45-1-antibody-3392?GroupID=BLG1933
Alexa Fluor anti-mouse App:流式细胞仪 反应:小鼠;https://www.biolegend.com/en-us/products/alexa-fluor-700-antimouse-cd45-1-antibody-3392?GroupID=BLG1933
For cell culture: 用于细胞培养:
Anti-mouse/rat IL-1b React: mouse, Rat; https://bioxcell.com/invivomab-anti-mouse-rat-il-1b
抗小鼠/大鼠 IL-1b 反应:小鼠、大鼠;https://bioxcell.com/invivomab-anti-mouse-rat-il-1b
Anti-mouse TNF React: mouse; https://bioxcell.com/invivomab-anti-mouse-tnfa
抗小鼠 TNF 反应:小鼠;https://bioxcell.com/invivomab-anti-mouse-tnfa
Anti-mouse/rat IL-6 React: mouse; https://bioxcell.com/invivomab-anti-mouse-il-6-be0046
抗小鼠/大鼠 IL-6 反应:小鼠;https://bioxcell.com/invivomab-anti-mouse-il-6-be0046
Anti-mouse CD3e React: mouse; https://bioxcell.com/invivomab-anti-mouse-cd3e-be0001-1
抗小鼠 CD3e 反应:小鼠;https://bioxcell.com/invivomab-anti-mouse-cd3e-be0001-1
Anti-mouse CD28 React: mouse; https://bioxcell.com/invivomab-anti-mouse-cd28-be0015-1
抗小鼠 CD28 反应:小鼠;https://bioxcell.com/invivomab-anti-mouse-cd28-be0015-1

Animals and other research organisms
动物和其他研究生物

Policy information about studies involving animals; ARRIVE guidelines recommended for reporting animal research, and Sex and Gender in Research
关于涉及动物的研究的政策信息;建议报告动物研究的 ARRIVE 准则,以及研究中的性别和性别问题
Laboratory animals 实验动物

Abstract 摘要

Jmjd1cf//fl and Stat3K140R/K140R mice were described before (Nat Immunol. 2022;23(9):1342-1354). To generate Rosa26LSLStat3CA mice, a CAG promoter-loxP-PGK-Neo-6*SV40 pA-loxP-Kozak-Mutant-Mouse Stat3 CDS-rBG pA cassette with p.A662C (GCG to TGT) and p.N664C(AAC to TGC) was inserted into the Rosa26 locus using CRISPR-Cas9 by Cyagen Blosciences Inc. Ifng-/- (002287), Foxp3CreYFP, Cd4cre, Rag1-/-(002216), B6 (C57BL/6J) and B6-CD45.1 (Ptprca Pepcb/Boy) mice were obtained from the Jackson Laboratory. BALB/c mice were obtained from the Animal Core Facility of Nanjing Medical University. Both male and female mice at 8 -12 weeks or 6 months were used for analysis. Mice were housed in a specific-pathogen-free environment in the Animal Core Facility of Nanjing Medical University and kept at light/dark cycle; temperature and relative humidity were maintained at and respectively. Mice were all fed with normal diets ( carbohydrate, protein and fat) purchased from Jiangsu Xietong Pharmaceutical Bio-engineering (#1010084). Animal protocols were reviewed and approved by the Institutional Animal Care and Use Committee of Nanjing Medical University (IACUC Issue NO. 2007033) and the Institutional Animal Care and Use Committee Shanghai Institute of Materia Medica, Chinese Academy of Sciences (IACUC Issue NO. 2022-06-JHL-28)
Jmjd1cf//fl和Stat3K140R/K140R小鼠已在之前进行过描述(Nat Immunol.2022;23(9):1342-1354).为了产生Rosa26LSLStat3CA小鼠,Cyagen Blosciences Inc.使用CRISPR-Cas9将带有p.A662C(GCG至TGT)和p.N664C(AAC至TGC)的CAG启动子-loxP-PGK-Neo-6*SV40 pA-loxP-Kozak-Mutant-小鼠Stat3 CDS-rBG pA盒插入Rosa26基因座。Ifng-/- (002287)、Foxp3CreYFP、Cd4cre、Rag1-/-(002216)、B6 (C57BL/6J) 和 B6-CD45.1 (Ptprca Pepcb/Boy) 小鼠来自杰克逊实验室。BALB/c 小鼠来自南京医科大学动物核心实验室。8-12周或6个月的雌雄小鼠均用于分析。小鼠饲养在南京医科大学动物中心的无特定病原体环境中,光/暗周期为 ,温度和相对湿度分别保持在 。小鼠均饲喂购自江苏协通药业生物工程有限公司(#1010084)的普通饲料( 碳水化合物、 蛋白质和 脂肪)。动物实验方案经南京医科大学动物保育与使用委员会(IACUC 编号:2007033)和中国科学院上海药物研究所动物保育与使用委员会(IACUC 编号:2022-06-JHL-28)审查批准。

Wild animals 野生动物
This study did not involve wild animals.
这项研究不涉及野生动物。
Reporting on sex 关于性的报道
Both male and female mice were used in the study. Sex-matched controls were used throughout the study. Based on our preliminary experiments, Jmjd1c loss resulted in similar Treg phenotypes in male and female mice. Therefore, the sex information was not collected and disaggregated in the data shown for the manuscript.
研究中使用了雄性和雌性小鼠。在整个研究过程中使用了性别匹配的对照组。根据我们的初步实验,Jmjd1c 缺失会导致雌雄小鼠出现相似的 Treg 表型。因此,手稿中的数据没有收集和分列性别信息。
Field-collected samples 实地采集样本
No field collected samples were used in this study.
本研究没有使用实地采集的样本。
Ethics oversight 道德监督
Animal protocols were reviewed and approved by the Institutional Animal Care and Use Committee of Nanjing Medical University (LACUC-2007033) and the Institutional Animal Care and Use Committee Shanghai Institute of Materia Medica, Chinese Academy of Sciences (IACUC Issue NO. 2022-06-JHL-28).
动物实验方案经南京医科大学动物保育与使用委员会(LACUC-2007033)和中国科学院上海药物研究所动物保育与使用委员会(IACUC 编号:2022-06-JHL-28)审查批准。
Note that full information on the approval of the study protocol must also be provided in the manuscript.
请注意,手稿中还必须提供有关研究方案批准情况的完整信息。

Flow Cytometry 流式细胞术

Plots 地块
Confirm that: 请确认
The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).
轴标签说明了所用的标记和荧光色素(如 CD4-FITC)。
XThe axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).
X坐标轴刻度清晰可见。仅在组的左下方图中沿坐标轴包含数字("组 "是对相同标记的分析)。
All plots are contour plots with outliers or pseudocolor plots.
所有图均为带离群值的等值线图或伪彩色图。
A numerical value for number of cells or percentage (with statistics) is provided.
提供单元格数量或百分比(含统计数据)的数值。
Methodology 方法
Sample preparation 样品制备
Instrument 仪器
Software 软件
Spleen, and lymph nodes were collected, mashed then filtered through cell strainers for single-cell suspensions. Tumors were minced into small pieces in RPMI containing penilillin-streptomycin, DNase I ; SigmaAldrich) and collagenase ( ; Sigma-Aldrich) and digested for 60 min at , followed by the filtration with a cell strainer. TLLs were then isolated over a 40-80% Percoll density gradient (GE Healthcare) by centrifugation at for at room temperature.
收集脾脏和淋巴结,捣碎后通过 细胞过滤器过滤,得到单细胞悬浮液。在含有 青霉素-链霉素、DNase I ; SigmaAldrich)和胶原酶( ; Sigma-Aldrich)的 RPMI 中将肿瘤切成小块,在 下消化 60 分钟,然后用 细胞过滤器过滤。然后在室温下 离心 ,在 40-80% Percoll 密度梯度(GE Healthcare)上分离 TLL。
BD Aria Fusion cell sorter, BD Aria II cell sorter, Beckman CytoFLEX.
BD Aria Fusion 细胞分拣机、BD Aria II 细胞分拣机、Beckman CytoFLEX。
BD FACSDIVA v8.0.2, and Beckman CytExpert v2.4 were used to collect the Data. Flowjo v10 was used to analyze the data.
采集数据时使用了 BD FACSDIVA v8.0.2 和 Beckman CytExpert v2.4。使用 Flowjo v10 分析数据。
Cell population abundance
细胞群丰度
Gating strategy 门控策略
Sorting Treg cells for stimulation and sequencing. Post-sort fractions were pure, verified through flow cytometry analysis on the sorter used for sorting.
分选 Treg 细胞以进行刺激和测序。通过对分拣所用分拣机的流式细胞仪分析验证,分拣后的馏分纯度为
Before gating on the cells of interest shown in figures and method, dead cells were first excluded using viability dye, followed by FSC-A/SSC-A to exclude debris and then FSC-H/FSC-A to gate on singlets.
在对图和方法中所示的相关细胞进行门控之前,首先用活力染料排除死细胞,然后用 FSC-A/SSC-A 排除碎片,再用 FSC-H/FSC-A 对单细胞进行门控。
Tick this box to confirm that a figure exemplifying the gating strategy is provided in the Supplementary Information.
勾选此框以确认补充信息中提供了门控策略示例图。

  1. Department of Immunology, Key Laboratory of Immune Microenvironment and Diseases, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Nanjing, China. Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China. Department of Laboratory Medicine, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China. CAS Key Laboratory of Tissue Microenvironment and Tumor, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. These authors contributed equally: Xuehui Long, Sulin Zhang, Yuliang Wang, Jingjing Chen, Yanlai Lu, Hui Hou, Bichun Lin. e-mail: myzheng@simm.ac.cn; qinjun@sibs.ac.cn; xmwang@njmu.edu.cn
    南京医科大学附属无锡人民医院免疫科、免疫微环境与疾病重点实验室、无锡市人民医院、无锡市医学中心、南京医科大学泰州附属人民医院江苏省肿瘤生物标志物与防治重点实验室、南京医科大学泰州临床医学院肿瘤个体化医学协同创新中心。 中国科学院上海药物研究所药物研究国家重点实验室药物发现与设计中心,中国科学院大学,上海。 南京医科大学附属无锡人民医院检验医学科、无锡市人民医院、南京医科大学无锡医学中心,无锡,中国。 中科院组织微环境与肿瘤重点实验室、中科院分子细胞科学卓越中心、中国科学院上海营养与健康研究院,中国,上海。 这些作者的贡献相同:龙雪辉、张素林、王玉良、陈晶晶、卢艳来、侯辉、林碧春。电子邮箱:myzheng@simm.ac.cn; qinjun@sibs.ac.cn; xmwang@njmu.edu.cn
  2. , Percentages of Foxp cells in the indicated tissues. for DMSO; for 193D7.1, Flow cytometric analysis of PD1 and NRP1 expression in cells in the mice shown in , Flow cytometric analysis of pSTAT3 expression in cells from k. for DMSO; for 193D7. n, Lymphocytes were isolated from the indicated tissues of mice from , stimulated and stained for IFN for DMSO; for 193D7.o,p, and mice were challenged with MCA205 cells and treated with 193D7, and tumor progression was monitored. , Flow cytometric analysis of cell frequency in tumors from 193D7-treated mice. . Data represent three , four or six (c) experiments. Data were pooled from two experiments ( . Data in and are shown as mean s.d. Data in and are shown as mean s.e.m. Two-way ANOVA (g, and ), two-tailed unpaired Student's -test (k-n and ) and one-way ANOVA (h and ) were used to analyze the data. GNN, graph neural network.
    (DMSO); (193D7.1),流式细胞仪分析 中所示小鼠 细胞中 PD1 和 NRP1 的表达,流式细胞仪分析来自 k 的 细胞中 pSTAT3 的表达。 (DMSO); (193D7.n,从 小鼠的指定组织中分离淋巴细胞,对 IFN 进行刺激和染色 for DMSO; for 193D7.o,p, 和 小鼠接受 MCA205 细胞挑战和 193D7 治疗,并监测肿瘤进展。 , 193D7 处理的 小鼠肿瘤中 细胞频率的流式细胞分析。 。数据代表三次 、四次 或六次 (c) 实验。数据来自两次实验 ( 。 和 中的数据显示为平均值 s.d.。 和 中的数据显示为平均值 s.e.m。采用双向方差分析(g、 和 )、双尾非配对学生 检验(k-n 和 )和单向方差分析(h 和 )分析数据。GNN,图神经网络。