线粒体靶向atovaquone通过重塑肿瘤微环境和增强抗肿瘤免疫细胞的能量代谢来促进抗肺癌癌症免疫。

IF 20.1 1区 医学 Q1 ONCOLOGY Cancer Communications Pub Date : 2023-11-06 DOI:10.1002/cac2.12500
Donghai Xiong, Zheng Yin, Mofei Huang, Yian Wang, Micael Hardy, Balaraman Kalyanaraman, Stephen T Wong, Ming You
{"title":"线粒体靶向atovaquone通过重塑肿瘤微环境和增强抗肿瘤免疫细胞的能量代谢来促进抗肺癌癌症免疫。","authors":"Donghai Xiong,&nbsp;Zheng Yin,&nbsp;Mofei Huang,&nbsp;Yian Wang,&nbsp;Micael Hardy,&nbsp;Balaraman Kalyanaraman,&nbsp;Stephen T Wong,&nbsp;Ming You","doi":"10.1002/cac2.12500","DOIUrl":null,"url":null,"abstract":"<p>Atovaquone (ATO), a mitochondrial inhibitor, has anti-cancer effects [<span>1</span>]. Based on ATO, we developed mitochondria-targeted atovaquone (Mito-ATO) that had even stronger anti-tumor efficacy than ATO [<span>2</span>]. We synthesized Mito-ATO by attaching the bulky triphenylphosphonium (TPP) group to ATO via a ten-carbon alkyl chain (Supplementary file of methods; Supplementary Figure S1). To assess the effects of Mito-ATO on tumor microenvironment, we conducted single-cell RNA-sequencing (scRNA-seq) on treated immune cells from mice having lung tumors either treated with or without Mito-ATO. Seurat was used for clustering and annotation of CD45<sup>+</sup> immune cells [<span>3</span>]. The detected lymphoid cell populations were CD8<sup>+</sup> T cells, CD4<sup>+</sup> T cells, regulatory T cells (Tregs), gamma-delta T (Tgd) cells, B cells, and natural killer (NK) cells; and the myeloid cells identified were macrophages, neutrophils, plasmacytoid dendritic cells (pDCs), conventional dendritic cells (cDCs) and mast cells (Figure 1A-C). Clustering of CD4<sup>+</sup> T cells into seven subpopulations, the separation of neutrophils and granulocytic myeloid-derived suppressor cells (G-MDSCs), and the division of macrophages into M1 and M2 subtypes were described in our previous publication [<span>2</span>]. In this study, we further divided CD8<sup>+</sup> T cells into four subpopulations, i.e., exhausted CD8<sup>+</sup> T (CD8T_Exhausted) cells, memory like CD8<sup>+</sup> T (CD8T_MemoryLike) cells, effector memory like CD8<sup>+</sup> T (CD8T_EffectorMemory) cells and naive CD8<sup>+</sup> T (CD8T_Naive) cells, using the tumor-infiltrating CD8<sup>+</sup> lymphocyte state predictor (TILPRED) method [<span>4</span>] (Figure 1D-E). Probability scores computed with TILPRED could discriminate CD8T_Exhausted from CD8T_MemoryLike cells despite overlap between the two subsets on UMAP representation (Supplementary Figure S2). Mito-ATO treatment significantly decreased the proportion of the CD8T_Exhausted cells (7.3% vs. 32.5%, <i>P</i> &lt; 0.001) but increased the proportion of anti-tumor CD8T_EffectorMemory cells as compared with vehicle treatment (37.3% vs. 11.9%, <i>P</i> &lt; 0.001) (Figure 1F). In comparison, the percentages of CD8<sup>+</sup> T cells out of total T cells were not different between the two groups (Supplementary Table S1). For validation, we verified that Mito-ATO treatment induced changes in CD8<sup>+</sup> T cell repartition by conducting flow cytometry. Mito-ATO treatment significantly increased the percentage of cytotoxic tumor necrosis factor-alpha (TNF-α)<sup>+</sup>CD8<sup>+</sup> T cells and decreased the percentage of programmed cell death protein-1 (PD-1)<sup>+</sup> T cell immunoglobulin and mucin domain-containing protein 3 (TIM3)<sup>+</sup>CD8<sup>+</sup> T cells (Supplementary Figure S3). These matched the scRNA-seq results. We also observed a slight trend toward the upregulation of genes involved in CD8<sup>+</sup> T cell recruitment: Ccl25, Ccr7, Cxcl10, Cxcr3, Icam1, and S1pr1 (Supplementary Figure S4).</p><p>Mito-ATO treatment significantly up-regulated oxidative phosphorylation (OXPHOS) activity in four anti-tumor immune cell populations, i.e., CD8T_EffectorMemory cells, CD8T_MemoryLike cells, cytotoxic CD4<sup>+</sup> T cells (CD4T_Cytotoxic), and M1 macrophage cells (Figure 1G). Particularly, the upregulated genes after Mito-ATO treatment were significantly enriched for T cell differentiation (Supplementary Figure S5), suggesting that Mito-ATO treatment may induce CD8<sup>+</sup> T cell differentiation. In contrast, Mito-ATO treatment significantly down-regulated OXPHOS activity in five pro-tumor immune cell populations, i.e., interleukin-2 receptor subunit alpha (IL2RA)-low CD4<sup>+</sup> (CD4IL2RALO) Tregs, G-MDSCs, mast cells, IL2RA-high CD4<sup>+</sup> (CD4IL2RAHI) Tregs, and exhausted CD4<sup>+</sup> T cells (CD4T_Exhausted) (Figure 1G). The two types of Treg cells were named following the previous practice [<span>2, 5</span>]. Ten metabolic pathways activity changes were similar to OXPHOS activity changes by Mito-ATO treatment in the above immune cell populations. These pathways were glycolysis, the tricarboxylic acid (TCA) cycle, pyruvate metabolism, glutamine metabolism, Complex I, Complex III, Complex V, DNA repair, purine metabolism and pyrimidine metabolism (Figure 1G). The changes of four cell death-related pathways, i.e., DNA damage, apoptosis, cell death, and reactive oxygen species (ROS) pathways, were negatively correlated with OXPHOS activity changes by Mito-ATO treatment (Figure 1G). These suggested that Mito-ATO enhances energy metabolism and suppresses cell death in anti-tumor immune cells while inhibiting energy metabolism and promoting cell death in pro-tumor immune cells.</p><p>Compass metabolism analysis [<span>6</span>] showed similar results (Supplementary Figures S6-S14) . The key metabolic reactions of the TCA cycle and glutamine metabolism were up-regulated in the anti-tumor immune cell populations but down-regulated in the pro-tumor immune cell populations (Figure 1H-I). We identified key metabolic reactions differentially regulated by Mito-ATO across anti-tumor and pro-tumor immune cells, including aconitase 1 (Aco1)/Aco2, malate dehydrogenase 1 (Mdh1)/Mdh2, isocitrate dehydrogenase 3 alpha (Idh3a)/Idh3b/Idh3g in TCA cycle and the glutamate dehydrogenase 1 (Glud1) enzyme in glutamine metabolism. These metabolic reactions were consistently up-regulated by Mito-ATO in anti-tumor immune cells but down-regulated in pro-tumor immune cells (Figure 1J).</p><p>Furthermore, we performed gene set enrichment analysis (GSEA) [<span>7</span>]. We combined datasets of anti-tumor immune cells, which were termed Mito-ATO-stimulated OXPHOS-high cells since their OXPHOS was enhanced by Mito-ATO treatment. Analogously, we combined the pro-tumor immune cells and named them Mito-ATO-suppressed OXPHOS-low cells. The pyruvate pathway was up-regulated by Mito-ATO in Mito-ATO-stimulated OXPHOS-high cells (false discovery rate [FDR] = 0.18, normalized enrichment score [NES] = 1.23, Figure 1K) while down-regulated in Mito-ATO-suppressed OXPHOS-low cells (FDR = 0.13, NES = -1.22) (Figure 1L). The glutamine pathway was not significantly changed by Mito-ATO in Mito-ATO-stimulated OXPHOS-high cells (FDR = 0.65, NES = -0.86, Figure 1M) but down-regulated in Mito-ATO-suppressed OXPHOS-low cells (FDR = 0.03, NES = -1.40, Figure 1N). For pyruvate metabolism, Mito-ATO treatment up-regulated lactate dehydrogenase A (Ldha), mitochondrial pyruvate carrier 2 (Mpc2), pyruvate kinase (Pkm) expression in Mito-ATO-stimulated OXPHOS-high cells while down-regulated their expression in Mito-ATO-suppressed OXPHOS-low cells (Figure 1O). For the glutamine metabolism pathway, Mito-ATO treatment up-regulated Glud1, glutamic-oxaloacetic transaminase 1 (Got1) and Mdh1 expression in Mito-ATO-stimulated OXPHOS-high cells while down-regulated their expression in Mito-ATO-suppressed OXPHOS-low cells (Figure 1P). Interestingly, Mdh1 and Glud1 were also identified by Compass analysis to be significant TCA cycle and glutamine metabolic reaction regulators (Figure 1J). Therefore, the anti-cancer efficacy of Mito-ATO treatment may be realized through differential regulation of TCA and glutamine metabolism between anti-tumor and pro-tumor immune cells, in which the expression changes of Mdh1 and Glud1 could be critical. As orthogonal validation, the Seahorse metabolic flux assay showed that Mito-ATO treatment significantly increased OXPHOS activity and aerobic glycolysis in activated CD8<sup>+</sup> T (Figure 1Q-R). In contrast, Mito-ATO significantly suppressed OXPHOS and glycolysis in G-MDSCs (Figure 1S-T). These supported the predicted higher OXPHOS and glycolysis in effector memory CD8<sup>+</sup> T cells and lower OXPHOS and glycolysis in G-MDSCs upon Mito-ATO treatment.</p><p>The metabolic plasticity of different types of cells in the tumor microenvironment (TME) in response to a glutaminase inhibitor Ethyl 2-(2-amino-4-methylpentanamido)-DON (JHU083) has been reported [<span>8</span>]. In the present study, we found that Mito-ATO may differentially regulate pyruvate metabolism, glutamine metabolism and TCA cycle across immune cells with distinct roles in the TME. The metabolic plasticity effects caused by Mito-ATO treatment may contribute to the overall efficacy of this drug on lung tumors. Mito-ATO's parental compound – ATO has begun to be applied to anti-cancer clinical trials [<span>9</span>]. Given that Mito-ATO is much more potent against human cancer cell lines compared to ATO [<span>10</span>], it is reasonable to predict that Mito-ATO has great potential in clinics.</p><p>DHX did the data analysis of this project and drafted the manuscript. ZY helped with Compass analysis. MFH did the mice experiment and scRNA-seq experiment. MH synthesized the Mito-ATO compound used in this study. YW, BK, and STW helped in preparing experimental samples and worked with MY to revise the manuscript. MY also designed this study.</p><p>The authors declare no conflict of Interest.</p><p>This research was supported by National Institutes of Health (NIH): R01CA223804, R01CA232433, R01CA205633, and R01CA280746.</p><p>The animal study was reviewed, and all procedures were approved by the Medical College of Wisconsin (MCW) Institutional Animal Care and Use Committee (Ethics approval number of AUA00001807).</p><p>Not applicable.</p>","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":null,"pages":null},"PeriodicalIF":20.1000,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12500","citationCount":"0","resultStr":"{\"title\":\"Mitochondria-targeted atovaquone promotes anti-lung cancer immunity by reshaping tumor microenvironment and enhancing energy metabolism of anti-tumor immune cells\",\"authors\":\"Donghai Xiong,&nbsp;Zheng Yin,&nbsp;Mofei Huang,&nbsp;Yian Wang,&nbsp;Micael Hardy,&nbsp;Balaraman Kalyanaraman,&nbsp;Stephen T Wong,&nbsp;Ming You\",\"doi\":\"10.1002/cac2.12500\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Atovaquone (ATO), a mitochondrial inhibitor, has anti-cancer effects [<span>1</span>]. Based on ATO, we developed mitochondria-targeted atovaquone (Mito-ATO) that had even stronger anti-tumor efficacy than ATO [<span>2</span>]. We synthesized Mito-ATO by attaching the bulky triphenylphosphonium (TPP) group to ATO via a ten-carbon alkyl chain (Supplementary file of methods; Supplementary Figure S1). To assess the effects of Mito-ATO on tumor microenvironment, we conducted single-cell RNA-sequencing (scRNA-seq) on treated immune cells from mice having lung tumors either treated with or without Mito-ATO. Seurat was used for clustering and annotation of CD45<sup>+</sup> immune cells [<span>3</span>]. The detected lymphoid cell populations were CD8<sup>+</sup> T cells, CD4<sup>+</sup> T cells, regulatory T cells (Tregs), gamma-delta T (Tgd) cells, B cells, and natural killer (NK) cells; and the myeloid cells identified were macrophages, neutrophils, plasmacytoid dendritic cells (pDCs), conventional dendritic cells (cDCs) and mast cells (Figure 1A-C). Clustering of CD4<sup>+</sup> T cells into seven subpopulations, the separation of neutrophils and granulocytic myeloid-derived suppressor cells (G-MDSCs), and the division of macrophages into M1 and M2 subtypes were described in our previous publication [<span>2</span>]. In this study, we further divided CD8<sup>+</sup> T cells into four subpopulations, i.e., exhausted CD8<sup>+</sup> T (CD8T_Exhausted) cells, memory like CD8<sup>+</sup> T (CD8T_MemoryLike) cells, effector memory like CD8<sup>+</sup> T (CD8T_EffectorMemory) cells and naive CD8<sup>+</sup> T (CD8T_Naive) cells, using the tumor-infiltrating CD8<sup>+</sup> lymphocyte state predictor (TILPRED) method [<span>4</span>] (Figure 1D-E). Probability scores computed with TILPRED could discriminate CD8T_Exhausted from CD8T_MemoryLike cells despite overlap between the two subsets on UMAP representation (Supplementary Figure S2). Mito-ATO treatment significantly decreased the proportion of the CD8T_Exhausted cells (7.3% vs. 32.5%, <i>P</i> &lt; 0.001) but increased the proportion of anti-tumor CD8T_EffectorMemory cells as compared with vehicle treatment (37.3% vs. 11.9%, <i>P</i> &lt; 0.001) (Figure 1F). In comparison, the percentages of CD8<sup>+</sup> T cells out of total T cells were not different between the two groups (Supplementary Table S1). For validation, we verified that Mito-ATO treatment induced changes in CD8<sup>+</sup> T cell repartition by conducting flow cytometry. Mito-ATO treatment significantly increased the percentage of cytotoxic tumor necrosis factor-alpha (TNF-α)<sup>+</sup>CD8<sup>+</sup> T cells and decreased the percentage of programmed cell death protein-1 (PD-1)<sup>+</sup> T cell immunoglobulin and mucin domain-containing protein 3 (TIM3)<sup>+</sup>CD8<sup>+</sup> T cells (Supplementary Figure S3). These matched the scRNA-seq results. We also observed a slight trend toward the upregulation of genes involved in CD8<sup>+</sup> T cell recruitment: Ccl25, Ccr7, Cxcl10, Cxcr3, Icam1, and S1pr1 (Supplementary Figure S4).</p><p>Mito-ATO treatment significantly up-regulated oxidative phosphorylation (OXPHOS) activity in four anti-tumor immune cell populations, i.e., CD8T_EffectorMemory cells, CD8T_MemoryLike cells, cytotoxic CD4<sup>+</sup> T cells (CD4T_Cytotoxic), and M1 macrophage cells (Figure 1G). Particularly, the upregulated genes after Mito-ATO treatment were significantly enriched for T cell differentiation (Supplementary Figure S5), suggesting that Mito-ATO treatment may induce CD8<sup>+</sup> T cell differentiation. In contrast, Mito-ATO treatment significantly down-regulated OXPHOS activity in five pro-tumor immune cell populations, i.e., interleukin-2 receptor subunit alpha (IL2RA)-low CD4<sup>+</sup> (CD4IL2RALO) Tregs, G-MDSCs, mast cells, IL2RA-high CD4<sup>+</sup> (CD4IL2RAHI) Tregs, and exhausted CD4<sup>+</sup> T cells (CD4T_Exhausted) (Figure 1G). The two types of Treg cells were named following the previous practice [<span>2, 5</span>]. Ten metabolic pathways activity changes were similar to OXPHOS activity changes by Mito-ATO treatment in the above immune cell populations. These pathways were glycolysis, the tricarboxylic acid (TCA) cycle, pyruvate metabolism, glutamine metabolism, Complex I, Complex III, Complex V, DNA repair, purine metabolism and pyrimidine metabolism (Figure 1G). The changes of four cell death-related pathways, i.e., DNA damage, apoptosis, cell death, and reactive oxygen species (ROS) pathways, were negatively correlated with OXPHOS activity changes by Mito-ATO treatment (Figure 1G). These suggested that Mito-ATO enhances energy metabolism and suppresses cell death in anti-tumor immune cells while inhibiting energy metabolism and promoting cell death in pro-tumor immune cells.</p><p>Compass metabolism analysis [<span>6</span>] showed similar results (Supplementary Figures S6-S14) . The key metabolic reactions of the TCA cycle and glutamine metabolism were up-regulated in the anti-tumor immune cell populations but down-regulated in the pro-tumor immune cell populations (Figure 1H-I). We identified key metabolic reactions differentially regulated by Mito-ATO across anti-tumor and pro-tumor immune cells, including aconitase 1 (Aco1)/Aco2, malate dehydrogenase 1 (Mdh1)/Mdh2, isocitrate dehydrogenase 3 alpha (Idh3a)/Idh3b/Idh3g in TCA cycle and the glutamate dehydrogenase 1 (Glud1) enzyme in glutamine metabolism. These metabolic reactions were consistently up-regulated by Mito-ATO in anti-tumor immune cells but down-regulated in pro-tumor immune cells (Figure 1J).</p><p>Furthermore, we performed gene set enrichment analysis (GSEA) [<span>7</span>]. We combined datasets of anti-tumor immune cells, which were termed Mito-ATO-stimulated OXPHOS-high cells since their OXPHOS was enhanced by Mito-ATO treatment. Analogously, we combined the pro-tumor immune cells and named them Mito-ATO-suppressed OXPHOS-low cells. The pyruvate pathway was up-regulated by Mito-ATO in Mito-ATO-stimulated OXPHOS-high cells (false discovery rate [FDR] = 0.18, normalized enrichment score [NES] = 1.23, Figure 1K) while down-regulated in Mito-ATO-suppressed OXPHOS-low cells (FDR = 0.13, NES = -1.22) (Figure 1L). The glutamine pathway was not significantly changed by Mito-ATO in Mito-ATO-stimulated OXPHOS-high cells (FDR = 0.65, NES = -0.86, Figure 1M) but down-regulated in Mito-ATO-suppressed OXPHOS-low cells (FDR = 0.03, NES = -1.40, Figure 1N). For pyruvate metabolism, Mito-ATO treatment up-regulated lactate dehydrogenase A (Ldha), mitochondrial pyruvate carrier 2 (Mpc2), pyruvate kinase (Pkm) expression in Mito-ATO-stimulated OXPHOS-high cells while down-regulated their expression in Mito-ATO-suppressed OXPHOS-low cells (Figure 1O). For the glutamine metabolism pathway, Mito-ATO treatment up-regulated Glud1, glutamic-oxaloacetic transaminase 1 (Got1) and Mdh1 expression in Mito-ATO-stimulated OXPHOS-high cells while down-regulated their expression in Mito-ATO-suppressed OXPHOS-low cells (Figure 1P). Interestingly, Mdh1 and Glud1 were also identified by Compass analysis to be significant TCA cycle and glutamine metabolic reaction regulators (Figure 1J). Therefore, the anti-cancer efficacy of Mito-ATO treatment may be realized through differential regulation of TCA and glutamine metabolism between anti-tumor and pro-tumor immune cells, in which the expression changes of Mdh1 and Glud1 could be critical. As orthogonal validation, the Seahorse metabolic flux assay showed that Mito-ATO treatment significantly increased OXPHOS activity and aerobic glycolysis in activated CD8<sup>+</sup> T (Figure 1Q-R). In contrast, Mito-ATO significantly suppressed OXPHOS and glycolysis in G-MDSCs (Figure 1S-T). These supported the predicted higher OXPHOS and glycolysis in effector memory CD8<sup>+</sup> T cells and lower OXPHOS and glycolysis in G-MDSCs upon Mito-ATO treatment.</p><p>The metabolic plasticity of different types of cells in the tumor microenvironment (TME) in response to a glutaminase inhibitor Ethyl 2-(2-amino-4-methylpentanamido)-DON (JHU083) has been reported [<span>8</span>]. In the present study, we found that Mito-ATO may differentially regulate pyruvate metabolism, glutamine metabolism and TCA cycle across immune cells with distinct roles in the TME. The metabolic plasticity effects caused by Mito-ATO treatment may contribute to the overall efficacy of this drug on lung tumors. Mito-ATO's parental compound – ATO has begun to be applied to anti-cancer clinical trials [<span>9</span>]. Given that Mito-ATO is much more potent against human cancer cell lines compared to ATO [<span>10</span>], it is reasonable to predict that Mito-ATO has great potential in clinics.</p><p>DHX did the data analysis of this project and drafted the manuscript. ZY helped with Compass analysis. MFH did the mice experiment and scRNA-seq experiment. MH synthesized the Mito-ATO compound used in this study. YW, BK, and STW helped in preparing experimental samples and worked with MY to revise the manuscript. MY also designed this study.</p><p>The authors declare no conflict of Interest.</p><p>This research was supported by National Institutes of Health (NIH): R01CA223804, R01CA232433, R01CA205633, and R01CA280746.</p><p>The animal study was reviewed, and all procedures were approved by the Medical College of Wisconsin (MCW) Institutional Animal Care and Use Committee (Ethics approval number of AUA00001807).</p><p>Not applicable.</p>\",\"PeriodicalId\":9495,\"journal\":{\"name\":\"Cancer Communications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":20.1000,\"publicationDate\":\"2023-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12500\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Communications\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cac2.12500\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Communications","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cac2.12500","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
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摘要

线粒体抑制剂阿托伐醌(ATO)具有抗癌作用[1]。在 ATO 的基础上,我们开发出了线粒体靶向阿托伐醌(Mitochondria-targeted atovaquone,Mito-ATO),其抗肿瘤效果比 ATO 更强[2]。我们通过一条十碳烷基链将笨重的三苯基膦(TPP)基团连接到 ATO 上,从而合成了 Mito-ATO(方法的补充文件;补充图 S1)。为了评估Mito-ATO对肿瘤微环境的影响,我们对肺肿瘤小鼠的免疫细胞进行了单细胞RNA测序(scRNA-seq),这些免疫细胞有的接受过Mito-ATO治疗,有的没有。采用 Seurat 对 CD45+ 免疫细胞进行聚类和注释 [3]。检测到的淋巴细胞群包括 CD8+ T 细胞、CD4+ T 细胞、调节性 T 细胞(Tregs)、γ-δ T 细胞(Tgd)、B 细胞和自然杀伤(NK)细胞;检测到的骨髓细胞包括巨噬细胞、中性粒细胞、浆细胞树突状细胞(pDCs)、传统树突状细胞(cDCs)和肥大细胞(图 1A-C)。CD4+T细胞聚类为七个亚群,中性粒细胞和粒细胞髓源性抑制细胞(G-MDSCs)分离,巨噬细胞分为M1和M2亚型,这些在我们之前发表的文章中都有描述[2]。在本研究中,我们进一步将 CD8+ T 细胞分为四个亚群,即我们使用肿瘤浸润 CD8+ 淋巴细胞状态预测法(TILPRED)[4]进一步将 CD8+ T 细胞分为四个亚群,即衰竭 CD8+ T(CD8T_Exhausted)细胞、记忆 CD8+ T(CD8T_MemoryLike)细胞、效应记忆 CD8+ T(CD8T_EffectorMemory)细胞和幼稚 CD8+ T(CD8T_Naive)细胞(图 1D-E)。尽管CD8T_Exhausted和CD8T_MemoryLike两个亚群在UMAP表征上有重叠,但用TILPRED计算的概率分数可以区分这两个亚群(补充图S2)。与车辆处理相比,Mito-ATO 处理明显降低了 CD8T_Exhausted 细胞的比例(7.3% vs. 32.5%,P &lt; 0.001),但增加了抗肿瘤 CD8T_EffectorMemory 细胞的比例(37.3% vs. 11.9%,P &lt; 0.001)(图 1F)。相比之下,两组 CD8+ T 细胞占 T 细胞总数的百分比没有差异(补充表 S1)。为了进行验证,我们通过流式细胞术验证了米托-ATO 治疗诱导了 CD8+ T 细胞重新分区的变化。米托-ATO治疗明显增加了细胞毒性肿瘤坏死因子-α(TNF-α)+CD8+ T细胞的比例,降低了程序性细胞死亡蛋白-1(PD-1)+ T细胞免疫球蛋白和含粘蛋白结构域蛋白3(TIM3)+CD8+ T细胞的比例(补充图S3)。这些结果与 scRNA-seq 的结果相吻合。我们还观察到参与 CD8+ T 细胞招募的基因有轻微的上调趋势:Ccl25、Ccr7、Cxcl10、Cxcr3、Icam1和S1pr1(补充图S4)。米托-ATO处理显著上调了四个抗肿瘤免疫细胞群的氧化磷酸化(OXPHOS)活性,即CD8T_EffectorMemory细胞、CD8T_MemoryLike细胞、细胞毒性CD4+ T细胞(CD4T_Cytotoxic)和M1巨噬细胞(图1G)。特别是,经 Mito-ATO 处理后上调的基因明显富集于 T 细胞分化(补充图 S5),表明 Mito-ATO 处理可能诱导 CD8+ T 细胞分化。相比之下,Mito-ATO 处理显著下调了五种促肿瘤免疫细胞群的 OXPHOS 活性,即白细胞介素-2 受体亚基α(IL2RA)-低的 CD4+ (CD4IL2RALO)Tregs、G-MDSCs、肥大细胞、IL2RA-高的 CD4+ (CD4IL2RAHI)Tregs 和衰竭的 CD4+ T 细胞(CD4T_Exhausted)(图 1G)。这两种类型的 Treg 细胞是按照以往的做法命名的[2, 5]。在上述免疫细胞群中,有十种代谢途径的活性变化与经 Mito-ATO 处理后的 OXPHOS 活性变化相似。这些途径分别是糖酵解、三羧酸(TCA)循环、丙酮酸代谢、谷氨酰胺代谢、复合体 I、复合体 III、复合体 V、DNA 修复、嘌呤代谢和嘧啶代谢(图 1G)。DNA损伤、细胞凋亡、细胞死亡和活性氧(ROS)途径等四种细胞死亡相关途径的变化与OXPHOS活性的变化呈负相关(图1G)。Compass 代谢分析[6]显示了类似的结果(补充图 S6-S14)。TCA 循环和谷氨酰胺代谢的关键代谢反应在抗肿瘤免疫细胞群中上调,而在促肿瘤免疫细胞群中下调(图 1H-I)。
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Mitochondria-targeted atovaquone promotes anti-lung cancer immunity by reshaping tumor microenvironment and enhancing energy metabolism of anti-tumor immune cells

Atovaquone (ATO), a mitochondrial inhibitor, has anti-cancer effects [1]. Based on ATO, we developed mitochondria-targeted atovaquone (Mito-ATO) that had even stronger anti-tumor efficacy than ATO [2]. We synthesized Mito-ATO by attaching the bulky triphenylphosphonium (TPP) group to ATO via a ten-carbon alkyl chain (Supplementary file of methods; Supplementary Figure S1). To assess the effects of Mito-ATO on tumor microenvironment, we conducted single-cell RNA-sequencing (scRNA-seq) on treated immune cells from mice having lung tumors either treated with or without Mito-ATO. Seurat was used for clustering and annotation of CD45+ immune cells [3]. The detected lymphoid cell populations were CD8+ T cells, CD4+ T cells, regulatory T cells (Tregs), gamma-delta T (Tgd) cells, B cells, and natural killer (NK) cells; and the myeloid cells identified were macrophages, neutrophils, plasmacytoid dendritic cells (pDCs), conventional dendritic cells (cDCs) and mast cells (Figure 1A-C). Clustering of CD4+ T cells into seven subpopulations, the separation of neutrophils and granulocytic myeloid-derived suppressor cells (G-MDSCs), and the division of macrophages into M1 and M2 subtypes were described in our previous publication [2]. In this study, we further divided CD8+ T cells into four subpopulations, i.e., exhausted CD8+ T (CD8T_Exhausted) cells, memory like CD8+ T (CD8T_MemoryLike) cells, effector memory like CD8+ T (CD8T_EffectorMemory) cells and naive CD8+ T (CD8T_Naive) cells, using the tumor-infiltrating CD8+ lymphocyte state predictor (TILPRED) method [4] (Figure 1D-E). Probability scores computed with TILPRED could discriminate CD8T_Exhausted from CD8T_MemoryLike cells despite overlap between the two subsets on UMAP representation (Supplementary Figure S2). Mito-ATO treatment significantly decreased the proportion of the CD8T_Exhausted cells (7.3% vs. 32.5%, P < 0.001) but increased the proportion of anti-tumor CD8T_EffectorMemory cells as compared with vehicle treatment (37.3% vs. 11.9%, P < 0.001) (Figure 1F). In comparison, the percentages of CD8+ T cells out of total T cells were not different between the two groups (Supplementary Table S1). For validation, we verified that Mito-ATO treatment induced changes in CD8+ T cell repartition by conducting flow cytometry. Mito-ATO treatment significantly increased the percentage of cytotoxic tumor necrosis factor-alpha (TNF-α)+CD8+ T cells and decreased the percentage of programmed cell death protein-1 (PD-1)+ T cell immunoglobulin and mucin domain-containing protein 3 (TIM3)+CD8+ T cells (Supplementary Figure S3). These matched the scRNA-seq results. We also observed a slight trend toward the upregulation of genes involved in CD8+ T cell recruitment: Ccl25, Ccr7, Cxcl10, Cxcr3, Icam1, and S1pr1 (Supplementary Figure S4).

Mito-ATO treatment significantly up-regulated oxidative phosphorylation (OXPHOS) activity in four anti-tumor immune cell populations, i.e., CD8T_EffectorMemory cells, CD8T_MemoryLike cells, cytotoxic CD4+ T cells (CD4T_Cytotoxic), and M1 macrophage cells (Figure 1G). Particularly, the upregulated genes after Mito-ATO treatment were significantly enriched for T cell differentiation (Supplementary Figure S5), suggesting that Mito-ATO treatment may induce CD8+ T cell differentiation. In contrast, Mito-ATO treatment significantly down-regulated OXPHOS activity in five pro-tumor immune cell populations, i.e., interleukin-2 receptor subunit alpha (IL2RA)-low CD4+ (CD4IL2RALO) Tregs, G-MDSCs, mast cells, IL2RA-high CD4+ (CD4IL2RAHI) Tregs, and exhausted CD4+ T cells (CD4T_Exhausted) (Figure 1G). The two types of Treg cells were named following the previous practice [2, 5]. Ten metabolic pathways activity changes were similar to OXPHOS activity changes by Mito-ATO treatment in the above immune cell populations. These pathways were glycolysis, the tricarboxylic acid (TCA) cycle, pyruvate metabolism, glutamine metabolism, Complex I, Complex III, Complex V, DNA repair, purine metabolism and pyrimidine metabolism (Figure 1G). The changes of four cell death-related pathways, i.e., DNA damage, apoptosis, cell death, and reactive oxygen species (ROS) pathways, were negatively correlated with OXPHOS activity changes by Mito-ATO treatment (Figure 1G). These suggested that Mito-ATO enhances energy metabolism and suppresses cell death in anti-tumor immune cells while inhibiting energy metabolism and promoting cell death in pro-tumor immune cells.

Compass metabolism analysis [6] showed similar results (Supplementary Figures S6-S14) . The key metabolic reactions of the TCA cycle and glutamine metabolism were up-regulated in the anti-tumor immune cell populations but down-regulated in the pro-tumor immune cell populations (Figure 1H-I). We identified key metabolic reactions differentially regulated by Mito-ATO across anti-tumor and pro-tumor immune cells, including aconitase 1 (Aco1)/Aco2, malate dehydrogenase 1 (Mdh1)/Mdh2, isocitrate dehydrogenase 3 alpha (Idh3a)/Idh3b/Idh3g in TCA cycle and the glutamate dehydrogenase 1 (Glud1) enzyme in glutamine metabolism. These metabolic reactions were consistently up-regulated by Mito-ATO in anti-tumor immune cells but down-regulated in pro-tumor immune cells (Figure 1J).

Furthermore, we performed gene set enrichment analysis (GSEA) [7]. We combined datasets of anti-tumor immune cells, which were termed Mito-ATO-stimulated OXPHOS-high cells since their OXPHOS was enhanced by Mito-ATO treatment. Analogously, we combined the pro-tumor immune cells and named them Mito-ATO-suppressed OXPHOS-low cells. The pyruvate pathway was up-regulated by Mito-ATO in Mito-ATO-stimulated OXPHOS-high cells (false discovery rate [FDR] = 0.18, normalized enrichment score [NES] = 1.23, Figure 1K) while down-regulated in Mito-ATO-suppressed OXPHOS-low cells (FDR = 0.13, NES = -1.22) (Figure 1L). The glutamine pathway was not significantly changed by Mito-ATO in Mito-ATO-stimulated OXPHOS-high cells (FDR = 0.65, NES = -0.86, Figure 1M) but down-regulated in Mito-ATO-suppressed OXPHOS-low cells (FDR = 0.03, NES = -1.40, Figure 1N). For pyruvate metabolism, Mito-ATO treatment up-regulated lactate dehydrogenase A (Ldha), mitochondrial pyruvate carrier 2 (Mpc2), pyruvate kinase (Pkm) expression in Mito-ATO-stimulated OXPHOS-high cells while down-regulated their expression in Mito-ATO-suppressed OXPHOS-low cells (Figure 1O). For the glutamine metabolism pathway, Mito-ATO treatment up-regulated Glud1, glutamic-oxaloacetic transaminase 1 (Got1) and Mdh1 expression in Mito-ATO-stimulated OXPHOS-high cells while down-regulated their expression in Mito-ATO-suppressed OXPHOS-low cells (Figure 1P). Interestingly, Mdh1 and Glud1 were also identified by Compass analysis to be significant TCA cycle and glutamine metabolic reaction regulators (Figure 1J). Therefore, the anti-cancer efficacy of Mito-ATO treatment may be realized through differential regulation of TCA and glutamine metabolism between anti-tumor and pro-tumor immune cells, in which the expression changes of Mdh1 and Glud1 could be critical. As orthogonal validation, the Seahorse metabolic flux assay showed that Mito-ATO treatment significantly increased OXPHOS activity and aerobic glycolysis in activated CD8+ T (Figure 1Q-R). In contrast, Mito-ATO significantly suppressed OXPHOS and glycolysis in G-MDSCs (Figure 1S-T). These supported the predicted higher OXPHOS and glycolysis in effector memory CD8+ T cells and lower OXPHOS and glycolysis in G-MDSCs upon Mito-ATO treatment.

The metabolic plasticity of different types of cells in the tumor microenvironment (TME) in response to a glutaminase inhibitor Ethyl 2-(2-amino-4-methylpentanamido)-DON (JHU083) has been reported [8]. In the present study, we found that Mito-ATO may differentially regulate pyruvate metabolism, glutamine metabolism and TCA cycle across immune cells with distinct roles in the TME. The metabolic plasticity effects caused by Mito-ATO treatment may contribute to the overall efficacy of this drug on lung tumors. Mito-ATO's parental compound – ATO has begun to be applied to anti-cancer clinical trials [9]. Given that Mito-ATO is much more potent against human cancer cell lines compared to ATO [10], it is reasonable to predict that Mito-ATO has great potential in clinics.

DHX did the data analysis of this project and drafted the manuscript. ZY helped with Compass analysis. MFH did the mice experiment and scRNA-seq experiment. MH synthesized the Mito-ATO compound used in this study. YW, BK, and STW helped in preparing experimental samples and worked with MY to revise the manuscript. MY also designed this study.

The authors declare no conflict of Interest.

This research was supported by National Institutes of Health (NIH): R01CA223804, R01CA232433, R01CA205633, and R01CA280746.

The animal study was reviewed, and all procedures were approved by the Medical College of Wisconsin (MCW) Institutional Animal Care and Use Committee (Ethics approval number of AUA00001807).

Not applicable.

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来源期刊
Cancer Communications
Cancer Communications Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
25.50
自引率
4.30%
发文量
153
审稿时长
4 weeks
期刊介绍: Cancer Communications is an open access, peer-reviewed online journal that encompasses basic, clinical, and translational cancer research. The journal welcomes submissions concerning clinical trials, epidemiology, molecular and cellular biology, and genetics.
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