Yong Peng, Jason Karpus, Jyoti D Patel, Everett E Vokes, Marina Chiara Garassino, Kirsteen Lugtu, Zhou Zhang, Wei Zhang, Mengjie Chen, Chuan He, Christine M Bestvina
{"title":"Epigenomic exploration of disease status of EGFR-mutated non-small cell lung cancer using plasma cell-free DNA hydroxymethylomes.","authors":"Yong Peng, Jason Karpus, Jyoti D Patel, Everett E Vokes, Marina Chiara Garassino, Kirsteen Lugtu, Zhou Zhang, Wei Zhang, Mengjie Chen, Chuan He, Christine M Bestvina","doi":"10.1002/cac2.12606","DOIUrl":"https://doi.org/10.1002/cac2.12606","url":null,"abstract":"","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":" ","pages":""},"PeriodicalIF":20.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142615168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yichuan Liu, Hui-Qi Qu, Xiao Chang, Frank D Mentch, Haijun Qiu, Kenny Nguyen, Kayleigh Ostberg, Tiancheng Wang, Joseph Glessner, Hakon Hakonarson
<p>Childhood solid tumors represent a significant public health challenge worldwide, with approximately 15,000 new cases annually in the United States and an estimated 300,000 globally. Down syndrome (DS), a genetic disorder characterized by an extra full or partial copy of chromosome 21, results in distinctive developmental and physical features. Notably, individuals with DS exhibit a remarkable resilience against solid tumors compared to the general population, with an overall standardized incidence ratio (SIR) of 0.45, despite their increased susceptibility to hematologic malignancies [<span>1</span>]. This paradoxical observation has spurred extensive research aimed at uncovering the biological underpinnings of this natural resistance to solid cancers. Current theories suggest that the overexpression of specific genes on chromosome 21 may confer protective benefits (e.g. <i>RCAN1</i> contributes to antiangiogenic effects), and alterations in immune system function may enhance apoptosis and DNA repair pathways in individuals with trisomy 21 DS [<span>2</span>]. The well-established epigenetic effects of trisomy 21, which influence the entire genome, are another potential contributor to the reduced risk of solid tumors [<span>3</span>]. Nonetheless, these hypotheses face significant challenges, such as the potential oversimplification of complex genetic interactions and the lack of comprehensive genome-wide analyses. This study seeks to critically evaluate the correlations between genomic variants and cancer clinical phenotypes in patients with DS, and proposes directions for future research into the genetic and molecular mechanisms that confer cancer resistance in DS, potentially transforming our understanding and treatment of pediatric cancers.</p><p>We conducted an innovative unbiased data-driven analysis in 2,452 whole-genome sequencing (WGS) samples with both DS individuals (<i>n</i> = 635) and pediatric oncology cases (<i>n</i> = 280) within the Gabriella Miller Kids First program project (https://kidsfirstdrc.org/) housed at the Children's Hospital of Philadelphia (Supplementary Figure S1). Additionally, 284 RNA sequencing samples from human peripheral blood mononuclear cells (PBMCs), a subset of WGS samples, were also analyzed, offering unprecedented insights into the complex interplay of genetic and immunological factors influencing cancer resistance.</p><p>The importance of each variant was calculated using deep learning algorithms, and their corresponding weights to DS cancer were generated based on linear algebra models as described in the Supplementary Materials and Methods. There were 2,523 unique cancer protective variants identified based on deep learning algorithms combined with linear algebra models in exonic, intronic, non-coding RNA and 5’untranslated region (5’UTR) regions. The prevalence for cancer protective variants in the DS cancer group (89.2%) is significantly higher compared to non-DS cancer individuals (58.1%) (<i>P
{"title":"Deciphering protective genomic factors of tumor development in pediatric Down syndrome via deep learning approach to whole genome and RNA sequencing","authors":"Yichuan Liu, Hui-Qi Qu, Xiao Chang, Frank D Mentch, Haijun Qiu, Kenny Nguyen, Kayleigh Ostberg, Tiancheng Wang, Joseph Glessner, Hakon Hakonarson","doi":"10.1002/cac2.12612","DOIUrl":"10.1002/cac2.12612","url":null,"abstract":"<p>Childhood solid tumors represent a significant public health challenge worldwide, with approximately 15,000 new cases annually in the United States and an estimated 300,000 globally. Down syndrome (DS), a genetic disorder characterized by an extra full or partial copy of chromosome 21, results in distinctive developmental and physical features. Notably, individuals with DS exhibit a remarkable resilience against solid tumors compared to the general population, with an overall standardized incidence ratio (SIR) of 0.45, despite their increased susceptibility to hematologic malignancies [<span>1</span>]. This paradoxical observation has spurred extensive research aimed at uncovering the biological underpinnings of this natural resistance to solid cancers. Current theories suggest that the overexpression of specific genes on chromosome 21 may confer protective benefits (e.g. <i>RCAN1</i> contributes to antiangiogenic effects), and alterations in immune system function may enhance apoptosis and DNA repair pathways in individuals with trisomy 21 DS [<span>2</span>]. The well-established epigenetic effects of trisomy 21, which influence the entire genome, are another potential contributor to the reduced risk of solid tumors [<span>3</span>]. Nonetheless, these hypotheses face significant challenges, such as the potential oversimplification of complex genetic interactions and the lack of comprehensive genome-wide analyses. This study seeks to critically evaluate the correlations between genomic variants and cancer clinical phenotypes in patients with DS, and proposes directions for future research into the genetic and molecular mechanisms that confer cancer resistance in DS, potentially transforming our understanding and treatment of pediatric cancers.</p><p>We conducted an innovative unbiased data-driven analysis in 2,452 whole-genome sequencing (WGS) samples with both DS individuals (<i>n</i> = 635) and pediatric oncology cases (<i>n</i> = 280) within the Gabriella Miller Kids First program project (https://kidsfirstdrc.org/) housed at the Children's Hospital of Philadelphia (Supplementary Figure S1). Additionally, 284 RNA sequencing samples from human peripheral blood mononuclear cells (PBMCs), a subset of WGS samples, were also analyzed, offering unprecedented insights into the complex interplay of genetic and immunological factors influencing cancer resistance.</p><p>The importance of each variant was calculated using deep learning algorithms, and their corresponding weights to DS cancer were generated based on linear algebra models as described in the Supplementary Materials and Methods. There were 2,523 unique cancer protective variants identified based on deep learning algorithms combined with linear algebra models in exonic, intronic, non-coding RNA and 5’untranslated region (5’UTR) regions. The prevalence for cancer protective variants in the DS cancer group (89.2%) is significantly higher compared to non-DS cancer individuals (58.1%) (<i>P","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":"44 11","pages":"1374-1378"},"PeriodicalIF":20.1,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12612","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142458708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ji Jiang, Pengfei Ye, Ningning Sun, Weihua Zhu, Mei Yang, Manman Yu, Jingjing Yu, Hui Zhang, Zijie Gao, Ningjie Zhang, Shijie Guo, Yuru Ji, Siqi Li, Cuncun Zhang, Sainan Miao, Mengqi Chai, Wenmin Liu, Yue An, Jian Hong, Wei Wei, Shihao Zhang, Huan Qiu
Background
Despite significant strides in lung cancer immunotherapy, the response rates for Kirsten rat sarcoma viral oncogene homolog (KRAS)-driven lung adenocarcinoma (LUAD) patients remain limited. Fibrinogen-like protein 1 (FGL1) is a newly identified immune checkpoint target, and the study of related resistance mechanisms is crucial for improving the treatment outcomes of LUAD patients. This study aimed to elucidate the potential mechanism by which FGL1 regulates the tumor microenvironment in KRAS-mutated cancer.
Methods
The expression levels of FGL1 and SET1 histone methyltransferase (SET1A) in lung cancer were assessed using public databases and clinical samples. Lentiviruses were constructed for transduction to overexpress or silence FGL1 in lung cancer cells and mouse models. The effects of FGL1 and Yes-associated protein (Yap) on the immunoreactivity of cytotoxic T cells in tumor tissues were evaluated using immunofluorescence staining and flow cytometry. Chromatin immunoprecipitation and dual luciferase reporter assays were used to study the SET1A-directed transcriptional program.
Results
Upregulation of FGL1 expression in KRAS-mutated cancer was inversely correlated with the infiltration of CD8+ T cells. Mechanistically, KRAS activated extracellular signal-regulated kinase 1/2 (ERK1/2), which subsequently phosphorylated SET1A and increased its stability and nuclear localization. SET1A-mediated methylation of Yap led to Yap sequestration in the nucleus, thereby promoting Yap-induced transcription of FGL1 and immune evasion in KRAS-driven LUAD. Notably, dual blockade of programmed cell death-1 (PD-1) and FGL1 further increased the therapeutic efficacy of anti-PD-1 immunotherapy in LUAD patients.
Conclusion
FGL1 could be used as a diagnostic biomarker of KRAS-mutated lung cancer, and targeting the Yap-FGL1 axis could increase the efficacy of anti-PD-1 immunotherapy.
{"title":"Yap methylation-induced FGL1 expression suppresses anti-tumor immunity and promotes tumor progression in KRAS-driven lung adenocarcinoma","authors":"Ji Jiang, Pengfei Ye, Ningning Sun, Weihua Zhu, Mei Yang, Manman Yu, Jingjing Yu, Hui Zhang, Zijie Gao, Ningjie Zhang, Shijie Guo, Yuru Ji, Siqi Li, Cuncun Zhang, Sainan Miao, Mengqi Chai, Wenmin Liu, Yue An, Jian Hong, Wei Wei, Shihao Zhang, Huan Qiu","doi":"10.1002/cac2.12609","DOIUrl":"10.1002/cac2.12609","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Despite significant strides in lung cancer immunotherapy, the response rates for Kirsten rat sarcoma viral oncogene homolog (<i>KRAS</i>)-driven lung adenocarcinoma (LUAD) patients remain limited. Fibrinogen-like protein 1 (FGL1) is a newly identified immune checkpoint target, and the study of related resistance mechanisms is crucial for improving the treatment outcomes of LUAD patients. This study aimed to elucidate the potential mechanism by which FGL1 regulates the tumor microenvironment in <i>KRAS</i>-mutated cancer.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The expression levels of FGL1 and SET1 histone methyltransferase (SET1A) in lung cancer were assessed using public databases and clinical samples. Lentiviruses were constructed for transduction to overexpress or silence FGL1 in lung cancer cells and mouse models. The effects of FGL1 and Yes-associated protein (Yap) on the immunoreactivity of cytotoxic T cells in tumor tissues were evaluated using immunofluorescence staining and flow cytometry. Chromatin immunoprecipitation and dual luciferase reporter assays were used to study the SET1A-directed transcriptional program.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Upregulation of FGL1 expression in <i>KRAS</i>-mutated cancer was inversely correlated with the infiltration of CD8<sup>+</sup> T cells. Mechanistically, <i>KRAS</i> activated extracellular signal-regulated kinase 1/2 (ERK1/2), which subsequently phosphorylated SET1A and increased its stability and nuclear localization. SET1A-mediated methylation of Yap led to Yap sequestration in the nucleus, thereby promoting Yap-induced transcription of FGL1 and immune evasion in <i>KRAS</i>-driven LUAD. Notably, dual blockade of programmed cell death-1 (PD-1) and FGL1 further increased the therapeutic efficacy of anti-PD-1 immunotherapy in LUAD patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>FGL1 could be used as a diagnostic biomarker of <i>KRAS</i>-mutated lung cancer, and targeting the Yap-FGL1 axis could increase the efficacy of anti-PD-1 immunotherapy.</p>\u0000 </section>\u0000 </div>","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":"44 11","pages":"1350-1373"},"PeriodicalIF":20.1,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12609","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142342201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Epidemiological evidence indicates that major depressive disorder (MDD) may predispose the development and prognosis of breast cancer (BC) in females [<span>1</span>]. However, the mechanisms linking these phenotypes are not fully understood. Chronic stress, a hallmark of depression, has been underscored to affect anti-tumor immunity, tumor metabolic reprogramming, hormone synthesis in BC [<span>2, 3</span>], and increase tumor metastasis [<span>4</span>], but there is a lack of detailed cellular-level characterization of how MDD history affects the tumorigenesis of BC. This study explored the single-cell atlas of multiple tissues from BC patients with and without a history of MDD for characterizing the potential molecular alternations in their tumorigenesis (Figure 1A).</p><p>Paired primary tumor tissues (<i>n</i> = 10), adjacent normal tissues (<i>n</i> = 7), and peripheral blood samples (<i>n</i> = 10) were collected from a cohort of 10 BC patients, 5 of whom had a history of MDD (Supplementary Table S1). All BC patients had estrogen receptor (ER)-positive tumors and were further predicted as Luminal A (<i>n</i> = 9) and B subtypes (<i>n</i> = 1) (Supplementary Table S2). Further details on patient recruitment, sample handling, and single-cell data analysis are provided in Supplementary Methods. In total, we obtained 224,557 single cells and further annotated them into major cell subsets based on lineage markers and copy number variations [<span>5</span>] (Figure 1B, Supplementary Figure S1A-B). Aneuploid cells in primary tumor tissues were obtained (Supplementary Table S3) to characterize their phenotypic differences in BC patients with MDD history (BC-MDD) or not (BC-Ctrl). The Uniform Manifold Approximation and Projection (UMAP) of unintegrated aneuploid cells revealed intrinsic differences across individual patients (Supplementary Figure S1C). Downstream functional profiling analysis identified distinct immune response pathways in BC-MDD and BC-Ctrl groups and enrichment of the oxidative phosphorylation (OXPHOS) pathway in BC-Ctrl tumors (Supplementary Figure S1D-E). Cellular Gene Set Variation Analysis (GSVA) [<span>6</span>] confirmed the distinct metabolic phenotypes between BC-MDD and BC-Ctrl groups (Figure 1C). Additionally, utilizing predefined gene module (GM) signatures of BC tumor cells [<span>7</span>], we observed specific restraint of GM4 and GM6 in BC-MDD (Supplementary Figure S1F-G). GM6 encompasses various antigen presentation genes, aligning with the observed downregulation of major histocompatibility complex class I (MHC-I) class genes in BC-MDD tumor cells (Supplementary Figure S1H).</p><p>Upon re-clustering 12,371 normal epithelial cells within primary breast tumor and adjacent normal tissues from the 10 patients, we identified 9 cell clusters, including luminal hormone-responsive (LumHR), luminal secretory (LumSec), and myoepithelial cells [<span>8</span>] (Supplementary Figure S2A-B). Distribution analysis suggested
{"title":"Single-cell transcriptomic atlas reveals immune and metabolism perturbation of depression in the pathogenesis of breast cancer","authors":"Lingling Wu, Junwei Liu, Yimeng Geng, Jianwen Fang, Xingle Gao, Jianbo Lai, Minya Yao, Shaojia Lu, Weiwei Yin, Peifen Fu, Wei Chen, Shaohua Hu","doi":"10.1002/cac2.12603","DOIUrl":"10.1002/cac2.12603","url":null,"abstract":"<p>Epidemiological evidence indicates that major depressive disorder (MDD) may predispose the development and prognosis of breast cancer (BC) in females [<span>1</span>]. However, the mechanisms linking these phenotypes are not fully understood. Chronic stress, a hallmark of depression, has been underscored to affect anti-tumor immunity, tumor metabolic reprogramming, hormone synthesis in BC [<span>2, 3</span>], and increase tumor metastasis [<span>4</span>], but there is a lack of detailed cellular-level characterization of how MDD history affects the tumorigenesis of BC. This study explored the single-cell atlas of multiple tissues from BC patients with and without a history of MDD for characterizing the potential molecular alternations in their tumorigenesis (Figure 1A).</p><p>Paired primary tumor tissues (<i>n</i> = 10), adjacent normal tissues (<i>n</i> = 7), and peripheral blood samples (<i>n</i> = 10) were collected from a cohort of 10 BC patients, 5 of whom had a history of MDD (Supplementary Table S1). All BC patients had estrogen receptor (ER)-positive tumors and were further predicted as Luminal A (<i>n</i> = 9) and B subtypes (<i>n</i> = 1) (Supplementary Table S2). Further details on patient recruitment, sample handling, and single-cell data analysis are provided in Supplementary Methods. In total, we obtained 224,557 single cells and further annotated them into major cell subsets based on lineage markers and copy number variations [<span>5</span>] (Figure 1B, Supplementary Figure S1A-B). Aneuploid cells in primary tumor tissues were obtained (Supplementary Table S3) to characterize their phenotypic differences in BC patients with MDD history (BC-MDD) or not (BC-Ctrl). The Uniform Manifold Approximation and Projection (UMAP) of unintegrated aneuploid cells revealed intrinsic differences across individual patients (Supplementary Figure S1C). Downstream functional profiling analysis identified distinct immune response pathways in BC-MDD and BC-Ctrl groups and enrichment of the oxidative phosphorylation (OXPHOS) pathway in BC-Ctrl tumors (Supplementary Figure S1D-E). Cellular Gene Set Variation Analysis (GSVA) [<span>6</span>] confirmed the distinct metabolic phenotypes between BC-MDD and BC-Ctrl groups (Figure 1C). Additionally, utilizing predefined gene module (GM) signatures of BC tumor cells [<span>7</span>], we observed specific restraint of GM4 and GM6 in BC-MDD (Supplementary Figure S1F-G). GM6 encompasses various antigen presentation genes, aligning with the observed downregulation of major histocompatibility complex class I (MHC-I) class genes in BC-MDD tumor cells (Supplementary Figure S1H).</p><p>Upon re-clustering 12,371 normal epithelial cells within primary breast tumor and adjacent normal tissues from the 10 patients, we identified 9 cell clusters, including luminal hormone-responsive (LumHR), luminal secretory (LumSec), and myoepithelial cells [<span>8</span>] (Supplementary Figure S2A-B). Distribution analysis suggested","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":"44 11","pages":"1311-1315"},"PeriodicalIF":20.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12603","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dysfunction of CD8+ T cells in the tumor microenvironment (TME) contributes to tumor immune escape and immunotherapy tolerance. The effects of hormones such as leptin, steroid hormones, and glucocorticoids on T cell function have been reported previously. However, the mechanism underlying thyroid-stimulating hormone (TSH)/thyroid-stimulating hormone receptor (TSHR) signaling in CD8+ T cell exhaustion and tumor immune evasion remain poorly understood. This study was aimed at investigating the effects of TSH/TSHR signaling on the function of CD8+ T cells and immune evasion in colorectal cancer (CRC).
Methods
TSHR expression levels in CD8+ T cells were assessed with immunofluorescence and flow cytometry. Functional investigations involved manipulation of TSHR expression in cellular and mouse models to study its role in CD8+ T cells. Mechanistic insights were mainly gained through RNA-sequencing, Western blotting, chromatin immunoprecipitation and luciferase activity assay. Immunofluorescence, flow cytometry and Western blotting were used to investigate the source of TSH and TSHR in CRC tissues.
Results
TSHR was highly expressed in cancer cells and CD8+ T cells in CRC tissues. TSH/TSHR signaling was identified as the intrinsic pathway promoting CD8+ T cell exhaustion. Conditional deletion of TSHR in CD8+ tumor-infiltrating lymphocytes (TILs) improved effector differentiation and suppressed the expression of immune checkpoint receptors such as programmed cell death 1 (PD-1) and hepatitis A virus cellular receptor 2 (HAVCR2 or TIM3) through the protein kinase A (PKA)/cAMP-response element binding protein (CREB) signaling pathway. CRC cells secreted TSHR via exosomes to increase the TSHR level in CD8+ T cells, resulting in immunosuppression in the TME. Myeloid-derived suppressor cells (MDSCs) was the main source of TSH within the TME. Low expression of TSHR in CRC was a predictor of immunotherapy response.
Conclusions
The present findings highlighted the role of endogenous TSH/TSHR signaling in CD8+ T cell exhaustion and immune evasion in CRC. TSHR may be suitable as a predictive and therapeutic biomarker in CRC immunotherapy.
肿瘤微环境（TME）中的 CD8+ T 细胞功能失调会导致肿瘤免疫逃逸和免疫治疗耐受。瘦素、类固醇激素和糖皮质激素等激素对T细胞功能的影响已有报道。然而，促甲状腺激素（TSH）/促甲状腺激素受体（TSHR）信号在CD8+ T细胞衰竭和肿瘤免疫逃避中的作用机制仍不甚明了。本研究旨在探讨TSH/TSHR信号对CD8+ T细胞功能和结直肠癌（CRC）免疫逃避的影响。
{"title":"Local TSH/TSHR signaling promotes CD8+ T cell exhaustion and immune evasion in colorectal carcinoma","authors":"Sisi Zeng, Huiling Hu, Zhiyang Li, Qi Hu, Rong Shen, Mingzhou Li, Yunshi Liang, Zuokang Mao, Yandong Zhang, Wanqi Zhan, Qin Zhu, Feifei Wang, Jianbiao Xiao, Bohan Xu, Guanglong Liu, Yanan Wang, Bingsong Li, Shaowan Xu, Zhaowen Zhang, Ceng Zhang, Zhizhang Wang, Li Liang","doi":"10.1002/cac2.12605","DOIUrl":"10.1002/cac2.12605","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Dysfunction of CD8<sup>+</sup> T cells in the tumor microenvironment (TME) contributes to tumor immune escape and immunotherapy tolerance. The effects of hormones such as leptin, steroid hormones, and glucocorticoids on T cell function have been reported previously. However, the mechanism underlying thyroid-stimulating hormone (TSH)/thyroid-stimulating hormone receptor (TSHR) signaling in CD8<sup>+</sup> T cell exhaustion and tumor immune evasion remain poorly understood. This study was aimed at investigating the effects of TSH/TSHR signaling on the function of CD8<sup>+</sup> T cells and immune evasion in colorectal cancer (CRC).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>TSHR expression levels in CD8<sup>+</sup> T cells were assessed with immunofluorescence and flow cytometry. Functional investigations involved manipulation of TSHR expression in cellular and mouse models to study its role in CD8<sup>+</sup> T cells. Mechanistic insights were mainly gained through RNA-sequencing, Western blotting, chromatin immunoprecipitation and luciferase activity assay. Immunofluorescence, flow cytometry and Western blotting were used to investigate the source of TSH and TSHR in CRC tissues.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>TSHR was highly expressed in cancer cells and CD8<sup>+</sup> T cells in CRC tissues. TSH/TSHR signaling was identified as the intrinsic pathway promoting CD8<sup>+</sup> T cell exhaustion. Conditional deletion of TSHR in CD8<sup>+</sup> tumor-infiltrating lymphocytes (TILs) improved effector differentiation and suppressed the expression of immune checkpoint receptors such as programmed cell death 1 (PD-1) and hepatitis A virus cellular receptor 2 (HAVCR2 or TIM3) through the protein kinase A (PKA)/cAMP-response element binding protein (CREB) signaling pathway. CRC cells secreted TSHR via exosomes to increase the TSHR level in CD8<sup>+</sup> T cells, resulting in immunosuppression in the TME. Myeloid-derived suppressor cells (MDSCs) was the main source of TSH within the TME. Low expression of TSHR in CRC was a predictor of immunotherapy response.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The present findings highlighted the role of endogenous TSH/TSHR signaling in CD8<sup>+</sup> T cell exhaustion and immune evasion in CRC. TSHR may be suitable as a predictive and therapeutic biomarker in CRC immunotherapy.</p>\u0000 </section>\u0000 </div>","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":"44 11","pages":"1287-1310"},"PeriodicalIF":20.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12605","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ai Zhuang, Xiang Gu, Tongxin Ge, Shaoyun Wang, Shengfang Ge, Peiwei Chai, Renbing Jia, Xianqun Fan
The cover image is based on the Original Article Targeting histone deacetylase suppresses tumor growth through eliciting METTL14-modified m6A RNA methylation in ocular melanoma by Ai Zhuang et al., https://doi.org/10.1002/cac2.12471.
Yongzhan Nie, Xianchun Gao, Xiqiang Cai, Zhen Wu, Qiaoyi Liang, Guobing Xu, Na Liu, Peng Gao, Jingyu Deng, Hongzhi Xu, Zhanlong Shen, Changqi Cao, Fenrong Chen, Nannan Zhang, Yongxi Song, Mingjun Sun, Chengyin Liu, Guangpeng Zhou, Weili Han, Jianhua Dou, Huahong Xie, Liping Yao, Zhiguo Liu, Gang Ji, Xin Wang, Qingchuan Zhao, Lei Shang, Daiming Fan, Xiaoliang Han, Jianlin Ren, Han Liang, Zhenning Wang, Jinhai Wang, Qi Wu, Jun Yu, Kaichun Wu, the MAGIS Study Group
The cover image is based on the Correspondence Combining methylated SEPTIN9 and RNF180 plasma markers for diagnosis and early detection of gastric cancer by Yongzhan Nie et al., https://doi.org/10.1002/cac2.12478.
Donghai Xiong, Zheng Yin, Mofei Huang, Yian Wang, Micael Hardy, Balaraman Kalyanaraman, Stephen T Wong, Ming You
<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> < 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> < 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<su
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 < 0.001），但增加了抗肿瘤 CD8T_EffectorMemory 细胞的比例（37.3% vs. 11.9%，P < 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）。
{"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, Zheng Yin, Mofei Huang, Yian Wang, Micael Hardy, Balaraman Kalyanaraman, Stephen T Wong, Ming You","doi":"10.1002/cac2.12500","DOIUrl":"10.1002/cac2.12500","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> < 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> < 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<su","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":"44 3","pages":"448-452"},"PeriodicalIF":16.2,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12500","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71478363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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