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• Research Paper Volume 13, Issue 10 pp 13443-13459

  Immunological features beyond CD4/CD8 ratio values in older individuals

  Relevance score: 6.1983614

  Vanesa Garrido-Rodríguez, Inés Herrero-Fernández, María José Castro, Ana Castillo, Isaac Rosado-Sánchez, María Isabel Galvá, Raquel Ramos, Israel Olivas-Martínez, Ángel Bulnes-Ramos, Julio Cañizares, Manuel Leal, Yolanda María Pacheco

  Keywords: CD4/CD8 T-cell ratio, thymic output, inflammation, Treg, TREC

  Published in Aging on May 26, 2021

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  The CD4/CD8 T-cell ratio is emerging as a relevant marker of evolution for many pathologies and therapies. We aimed to explore immunological features beyond CD4/CD8 ratio values in older subjects (>65 years old) who were classified as having lower (<1.4), intermediate (1.4-2), or higher (>2) ratio values. The lower group showed a lower thymic output (sj/β-TREC ratio) and frequency of naïve T-cells, concomitant with increased mature T-cells. In these subjects, the CD4 T-cell subset was enriched in CD95+ but depleted of CD98+ cells. The regulatory T-cell (Treg) compartment was enriched in CTLA-4+ cells. The CD8 T-cell pool exhibited increased frequencies of CD95+ cells but decreased frequencies of integrin-β7+ cells. Interestingly, in the intermediate group, the CD4 pool showed greater differences than the CD8 pool, mostly for cellular senescence. Regarding inflammation, only hsCRP was elevated in the lower group; however, negative correlations between the CD4/CD8 ratio and β2-microglobulin and sCD163 were detected. These subjects displayed trends of more comorbidities and less independence in daily activities. Altogether, our data reveal different thymic output and immune profiles for T-cells across CD4/CD8 ratio values that can define immune capabilities, affecting health status in older individuals. Thus, the CD4/CD8 ratio may be used as an integrative marker of biological age.

• Research Paper Volume 12, Issue 7 pp 6225-6239

  Rotating magnetic field ameliorates experimental autoimmune encephalomyelitis by promoting T cell peripheral accumulation and regulating the balance of Treg and Th1/Th17

  Relevance score: 6.824015

  Tianying Zhan, Xiaomei Wang, Zijun Ouyang, Youli Yao, Jiangyao Xu, Shikang Liu, Kan Liu, Qiyu Deng, Yushu Wang, Yingying Zhao

  Keywords: rotating magnetic field, EAE, inflammation, chemokines, Treg cell

  Published in Aging on April 7, 2020

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  Multiple sclerosis (MS) is an autoimmune disease characterized by T cell infiltration and demyelination of the central nervous system (CNS). Experimental autoimmune encephalomyelitis (EAE) is a classical preclinical animal model of MS. In this study, we found that rotating magnetic field (RMF) treatment exerts potential preventive effects on the discovery of EAE, including reducing the severity of the disease and delaying the onset of the disease. The results indicated that RMF (0.2 T, 4 Hz) treatment increases the accumulation of CD4⁺ cells in the spleen and lymph nodes by downregulating the expression of CCL-2, CCL-3 and CCL-5, but has no significant effect on myelin oligodendrocyte glycoprotein (MOG) specific T cell responses. Simultaneously, RMF treatment adjusted the imbalance between regulatory T (Treg) cell and T helper 1 (Th1) cells or T helper 17 (Th17) cells by increasing the proportion of Treg cells and inhibiting the ratio of Th1 and Th17 cell subsets. These findings suggest that exposure to RMF may improve EAE disease by promoting CD4+ cell accumulation into peripheral lymphoid tissue, improving the imbalance between Treg and Th1/Th17 cells. Therefore, as a mild physical therapy approach, RMF, is likely to be a potential way to alter the development of EAE.

  

  Protective impact of RMF-exposure on the advancement of EAE in mice. EAE mice and C57BL/6 mice were treated daily with RMF or non-RMF starting from day 0 following vaccination. Animals were observed for the clinical indications as well as disease advancement of EAE, comprising (A) body relative weight, (B) clinical scores and (C) the percentage of EAE incidence. (D) Spinal cord sections of the treated mice on day 20 following vaccination by H&E, Scale bar, 200 μm and 50 μm. The graph shows the number of inflammatory cells in per low magnification field (calculated with animal number: control, n = 3; RMF, n = 3; EAE, n = 6; EAE+RMF, n = 6). (E) LFB of Spinal cord sections in both groups on day 20. Scale bar, 200 μm and 50 μm. The graph shows the percentages of demyelinated area in sections (control, n = 3; RMF, n = 3; EAE, n = 6; EAE+RMF, n = 6). On day 20, (F) the behavioral trajectory of mice analyzed by rhythm cage: (A) Control, (B) RMF, (C) EAE, (D) EAE+RMF. Subsequently, we measured moving distance and average speed of mice within 30 min. Data are shown as the mean ± SEM of three independent experiments. *P <0.05, ***P <0.001.

  
  
  

  

  RMF exposure primarily affects genetic changes in the immune system. Spinal cord was isolated from mice for whole transcriptome sequencing analysis at day 20 after immunization. (A) Classification map of differential gene KEGG pathway. (B) Differential gene KEGG pathway enrichment map.

  
  
  

  

  Minor impacts of RMF on generation of Th1/Th2/Th17 cytokines as well as T cell propagation. Cytokines in serum from the treated EAE mice were detected at (A) day 10 and (B) day 20 after immunization. (C) Spleen cells and (D) lymph node cells derived from the treated EAE mice at day 10 following vaccination were re-activated with 10 μg/mL of MOG35–55 peptide. (C, D) Propagation was detected after 72 h of incubation. (E) IFN-γ, IL-2, IL-4 as well as IL-17A were detected following 48 h of incubation. Data are shown as the mean ± SEM of three independent experiments. *P <0.05.

  
  
  

  

  Impact of RMF on lymphocyte homing to peripheral lymphoid tissues. (A) Demonstrative pictures of the spleen and the mass of the spleen was weighed and the mass of body weight (BW) was calculated. (B) Proportions of CD4⁺ as well as CD8⁺ T lymphocytes in the spleen and lymph nodes were determined by flow cytometry. The overall cell numbers as well as CD4⁺ and CD8⁺ cell numbers in the (C) spleens and (D) lymph nodes. (E) Spinal cords from the treated mice at day 20 following vaccination were stained with an antibody specific for CD4. Scale bar, 50 μm. Data are shown as the mean ± SEM of three independent experiments. *P <0.05, **P <0.01, ***P <0.001.

  
  
  

  

  Effect of RMF on chemokines. (A) Heatmap of CCL-2, CCL-3 and CCL-5 expression difference in the spinal cord. (B) The manifestation of CCL-2, CCL-3 and CCL-5 mRNA in spinal cord was measured by qPCR. (C) Heatmap of CCL-2, CCL-3 and CCL-5 expression difference in the spinal cord. (D) The manifestation of CXCL-1, CXCL-2, CXCL-9 and CXCL-10 mRNA in spinal cord was measured by qPCR. Data are shown as the mean ± SEM. of three independent experiments. *P <0.05, **P <0.01.

  
  
  

  

  Impact of RMF on Treg cells. (A) Proportions of Treg cells in the spleen as well as lymph nodes were determined. (B) Heat map of TGF-β, Foxp3 and IL-10 expression difference in the spinal cord. (C) The manifestation of TGF-β, Foxp3 and IL-10 mRNA in spinal cord was measured by qPCR. Data are shown as the mean ± SEM of three independent experiments. *P <0.05, **P <0.01.

  
  
  

  

  Impact of RMF on peripheral CD4⁺ T cell subsets. (A) The percentages of CD4⁺IFN-γ⁺, CD4⁺IL-2⁺ and CD4⁺IL-17⁺ cells in the lymph node were detected. (B) Heatmap of T-bet and Rorc expression difference in the spinal cord. (C) The manifestation of T-bet and Rorc mRNA in spinal cord was measured by qPCR. Data are shown as the mean ± SEM of three independent experiments. *P <0.05, **P <0.01.

  
  
  

  

  Effect of RMF on spinal cord. Spinal cords from the treated mice at day 20 after immunization were stained with an antibody specific for (A) IFN-γ, (B) IL-2, and (C) IL-17. Scale bar, 50 μm. (D) The diagram presents the proportion of positive cells in EAE lesions or corresponding areas (control, n = 3; RMF, n = 3; EAE, n = 6; EAE+RMF, n = 6). (E) Heatmap of IFN-γ and IL-17 expression difference in the spinal cord. (F) The expression level of CD4, IFN-γ and IL-17 mRNA in spinal cord was measured by qPCR. Data are shown as the mean ± SEM of three independent experiments. *P <0.05, **P <0.01, ***P <0.001.

  
  
  

  

  RMF exposure device. (A) Treatment tables were positioned at the central top of the device. Rotating frequency was 4.0 Hz and intensity was 0.2 T. (B) The magnetic field of different amplitude consisting of two overlapping components was formed above the device: (C) translational (with fluctuating inversion time) and (D) rotational (with fluctuating rotational frequencies).

  
  
  

• Research Paper Volume 11, Issue 21 pp 9478-9491

  Identifying hub genes of clear cell renal cell carcinoma associated with the proportion of regulatory T cells by weighted gene co-expression network analysis

  Relevance score: 4.778992

  Ye-Hui Chen, Shao-Hao Chen, Jian Hou, Zhi-Bin Ke, Yu-Peng Wu, Ting-Ting Lin, Yong Wei, Xue-Yi Xue, Qing-Shui Zheng, Jin-Bei Huang, Ning Xu

  Keywords: ccRCC, weighted gene co-expression network analysis, Treg cells, hub genes, anti-tumor immune

  Published in Aging on October 31, 2019

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  Background: Numerous patients with clear cell renal cell carcinoma (ccRCC) experience drug resistance after immunotherapy. Regulatory T (Treg) cells may work as a suppressor for anti-tumor immune response.

  Purpose: We performed bioinformatics analysis to better understand the role of Treg cells in ccRCC.

  Results: Module 10 revealed the most relevance with Treg cells. Functional annotation showed that biological processes and pathways were mainly related to activation of the immune system and the processes of immunoreaction. Four hub genes were selected: LCK, MAP4K1, SLAMF6, and RHOH. Further validation showed that the four hub genes well-distinguished tumor and normal tissues and were good prognostic biomarkers for ccRCC.

  Conclusion: The identified hub genes facilitate our knowledge of the underlying molecular mechanism of how Treg cells affect ccRCC in anti-tumor immune therapy.

  Methods: The CIBERSORT algorithm was performed to evaluate tumor-infiltrating immune cells based on the Cancer Genome Atlas cohort. Weighted gene co-expression network analysis was conducted to explore the modules related to Treg cells. Gene Ontology analysis and pathway enrichment analysis were performed for functional annotation and a protein–protein interaction network was built. Samples from the International Cancer Genomics Consortium database was used as a validation set.

  

  CIBERSORT analysis and clinical significance of Treg cells in ccRCC. (A) Relative percentage of each type of immune cell in 539 ccRCC samples from TCGA cohort. (B) Proportion of Treg cells in different pathological grades. (C) Proportion of Treg cells in different AJCC stages. (D) Overall survival between patients with high and low proportions of infiltrating Treg cells.

  
  
  

  

  Determination of soft-thresholding parameter in WGCNA. (A) Analysis of the scale-free fit index for various soft-thresholding parameters. (B) Analysis of the mean connectivity for various soft-thresholding parameters. (C) Histogram of connectivity distribution when β=9. (D) Check of scale-free topology when β=9.

  
  
  

  

  Sample dendrogram and clustering dendrogram of WGCNA. (A) Sample dendrogram and corresponding clinical characteristics. (B) Cluster dendrogram of 432 samples with eligible data.

  
  
  

  

  Identification of modules associated with clinical characteristics. (A) Distribution of average gene significance and errors in the modules associated with the proportion of Treg cells in ccRCC. (B) Scatter plot of module eigengenes in module 10. (C) Heatmap of the correlation between module eigengenes and different clinical characteristics of ccRCC.

  
  
  

  

  Functional enrichment analysis and construction of PPI network. (A) GO and pathway enrichment analysis of genes in the module 10. (B) P-value of each gene in the network. (C) PPI network constructed using STRING.

  
  
  

  

  Validation of the four hub genes based on the ICGC cohort. (A–D) Expression levels of the four hub genes between ccRCC samples and normal tissues. (E–H) Overall survival between patients with high and low expression of the four hub genes. (I–L) ROC curves of the four genes to evaluate their capability in distinguishing tumor tissue and normal kidney tissue.

  
  
  

  

  Flowchart detailing the study design and samples at each stage of the analysis.

  
  
  

• Editorial Volume 11, Issue 17 pp 6614-6615

  TLR8 reprograms human Treg metabolism and function

  Relevance score: 6.4395914

  Xia Liu, Lingyun Li, Guangyong Peng

  Keywords: Treg cells, metabolism, glycolysis, TLR8, cancer immunotherapy

  Published in Aging on September 4, 2019

  

  TLR8 signaling enhances anti-tumor immunity and immunotherapy. Treg cells and tumor cells have accelerated glucose metabolism and induce senescence and suppression in effector T cells during their cross-talks. TLR8 signaling inhibits glucose metabolism in Treg cells and decreases tumor-produced cAMP, resulting in reversal of responder T cell senescence and enhanced anti-tumor immune responses.

  
  
  

• Research Paper pp undefined-undefined

  PBRM1 mutation and WDR72 expression as potential combinatorial biomarker for predicting the response to Nivolumab in patients with ccRCC: a tumor marker prognostic study

  Relevance score: 5.910245

  Qinzheng Chang, Jiajia Sun, Shuo Zhao, Luchao Li, Nianzhao Zhang, Lei Yan, Yidong Fan, Jikai Liu

  Keywords: clear cell renal cell carcinoma, immune checkpoint therapy, PBRM1 mutation, nivolumab, treg cell

  Published in Aging on Invalid Date

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  Purpose: Immune checkpoint therapy (ICT) provides a new idea for the treatment of advanced clear cell renal cell carcinoma(ccRCC), which can bring significant benefits to patients. However, the clinical application of ICT is limited because of the lack of predictive biomarkers to select potential responders. This study aims to propose a new biomarker to predict the response to Nivolumab in patients with ccRCC.

  Materials and methods: The genes that significantly improve the prognosis of ccRCC were retrieved from The Cancer Genome Atlas (TCGA) database. The genomic and clinical data was from patients that had been registered in prospective clinical trials (CheckMate009, CheckMate010 and CheckMate025). TCGA, Gene Expression Omnibus (GEO), and The Human Protein Atlas database were used to analyze the gene and protein expression of WD repeat-containing protein 72 (WDR72) in ccRCC. Gene Ontology (GO)&The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were performed to dig relevant mechanisms of WDR72. Single sample gene set enrichment analysis (ssGSEA) was conducted to evaluate the role of WDR72 in immune infiltration. Cell proliferation assay, FAO and ATP quantification were used to explore and verify the molecular mechanisms. The expression of WDR72, FOXP3, CD8, and CPT1A was examined by IHC in 20 advanved ccRCC tissue samples at the urology department of our hospital. The MethSurv was used to identify PBRM1 and WDR72 gene methylation and its effect on prognosis of ccRCC.

  Results: WDR72 is the most significant gene for improving overall survival (OS) in ccRCC. In all three checkmates, OS and progression free survival (PFS) were found to be significantly higher in WDR72 high expression group than that in WDR72 low expression group (P=0.040 and P=0.012, respectively), and similar conclusions could be drawn from the PBRM1-mutation (MUT) compared with the PBRM1-wildtype (WT) (P=0.007 and P=0.006, respectively). What’s more, high expression of WDR72 plus PBRM1-MUT as a combinatorial biomarker showed improved OS (HR=0.388, P=0.0026) and PFS (HR=0.39, P=0.0066) compared to low expression of WDR72 plus PBRM1-WT. Functional enrichment analysis showed that WDR72 was closely positively related to fatty acid degradation and fatty acid beta oxidation pathway in ccRCC. In vitro experiments showed that high expression of WDR72 can promote fatty acids oxidation and inhibit the proliferation of ccRCC cells. Immune analysis revealed that WDR72 high expression was associated with decreased infiltration of Treg cells and low ssGSEA score of check-point. IHC results showed that WDR72 was negatively correlated with FOXP3 expression (r=-0.506, P=0.023) and positively correlated with CPT1A expression (r=0.529, P=0.017).

  Conclusions: The present study indicated that high expression of WDR72 may indicate a good prognosis of patients treated with Nivolumab and WDR72 expression combined with PBRM1 mutation could be more persuasive to predict the response for ICT in ccRCC patients.

• Research Paper pp undefined-undefined

  Long noncoding RNA MEG8 induces an imbalance of Th17/Treg cells through the miR-107/STAT3 axis in Henoch-Schonlein purpura rats

  Relevance score: 4.0356455

  Mingyu Jiang, Jicheng Dai, Chunming Jiang, Yanbo Pan, Mingyong Ren, Mengnan Xing

  Keywords: Henoch-Schonlein purpura, maternally expressed gene 8, miR-107, signal transducer and activator of transcription-3, Th17/Treg imbalance

  Published in Aging on Invalid Date

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  T-helper (Th) 17/ T-regulatory (Treg) cell dysregulation underlies the pathogenesis of Henoch-Schonlein purpura (HSP). This research focused on the implication/s of the long noncoding RNA (lncRNAs) maternally expressed gene 8 (MEG8) in Th17 and Treg cell differentiation in HSP rats. MEG8, miR-107, signal transducer and activator of transcription-3 (STAT3), receptor-related orphan receptor γt (RORγt), and the transcription factor forkhead box P3 (Foxp3) expression levels were detected using real-time quantitative polymerase chain reaction and Western blot analyses. Flow cytometry was employed for measuring Th17 and Treg cells within the CD4+ T cell population. The interaction between miR-107 and MEG8 or STAT3 was examined. A low proportion of MEG8 and Treg cells together with Th17 cells were denoted within HSP rats. Moreover, MEG8 overexpression altered the Th17/Treg imbalance in peripheral blood CD4+ T-cell population, and the miR-107 mimic and STAT3 silencing reversed this effect. Thus, MEG8 served as a sponge for miR-107, lowering binding activity to STAT3 and thus overexpressing the molecule. Taken together, MEG8 induces an imbalance of Th17/Treg cells through the miR-107/STAT3 axis in HSP rats.

• Research Paper pp undefined-undefined

  FABP6 serves as a new therapeutic target in esophageal tumor

  Relevance score: 6.4395914

  Dengfeng Zhang, Fangchao Zhao, Haitao Liu, Pengfei Guo, Zhirong Li, Shujun Li

  Keywords: esophageal tumor, FABP6, Treg, prognostic biomarker, migration

  Published in Aging on Invalid Date

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  Background: Esophageal cancer is one of the most common malignant tumors with high incidence and mortality rates. Despite the continuous development of treatment options, the prognosis for esophageal cancer patients remains poor. Therefore, there is an urgent need for new diagnostic and therapeutic targets in clinical practice to improve the survival of patients with esophageal cancer.

  Methods: In this study, we conducted a comprehensive scRNA-seq analysis of the tumor microenvironment in primary esophageal tumors to elucidate cell composition and heterogeneity. Using Seurat, we identified eight clusters, encompassing non-immune cells (fibroblasts, myofibroblasts, endothelial cells, and epithelial cells) and immunocytes (myeloid-derived cells, T cells, B cells, and plasma cells). Compared to normal tissues, tumors exhibited an increased proportion of epithelial cells and alterations in immune cell infiltration. Analysis of epithelial cells revealed a cluster (cluster 0) with a high differentiation score and early distribution, suggesting its importance as a precursor cell.

  Results: Cluster 0 was characterized by high expression of FABP6, indicating a potential role in fatty acid metabolism and tumor growth. T cell analysis revealed shifts in the balance between Treg and CD8+ effector T cells in tumor tissues. Cellular communication analysis identified increased interactions between FABP6+ tumor cells and T cells, with the involvement of the MIF-related pathway and the CD74-CD44 interaction. This study provides insights into the cellular landscape and immune interactions within esophageal tumors, contributing to a better understanding of tumor heterogeneity and potential therapeutic targets.

• Research Paper pp undefined-undefined

  CircRNA has_circ_0069313 induced OSCC immunity escape by miR-325-3p-Foxp3 axes in both OSCC cells and Treg cells

  Relevance score: 7.4870152

  Yiyang Chen, Zeyu Li, Jianfeng Liang, Jiayu Liu, Jiansuo Hao, Quan Wan, Jiameng Liu, Chongdai Luo, Zhiyuan Lu

  Keywords: circRNA, OSCC, cancer immunity, PDL1, Treg

  Published in Aging on Invalid Date

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  Introduction: CircRNAs are engaged in the tumorigenesis and progression of oral squamous cancer cells (OSCC). However, the function and underlying mechanism of circRNAs on tumor-associated immunity escape are largely unknown.

  Materials and methods: We analyzed the expression pattern of has_circ_0069313 in our in-house database and its correlation with OSCC prognosis. Immunohistochemistry was applied to detected PDL1 expression. RNA fluorescence in situ hybridization was applied to detect subcellular location of circRNA. A luciferase activity assay was used to detect the interaction of has_circ_0069313 and miR-325-3p and its downstream target, Foxp3. Exosomes were collected to detect the exosomal circRNAs and co-culture assays were performed to detect the function of exosomal circRNAs on Tregs.

  Results: has_circ_0069313 was upregulated in OSCC tissues and predicts poor prognosis. has_circ_0069313 promotes immunity escape through inhibiting miR-325-3p-induced Foxp3 degradation. has_circ_0069313 is an exosomal circRNA and the transfer of has_circ_0069313 to Treg cells promotes the Treg function through maintaining Foxp3 levels.

  Conclusion: Our results indicate that has_circ_0069313 induces OSCC immunity escape via the miR-325-3p-Foxp3 axis in both OSCC cells and Treg cells.

• Research Paper pp undefined-undefined

  RIOK3 promotes mTORC1 activation by facilitating SLC7A2-mediated arginine uptake in pancreatic ductal adenocarcinoma

  Relevance score: 6.824015

  Henan Qin, Rui Sun, Xin Guo, Lei Fang, Mengyuan Xu, Yibin Teng, Ning Zhen, Aman Wang, Jiwei Liu

  Keywords: RIOK3, SLC7A2, arginine metabolism, pancreatic ductal adenocarcinoma, Treg

  Published in Aging on Invalid Date

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  Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a poor prognosis. Reprogramming of amino acid metabolism is one of the characteristics of PDAC, in which arginine metabolism is significantly altered in PDAC cells and is involved in important signaling pathways. Current studies have identified arginine deprivation as a potential strategy for PDAC treatment. In this study, we performed Liquid Chromatograph Mass Spectrometer (LC-MS)-based non-targeted metabolomic analysis on PDAC cell lines with stable Rio Kinase 3 (RIOK3) knockdown and PDAC tissues with different RIOK3 expressions and found that RIOK3 expression was significantly correlated with arginine metabolism in PDAC. Subsequent RNA sequencing (RNA-Seq) and Western blot analysis showed that RIOK3 knockdown significantly inhibited the expression of arginine transporter solute carrier family 7 member 2 (SLC7A2). Further studies revealed that RIOK3 promoted arginine uptake, mechanistic target of rapamycin complex 1 (mTORC1) activation, cell invasion, and metastasis in PDAC cells via SLC7A2. Finally, we found that patients with high expression of both RIOK3 and infiltrating Treg cells had a worse prognosis. Overall, our study found that RIOK3 in PDAC cells promotes arginine uptake and mTORC1 activation through upregulation of SLC7A2 expression, and also provides a new therapeutic target for therapeutic strategies targeting arginine metabolism.