immune microenvironment
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2022 ◽  
Vol 12 (4) ◽  
pp. 841-847
Meijiao Du ◽  
Zhengmei Wang ◽  
Geng Su ◽  
Yunxia Zhou ◽  
Chuan Luo

This study aims to analyze the role of mTOR inhibitor on the expression of miR-211 in rat brain tissue and the biological effect of miR-211 in attenuating seizure. Rats were randomly divided into four groups, and the number of seizures and the duration of single seizure were observed within 24 hours after intervention. The level of miR-211 in brain tissue was detected by RT qPCR, the apoptosis of nerve cells was assessed by TUNEL staining, the level of immune cells was detected by flow cytometry, and the level of serum inflammatory factors was determined by ELISA. The number of seizures and the duration of single seizure in the three groups treated by rapamycin within 24 hours were lower than those in the control group, and the symptom relief in group C was the best. After treatment, the expression level of miR-211 in the brain tissue of epileptic rats increased. TUNEL staining showed that neuronal apoptosis was obvious in epileptic rats. The anti apoptotic ability of group C was the most significant, followed by group D and group B. Compared with group A, the levels of CD3+ cells, CD8+ cells and CD4+/CD25+ cells in brain tissue of group C were decreased, while the levels of IL-2 and IFN-γ were lower in group C than those in control. In group C (n = 5), the levels of CD3+ cells, CD8+ cells and CD4+/CD25+ cells were elevated, and the levels of immune related cytokines IL-2 and IFN-γ were higher than those of rats without miR-211 inhibition. mTOR inhibitors can improve the local immune microenvironment, reduce the release of inflammatory factors, and finally decrease the frequency and duration of seizures by up regulating the level of miR-211 in rat brain tissue.

2022 ◽  
Vol 527 ◽  
pp. 95-106
Xuehui Jiang ◽  
Chaohui Wang ◽  
Ziliang Ke ◽  
Lina Duo ◽  
Ting Wu ◽  

2022 ◽  
Vol 12 ◽  
Hang Ji ◽  
Hongtao Zhao ◽  
Jiaqi Jin ◽  
Zhihui Liu ◽  
Xin Gao ◽  

Effective treatment of glioblastoma (GBM) remains an open challenge. Given the critical role of the immune microenvironment in the progression of cancers, we aimed to develop an immune-related gene (IRG) signature for predicting prognosis and improving the current treatment paradigm of GBM. Multi-omics data were collected, and various bioinformatics methods, as well as machine learning algorithms, were employed to construct and validate the IRG-based signature and to explore the characteristics of the immune microenvironment of GBM. A five-gene signature (ARPC1B, FCGR2B, NCF2, PLAUR, and S100A11) was identified based on the expression of IRGs, and an effective prognostic risk model was developed. The IRG-based risk model had superior time-dependent prognostic performance compared to well-studied molecular pathology markers. Besides, we found prominent inflamed features in the microenvironment of the high-risk group, including neutrophil infiltration, immune checkpoint expression, and activation of the adaptive immune response, which may be associated with increased hypoxia, epidermal growth factor receptor (EGFR) wild type, and necrosis. Notably, the IRG-based risk model had the potential to predict the effectiveness of radiotherapy. Together, our study offers insights into the immune microenvironment of GBM and provides useful information for clinical management of this desperate disease.

2022 ◽  
Vol 23 (1) ◽  
Yingqi Qiu ◽  
Hao Wang ◽  
Peiyun Liao ◽  
Binyan Xu ◽  
Rong Hu ◽  

Abstract Background Belonging to the protein arginine methyltransferase (PRMT) family, the enzyme encoded by coactivator associated arginine methyltransferase 1 (CARM1) catalyzes the methylation of protein arginine residues, especially acts on histones and other chromatin related proteins, which is essential in regulating gene expression. Beyond its well-established involvement in the regulation of transcription, recent studies have revealed a novel role of CARM1 in tumorigenesis and development, but there is still a lack of systematic understanding of CARM1 in human cancers. An integrated analysis of CARM1 in pan-cancer may contribute to further explore its prognostic value and potential immunological function in tumor therapy. Results Based on systematic analysis of data in multiple databases, we firstly verified that CARM1 is highly expressed in most tumors compared with corresponding normal tissues, and is bound up with poor prognosis in some tumors. Subsequently, relevance between CARM1 expression level and tumor immune microenvironment is analyzed from the perspectives of tumor mutation burden, microsatellite instability, mismatch repair genes, methyltransferases genes, immune checkpoint genes and immune cells infiltration, indicating a potential relationship between CARM1 expression and tumor microenvironment. A gene enrichment analysis followed shortly, which implied that the role of CARM1 in tumor pathogenesis may be related to transcriptional imbalance and viral carcinogenesis. Conclusions Our first comprehensive bioinformatics analysis provides a broad molecular perspective on the role of CARM1 in various tumors, highlights its value in clinical prognosis and potential association with tumor immune microenvironment, which may furnish an immune based antitumor strategy to provide a reference for more accurate and personalized immunotherapy in the future.

2022 ◽  
Vol 2022 ◽  
pp. 1-17
Yongjie Zhou ◽  
Liangwen Wang ◽  
Wen Zhang ◽  
Jingqin Ma ◽  
Zihan Zhang ◽  

Purpose. The long noncoding RNAs (lncRNAs) play the important role in tumor occurrence and progression, and the epithelial to mesenchymal transition (EMT) is the critical process for tumor migration. However, the role of EMT-related lncRNA in hepatocellular carcinoma (HCC) has not been elucidated. Methods. In this study, we selected the EMT-related lncRNAs in HCC by using data from The Cancer Genome Atlas database (TCGA). Two prognostic models of the overall survival (OS) and relapse-free survival (RFS) were constructed and validated through Cox regression model, Kaplan-Meier analysis, and the receiver-operating characteristic (ROC) curves. The unsupervised clustering analysis was utilized to investigate the association between EMT-lncRNAs with tumor immune microenvironment. ESTIMATE algorithm and gene set enrichment analysis (GSEA) were used to estimate tumor microenvironment and associated KEGG pathways. Results. Two EMT-related lncRNA prognostic models of OS and RFS were constructed. Kaplan-Meier curves showed the dismal prognosis of OS and RFS in the group with high-risk score. The ROC curves and AUC values in two prognostic models indicated the discriminative value in the training set and validation set. Patients with HCC were clustered into two subgroups according the unsupervised clustering analysis. Lnc-CCNY-1 was selected as the key lncRNA. GSVA analysis showed that lnc-CCNY-1 was negatively associated with peroxisome proliferator-activated receptor (PPAR) signaling pathway and positively correlated with CELL cycle pathway. Conclusion. Two EMT-related lncRNA prognostic models of OS and RFS were constructed to discriminate patients and predict prognosis of HCC. EMT-related lncRNAs may play a role on prognosis of HCC by influencing the immune microenvironment. Lnc-CCNY-1 was selected as the key EMT-related lncRNA for further exploration.

2022 ◽  
Vol 6 (1) ◽  
Shuhang Wang ◽  
Pei Yuan ◽  
Beibei Mao ◽  
Ning Li ◽  
Jianming Ying ◽  

AbstractSeveral clinical trials have shown the safety and effectiveness of PD-1/PD-L1 inhibitors in neoadjuvant therapy in resectable non-small cell lung cancer (NSCLC). However, 18–83% patients can benefit from it. In this study, we aimed to assess the association of PD-L1 expression, tumor mutation burden, copy number alteration (CNA, including copy number gain and loss) burden with the pathologic response to neoadjuvant PD-1 blockade and investigate the changes in the tumor immune microenvironment (TIME) during neoadjuvant immunotherapy in NSCLC. Pre-immunotherapy treatment tumor samples from twenty-nine NSCLC patients who received neoadjuvant immunotherapy with sintilimab, an anti-PD-1 drug, were subjected to targeted DNA sequencing and PD-L1 immunochemistry staining. The pathological response was positively correlated with tumor proportion score (TPS) of PD-L1 and negatively correlated with copy number gain (CNgain) burden. Of note, the combination of CNgain burden and TPS can better stratify major pathological response (MPR) patients than did CNgain or TPS alone. Whereas, TMB showed a limited correlation with pathological regression. Additionally, PD-1 blockade led to an increase in CD8+PD-1−T cells which was clinically relevant to MPR as evaluated by multiplex immunofluorescence. A significant reduction in CD19+ cells was observed in the Non-MPR group but not in the MPR group, indicating the involvement of B cells in improving neoadjuvant immunotherapy response in NSCLC. Together, our study provides new data for the correlation of PD-L1 expression and genomic factors with drug response in neoadjuvant immunotherapy settings in NSCLC. The changes of TIME may provide novel insight into the immune responses to neoadjuvant anti-PD-1 therapy.

2022 ◽  
Vol 12 ◽  
Lan-Xin Mu ◽  
You-Cheng Shao ◽  
Lei Wei ◽  
Fang-Fang Chen ◽  
Jing-Wei Zhang

Purpose: This study aims to reveal the relationship between RNA N6-methyladenosine (m6A) regulators and tumor immune microenvironment (TME) in breast cancer, and to establish a risk model for predicting the occurrence and development of tumors.Patients and methods: In the present study, we respectively downloaded the transcriptome dataset of breast cancer from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database to analyze the mutation characteristics of m6A regulators and their expression profile in different clinicopathological groups. Then we used the weighted correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and cox regression to construct a risk prediction model based on m6A-associated hub genes. In addition, Immune infiltration analysis and gene set enrichment analysis (GSEA) was used to evaluate the immune cell context and the enriched gene sets among the subgroups.Results: Compared with adjacent normal tissue, differentially expressed 24 m6A regulators were identified in breast cancer. According to the expression features of m6A regulators above, we established two subgroups of breast cancer, which were also surprisingly distinguished by the feature of the immune microenvironment. The Model based on modification patterns of m6A regulators could predict the patient’s T stage and evaluate their prognosis. Besides, the low m6aRiskscore group presents an immune-activated phenotype as well as a lower tumor mutation load, and its 5-years survival rate was 90.5%, while that of the high m6ariskscore group was only 74.1%. Finally, the cohort confirmed that age (p < 0.001) and m6aRiskscore (p < 0.001) are both risk factors for breast cancer in the multivariate regression.Conclusion: The m6A regulators play an important role in the regulation of breast tumor immune microenvironment and is helpful to provide guidance for clinical immunotherapy.

2022 ◽  
Vol 2022 ◽  
pp. 1-30
Cancan Luo ◽  
Han Nie ◽  
Li Yu

Diffuse large B-cell lymphoma (DLBCL) is a complex invasive tumour that occurs mainly among the elderly. Therefore, we analysed the relationship between ageing-related genes (AG) and DLBCL prognosis. Datasets related to DLBCL and human AGs were downloaded and screened from the Gene Expression Omnibus (GEO) database and HAGR website, respectively. LASSO and Cox regression were used to analyse AGs in the dataset and construct an AG predictive model related to DLBCL prognosis. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment were used to analyse the function of the AG predictive model. The immune microenvironment and immune cell infiltration in DLBCL and their relationship with the AG prediction model were also analysed. After the analysis, 118 AGs were identified as genes related to DLBCL prognosis. Using the LASSO and Cox regression analyses, 9 AGs (PLAU, IL7R, MYC, S100B, IGFBP3, NR3C1, PTK2, TBP, and CLOCK) were used to construct an AG prognostic model. In the training and verification sets, this model exhibited excellent predictive ability for the prognosis of patients with DLBCL who have different clinical characteristics. Further analysis revealed that the high- and low-risk groups of the AG prognostic model were significantly correlated with immune cell infiltration and tumour microenvironment in DLBCL. Functional enrichment analysis also showed that the genes in the AG model were associated with immune-related functions and pathways. In conclusion, we constructed an AG model with a strong predictive function in DLBCL, with the ability to predict the prognosis of patients with different clinical features. This model provides new ideas and potential therapeutic targets for the study of the pathogenesis of DLBCL.

2022 ◽  
Vol 2022 ◽  
pp. 1-22
Wei Tan ◽  
Shuai Peng ◽  
Zhuokai Li ◽  
Ruiqian Zhang ◽  
Yangrui Xiao ◽  

Background. Hepatocellular carcinoma (HCC) is predominant among all types of primary liver cancers characterised by high morbidity and mortality. Genes in the mediator complex (MED) family are engaged in the tumour-immune microenvironment and function as regulatory hubs mediating carcinogenesis and progression across diverse cancer types. Whereas research studies have been conducted to examine the mechanisms in several cancers, studies that systematically focused on the therapeutic and prognostic values of MED in patients with HCC are limited. Methods. The online databases ONCOMINE, GEPIA, UALCAN, GeneMANIA, cBioPortal, OmicStudio, STING, Metascape, and TIMER were used in this study. Results. The transcriptional levels of all members of the MED family in HCC presented an aberrant high expression pattern. Significant correlations were found between the MED1, MED6, MED8, MED10, MED12, MED15, MED17, MED19, MED20, MED21, MED22, MED23, MED24, MED25, MED26, and MED27 expression levels and the pathological stage in the patients with HCC. The patients with high expression levels of MED6, MED8, MED10, MED17, MED19, MED20, MED21, MED22, MED24, and MED25 were significantly associated with poor prognosis. Functional enrichment analysis revealed that the members of the MED family were mainly enriched in the nucleobase-containing compound catabolic process, regulation of chromosome organisation, and transcriptional regulation by TP53. Significant correlations were found between the MED6, MED8, MED10, MED17, MED19, MED20, MED21, MED22, MED24, and MED25 expression levels and all types of immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells). B cells and MED8 were independent predictors of overall survival. We found significant correlations between the somatic copy number alterations of the MED6, MED8, MED10, MED20, MED21, MED22, MED24, and MED25 molecules and the abundance of immune infiltrates. Conclusions. Our study delineated a thorough landscape to investigate the therapeutic and prognostic potentials of the MED family for HCC cases, which yielded promising results for the development of immunotherapeutic drugs and construction of a prognostic stratification model.

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