Cuproptosis-related genes are involved in immunodeficiency following ischemic stroke.
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ABSTRACT: Introduction
Accumulating studies have shown that copper has a detrimental effect in cells, and the cuproptosis-related gene signatures have been constructed as clinical tools to predict prognosis in tumors. However, the heterogeneity of cuproptosis has not been fully investigated in ischemic stroke.Methods: Here, we combined the bulk RNA-seq and single cell-RNA-seq data for stroke to investigate the role of cuproptosis in stroke.Results
We identified the cuproptosis-related differentially expressed genes (CuDEGs) in ischemic stroke. Then, we tried to find the hub genes with the machine learning method and WGCNA. We highlighted four genes identified by these methods and proposed a potential diagnostic model in ischemic stroke.Conclusions
Our findings revealed cuproptosis-related hub genes, which could provide useful biomarkers in ischemic stroke.
SUBMITTER: Jinshi L
PROVIDER: S-EPMC10895967 | biostudies-literature | 2024
REPOSITORIES: biostudies-literature
Publications
Cuproptosis-related genes are involved in immunodeficiency following ischemic stroke.
Jinshi Li L Cong Yu Y Liang Shu S Dabin Ren R Ping Zheng Z
Archives of medical science : AMS 20240131 1
<h4>Introduction</h4>Accumulating studies have shown that copper has a detrimental effect in cells, and the cuproptosis-related gene signatures have been constructed as clinical tools to predict prognosis in tumors. However, the heterogeneity of cuproptosis has not been fully investigated in ischemic stroke.Methods: Here, we combined the bulk RNA-seq and single cell-RNA-seq data for stroke to investigate the role of cuproptosis in stroke.<h4>Results</h4>We identified the cuproptosis-related diff ...[more]
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Project description:BackgroundImmune infiltration plays an important role in the course of ischemic stroke (IS) progression. Cuproptosis is a newly discovered form of programmed cell death. To date, no studies on the mechanisms by which cuproptosis-related genes regulate immune infiltration in IS have been reported.MethodsIS-related microarray datasets were retrieved from the Gene Expression Omnibus (GEO) database and standardized. Immune infiltration was extracted and quantified based on the processed gene expression matrix. The differences between the IS group and the normal group as well as the correlation between the infiltrating immune cells and their functions were analyzed. The cuproptosis-related DEGs most related to immunity were screened out, and the risk model was constructed. Finally, Gene Ontology (GO) function, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and drug target were performed using the Enrichr website database. miRNAs were predicted using FunRich software. Finally, cuproptosis-related differentially expressed genes (DEGs) in IS samples were typed, and Gene Set Variation Analysis (GSVA) was used to analyze the differences in biological functions among the different types.ResultsSeven Cuproptosis-related DEGs were obtained by merging the GSE16561 and GSE37587 datasets. Correlation analysis of the immune cells showed that NLRP3, NFE2L2, ATP7A, LIPT1, GLS, and MTF1 were significantly correlated with immune cells. Subsequently, these six genes were included in the risk study, and the risk prediction model was constructed to calculate the total score to analyze the risk probability of the IS group. KEGG analysis showed that the genes were mainly enriched in the following two pathways: D-glutamine and D-glutamate metabolism; and lipids and atherosclerosis. Drug target prediction found that DMBA CTD 00007046 and Lithocholate TTD 00009000 were predicted to have potential therapeutic effects of candidate molecules. GSVA showed that the TGF-β signaling pathway and autophagy regulation pathways were upregulated in the subgroup with high expression of cuproptosis-related DEGs.ConclusionsNLRP3, NFE2L2, ATP7A, LIPT1, GLS and MTF1 may serve as predictors of cuproptosis and play an important role in the pathogenesis of immune infiltration in IS.
| S-EPMC9933552 | biostudies-literature
Project description:The present study elucidated cuproptosis-related molecular clusters involved in ischemic stroke and developed predictive models. Transcriptomic and immunological profiles of ischemic stroke-related datasets were extracted from the Gene Expression Omnibus database. Next, we conducted weighted gene co-expression network analysis to determine cluster-specific differentially expressed genes (DEGs). Models such as random forest and eXtreme gradient boosting (XGB) were evaluated to select the best prediction performance model. Subsequently, we validated the model's predictive efficiency by using nomograms, decision curve analysis, calibration curves, and receiver operating characteristic curve analysis with an external dataset. We identified two cuproptosis-related clusters involved in ischemic stroke. The DEGs in Cluster 2 were closely associated with amino acid metabolism, various immune responses, and cell proliferation pathways. The XGB model showed lower residuals, a smaller root mean square error, and a greater area under the curve value (AUC = 0.923), thus exhibiting the best discriminative performance. The AUC value for the external validation dataset was 0.921, thus confirming the high performance of the model. NFE2L2, NLRP3, GLS, LIPT1, and MTF1 were identified as potential cuproptosis predictors, thus shedding new light on ischemic stroke pathogenesis and heterogeneity.
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Project description:ObjectiveIschemic stroke (IS) is a significant health concern with high disability and fatality rates despite available treatments. Immune cells and cuproptosis are associated with the onset and progression of IS. Investigating the interaction between cuproptosis-related genes (CURGs) and immune cells in IS can provide a theoretical basis for IS treatment.MethodsWe obtained IS datasets from the Gene Expression Omnibus (GEO) and employed machine learning to identify CURGs. The diagnostic efficiency of the CURGs was evaluated using receiver operating characteristic (ROC) curves. KEGG and gene set enrichment analysis (GSEA) were also conducted to identify biologically relevant pathways associated with CURGs in IS patients. Single-cell analysis was used to confirm the expression of 19 CURGs, and pathway activity calculations were performed using the AUCell package. Additionally, a risk prediction model for IS patients was developed, and core modules and hub genes related to IS were identified using weighted gene coexpression network analysis (WGCNA). We classified IS patients using a method of consensus clustering.ResultsWe established a precise diagnostic model for IS. Enrichment analysis revealed major pathways, including oxidative phosphorylation, the NF-kappa B signaling pathway, the apoptosis pathway, and the Wnt signaling pathway. At the single-cell level, compared to those in non-IS samples, 19 CURGs were primarily overexpressed in the immune cells of IS samples and exhibited high activity in natural killer cell-mediated cytotoxicity, steroid hormone biosynthesis, and oxidative phosphorylation. Two clusters were obtained through consensus clustering. Notably, immune cell types including B cells, plasma cells, and resting NK cells, varied between the two clusters. Furthermore, the red module and hub genes associated with IS were uncovered. The expression patterns of CURGs varied over time.ConclusionThis study developed a precise diagnostic model for IS by identifying CURGs and evaluating their interaction with immune cells. Enrichment analyses revealed key pathways involved in IS, and single-cell analysis confirmed CURG overexpression in immune cells. A risk prediction model and core modules associated with IS were also identified.
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Project description:BackgroundColorectal cancer (CRC) is a common malignancy, with high incidence and high mortality rates. Cuproptosis, a novel form of copper-induced programmed cell death, contributes to tumor progression. However, whether cuproptosis-related genes (CRGs) play a role in CRC remains unclear. This study aims to elucidate the role of CRGs in CRC development, patient prognosis, and immune response.MethodsWe performed bioinformatics analysis of the differential expression of CRGs between CRC and normal tissues. Least absolute shrinkage and selection operator (LASSO), and univariate and multivariate Cox analyses were employed to identify risk factors, which were used to construct a risk score model. Patients with CRC were categorized into high- and low-risk groups based on their median risk scores. Receiver operating characteristic curve analysis was used to verify the predictive accuracy of the risk model. A nomogram was developed for CRC through univariate and multivariate Cox regression analyses. The chemotherapeutic drug sensitivity was compared between patients with high and low CDKN2A/DLAT expression using the Wilcoxon rank-sum test. Spearman's correlation and TISIDB database analyses were conducted to determine relationships between CDKN2A or DLAT and immune cell infiltration.ResultsEight of ten identified CRGs exhibited significant differential expression between CRC and normal tissues. Among the eight significant differential expression CRGs, CDKN2A and DLAT were identified as independent risk factors for predicting overall survival (OS) in CRC. Patients with CRC in the low-risk group had longer OS than those in the high-risk group. The risk score model had good predictive accuracy for OS. Based on CDKN2A, DLAT and some clinical characteristics, a prognostic nomogram was developed to predict OS for CRC patients and showed good predictive ability. CDKN2A and DLAT expressions were significantly associated with chemotherapeutic drug sensitivity and immune cell infiltration in CRC, and the molecular subtypes and immune subtypes differed between CDKN2A and DLAT.ConclusionsOur research revealed the prognostic value of CRGs, particularly CDKN2A and DLAT, in CRC and demonstrated the relationship between CDKN2A/DLAT and immune infiltration in CRC, thereby contributing to the outcome evaluation of patients with CRC and identifying novel targets for CRC immunotherapy.
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Project description:Rheumatoid arthritis (RA) is an autoimmune disease that severely affects patients' physical and mental health, leading to chronic synovitis and destruction of bone joints. Although various available clinical treatment options exist, patients respond with varying efficacies due to multiple factors, and there is an urgent need to discover new treatment options to improve clinical outcomes. Cuproptosis is a newly characterized form of cell death. Copper causes cuproptosis by binding to lipid-acylated components of the tricarboxylic acid cycle, leading to protein aggregation, loss of iron-sulfur cluster proteins, and eventually proteotoxic stress. Targeting copper cytotoxicity and cuproptosis are considered potential options for treating oncological diseases. The synovial hypoxic environment and the presence of excessive glycolysis in multiple cells appear to act as inhibitors of cuproptosis, which can lead to excessive survival and proliferation of multiple immune cells, such as fibroblast-like synoviocytes, effector T cells, and macrophages, further mediating inflammation and bone destruction in RA. Therefore, in this study, we attempted to elaborate and summarize the linkage of cuproptosis and key genes regulating cuproptosis to the pathological mechanisms of RA and their effects on a variety of immune cells. This study aimed to provide a theoretical basis and support for translating preclinical and experimental results of RA to clinical protocols.
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Project description:The regulation of the immune system and the occurrence of inflammation are vital factors in the pathophysiology of ischemic stroke. This study aims to screen target molecules which play key roles in alleviating the brain injury following ischemic stroke via regulating neuroinflammation. Several bioinformatics methods were used to identify immune-related genes in ischemic stroke. A total of 218 genes were identified as differentially expressed genes within the GSE97537 dataset. By performing GO, KEGG, and GSEA analyses, DEGs were mainly enriched in pathways related to immunity and inflammation. By utilizing the MCODE plugin in conjunction with Cytoscape software, a total of six crucial genes were identified, including C1qb, C1qc, Fcer1g, Fcgr3a, Tyrobp, and CD14. Based on the above crucial genes, 13 miRNAs were predicted. Furthermore, 71 potential drugs with therapeutic properties that target the crucial genes were screened, including lovastatin, ASPIRIN, and PREDNISOLONE. Moreover, the results of RT-qPCR showed that compared with Sham group, the expressions of C1qb, C1qc, Fcer1g, Fcgr3a, Tyrobp, and CD14 in MCAO group were significantly increased, which was consistent with the expression trend of validation dataset and training dataset. In conclusion, immune-related genes may play a key role in ischemic stroke. In addition, six crucial genes were identified as potential biomarkers and 71 promising drugs were screened to treat ischemic stroke patients.
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Project description:Ischemic stroke (IS) is a complex syndrome of neurological deficits due to stenosis or occlusion of the carotid and vertebral arteries for which there is still no effective treatment. Melatonin, a hormone secreted by the pineal gland, has multiple biological effects, such as antioxidant and anti-inflammatory properties, circadian rhythm regulation, and tissue regeneration, demonstrating potential applications in the treatment of IS. The aim of this study was to investigate key melatonin-regulated genes associated with IS using transcriptome sequencing and bioinformatics analyses and to explore their potential mechanisms of action in the disease process. We obtained gene expression data related to ischemic stroke (IS) from the Gene Expression Omnibus (GEO) database and identified candidate genes using machine learning algorithms. We then assessed the predictive power of these genes using PPI network analysis and diagnostic models. Finally, a series of enrichment analyses identified four key genes: ADM, PTGS2, MMP9, and VCAN. In addition, we determined the mRNA levels of these four key genes in an IS rat model using qPCR and found that all of these genes were significantly upregulated in the IS model compared to the control group, which is consistent with the results of previous analyses. Meanwhile, these genes have biological functions such as regulating vascular tone, participating in the inflammatory response, influencing tissue remodeling, and regulating cell adhesion and proliferation, playing key roles in the pathogenesis of IS. Therefore, we suggest that these four key genes may serve as prospective biomarkers for IS and help predict the risk of developing IS. In conclusion, this study elucidates for the first time the potential role of melatonin in the pathogenesis of IS and lays the foundation for in-depth studies on the functions of these key genes in the pathophysiology of IS and their potential applications in clinical diagnosis and treatment.
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Project description:Background. Women account for 60% of all stroke deaths and are more often permanently disabled than men, despite their higher observed stroke incidence. Considering the clinical population affected by stroke, an obvious drawback is that many pre-clinical and clinical studies only investigate young males. To improve therapeutic translation from bench to bedside, we believe that it is advantageous to include both sexes in experimental models of stroke. The aims of this study were to identify early cerebral vascular responses to ischemic stroke in females, compare the differential gene expression patterns with those seen in males, and identify potential new therapeutic targets. Results. Transient middle cerebral artery occlusion (tMCAO) was used to induce stroke in both female and male rats, the middle cerebral arteries (MCAs) were isolated 3 hours post reperfusion and RNA was extracted. Affymetrix whole transcriptome expression profiling was performed on female (n = 12) MCAs to reveal differentially expressed genes. In total, 1076 genes had an increased expression and 879 genes a decreased expression in the occluded MCAs as compared with the control MCAs from female rats. An enrichment of genes related to apoptosis, regulation of transcription, protein autophosphorylation, inflammation, oxidative stress, and tissue repair and recovery were seen in the occluded MCA. The high expression genes chosen for qPCR verification (Adamts4, Olr1, JunB, Fosl1, Serpine1, S1pr3, Ccl2 and Socs3) were all shown to be upregulated in the same manner in both females and males after tMCAO (p < 0.05; n = 23). When comparing the differentially expressed genes in female MCAs (occluded and non-occluded) with our previous findings in males after tMCAO, a total of 297 genes overlapped (all groups had 32 genes in common). Conclusions. The cascades of processes initiated in the vasculature following reperfusion are complex. Dynamic gene expression alterations were observed in the occluded MCAs, and to a less pronounced degree in the non-occluded MCAs. Dysregulation of inflammation and blood-brain barrier breakdown are possible pharmacological targets. The sample of genes (<1% of differentially expressed genes) validated for this microarray did not reveal any sex differences.
2020-11-25 | GSE162072 | GEO