Identification of key genes and novel immune infiltration-associated biomarkers of sepsis

Single-cell RNA sequencing and transcriptomic analysis reveal key genes and regulatory mechanisms in sepsis

The pathogenesis of sepsis, with a high mortality rate and often poor prognosis, has not been fully elucidated. Therefore, an in-depth study on the pathogenesis of sepsis at the molecular level is essential to identify key sepsis-related genes. The aim of this study was to explore the key genes and potential molecular mechanisms of sepsis using a bioinformatics approach. In addition, key genes with miRNA network correlation analysis and immune infiltration correlation analysis were investigated. The scRNA dataset (GSE167363) and RNA-seq dataset (GSE65682, GSE134347) from GEO database were used for screening out differentially expressed genes using single-cell sequencing and transcriptome sequencing. The analysis of immune infiltration was evaluated by the CIBERSORT method. Key genes and possible mechanisms were identified by WGCNA analysis, GSVA analysis, GSEA enrichment analysis and regulatory network analysis, and miRNA networks associated with key genes were constructed. Nine key genes associated with the development of sepsis, namely IL7R, CD3D, IL32, GPR183, HLA-DPB1, CD81, PEBP1, NCL, and ETS1 were screened, and the specific signaling mechanisms associated with the key genes causing sepsis were predicted. Immune profiling showed immune heterogeneity between control and sepsis samples. A regulatory network of 82 miRNAs, 266 pairs of mRNA-miRNA relationship pairs was also constructed. These nine key genes have the potential to become biomarkers for the diagnosis of sepsis and provide new targets and research directions for the treatment of sepsis.

Single-cell RNA-seq Reveals the Inhibitory Effect of Methamphetamine on Liver Immunity with the Involvement of Dopamine Receptor D1

Methamphetamine (METH) is a highly addictive psychostimulant that causes physical and psychological damage and immune system disorder, especially in the liver which contains a significant number of immune cells. Dopamine, a key neurotransmitter in METH addiction and immune regulation, plays a crucial role in this process. Here, we developed a chronic METH administration model and conducted single-cell RNA sequencing (scRNA-seq) to investigate the effect of METH on liver immune cells and the involvement of dopamine receptor D1 (DRD1). Our findings reveal that chronic exposure to METH induces immune cell identity shifts from IFITM3+ macrophage (Mac) and CCL5+ Mac to CD14+ Mac, as well as from FYN+CD4+ T effector (Teff), CD8+ T, and natural killer T (NKT) to FOS+CD4+ T and RORα+ group 2 innate lymphoid cell (ILC2), along with the suppression of multiple functional immune pathways. DRD1 is implicated in regulating certain pathways and identity shifts among the hepatic immune cells. Our results provide valuable insights into the development of targeted therapies to mitigate METH-induced immune impairment.

High expression of L-GILZ transcript variant 1 (GILZ TV 1) is associated with increased 30-day sepsis mortality, and a high expression ratio possibly contraindicates hydrocortisone administration

BACKGROUND

Sepsis presents a challenge due to its complex immune responses, where balance between inflammation and anti-inflammation is critical for survival. Glucocorticoid-induced leucine zipper (GILZ) is key protein in achieving this balance, suppressing inflammation and mediating glucocorticoid response. This study aims to investigate GILZ transcript variants in sepsis patients and explore their potential for patient stratification and optimizing glucocorticoid therapy.

METHODS

Sepsis patients meeting the criteria outlined in Sepsis-3 were enrolled, and RNA was isolated from whole blood samples. Quantitative mRNA expression of GILZ transcript variants in both sepsis patient samples (n = 121) and the monocytic U937 cell line (n = 3), treated with hydrocortisone and lipopolysaccharides, was assessed using quantitative PCR (qPCR).

RESULTS

Elevated expression of GILZ transcript variant 1 (GILZ TV 1) serves as a marker for heightened 30-day mortality in septic patients. Increased levels of GILZ TV 1 within the initial day of sepsis onset are associated with a 2.2-[95% CI 1.2-4.3] fold rise in mortality, escalating to an 8.5-[95% CI 2.0-36.4] fold increase by day eight. GILZ TV1 expression is enhanced by glucocorticoids in cell culture but remains unaffected by inflammatory stimuli such as LPS. In septic patients, GILZ TV 1 expression increases over the course of sepsis and in response to hydrocortisone treatment. Furthermore, a high expression ratio of transcript variant 1 relative to all GILZ mRNA TVs correlates with a 2.3-fold higher mortality rate in patients receiving hydrocortisone treatment.

CONCLUSION

High expression of GILZ TV 1 is associated with a higher 30-day sepsis mortality rate. Moreover, a high expression ratio of GILZ TV 1 relative to all GILZ transcript variants is a parameter for identifying patient subgroups in which hydrocortisone may be contraindicated.

Integrated multi-omics analysis and machine learning developed diagnostic markers and prognostic model based on Efferocytosis-associated signatures for septic cardiomyopathy

Septic cardiomyopathy (SCM) is characterized by an abnormal inflammatory response and increased mortality. The role of efferocytosis in SCM is not well understood. We used integrated multi-omics analysis to explore the clinical and genetic roles of efferocytosis in SCM. We identified six module genes (ATP11C, CD36, CEBPB, MAPK3, MAPKAPK2, PECAM1) strongly associated with SCM, leading to an accurate predictive model. Subgroups defined by EFFscore exhibited distinct clinical features and immune infiltration levels. Survival analysis showed that the C1 subtype with a lower EFFscore had better survival outcomes. scRNA-seq analysis of peripheral blood mononuclear cells (PBMCs) from sepsis patients identified four genes (CEBPB, CD36, PECAM1, MAPKAPK2) associated with high EFFscores, highlighting their role in SCM. Molecular docking confirmed interactions between diagnostic genes and tamibarotene. Experimental validation supported our computational results. In conclusion, our study identifies a novel efferocytosis-related SCM subtype and diagnostic biomarkers, offering new insights for clinical diagnosis and therapy.

Exploring the Role of Neutrophil-Related Genes in Osteosarcoma via an Integrative Analysis of Single-Cell and Bulk Transcriptome

BACKGROUND

The involvement of neutrophil-related genes (NRGs) in patients with osteosarcoma (OS) has not been adequately explored. In this study, we aimed to examine the association between NRGs and the prognosis as well as the tumor microenvironment of OS.

METHODS

The OS data were obtained from the TARGET-OS and GEO database. Initially, we extracted NRGs by intersecting 538 NRGs from single-cell RNA sequencing (scRNA-seq) data between aneuploid and diploid groups, as well as 161 up-regulated differentially expressed genes (DEGs) from the TARGET-OS datasets. Subsequently, we conducted Least Absolute Shrinkage and Selection Operator (Lasso) analyses to identify the hub genes for constructing the NRG-score and NRG-signature. To assess the prognostic value of the NRG signatures in OS, we performed Kaplan-Meier analysis and generated time-dependent receiver operating characteristic (ROC) curves. Gene enrichment analysis (GSEA) and gene set variation analysis (GSVA) were utilized to ascertain the presence of tumor immune microenvironments (TIMEs) and immunomodulators (IMs). Additionally, the KEGG neutrophil signaling pathway was evaluated using ssGSEA. Subsequently, PCR and IHC were conducted to validate the expression of hub genes and transcription factors (TFs) in K7M2-induced OS mice.

RESULTS

FCER1G and C3AR1 have been identified as prognostic biomarkers for overall survival. The findings indicate a significantly improved prognosis for OS patients. The effectiveness and precision of the NRG signature in prognosticating OS patients were validated through survival ROC curves and an external validation dataset. The results clearly demonstrate that patients with elevated NRG scores exhibit decreased levels of immunomodulators, stromal score, immune score, ESTIMATE score, and infiltrating immune cell populations. Furthermore, our findings substantiate the potential role of SPI1 as a transcription factor in the regulation of the two central genes involved in osteosarcoma development. Moreover, our analysis unveiled a significant correlation and activation of the KEGG neutrophil signaling pathway with FCER1G and C3AR1. Notably, PCR and IHC demonstrated a significantly higher expression of C3AR1, FCER1G, and SPI1 in Balb/c mice induced with K7M2.

CONCLUSIONS

Our research emphasizes the significant contribution of neutrophils within the TIME of osteosarcoma. The newly developed NRG signature could serve as a good instrument for evaluating the prognosis and therapeutic approach for OS.

C3AR1 is a regulatory factor associated with coagulation cascade and inflammation in sepsis

Sepsis is a leading cause of mortality in intensive care units. Sepsis is associated with activation of the coagulation cascade and inflammation. The aim of this study was to identify coagulation-related genes in sepsis that may provide translational potential therapeutic targets. The datasets GSE28750, GSE95233, and GSE65682 were downloaded from the gene expression omnibus database. Consensus-weighted gene co-expression network analysis (WGCNA) was used to identify sepsis modules. Gene set enrichment analysis was used to identify genes enriched in the coagulation cascade. The value of hub-gene in immunological analysis was tested in the validation sets (GSE95233). The value of hub-gene in clinical prognosis was tested in the validation sets (GSE65582). One thousand one hundred seventy-six genes with high connectivity in the clinically significant module were identified as hub genes. Ten genes were found to be enriched in coagulation-related signaling pathways. C3AR1 was selected for further analysis. The immune infiltration analysis showed that lower expression of C3AR1 was associated with immune response in sepsis and could be an independent predictor of survival status in sepsis patients. Meanwhile, univariate and multivariate Cox analysis showed that C3AR1 had a significant correlation with survival. C3AR1 may become an effective biomarker for worse outcomes in sepsis patients associated with immune and coagulation cascade.

Critical roles of S100A12, MMP9, and PRTN3 in sepsis diagnosis: Insights from multiple microarray data analyses

BACKGROUND

Sepsis, characterized by systemic inflammatory response syndrome and life-threatening organ dysfunction, remains a significant global cause of disability and death. Despite its impact, reliable biomarkers for sepsis diagnosis are yet to be identified.

OBJECTIVE

This study aims to investigate and identify key genes and pathways in sepsis through the analysis of multiple microarray datasets, providing potential treatment targets for future clinical trials.

METHODS

Two independent gene expression profiles (GSE54514 and GSE69528) were downloaded from the Gene Expression Omnibus (GEO) database. After merging and batch normalization, differentially expressed genes (DEGs) were obtained using the "limma" package. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were performed using "R" software. A Protein-Protein Interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING). The top 10 hub genes were identified using Cytoscape. A Nomogram model for predicting sepsis occurrence was constructed and evaluated.

RESULTS

Bioinformatic analysis of 210 sepsis and 91 control blood samples identified 72 DEGs. GO analyses revealed associations with immune response processes. GSEA indicated involvement in key signaling pathways. S100A12, MMP9, and PRTN3 were identified as independent risk factors for sepsis.

CONCLUSION

This study unveils critical genes and pathways in sepsis through bioinformatic methods. S100A12, MMP9, and PRTN3 may play essential roles in the immune response to infection, influencing sepsis prognosis.

E3 ubiquitin ligase COP1-mediated CEBPB ubiquitination regulates the inflammatory response of macrophages in sepsis-induced myocardial injury

CCAAT/enhancer-binding protein beta (CEBPB) has been associated with sepsis. However, its role in sepsis-induced myocardial injury (SIMI) remains ill-defined. This research was designed to illustrate the involvement of CEBPB in SIMI and its upstream modifier. The transcriptomic changes in heart biopsies of mice that had undergone polymicrobial sepsis were downloaded from the GEO dataset for KEGG enrichment analysis. CEBPB, on the TNF signaling pathway, was significantly enhanced in the myocardial tissues of mice with SIMI. Downregulation of CEBPB alleviated SIMI, as evidenced by minor myocardial injury and inflammatory manifestations. Moreover, ubiquitination modification of CEBPB by constitutive photomorphogenesis protein 1 homolog (COP1) led to the degradation of CEBPB and inhibited inflammatory responses in macrophages. Upregulation of COP1 protected against SIMI in mice overexpressing CEBPB. Collectively, our findings demonstrated that COP1 protected the heart against SIMI through the ubiquitination modification of CEBPB, which might be a novel therapeutic approach in the future.

Effect of BAFF blockade on the B cell receptor repertoire and transcriptome in a mouse model of systemic lupus erythematosus

Introduction

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Anti-B-cell-activating factor (BAFF) therapy effectively depletes B cells and reduces SLE disease activity. This research aimed to evaluate the effect of BAFF blockade on B cell receptor (BCR) repertoire and gene expression.

Methods

Through next-generation sequencing, we analyzed gene expression and BCR repertoire in MRL/lpr mice that received long-term anti-BAFF therapy. Based on gene expression profiles, we predicted the relative proportion of immune cells using ImmuCellAI-mouse, validating our predictions via flow cytometry and FluoroSpot.

Results

The loss of BCR repertoire diversity and richness, along with increased clonality and differential frequency distribution of the immunoglobulin heavy chain variable (IGHV) segment gene usage, were observed in BAFF-blockade mice. Meanwhile, the distribution of complementarity-determining region 3 (CDR3) length and CDR3 amino acid usage remained unaffected. BAFF blockade resulted in extensive changes in gene expression, particularly that of genes related to B cells and immunoglobulins. Besides, the tumor necrosis factor (TNF)-α responses and interferon (IFN)-α/γ were downregulated, consistent with the decrease in IFN-γ and TNF-α serum levels following anti-BAFF therapy. In addition, BAFF blockade significantly reduced B cell subpopulations and plasmacytoid dendritic cells, and caused the depletion of antibody-secreting cells.

Discussion

Our comparative BCR repertoire and transcriptome analyses of MRL/lpr mice subjected to BAFF blockade provide innovative insights into the molecular pathophysiology of SLE.

Immune-Related Molecules CD3G and FERMT3: Novel Biomarkers Associated with Sepsis

Sepsis ranks among the most common health problems worldwide, characterized by organ dysfunction resulting from infection. Excessive inflammatory responses, cytokine storms, and immune-induced microthrombosis are pivotal factors influencing the progression of sepsis. Our objective was to identify novel immune-related hub genes for sepsis through bioinformatic analysis, subsequently validating their specificity and potential as diagnostic and prognostic biomarkers in an animal experiment involving a sepsis mice model. Gene expression profiles of healthy controls and patients with sepsis were obtained from the Gene Expression Omnibus (GEO) and analysis of differentially expressed genes (DEGs) was conducted. Subsequently, weighted gene co-expression network analysis (WGCNA) was used to analyze genes within crucial modules. The functional annotated DEGs which related to the immune signal pathways were used for constructing protein-protein interaction (PPI) analysis. Following this, two hub genes, FERMT3 and CD3G, were identified through correlation analyses associated with sequential organ failure assessment (SOFA) scores. These two hub genes were associated with cell adhesion, migration, thrombosis, and T-cell activation. Furthermore, immune infiltration analysis was conducted to investigate the inflammation microenvironment influenced by the hub genes. The efficacy and specificity of the two hub genes were validated through a mice sepsis model study. Concurrently, we observed a significant negative correlation between the expression of CD3G and IL-1β and GRO/KC. These findings suggest that these two genes probably play important roles in the pathogenesis and progression of sepsis, presenting the potential to serve as more stable biomarkers for sepsis diagnosis and prognosis, deserving further study.

Biomarkers of ulcerative colitis disease activity CXCL1, CYP2R1, LPCAT1, and NEU4 and their relationship to immune infiltrates

The diagnosis and assessment of ulcerative colitis (UC) poses significant challenges, which may result in inadequate treatment and a poor prognosis for patients. This study aims to identify potential activity biomarkers for UC and investigate the role of infiltrating immune cells in the disease. To perform gene set enrichment analysis, we utilized the cluster profiler and ggplot2 packages. Kyoto encyclopedia of genes and genomes was used to analyze degenerate enrichment genes. Significant gene set enrichment was determined using the cluster profiler and ggplot2 packages. Additionally, quantitative PCR (qRT-PCR) was employed to validate the expression of each marker in the ulcerative colitis model. We identified 651 differentially expressed genes (DEGs) and further investigated potential UC activity biomarkers. Our analysis revealed that CXCL1 (AUC = 0.710), CYP2R1 (AUC = 0.863), LPCAT1 (AUC = 0.783), and NEU4 (AUC = 0.833) were promising activity markers for the diagnosis of UC. Using rat DSS model, we validated these markers through qRT-PCR, which showed statistically significant differences between UC and normal colon mucosa. Infiltrating immune cell analysis indicated that M1 macrophages, M2 macrophages, activated dendritic cells (DCs), and neutrophils played crucial roles in the occurrence and progression of UC. Moreover, the activity markers exhibited varying degrees of correlation with activated memory CD4 T cells, M0 macrophages, T follicular helper cells, memory B cells, and activated DCs. The potential diagnostic genes for UC activity, such as CXCL1, CYP2R1, LPCAT1, and NEU4, as well as the infiltration of immune cells, may contribute to the pathogenesis and progression of UC.

Predictive value of peripheral lymphocyte subsets for the disease progression in patients with sepsis

OBJECTIVE

To investigate the predictive value of peripheral lymphocyte subsets for sepsis progression.

METHODS

Patients with sepsis were divided into the improved group (n = 46) and severe group (n = 39) according to disease progression. Flow cytometric analysis was performed to enumerate absolute counts of peripheral lymphocyte subsets. Logistic regression analyses were conducted to identify clinical factors linked to sepsis progression.

RESULTS

The absolute counts of peripheral lymphocyte subsets were markedly decreased in septic patients compared with healthy controls. After treatment, the absolute counts of lymphocytes, CD3⁺ T cells, and CD8⁺ T cells were restored in the improved group, and reduced in the severe group. Logistic regression analysis indicated that a low CD8⁺ T cells count was a risk factor for sepsis progression. Receiver operating characteristic curve analysis revealed that CD8⁺ T cells count had the greatest ability to predict sepsis progression.

CONCLUSIONS

The absolute counts of CD3⁺ T cells, CD4⁺ T cells, CD8⁺ T cells, B cells, and natural killer cells were significantly higher in the improved group than the severe group. CD8⁺ T cells count was predictive of sepsis progression. Lymphopenia and CD8⁺ T cells depletion were associated with the clinical outcomes of sepsis, suggesting that CD8⁺ T cells have potential as a predictive biomarker and therapeutic target for patients with sepsis.

Identification of molecular subtypes of ischaemic stroke based on immune-related genes and weighted co-expression network analysis

Immune system has been reported to play a key role in the development of ischaemic stroke (IS). Nevertheless, its exact immune-related mechanism has not yet been fully revealed. Gene expression data of IS and healthy control samples was downloaded from Gene Expression Omnibus database and differentially expressed genes (DEGs) was obtained. Immune-related genes (IRGs) data was downloaded from the ImmPort database. The molecular subtypes of IS were identified based on IRGs and weighted co-expression network analysis (WGCNA). 827 DEGs and 1142 IRGs were obtained in IS. Based on 1142 IRGs, 128 IS samples were clustered into two molecular subtypes: clusterA and clusterB. Based on the WGCNA, the authors found that the blue module had the highest correlation with IS. In the blue module, 90 genes were screened as candidate genes. The top 55 genes were selected as the central nodes according to gene degree in protein-protein interactions network of all genes in blue module. Through taking overlap, nine real hub genes were obtained that might distinguish between clusterA subtype and clusterB subtype of IS. The real hub genes (IL7R, ITK, SOD1, CD3D, LEF1, FBL, MAF, DNMT1, and SLAMF1) may be associated with molecular subtypes and immune regulation of IS.

New insights of necroptosis and immune infiltration in sepsis-induced myocardial dysfunction from bioinformatics analysis through RNA-seq in mice

Sepsis is a life-threatening organ dysfunction caused by dysregulated host immune response to infection. Sepsis-induced myocardial dysfunction (SIMD) is a common complication in patients with severe sepsis and is associated with increased mortality. The molecular mechanisms underlying SIMD are complex and not well characterized. Excessive inflammation due to impaired regulation of immune response is one of the major causes of SIMD. Necroptosis is a novel type of cell death that is closely related to tissue injury and inflammation. However, the role of necroptosis in SIMD is not known. Therefore, in this study, we performed an in-depth bioinformatics analysis to investigate the relationship between necroptosis and SIMD using a mouse model generated by intraperitoneal injection of lipopolysaccharide (LPS) and the underlying mechanisms. Myocardial function was assessed by echocardiography. Histopathological changes in SIMD were analyzed by hematoxylin and eosin (H&E) staining. Gene expression profiles of the heart tissues from the SIMD and control mice were analyzed by bioinformatics analysis. Transcriptome sequencing demonstrated significant differences in the expression levels of 3654 genes in the heart tissues of SIMD mice including 1810 up-regulated and 1844 down-regulated genes. The necroptosis pathway genes were significantly enriched in the heart tissues from the SIMD group mice. We identified 35 necroptosis-related differentially expressed genes (NRDEGs) including MLKL and RIPK3. Cardiomyocyte necroptosis was confirmed by qRT-PCR and western blot analysis. The expression levels of most NRDEGs showed positive correlation with the infiltration levels of mast cells, macrophages, and neutrophils, and negative correlation with the infiltration levels of B cells and plasma cells in the heart tissues of the SIMD group mice. In conclusion, this study demonstrated that necroptosis was associated with changes in the infiltration levels of several immune cell types in the heart tissues of the SIMD model mice. This suggested that necroptosis influenced SIMD development by modulating the immune microenvironment. This suggested that NRDEGs are potential diagnostic biomarkers and therapeutic targets for patients with SIMD.

FCGR2C: An emerging immune gene for predicting sepsis outcome

Background

Sepsis is a life-threatening disease associated with immunosuppression. Immunosuppression could ultimately increase sepsis mortality. This study aimed to identify the prognostic biomarkers related to immunity in sepsis.

Methods

Public datasets of sepsis downloaded from the Gene Expression Omnibus (GEO) database were divided into the discovery cohort and the first validation cohort. We used R software to screen differentially expressed genes (DEGs) and analyzed DEGs' functional enrichment in the discovery dataset. Immune-related genes (IRGs) were filtered from the GeneCards website. A Lasso regression model was used to screen candidate prognostic genes from the intersection of DEGs and IRGs. Then, the candidate prognostic genes with significant differences were identified as prognostic genes in the first validation cohort. We further validated the expression of the prognostic genes in the second validation cohort of 81 septic patients recruited from our hospital. In addition, we used four immune infiltration methods (MCP-counter, ssGSEA, ImmuCellAI, and CIBERSORT) to analyze immune cell composition in sepsis. We also explored the correlation between the prognostic biomarker and immune cells.

Results

First, 140 genes were identified as prognostic-related immune genes from the intersection of DEGs and IRGs. We screened 18 candidate prognostic genes in the discovery cohort with the lasso regression model. Second, in the first validation cohort, we identified 4 genes (CFHR2, FCGR2C, GFI1, and TICAM1) as prognostic immune genes. Subsequently, we found that FCGR2C was the only gene differentially expressed between survivors and non-survivors in 81 septic patients. In the discovery and first validation cohorts, the AUC values of FCGR2C were 0.73 and 0.67, respectively. FCGR2C (AUC=0.84) had more value than SOFA (AUC=0.80) and APACHE II (AUC=0.69) in evaluating the prognosis of septic patients in our recruitment cohort. Moreover, FCGR2C may be closely related to many immune cells and functions, such as B cells, NK cells, neutrophils, cytolytic activity, and inflammatory promotion. Finally, enrichment analysis showed that FCGR2C was enriched in the phagosome signaling pathway.

Conclusion

FCGR2C could be an immune biomarker associated with prognosis, which may be a new direction of immunotherapy to reduce sepsis mortality.

The Impact of Curcumin on Immune Response: An Immunomodulatory Strategy to Treat Sepsis

Primary and secondary immunodeficiencies cause an alteration in the immune response which can increase the rate of infectious diseases and worsened prognoses. They can also alter the immune response, thus, making the infection even worse. Curcumin is the most biologically active component of the turmeric root and appears to be an antimicrobial agent. Curcumin cooperates with various cells such as macrophages, dendritic cells, B, T, and natural killer cells to modify the body's defence capacity. Curcumin also inhibits inflammatory responses by suppressing different metabolic pathways, reduces the production of inflammatory cytokines, and increases the expression of anti-inflammatory cytokines. Curcumin may also affect oxidative stress and the non-coding genetic material. This review analyses the relationships between immunodeficiency and the onset of infectious diseases and discusses the effects of curcumin and its derivatives on the immune response. In addition, we analyse some of the preclinical and clinical studies that support its possible use in prophylaxis or in the treatment of infectious diseases. Lastly, we examine how nanotechnologies can enhance the clinical use of curcumin.

CEBPB is associated with active tumor immune environment and favorable prognosis of metastatic skin cutaneous melanoma

Metastatic skin cutaneous melanoma (SKCM) is a common malignancy that accounts for low morbidity but high mortality of skin cancer. SKCM is characterized by high lymphocytic infiltration, whereas the states of infiltrated cells are variable in patients leading to a heterogeneous prognosis and hindering appropriate clinical decisions. It is therefore urgent to identify markers associated with lymphocytic infiltration, cellular conditions, and the prognosis of SKCM. In this study, we report that CEBPB, a transcriptional factor, is mainly expressed in macrophages in metastatic SKCM and associated with an active tumor immune environment and a favorable prognosis through integrated analysis of single-cell and bulk RNA-seq datasets. High CEBPB expression is significantly associated with active inflammation and immune response pathways in both macrophages and bulk SKCM tumor tissues. A signature based on CEBPB-associated genes that are specifically expressed in macrophages could robustly and prognostically separate different metastatic SKCM patients. In addition, the associations between the metastatic SKCM tumor signature and microenvironment with respect to T-cell recruitment and state, inflammation response, angiogenesis, and so on were also determined. In conclusion, we present here the first report on CEBPB in tumor immune environment and prognosis regulation in metastatic SKCM and construct a reliable signature, which should provide a useful biomarker for stratification of the patient's prognosis and therapeutic selection.

Curcumin Elevates microRNA-183-5p via Cathepsin B-Mediated Phosphatidylinositol 3-Kinase/AKT Pathway to Strengthen Lipopolysaccharide-Stimulated Immune Function of Sepsis Mice

Curcumin (Cur), a natural polyphenol compound, has been testified to modulate innate immune responses and also showed anti-inflammatory properties. Nevertheless, the mechanism was still poorly unknown, especially regarding Cur-modulated microRNAs (miRNAs) under the inflammatory response. CD39⁺ regulatory T cells (Tregs) were provided with distinct immunosuppressive action and exerted a critical role in the modulation of immune balance in sepsis. Nevertheless, the impact of Cur on the immune function of sepsis mice has not been reported. In this study, the influence of Cur on the inflammatory response and immune function of sepsis mice via augment of miR-183-5p and Cathepsin B (CTSB)-mediated phosphatidylinositol 3-kinase (PI3K)/AKT pathway was explored. Adoption of 20 mg/kg Cur was for gavage. In the meantime, injection of plasmid vectors of interference with miR-183-5p or CTSB was into the tail vein. Intraperitoneal injection of lipopolysaccharide (10 mg/kg) was to stimulate model of sepsis mice. Histopathological changes of sepsis mice were observed. The contents of tumor necrosis factor-α and Interleukin (IL)-1β and IL-6 in serum of mice were examined. Detection of alanine aminotransferase, aspartate aminotransferase (AST), urea nitrogen (BUN), and creatinine in serum of mice was performed. Test of the percentage of CD39⁺ Tregs in tail venous blood of mice was implemented. Examination of miR-183-5p, CTSB, and PI3K/AKT was performed. The targeting of miR-183-5p and CTSB was detected. Cur was available to ameliorate the histological damage, to reduce the content of inflammatory factors, AST, and BUN, and to decline the percentage of CD39⁺ Tregs in tail venous blood of sepsis mice. Elevated miR-183-5p or silenced CTSB was available to further enhance the protection of Cur. Cur was available to accelerate miR-183-5p, which negatively modulated CTSB and Cur-mediated PI3K/AKT pathway via the miR-183-5p/CTSB axis to restrain inflammation of sepsis mice and enhance its immune function.

A chromosome-level genome of Brachymystax tsinlingensis provides resources and insights into salmonids evolution

Brachymystax tsinlingensis Li, 1966 is an endangered freshwater fish with economic, ecological, and scientific values. Study of the genome of B. tsinlingensis might be particularly insightful given that this is the only Brachymystax species with genome. We present a high-quality chromosome-level genome assembly and protein-coding gene annotation for B. tsinlingensis with Illumina short reads, Nanopore long reads, Hi-C sequencing reads, and RNA-seq reads from 5 tissues/organs. The final chromosome-level genome size is 2,031,709,341 bp with 40 chromosomes. We found that the salmonids have a unique GC content and codon usage, have a slower evolutionary rate, and possess specific positively selected genes. We also confirmed the salmonids have undergone a whole-genome duplication event and a burst of transposon-mediated repeat expansion, and lost HoxAbβ Hox cluster, highly expressed genes in muscle may partially explain the migratory habits of B. tsinlingensis. The high-quality B. tsinlingensis assembled genome could provide a valuable reference for the study of other salmonids as well as aid the conservation of this endangered species.

Molecular Framework of Mouse Endothelial Cell Dysfunction during Inflammation: A Proteomics Approach

A key aspect of cytokine-induced changes as observed in sepsis is the dysregulated activation of endothelial cells (ECs), initiating a cascade of inflammatory signaling leading to leukocyte adhesion/migration and organ damage. The therapeutic targeting of ECs has been hampered by concerns regarding organ-specific EC heterogeneity and their response to inflammation. Using in vitro and in silico analysis, we present a comprehensive analysis of the proteomic changes in mouse lung, liver and kidney ECs following exposure to a clinically relevant cocktail of proinflammatory cytokines. Mouse lung, liver and kidney ECs were incubated with TNF-α/IL-1β/IFN-γ for 4 or 24 h to model the cytokine-induced changes. Quantitative label-free global proteomics and bioinformatic analysis performed on the ECs provide a molecular framework for the EC response to inflammatory stimuli over time and organ-specific differences. Gene Ontology and PANTHER analysis suggest why some organs are more susceptible to inflammation early on, and show that, as inflammation progresses, some protein expression patterns become more uniform while additional organ-specific proteins are expressed. These findings provide an in-depth understanding of the molecular changes involved in the EC response to inflammation and can support the development of drugs targeting ECs within different organs. Data are available via ProteomeXchange (identifier PXD031804).

Contribution of prognostic ferroptosis-related subtypes classification and hub genes of sepsis

BACKGROUND

Sepsis in patients is a great threat to human health due to its high incidence rate, its rapid and unpredictable progression, as well as it is difficult to treat, and it has poor prognosis. Ferroptosis is a newly discovered type of cell death characterized by the iron-dependent peroxide aggregation. Furthermore, ferroptosis is different from other forms of cell death, namely apoptosis, necrosis, pyroptosis and autophagy. Our study investigated the role of ferroptosis-related genes in sepsis.

METHODS

The GSE65682 dataset from the Gene Expression Omnibus (GEO) database was used to screen ferroptosis-related genes associated with sepsis, and the GSE134347 dataset for the external validation of selected hub genes. The univariate Cox regression analysis, Kaplan-Meier (K-M) survival analysis and weighted gene co-expression network analysis (WGCNA) were used to identify hub genes. Evaluation of the immune cell infiltration in sepsis was used to explain the immune heterogeneity among the cell subtypes. Gene set variation analysis (GSVA) and transcriptional regulatory analysis of selected hub genes further elucidated the probable mechanism of ferroptosis-related genes associated with prognosis in sepsis. Finally, we constructed a competing endogenous RNA (ceRNA) network model.

RESULTS

A total of 479 RNA-seq data points were used for analysis, including 365 samples from patients who survived sepsis and 114 samples from patients who succumbed to sepsis from the available GSE65682 dataset. Consequently, the univariate Cox regression analysis and consensus clustering analysis divide all 479 sepsis samples into two clusters of "survivals" vs. "non-survivals". Following complex analysis were identified as the most important ferroptosis-related genes. Indeed, the WGCNA and K-M analyses associated the expression patterns of NEDD4L and SIAH2 hub genes as the best prognosis for the survival of sepsis (p < 0.05). The expression trend was also consistent with the survival trend of the NEDD4L and SIAH2 hub genes by the external validation of GSE134347 (p < 0.05). Immune cell infiltration analysis indicated that the types and numbers of different immune cells vary among different subtypes and NEDD4L and SIAH2 hub genes. For example, NEDD4L and SIAH2 gene expression had a positive correlation with M0 macrophages and a negative correlation with neutrophils (p > 0.05). Finally, analysis of two hub genes and transcription factors (TFs) showed that 71 TFs were predicted to be related to NEDD4L while 64 TFs to SIAH2 by the Cistrome DB online database.

CONCLUSION

We suggest that NEDD4L and SIAH2 hub genes are involved in the ferroptosis-associated sepsis. The pattern of NEDD4L and SIAH2 expression in patients undergoing sepsis may have prognostic potential for the severity of sepsis and eventually for patients' survival.

Inhibition of TXNDC5 attenuates lipopolysaccharide-induced septic shock by altering inflammatory responses

Sepsis and its severe form, septic shock, represent the leading cause of death among hospitalized patients. Thioredoxin is a ubiquitous protein essential for cellular redox balance and its aberrant expression is associated with a wide spectrum of inflammation-related pathological conditions. The current study aimed to compare the expression of thioredoxin domain containing 5 (TXNDC5) in septic patients with or without septic shock and to explore the potential regulatory effects of TXNDC5 in sepsis. We analyzed the RNA expression data downloaded from the Gene Expression Omnibus database and measured the plasma level of TXNDC5 in septic patients. The results showed that TXNDC5 was upregulated in patients with septic shock compared to septic patients without shock or healthy controls. We further treated wild-type mice and cultured macrophages with lipopolysaccharide (LPS) and found that TXNDC5 was highly expressed in mice with LPS-induced sepsis and macrophages subjected to LPS stimulation compared to corresponding controls. Then a mouse strain with targeted depletion of Txndc5 was generated. Txndc5 depletion reduced inflammatory cytokine production and affected the recruitment of macrophages and neutrophils into the blood and peritoneum of mice challenged with LPS. Further analysis revealed that TXNDC5 inhibition alleviated LPS-induced sepsis by inhibiting the NF-κB signaling pathway. In summary, these findings suggested that the inhibition of TXNDC5 may be a potential approach to treat sepsis and related syndromes.

The Landscape of Featured Metabolism-Related Genes and Imbalanced Immune Cell Subsets in Sepsis

Sepsis is a heterogeneous disease state triggered by an uncontrolled inflammatory host response with high mortality and morbidity in severely ill patients. Unfortunately, the treatment effectiveness varies among sepsis patients and the underlying mechanisms have yet to be elucidated. The present aim is to explore featured metabolism-related genes that may become the biomarkers in patients with sepsis. In this study, differentially expressed genes (DEGs) between sepsis and non-sepsis in whole blood samples were identified using two previously published datasets (GSE95233 and GSE54514). A total of 66 common DEGs were determined, namely, 52 upregulated and 14 downregulated DEGs. The Gene Set Enrichment Analysis (GSEA) results indicated that these DEGs participated in several metabolic processes including carbohydrate derivative, lipid, organic acid synthesis oxidation reduction, and small-molecule biosynthesis in patients with sepsis. Subsequently, a total of 8 hub genes were screened in the module with the highest score from the Cytoscape plugin cytoHubba. Further study showed that these hub DEGs may be robust markers for sepsis with high area under receiver operating characteristic curve (AUROC). The diagnostic values of these hub genes were further validated in myocardial tissues of septic rats and normal controls by untargeted metabolomics analysis using liquid chromatography-mass spectrometry (LC-MS). Immune cell infiltration analysis revealed that different infiltration patterns were mainly characterized by B cells, T cells, NK cells, monocytes, macrophages, dendritics, eosinophils, and neutrophils between sepsis patients and normal controls. This study indicates that metabolic hub genes may be hopeful biomarkers for prognosis prediction and precise treatment in sepsis patients.

CD63 and C3AR1: The Potential Molecular Targets in the Progression of Septic Shock

Background

The molecular mechanism of septic shock is unknown. We studied the pathogenesis of septic shock and provide a novel strategy for treating and improving the prognosis of septic shock.

Methods

Gluten-Sensitive Enteropathy (GSE) 131761, GSE119217, GSE26378 datasets were downloaded from the Gene Expression Omnibus (GEO) database. The three datasets included 204 septic shock samples and 48 normal samples. The R packages “affy” and “limma” were employed to identify the differently expressed genes (DEGs) between septic shock and normal samples. Weighted gene co-expression network analysis (WGCNA) was performed to search for modules that play an important role in septic shock. Functional annotation of DEGs and construction and analysis of hub genes were used to explore the pathomechanism of septic shock. The receiver operating characteristic (ROC) curves were obtained using MedCalc software. The drug molecules that could regulate hub genes associated with septic shock were searched for in the CMap database. An animal model of septic shock was constructed to analyze the role of these hub genes.

Results

The merged series contained 321 up-regulated and 255 down-regulated genes. WGCNA showed the brown module had the highest correlation with the status of septic shock. GO and KEGG enrichment analysis results of the brown module genes showed they were mainly enriched in “leukocyte differentiation”, “Ras-proximate-1 (Rap1) signaling pathway”, and “cytokine–cytokine receptor interaction”. Through construction and analysis of a protein–protein interaction (PPI) network, cluster of differentiation 63 (CD63) and complement component 3a receptor 1 (C3AR1) were identified as hub genes of septic shock. The area under curve (AUC) of C3AR1 for the septic shock is 0.772 (P<0.001), and the AUC of CD63 for the septic shock is 0.871 (P<0.001). Small molecule drugs were filtered by the number of instances (n>3) and P-values <0.05, including “monensin”, “verteporfin”, “ikarugamycin”, “tetrahydroalstonine”, “cefamandole”, “etoposide”. In the animal model, the relative expression levels of interleukin-6 (IL-6), Tumor Necrosis Factor-α (TNF-α), and lactic acid were significantly higher in the septic shock group compared with the control group. Results of Real Time Quantitative PCR (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA) analysis for CD63 and C3AR1 showed that their relative expression levels were significantly lower in the septic shock group compared with the control group (P<0.05).

Conclusion

CD63 and C3AR1 are significant hub genes of septic shock and may represent potential molecular targets for future studies of septic shock.

Identification of key immune genes for sepsis-induced ARDS based on bioinformatics analysis

Regarding the extremely high mortality caused by sepsis-induced acute respiratory distress syndrome (ARDS), it is urgent to develop new biomarkers of sepsis-induced ARDS for treatment. Here, 532 differential expression genes (DEGs) related to sepsis and 433 DEGs related to sepsis-induced ARDS were screened in the GSE32707 dataset. Compared with sepsis samples, sepsis ARDS samples showed a higher infiltration of activated memory CD4 T cells and naive B cells, but a relatively lower infiltration of CD8 T cells. The pink and green modules which are significantly associated with sepsis-induced ARDS were then screened through co-expression network analysis. Differentially up-regulated GYPE and aberrantly down-regulated HSPB1, were subsequently found in the pink module of ARDS. CD81 and RPL22, two differentially low-expressed genes peculiar to ARDS, were identified in the green module. The function of CD81 was verified at the cellular level, and it was found that the up-regulation of CD81 in A549 could alleviate the LPS-induced injury of A549 cells. More importantly, the overexpressed CD81 can also increase the content of CD4⁺ CD25⁺ Foxp3⁺ Treg in Jurkat cells, and after the co-culture of overexpressed CD81 Jurkat cells with LPS treatment A549 cells, the LPS-induced lung epithelial cell damage can be improved. Overall, four new plasma biomarker candidates were found in sepsis-induced ARDS, and we verified that CD81 may play critical roles in the biological and immunological processes of sepsis-induced ARDS.

Identification and validation of potential novel biomarkers to predict distant metastasis in differentiated thyroid cancer

Background

Distant metastasis (DM) is not common in differentiated thyroid cancer (DTC). However, it is associated with a significantly poor prognosis. Early detection of high-risk DTC patients is difficult, and the molecular mechanism is still unclear. Therefore, the present study aims to establish a novel predictive model based on clinicopathological parameters and DM-related gene signatures to provide guidelines for clinicians in decision making.

Methods

Weighted gene co-expression network analysis (WGCNA) was performed to discover co-expressed gene modules and hub genes associated with DM. Univariate and multivariate analyses were carried out to identify independent clinicopathological risk factors based on The Cancer Genome Atlas (TCGA) database. An integrated nomogram prediction model was established. Finally, real hub genes were validated using the GSE60542 database and various thyroid cell lines.

Results

The midnightblue module was most significantly positively correlated with DM (R=0.56, P=9e-06) by as per WGCNA. DLX5 (AUC: 0.769), COX6B2 (AUC: 0.764), and LYPD1 (AUC: 0.760) were determined to be the real hub genes that play a crucial role in predicting DM. Meanwhile, univariate and multivariate analyses demonstrated that T-stage (OR, 15.03; 95% CI, 1.75-319.40; and P=0.024), histologic subtype (OR, 0.17; 95% CI, 0.03-0.92; and P=0.042) were the independent predictors of DM. Subsequently, a nomogram model was constructed based on gene signatures and independent clinical risk factors exhibited good performance. Additionally, the mRNA expressions of real hub genes in the GSE60542 dataset were consistent with TCGA.

Conclusions

The present study has provided a reliable model to predict DM in patients with DTC. This model is likely to serve as an individual risk assessment tool in therapeutic decision-making.

C3AR1 mRNA as a Potential Therapeutic Target Associates With Clinical Outcomes and Tumor Microenvironment in Osteosarcoma

Objective: Targeting cancer-specific messenger RNAs (mRNAs) may offer novel insights into therapeutic strategies in osteosarcoma. This study aimed to discover possible osteosarcoma-specific mRNA and probe its biological functions.

Methods: Based on mRNA-seq data from the TARGET database, stromal and immune scores were estimated for each osteosarcoma sample via the ESTIMATE algorithm. Stromal and immune mRNAs were obtained via integration of differentially expressed mRNAs between high and low stromal / immune score groups. Among hub and prognostic mRNAs, C3AR1 mRNA was focused and its prognostic value was assessed. The associations between C3AR1 mRNA and immune cells were analyzed via the CIBERSORT algorithm. Its expression was verified in osteosarcoma tissues and cells by RT-qPCR and western blot. The functions of C3AR1 were investigated by a series of experiments.

Results: Low stromal and immune scores were both indicative of unfavorable outcomes for osteosarcoma patients. Eighty-eight up-regulated and seven down-regulated stromal and immune mRNAs were identified. Among 30 hub mRNAs, low expression of C3AR1 mRNA indicated worse outcomes than its high expression. There was a lower mRNA expression of C3AR1 in metastatic than non-metastatic osteosarcoma. C3AR1 mRNA was closely correlated to various immune cells such as macrophages. C3AR1 was verified to be down-regulated in osteosarcoma tissues and cells. Its overexpression suppressed proliferation, migration and invasion and induced apoptosis in osteosarcoma cells.

Conclusion: C3AR1 mRNA could be a promising therapeutic target for osteosarcoma, linked with prognosis and tumor microenvironment.

MMP-9 Concentration in Peritoneal Fluid Is a Valuable Biomarker Associated with Endotoxemia in Equine Colic

The purpose of the study was to compare the results of sepsis scoring (clinical examination and clinical pathology) to the concentrations of matrix-metalloproteinases (MMPs) -2, -8, and -9; tissue-inhibitor of metalloproteinases (TIMPs) -1 and -2; and inflammatory chemokines interleukin (IL) 1β and tumor-necrosis-factor-alpha (TNF-α) in plasma and peritoneal fluid of equine colic patients. A modified sepsis scoring including general condition, heart and respiratory rate, rectal temperature, mucous membranes, white blood cell count (WBC), and ionized calcium was applied in 47 horses presented with clinical signs of colic. Using this scoring system, horses were classified as negative (n = 32, ≤6/19 points), questionable (n = 9, 7-9/19 points), or positive (n = 6, ≥10/19 points) for sepsis. MMPs, TIMPs, IL-1β, and TNF-α concentrations were evaluated in plasma and peritoneal fluid using species-specific sandwich ELISA kits. In a linear discriminant analysis, all parameters of sepsis scoring apart from calcium separated well between sepsis severity groups (P < 0.05). MMP-9 was the only biomarker of high diagnostic value, while all others remained insignificant. A significant influence of overall sepsis scoring on MMP-9 was found for peritoneal fluid (P = 0.005) with a regression coefficient of 0.092, while no association was found for plasma (P = 0.085). Using a MMP-9 concentration of >113 ng/ml in the peritoneal fluid was found to be the ideal cutoff to identify positive sepsis scoring (≥10/19 points; sensitivity of 83.3% and specificity of 82.9%). In conclusion, MMP-9 was found to be a biomarker of high diagnostic value for sepsis and endotoxemia in equine colic. The evaluation of peritoneal fluid seems preferable in comparison to plasma. As abdominocentesis is commonly performed in the diagnostic work-up of equine colic, a pen-side assay would be useful and easy-to-perform diagnostic support in the decision for therapeutic intervention.