Humoral immune transcriptome signature in myelomeningocele patients.

INTRODUCTION: Myelomeningocele (MMC) results from incomplete closure of the neural tube, and has a complex multifactorial etiology, including an inflammatory microenvironment. OBJECTIVE: We evaluated the contribution of humoral immune response for development of inflammatory milieu. METHODS: Using public repository Gene Expression Omnibus (GEO), we retrieve dataset transcriptome from the amniotic fluid of ten fetuses with myelomeningocele and ten healthy control fetuses to found differential gene expression associated with disturbances and inflammatory signatures in MMC. The identified DEGs were submitted to enrichment, network, and matrix correlation analyses. RESULTS: Our initial analysis revealed 90 DEGs in MMC, mainly associated with signaling pathways of inflammation, including the immune modules, humoral immune response and IFN-type I signatures. Protein-protein analysis (PPI) revealed an association with three protein networks; positive regulation of B cell proliferation constituted the largest network. Matrix correlation analyses showed that MMC alters the co-expression of genes related to inflammatory processes that promote microenvironment inflammation. CONCLUSION: These results revealed an altered humoral immune response in MMC patients, contributing to an inflammatory profile and providing opportunities for identifying potential biomarkers in myelomeningocele disease.

Autophagic reprogramming of bone marrow-derived macrophages.

Macro-autophagy is a highly conserved catabolic process among eukaryotes affecting macrophages. This work studies the genetic regulatory network involving the interplay between autophagy and macrophage polarization (activation). Autophagy-related genes (Atgs) and differentially expressed genes (DEGs) of macrophage polarization (M1-M2) were predicted, and their regulatory networks constructed. Naïve (M0) mouse bone marrow-derived monocytes were differentiated into M1 and M2a. Validation of the targets of Smad1, LC3A and LC3B, Atg16L1, Atg7, IL-6, CD68, Arg-1, and Vamp7 was performed in vitro. Immunophenotyping by flow cytometry revealed three macrophage phenotypes: M0 (IL-6 + /CD68 +), M1 (IL-6 + /CD68 + /Arg-1 +), and M2a (CD68 + /Arg-1). Confocal microscopy revealed increased autophagy in both M1 and M2a and a significant increase in the pre-autophagosomes size and number. Bafilomycin A increased the expression of CD68 and Arg-1 in all cell lineages. In conclusion, our approach predicted the protein targets mediating the interplay between autophagy and macrophage polarization. We suggest that autophagy reprograms macrophage polarization via CD68, arginase 1, Atg16L1-1, and Atg16L1-3. The current findings provide a foundation for the future use of macrophages in immunotherapy of different autoimmune disorders.

New Approach for Targeted Treatment of Mild COVID-19 by Honeysuckle through Network Pharmacology Analysis.

OBJECTIVE: To investigate the potential pharmacological value of extracts from honeysuckle on patients with mild coronavirus disease 2019 (COVID-19) infection. METHODS: The active components and targets of honeysuckle were screened by Traditional Chinese Medicine Database and Analysis Platform (TCMSP). SwissADME and pkCSM databases predict pharmacokinetics of ingredients. The Gene Expression Omnibus (GEO) database collected transcriptome data for mild COVID-19. Data quality control, differentially expressed gene (DEG) identification, enrichment analysis, and correlation analysis were implemented by R toolkit. CIBERSORT evaluated the infiltration of 22 immune cells. RESULTS: The seven active ingredients of honeysuckle had good oral absorption and medicinal properties. Both the active ingredient targets of honeysuckle and differentially expressed genes of mild COVID-19 were significantly enriched in immune signaling pathways. There were five overlapping immunosignature genes, among which RELA and MAP3K7 expressions were statistically significant (P < 0.05). Finally, immune cell infiltration and correlation analysis showed that RELA, MAP3K7, and natural killer (NK) cell are with highly positive correlation and highly negatively correlated with hematopoietic stem cells. CONCLUSION: Our analysis suggested that honeysuckle extract had a safe and effective protective effect against mild COVID-19 by regulating a complex molecular network. The main mechanism was related to the proportion of infiltration between NK cells and hematopoietic stem cells.

Reveals of quercetin's therapeutic effects on oral lichen planus based on network pharmacology approach and experimental validation.

Oral lichen planus (OLP) is a localized autoimmune disease of the oral mucosa, with an incidence of up to 2%. Although corticosteroids are the first-line treatment, they cause several adverse effects. Quercetin, a naturally occurring compound, has fewer side-effects and provides long-term benefits. Besides, it has powerful anti­inflammatory activities. Here, we combined network pharmacology with experimental verification to predict and verify the key targets of quercetin against OLP. First, 66 quercetin-OLP common targets were analyzed from various databases. The protein-protein interaction (PPI) network was constructed. Topology analysis and MCODE cluster analysis of common targets were conducted to identify 12 key targets including TP53, IL-6 and IFN-γ and their connections. Gene functions and key signaling pathways, including reactive oxygen species metabolism, IL-17 pathway and AGE-RAGE pathway, were enriched by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Then, in vitro experiments showed that quercetin interfered with Th1/Th2 balance by acting on IL-6 and IFN-γ to modulate the immune system in treating OLP. Quercetin considerably affected the apoptosis and migration of T lymphocytes in OLP patients. Our study reveals the potential therapeutic targets and signaling pathways of quercetin associated with OLP, and establishes the groundwork for future clinical applications.

Identification of immune features of HIV-infected patients with antiretroviral therapy through bioinformatics analysis.

BACKGROUND: Acquired immunodeficiency syndrome (AIDS) is a disease arising from human immunodeficiency virus (HIV). Antiretroviral therapy (ART) is a main therapeutic regimen for inhibiting HIV proliferation and viability. Identification of differentially expressed genes (DEGs) in HIV-infected patients with and without ART could provide theoretical evidence for deep research into the efficacy of ART and corresponding mechanism. METHODS: In this study, mRNA microarray data (GSE108296) of HIV-infected patients who received and didn't receive ART were downloaded from Gene Expression Omnibus (GEO) database. DEGs were obtained through differential analysis with R package limma. Then, protein-protein interaction (PPI) analysis was performed to identify hub genes and functional modules. Besides, immune-related DEGs were screened, followed by GO annotation and KEGG pathway enrichment analysis. Moreover, various immune cells and immune functions in samples were analyzed by ESTIMATE, ssGSEA and CIBERSORT, based on which the immune function of HIV-infected patients who received and didn't receive ART was evaluated. RESULTS: A total of 109 DEGs were obtained from differential analysis. Among them, 19 immune-related DEGs were identified and subjected to GO and KEGG enrichment analyses. Furthermore, PPI network analysis was undertaken on the 109 DEGs. 10 hub genes and 3 functional modules were further screened. It was shown that these genes and functional modules were correlated with immune functions and relevant signaling pathways. ESTIMATE, ssGSEA and CIBERSORT results displayed that HIV-infected patients with ART presented a relatively high immune level. CONCLUSION: According to bioinformatics analysis, we reasonably posited that HIV-infected patients who received ART had an increased immune level relative to patients who didn't receive ART.

A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.

In recent years, the increase in awareness of antimicrobial resistance together with the societal demand of healthier meat products have driven attention to health-related traits in livestock production. Previous studies have reported medium to high heritabilities for these traits and described genomic regions associated with them. Despite its genetic component, health- and immunity-related traits are complex and its study by association analysis with genomic markers may be missing some information. To analyse multiple phenotypes and gene-by-gene interactions, systems biology approaches, such as the association weight matrix (AWM), allows combining genome wide association study results with network inference algorithms. The present study aimed to identify gene networks, key regulators and candidate genes associated to immunocompetence in pigs by integrating multiple health-related traits, enriched for innate immune phenotypes, using the AWM approach. The co-association network analysis unveiled a network comprised of 3,636 nodes (genes) and 451,407 edges (interactions), including a total of 246 regulators. From these, five genes (ARNT2, BRMS1L, MED12L, SUPT3H and TRIM25) were selected as key regulators as they were associated with the maximum number of genes with the minimum overlapping (1,827 genes in total). The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. Furthermore, we identified genes co-associated with the key regulators previously reported as candidate genes (e.g., ANGPT1, CD4, CD36, DOCK1, PDE4B, PRKCE, PTPRC and SH2B3) for immunity traits in humans and pigs, but also new candidate ones (e.g., ACSL3, CXADR, HBB, MMP12, PTPN6, WLS) that were not previously described. The co-association analysis revealed new regulators associated with health-related traits in pigs. This approach also identified gene-by-gene interactions and candidate genes involved in pathways related to cell fate and metabolic and immune functions. Our results shed new light in the regulatory mechanisms involved in pig immunity and reinforce the use of the pig as biomedical model.

Analysis of immune-related key genes in Alzheimer's disease.

This research revealed that 15 modules were obtained through weighted gene co-expression network analysis, among which the magenta and blue modules were significantly associated with Alzheimer's Disease (AD). There were 121 genes in the magenta module and 1022 genes in the blue module. Through differently expressed genes analysis, significant differences were shown in 134 genes (88 were up-regulated and 46 were down-regulated). 34 immune-key genes were obtained after three types of genes were crossed. Functional enrichment analysis showed that genes were mainly enriched in cytokine receptor activity and immune receptor activity. Through protein-protein interaction (PPI) network analysis, 10 hub genes were obtained: SERPINE1, ZBTB16, CD44, BCL6, HMOX1, SLC11A1, CEACAM8, ITGA5, SOCS3, and IL4R. Through immune-infiltration analysis, significant differences were demonstrated in four immune cells: CD8 + T cells, resting NK cells, M2 macrophages, and activated dendritic cells, and a significant positive correlation was shown between CD8 + T cells and macrophages M2, or between the other two cells. CEACAM8 was positively correlated with CD8 + T cells and macrophages M2, and negatively correlated with the other two cells while the remaining nine genes showed the opposite. Receiver operating characteristic (ROC) curve analysis demonstrated that both the differential immune cells and 10 hub genes had good diagnostic values. In GSE122063, the hub genes were verified and BCL6, CD44, HMOX1, IL4R, ITGA5, and SOCS3 were up-regulated. Meanwhile, hub genes was up-regulated in the brain tissues of AD rats. This study is of great significance for the diagnosis and therapy of AD.

Identification of immune-related genes and susceptible population of pulmonary tuberculosis by constructing TF-miRNA-mRNA regulatory network.

We aimed to explore the potential biomarkers and susceptible population for early diagnosis and treatment of tuberculosis (TB). Ten hub differentially expressed TB-related genes (DETRGs) from GSE83456 dataset were screened with the "limma" package and the GeneCards database. Unsupervised clustering was utilized to identify susceptible population among TB patients based on 10 hub DETRGs. TRANSFAC, MirTarbase, miRanda and TargetScan was used to predict microRNAs and transcription factors (TFs) and construct TF-miRNA-mRNA regulatory network. The results showed that a total of 266 DEGs were identified. Functional analysis mainly enriched in interferon pathway, cytokine and receptor interaction and host defense response to virus, while the four-module genes screened were closely related to interferon-γ signal transduction pathway as well. Based on 10 DETRGs, TB patients were divided into two clusters with significant differences in neutrophil function and 16 hub miRNAs and 10 hub TFs were predicted. Finally, NFATc1- (miR145) - STAT1 regulatory pathway was identified as the critical regulatory pathway, which mediates cytokine receptor binding, interleukin-1 receptor binding and TNF signaling pathway. Hence, we concluded that immunoheterogeneity exists among TB patients and NFATC1-(miR145)-STAT1 regulatory pathway might be associated with tuberculosis infection, which may be valuable targets for prevention and treatment of tuberculosis.

Upregulation of a nuclear factor-kappa B-interacting immune gene network in mice cochleae with age-related hearing loss.

Epidemiological data suggest that inflammation and innate immunity play significant roles in the pathogenesis of age-related hearing loss (ARHL) in humans. In this mouse study, real-time RT-PCR array targeting 84 immune-related genes revealed that the expressions of 40 genes (47.6%) were differentially regulated with greater than a twofold change in 12-month-old cochleae with ARHL relative to young control mice, 33 (39.3%) of which were upregulated. These differentially regulated genes (DEGs) were involved in functional pathways for cytokine-cytokine receptor interaction, chemokine signaling, TNF signaling, and Toll-like receptor signaling. An NF-κB subunit, Nfkb1, was upregulated in aged cochleae, and bioinformatic analyses predicted that NF-κB would interact with the genomic regulatory regions of eight upregulated DEGs, including Tnf and Ptgs2. In aging cochleae, major proinflammatory molecules, IL1B and IL18rap, were upregulated by 6 months of age and thereafter. Remarkable upregulations of seven immune-related genes (Casp1, IL18r1, IL1B, Card9, Clec4e, Ifit1, and Tlr9) occurred at an advanced stage (between 9 and 12 months of age) of ARHL. Immunohistochemistry analysis of cochlear sections from the 12-month-old mice indicated that IL-18r1 and IL-1B were localized to the spiral ligament, spiral limbus, and organ of Corti. The two NF-κB-interacting inflammatory molecules, TNFα and PTGS2, immunolocalized ubiquitously in cochlear structures, including the lateral wall (the stria vascularis and spiral ligament), in the histological sections of aged cochleae. IBA1-positive macrophages were observed in the stria vascularis and spiral ligament in aged mice. Therefore, inflammatory and immune reactions are modulated in aged cochlear tissues with ARHL.

Identification and Validation of TREM2 in Intracranial Aneurysms.

Background: Intracranial aneurysm (IA) is a cerebrovascular disease that seriously endangers human heath and life. However, the pathogenesis of IA has not been clarified. Objective: In this study, we explored the role of the triggering receptor expressed on myeloid cells-2 (TREM2) gene to explore a novel mechanism underlying IA. Methods: First, we verified the role of the candidate gene, TREM2 in a modified mouse model of IA. Second, we verified elevated expression of TREM2 using the Gene Expression Omnibus (GEO) database (GSE54083 and GSE75436) and developed protein interaction (PPI) network analysis using the top one hundred DEGs from GSE75436 dataset. Finally, we predicted a likely mechanism by which TREM2 is involved in the pathology of IA using single-gene Gene Set Enrichment Analysis (GSEA). Results: The expression of TREM2 and inflammatory factors was significantly increased in the modified mouse IA model, and showed a positive correlation. Elevated expression of TREM2 was also found in IA patients tissues from the GSE54083 and GSE75436 data sets. PPI network analyses suggested that the DEGs were involved in a variety of inflammatory processes. The GSEA results suggest that TREM2 may participate in IA progression by regulating macrophage function. Conclusion: TREM2 is highly expressed in both human and mouse IA tissues, and may participate in IA progression by regulating macrophage function and inflammatory factor expression. The molecular mechanism of TREM2 involvement in the IA process can be further studied using our modified mouse IA model.

Analysis of Bulk RNA Sequencing Data Reveals Novel Transcription Factors Associated With Immune Infiltration Among Multiple Cancers.

Tumor-infiltrating immune cells shape the tumor microenvironment and are closely related to clinical outcomes. Several transcription factors (TFs) have also been reported to regulate the antitumor activity and immune cell infiltration. This study aimed to quantify the populations of different immune cells infiltrated in tumor samples based on the bulk RNA sequencing data obtained from 50 cancer patients using the CIBERSORT and the EPIC algorithm. Weighted gene coexpression network analysis (WGCNA) identified eigengene modules strongly associated with tumorigenesis and the activation of CD4+ memory T cells, dendritic cells, and macrophages. TF genes FOXM1, MYBL2, TAL1, and ERG are central in the subnetworks of the eigengene modules associated with immune-related genes. The analysis of The Cancer Genome Atlas (TCGA) cancer data confirmed these findings and further showed that the expression of these potential TF genes regulating immune infiltration, and the immune-related genes that they regulated, was associated with the survival of patients within multiple cancers. Exome-seq was performed on 24 paired samples that also had RNA-seq data. The expression quantitative trait loci (eQTL) analysis showed that mutations were significantly more frequent in the regions flanking the TF genes compared with those of non-TF genes, suggesting a driver role of these TF genes regulating immune infiltration. Taken together, this study presented a practical method for identifying genes that regulate immune infiltration. These genes could be potential biomarkers for cancer prognosis and possible therapeutic targets.

An immune response characterizes early Alzheimer's disease pathology and subjective cognitive impairment in hydrocephalus biopsies.

Early Alzheimer's disease (AD) pathology can be found in cortical biopsies taken during shunt placement for Normal Pressure Hydrocephalus. This represents an opportunity to study early AD pathology in living patients. Here we report RNA-seq data on 106 cortical biopsies from this patient population. A restricted set of genes correlate with AD pathology in these biopsies, and co-expression network analysis demonstrates an evolution from microglial homeostasis to a disease-associated microglial phenotype in conjunction with increasing AD pathologic burden, along with a subset of additional astrocytic and neuronal genes that accompany these changes. Further analysis demonstrates that these correlations are driven by patients that report mild cognitive symptoms, despite similar levels of biopsy ß-amyloid and tau pathology in comparison to patients who report no cognitive symptoms. Taken together, these findings highlight a restricted set of microglial and non-microglial genes that correlate with early AD pathology in the setting of subjective cognitive decline.

Identification of a novel 10 immune-related genes signature as a prognostic biomarker panel for gastric cancer.

BACKGROUND: Emerging evidence indicates that immune infiltrating cells in tumor microenvironment (TME) correlates with the development and progression of gastric cancer (GC). This study aimed to systematically investigate the immune-related genes (IRGs) to develop a prognostic signature to predict the overall survival (OS) in GC. METHOD: The gene expression profiles of training dataset (GSE62254), validation dataset I (GSE15459), and validation dataset II (GSE84437) were retrieved from GEO and TCGA databases. In the present study, we developed a 10 IRGs prognostic signature with the combination of weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator method (LASSO) COX model. RESULTS: In the training dataset, the accuracy of the signature was 0.681, 0.741, and 0.72 in predicting 1, 3, and 5-year OS separately. The signature also had good performance in validation dataset Ⅰ with the accuracy of 0.57, 0.619, and 0.694, and in validation dataset Ⅱ with the accuracy of 0.559, 0.624, and 0.585. Then, we constructed a nomogram using the signature and clinical information which had strong discrimination ability with the c-index of 0.756. In the immune infiltration analysis, the signature was correlated with multiple immune infiltrating cells such as CD8 T cells, CD4 memory T cells, NK cells, and macrophages. Furthermore, several significant pathways were enriched in gene set enrichment analysis (GSEA) analysis, including TGF-beta signaling pathway and Wnt signaling pathway. CONCLUSION: The signature of 10 IRGs we identified can effectively predict the prognosis of GC and provides new insight into discovering candidate prognostic biomarkers of GC.

Analysis of Immune Associated Co-Expression Networks Reveals Immune-Related Long Non-Coding RNAs during MI in the Presence and Absence of HDC.

Myocardial infarction (MI) is one of the most common cardiovascular diseases. Although previous studies have shown that histidine decarboxylase (HDC), a histamine-synthesizing enzyme, is involved in the stress response and heart remodeling after MI, the mechanism underlying it remains unclear. In this study, using Hdc-deficient mice (Hdc-/- mice), we established an acute myocardial infarction mouse model to explore the potential roles of Hdc/histamine in cardiac immune responses. Comprehensive analysis was performed on the transcriptomes of infarcted hearts. Differentially expressed gene (DEG) analysis identified 2126 DEGs in Hdc-deficient groups and 1013 in histamine-treated groups. Immune related pathways were enriched in Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Then we used the ssGSEA algorithm to evaluate 22 kinds of infiltrated immunocytes, which indicated that myeloid cells and T memory/follicular helper cells were tightly regulated by Hdc/histamine post MI. The relationships of lncRNAs and the Gene Ontology (GO) functions of protein-coding RNAs and immunocytes were dissected in networks to unveil immune-associated lncRNAs and their roles in immune modulation after MI. Finally, we screened out and verified four lncRNAs, which were closely implicated in tuning the immune responses after MI, including ENSMUST00000191157, ENSMUST00000180693 (PTPRE-AS1), and ENSMUST-00000182785. Our study highlighted the HDC-regulated myeloid cells as a driving force contributing to the government of transmission from innate immunocytes to adaptive immunocytes in the progression of the injury response after MI. We identified the potential role of the Hdc/histamine-lncRNAs network in regulating cardiac immune responses, which may provide novel promising therapeutic targets for further promoting the treatment of ischemic heart disease.

An Immune-Related Prognostic Classifier Is Associated with Diffuse Large B Cell Lymphoma Microenvironment.

BACKGROUND: Diffuse large B cell lymphoma (DLBCL) is a life-threatening malignant tumor characterized by heterogeneous clinical, phenotypic, and molecular manifestations. Given the association between immunity and tumors, identifying a suitable immune biomarker could improve DLBCL diagnosis. METHODS: We systematically searched for DLBCL gene expression microarray datasets from the GEO database. Immune-related genes (IRGs) were obtained from the ImmPort database, and 318 transcription factor (TF) targets in cancer were retrieved from the Cistrome Cancer database. An immune-related classifier for DLBCL prognosis was constructed using Cox regression and LASSO analysis. To assess differences in overall survival between the low- and high-risk groups, we analyzed the tumor microenvironment (TME) and immune infiltration in DLBCL using the ESTIMATE and CIBERSORT algorithms. WGCNA was applied to study the molecular mechanisms explaining the clinical significance of our immune-related classifier and TFs. RESULTS: Eighteen IRGs were selected to construct the classifier. The multi-IRG classifier showed powerful predictive ability. Patients with a high-risk score had poor survival. Based on the AUC for three- and five-year survival, the classifier exhibited better predictive power than clinical data. Discrepancies in overall survival between the low- and high-risk score groups might be explained by differences in immune infiltration, TME, and transcriptional regulation. CONCLUSIONS: Our study describes a novel prognostic IRG classifier with strong predictive power in DLBCL. Our findings provide valuable guidance for further analysis of DLBCL pathogenesis and clinical treatment.

Crosstalk between RNA-Binding Proteins and Immune Microenvironment Revealed Two RBP Regulatory Patterns with Distinct Immunophenotypes in Periodontitis.

Periodontitis is an inflammatory disease whose pathogenesis is closely related with immunology. RNA-binding proteins (RBPs) were found to play crucial roles in immunity. Therefore, we aimed to investigate the potential impact of RBPs in the immune microenvironment in periodontitis. The differential expressions of RBPs in periodontitis and healthy samples were determined and were used to construct an RBP-based classifier for periodontitis using logistic regression. The correlations between RBPs and immune characteristics were investigated by the Spearman correlation. Unsupervised clustering was conducted to identify the RBP regulatory patterns. RBP-related genes were identified by WGCNA, while biological distinctions were revealed by GSVA and GO. 24 dysregulated RBPs were identified, from which a 12-RBP classifier was established to distinguish periodontitis with AUC of 0.942. Close protein-protein interactions and expression correlations were observed especially between SPATS2 and ISG20. ISG20 and ESRP1 were found to be highly correlated with immunocyte infiltration, immune signaling activation, and HLA expressions in periodontitis. Two distinct RBP regulatory patterns were identified with different immune and other biological characteristics in periodontitis. Our findings indicate a significant impact of RBPs in shaping the immune microenvironment in periodontitis, which might bring new insights into the understanding of immune mechanisms in the pathogenesis of periodontitis.

Gene Regulatory Network of Human GM-CSF-Secreting T Helper Cells.

GM-CSF produced by autoreactive CD4-positive T helper cells is involved in the pathogenesis of autoimmune diseases, such as multiple sclerosis. However, the molecular regulators that establish and maintain the features of GM-CSF-positive CD4 T cells are unknown. In order to identify these regulators, we isolated human GM-CSF-producing CD4 T cells from human peripheral blood by using a cytokine capture assay. We compared these cells to the corresponding GM-CSF-negative fraction, and furthermore, we studied naïve CD4 T cells, memory CD4 T cells, and bulk CD4 T cells from the same individuals as additional control cell populations. As a result, we provide a rich resource of integrated chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) data from these primary human CD4 T cell subsets and we show that the identified signatures are associated with human autoimmune diseases, especially multiple sclerosis. By combining information about mRNA expression, DNA accessibility, and predicted transcription factor binding, we reconstructed directed gene regulatory networks connecting transcription factors to their targets, which comprise putative key regulators of human GM-CSF-positive CD4 T cells as well as memory CD4 T cells. Our results suggest potential therapeutic targets to be investigated in the future in human autoimmune disease.

Altered Genes and Biological Functions in Response to Severe Burns.

Severe burns are acute wounds caused by local heat exposure, resulting in life-threatening systemic effects and poor survival. However, the specific molecular mechanisms remain unclear. First, we downloaded gene expression data related to severe burns from the GEO database (GSE19743, GSE37069, and GSE77791). Then, a gene expression analysis was performed to identify differentially expressed genes (DEGs) and construct protein-protein interaction (PPI) network. The molecular mechanism was identified by enrichment analysis and Gene Set Enrichment Analysis. In addition, STEM software was used to screen for genes persistently expressed during response to severe burns, and receiver operating characteristic (ROC) curve was used to identify key DEGs. A total of 2631 upregulated and 3451 downregulated DEGs were identified. PPI network analysis clustered these DEGs into 13 modules. Importantly, module genes mostly related with immune responses and metabolism. In addition, we identified genes persistently altered during the response to severe burns corresponding to survival and death status. Among the genes with high area under the ROC curve in the PPI network gene, CCL5 and LCK were identified as key DEGs, which may affect the prognosis of burn patients. Gene set variation analysis showed that the immune response was inhibited and several types of immune cells were decreased, while the metabolic response was enhanced. The results showed that persistent gene expression changes occur in response to severe burns, which may underlie chronic alterations in physiological pathways. Identifying the key altered genes may reveal potential therapeutic targets for mitigating the effects of severe burns.

PD-1 Coexpression Gene Analysis and the Regulatory Network in Endometrial Cancer Based on Bioinformatics Analysis.

Gynecological malignancies are tumors of the female reproductive system, mainly cervical cancer, endometrial cancer, and ovarian cancer. Endometrial cancer (EC) is the most common gynecological malignant tumor in developed countries. The aim of this study was to construct a network of programmed cell death protein 1 (PD-1) coexpressed genes through bioinformatics analysis and screen the potential biomarkers of PD-1 in endometrial cancer. In addition, genes and pathways involved in PD-1 and modulating tumor immune status were identified. We select the EC transcriptomic dataset in TCGA to retrieve gene sets on the cBioPortal platform, and the PD-1 coexpressed genes were obtained on the platform. GO and KEGG enrichment analysis of coexpressed genes was performed using the DAVID database. The target protein-protein interaction (PPI) network was constructed using Cytoscape 3.7.1 software, and the hub genes were then screened. A total of 976 coexpression genes were obtained. The enrichment analysis showed that PD-1 coexpressed genes were significantly enriched in overall components of the cell structure, the interaction of cytokines with cytokine receptors, chemokine signaling pathways, and cell adhesion molecules (CAMs). Ten hub genes were obtained by node degree analysis. CD3E gene is involved in the prognosis and immune process of EC, and the expression level is related to PD-1 (Pearson correlation coefficient is 0.82, P < 0.01). Patients with low CD3E gene expression in EC have a poor prognosis. The coexpression hub genes of PD-1 are related to immunity, in which CD3E is a prognostic marker that is involved in the PD-1/PD-L1-induced tumor immune escape. This study provides a new area to study the mechanism of PD-1/PD-L1 in EC and the precise treatment with targeted drugs.

Identification of prognostic markers for hepatocellular carcinoma based on the epithelial-mesenchymal transition-related gene BIRC5.

BACKGROUND: The baculoviral IAP repeat containing 5 (BIRC5) related to epithelial-mesenchymal transition (EMT) plays a crucial role in the pathogenesis of hepatocellular carcinoma (HCC). However, it remains unclear whether BIRC5-related genes can be used as prognostic markers of HCC. METHODS: Kaplan-Meier (K-M) survival curve was used to assess the Overall Survival (OS) of high- and low-expression group divided by the median of BIRC5 expression. The differentially expressed genes (DEGs) between the two groups were screened using the limma package, and performed the functional enrichment analysis by the clusterProfiler package. WGCNA was used to analyze the relationship of the module and the clinical traits. The risk signature was constructed by univariate and multivariate Cox regression analyses and the enrichment analysis of genes in the risk signature was performed by the Intelligent pathway analysis (IPA). The immunophenoscore (IPS) and the tumor immune dysfunction and exclusion (TIDE) were used to estimate the clinical significance of the risk groups. RESULTS: BIRC5 was high-expressed in HCC samples and associated with a poor prognosis (p-value < 0.0001). WGCNA screened 180 module genes which were overlapped with the 241 DEGs, ultimately getting 33 candidate genes. After the Cox regression analyses, CENPA, CDCA8, EZH2, KIF20A, KPNA2, CCNB1, KIF18B and MCM4 were preserved and used to construct risk signature, followed by calculating the risk score. The patients in high-risk groups stratified by median of the risk score were associated with a poor prognosis. The risk score had high accuracy [the area under the curve (AUC) > 0.72] and was closely associated with clinicopathological characteristics of HCC patients. IPA suggested that the 8 genes were enriched in Cancer and Immunological disease related pathways. IPS and TIDE score indicated that the genes in low-risk group could cause an immune response, and patients in the low-risk group may be more sensitive to the immune checkpoint blockade (ICB) therapy. CONCLUSION: The risk score constructed by the 8 genes could not only predict the clinical outcome but also distinguish the cohort of ICB therapy in HCC, which exerted a vital value in treatment and prognosis of HCC.