Transcriptomics explores potential mechanisms for the development of Primary Sjogren's syndrome to diffuse large B-cell lymphoma in B cells.

PURPOSE: Primary Sjogren's syndrome (pSS) is a prevalent autoimmune disease. The immune dysregulation it causes often leads to the development of diffuse large B-cell lymphoma (DLBCL) in clinical practice. However, how it contributes to these two disorders at the molecular level is not yet known. This study explored the potential molecular mechanisms associated with the differences between DLBCL and pSS. PATIENTS AND METHODS: Gene expression matrices from discovery cohort 1, discovery cohort 2, and the validation cohort were downloaded from the GEO and TCGA databases. Weighted gene coexpression network analysis (WGCNA) was performed to identify the coexpression modules of DLBCL and pSS in discovery cohort 1 and obtain shared genes. GO and KEGG enrichment analyses and PPI network analysis were performed on the shared genes. Immune-related genes (IRGs) were intersected with shared genes to obtain common genes. Afterward, common genes were identified via machine learning methods. The immune infiltration analysis, miRNA-TF-hub gene regulatory chart, gene interactions of the hub genes, and gene‒drug target analysis were performed. Finally, STAT1 was identified as a possible essential gene by the above analysis, and immune infiltration and GSEA pathway analyses were performed in the high- and low-expression groups in discovery cohort 2. The diagnostic efficacy of the hub genes was assessed in the validation cohort, and clinical samples were collected for validation. RESULTS: By WGCNA, one modular gene in each group was considered highly associated with the disease, and we obtained 28 shared genes. Enrichment analysis revealed shared genes involved in the viral response and regulation. We obtained four hub genes (ISG20, STAT1, TLR7, and RSAD2) via the algorithm. Hub genes and similar genes are primarily involved in regulating type I IFNs. The construction of a miRNA-TF-hub gene regulatory chart revealed that hsa-mir-155-5p, hsa-mir-146b-5p, hsa-mir-21-3p, and hsa-mir-126-3p play essential roles in both diseases. Hub genes were differentially expressed in B-cell memory according to immune infiltration analysis. Hub genes had a strong diagnostic effect on both diseases. STAT1 plays an essential role in immune cells in both diseases. CONCLUSION: We identified hub susceptibility genes for DLBCL and pSS and identified hub genes and potential therapeutic targets that may act as biomarkers.

Comparison of immune-related gene signatures and immune infiltration features in early- and late-onset preeclampsia.

BACKGROUND: Preeclampsia, a severe pregnancy syndrome, is widely accepted divided into early- and late-onset preeclampsia (EOPE and LOPE) based on the onset time of preeclampsia, with distinct pathophysiological origins. However, the molecular mechanism especially immune-related mechanisms for EOPE and LOPE is currently obscure. In the present study, we focused on placental immune alterations between EOPE and LOPE and search for immune-related biomarkers that could potentially serve as potential therapeutic targets through bioinformatic analysis. METHODS: The gene expression profiling data was obtained from the Gene Expression Omnibus database. ESTIMATE algorithm and Gene Set Enrichment Analysis were employed to evaluate the immune status. The intersection of differentially expressed genes in GSE74341 series and immune-related genes set screened differentially expressed immune-related genes. Protein-protein interaction network and random forest were used to identify hub genes with a validation by a quantitative real-time PCR. Kyoto Encyclopedia of Genes and Genomes pathways, Gene Ontology and gene set variation analysis were utilized to conduct biological function and pathway enrichment analyses. Single-sample gene set enrichment analysis and CIBERSORTx tools were employed to calculate the immune cell infiltration score. Correlation analyses were evaluated by Pearson correlation analysis. Hub genes-miRNA network was performed by the NetworkAnalyst online tool. RESULTS: Immune score and stromal score were all lower in EOPE samples. The immune system-related gene set was significantly downregulated in EOPE compared to LOPE samples. Four hub differentially expressed immune-related genes (IL15, GZMB, IL1B and CXCL12) were identified based on a protein-protein interaction network and random forest. Quantitative real-time polymerase chain reaction validated the lower expression levels of four hub genes in EOPE compared to LOPE samples. Immune cell infiltration analysis found that innate and adaptive immune cells were apparent lacking in EOPE samples compared to LOPE samples. Cytokine-cytokine receptor, para-inflammation, major histocompatibility complex class I and T cell co-stimulation pathways were significantly deficient and highly correlated with hub genes. We constructed a hub genes-miRNA regulatory network, revealing the correlation between hub genes and hsa-miR-374a-5p, hsa-miR-203a-3p, hsa-miR-128-3p, hsa-miR-155-3p, hsa-miR-129-2-3p and hsa-miR-7-5p. CONCLUSIONS: The innate and adaptive immune systems were severely impaired in placentas of EOPE. Four immune-related genes (IL15, GZMB, IL1B and CXCL12) were closely correlated with immune-related pathogenesis of EOPE. The result of our study may provide a new basis for discriminating between EOPE and LOPE and acknowledging the role of the immune landscape in the eventual interference and tailored treatment of EOPE.

Developing neural network diagnostic models and potential drugs based on novel identified immune-related biomarkers for celiac disease.

BACKGROUND: As one of the most common intestinal inflammatory diseases, celiac disease (CD) is typically characterized by an autoimmune disorder resulting from ingesting gluten proteins. Although the incidence and prevalence of CD have increased over time, the diagnostic methods and treatment options are still limited. Therefore, it is urgent to investigate the potential biomarkers and targeted drugs for CD. METHODS: Gene expression data was downloaded from GEO datasets. Differential gene expression analysis was performed to identify the dysregulated immune-related genes. Multiple machine algorithms, including randomForest, SVM-RFE, and LASSO, were used to select the hub immune-related genes (HIGs). The immune-related genes score (IG score) and artificial neural network (ANN) were constructed based on HIGs. Potential drugs targeting HIGs were identified by using the Enrichr platform and molecular docking method. RESULTS: We identified the dysregulated immune-related genes at a genome-wide level and demonstrated their roles in CD-related immune pathways. The hub genes (MR1, CCL25, and TNFSF13B) were further screened by integrating several machine algorithms. Meanwhile, the CD patients were divided into distinct subtypes with either high- or low-immunoactivity using single-sample gene set enrichment analysis (ssGSEA) and consensus clustering. By constructing IG score based on HIGs, we found that patients with high IG score were mainly attributed to high-immunoactivity subgroups, which suggested a strong link between HIGs and immunoactivity of CD patients. In addition, the novel constructed ANN model showed the sound diagnostic ability of HIGs. Mechanistically, we validated that the HIGs play pivotal roles in regulating CD's immune and inflammatory state. Through targeting the HIGs, we also found potential drugs for anti-CD treatment by using the Enrichr platform and molecular docking method. CONCLUSIONS: This study unveils the HIGs and elucidates the networks regulated by these genes in the context of CD. It underscores the pivotal significance of HIGs in accurately predicting the presence or absence of CD in patients. Consequently, this research offers promising prospects for the development of diagnostic biomarkers and therapeutic targets for CD.

Comparative transcriptome analysis of hepatopancreas reveals the potential mechanism of shrimp resistant to Vibrio parahaemolyticus infection.

Vibrio parahaemolyticus carrying a pathogenic plasmid (VPAHPND) is one of the main causative agents of acute hepatopancreatic necrosis disease (AHPND) in shrimp aquaculture. Knowledge about the mechanism of shrimp resistant to VPAHPND is very helpful for developing efficient strategy for breeding AHPND resistant shrimp. In order to learn the mechanism of shrimp resistant to AHPND, comparative transcriptome was applied to analyze the different expressions of genes in the hepatopancreas of shrimp from different families with different resistance to VPAHPND. Through comparative analysis on the hepatopancreas of shrimp from VPAHPND resistant family and susceptible family, we found that differentially expressed genes (DEGs) were mainly involved in immune and metabolic processes. Most of the immune-related genes among DEGs were highly expressed in the hepatopancreas of shrimp from resistant family, involved in recognition of pathogen-associated molecular patterns, phagocytosis and elimination of pathogens, maintenance of reactive oxygen species homeostasis and other immune processes etc. However, most metabolic-related genes were highly expressed in the hepatopancreas of shrimp from susceptible family, involved in metabolism of lipid, vitamin, cofactors, glucose, carbohydrate and serine. Interestingly, when we analyzed the expression of above DEGs in the shrimp after VPAHPND infection, we found that the most of identified immune-related genes remained at high expression levels in the hepatopancreas of shrimp from the VPAHPND resistant family, and most of the identified metabolic-related genes were still at high expression levels in the hepatopancreas of shrimp from the VPAHPND susceptible family. The data suggested that the differential expression of these immune-related and metabolic-related genes in hepatopancreas might contribute to the resistance variations of shrimp to VPAHPND. These results provided valuable information for understanding the resistant mechanism of shrimp to VPAHPND.

MicroRNA-30e-3p regulates the inflammatory response by targeting the gimap8 gene in Ctenopharyngodon idella kidney (CIK) cells.

Recent studies have increasingly linked miRNAs with the modulation of inflammatory responses and immunosuppressive activities. This investigation reveals that mir-30e-3p selectively binds to and modulates gimap8, as demonstrated by luciferase reporter assays and qPCR analyses. Upon LPS stimulation of CIK cells, mir-30e-3p expression was notably elevated, inversely correlating with a decrease in gimap8 mRNA levels. Overexpression of mir-30e-3p attenuated the mRNA levels of pro-inflammatory cytokines beyond the effect of LPS alone, suggesting a regulatory role of mir-30e-3p in inflammation mediated by the gimap8 gene. These insights contribute to our understanding of the complex mechanisms governing inflammatory and immune responses.

Effects of adding Bacillus subtilis natto NTU-18 in paste feed on growth, intestinal morphology, gastrointestinal microbiota diversity, immunity, and disease resistance of Anguilla japonica glass eels.

Japanese eel, Anguilla japonica, holds significant importance in Taiwanese aquaculture. With the intensification of eel farming, the impact of Edwardsiella tarda has become increasingly severe. Consequently, the abusive use of antibiotics has risen. Bacillus subtilis natto NTU-18, a strain of Bacillus with a high survival rate in feed processing, plays a crucial role in promoting intestinal health through competitive rejection, enhancing immune responses against bacterial pathogens, and improving intestinal health by modulating gastrointestinal microbiota to produce beneficial metabolites of mice and grass carp, Ctenopharyngodon idella. This study investigated the effects of different proportions (control, 0.25 %, 0.5 %, 1 %, and 2 %) of B. subtilis natto NTU-18 added to paste feed on the growth performance, intestinal morphology, and microbiota, expression of immune-related genes, and resistance to E. tarda in Japanese glass eel. The results indicated that the growth performance of all groups with B. subtilis natto NTU-18 added was significantly higher than that of the control group and did not impact the villi morphology. The expression of immune-related genes in the kidney, specifically HSP70 and SOD, was significantly higher from 0.5 % and above than the control; however, no significant differences were observed in CAT, POD, and HSP90. In the liver, significant differences were found in HSP70 and IgM above 0.25 % compared to the control group, with no significant differences in SOD, CAT, POD, and HSP90 among all groups. Additionally, intestinal microbiota analysis revealed that the 2 % additional group had significantly lower diversity than other groups, with Cetobacterium as the dominant species. The challenge test observed that the survival rates of the 0.5 % and 1 % groups were significantly higher. This research suggests that adding 0.5 % and 1 % of B. subtilis natto NTU-18 to the diet is beneficial for Japanese glass eel's immunity, growth performance, and disease resistance.

Molecular structure and functional responses of IgM, IgT and IgD to Flavobacterium covae and Streptococcus iniae infection in Asian seabass (Lates calcarifer Bloch, 1790).

The Asian seabass (Lates calcarifer) faces significant disease threats, which are exacerbated by intensive farming practices and environmental changes. Therefore, understanding its immune system is crucial. The current study presents a comprehensive analysis of immune-related genes in Asian seabass peripheral blood leukocytes (PBLs) using Iso-seq technology, identifying 16 key pathways associated with 7,857 immune-related genes, comprising 634 unique immune-related genes. The research marks the first comprehensive report on the entire immunoglobulin repertoire in Asian seabass, revealing specific characteristics of immunoglobulin heavy chain constant region transcripts, including IgM (Cµ, ighm), IgT (Cτ, ight), and IgD (Cδ, ighd). The study confirms the presence of membrane-bound form, ighmmb, ightmb, ighdmb of IgM, IgT and IgD and secreted form, ighmsc and ightsc of IgM and IgT, respectively, with similar structural patterns and conserved features in amino acids across immunoglobulin molecules, including cysteine residues crucial for structural integrity observed in other teleost species. In response to bacterial infections by Flavobacterium covae (formerly F. columnare genomovar II) and Streptococcus iniae, both secreted and membrane-bound forms of IgM (ighmmb and ighmsc) and IgT (ightmb and ightsc) show significant expression, indicating their roles in systemic and mucosal immunity. The expression of membrane-bound form IgD gene, ighdmb, predominantly exhibits targeted upregulation in PBLs, suggesting a regulatory role in B cell-mediated immunity. The findings underscore the dynamic and tissue-specific expression of immunoglobulin repertoires, ighmmb, ighmsc, ightmb, ightsc and ighdmb in Asian seabass, indicating a sophisticated immune response to bacterial pathogens. These findings have practical implications for fish aquaculture, and disease control strategies, serving as a valuable resource for advancing research in Asian seabass immunology.

Isolation and the pathogenicity characterization of Decapod iridescent virus 1 (DIV1) from diseased Macrobrachium nipponense and its activation on host immune response.

The high morbidity and mortality of Macrobrachium nipponense occurred in several farms in China, with cardinal symptoms of slow swimming, loss of appetite, empty of intestine, reddening of the hepatopancreas and gills. The pathogen has been confirmed as Decapod Iridescent Virus 1 (DIV1), namely DIV1-mn, by molecular epidemiology, histopathological examination, TEM observation, challenge experiment, and viral load detection. Histopathological analysis showed severe damage in hepatopancreas and gills of diseased prawns, exhibited few eosinophilic inclusions and pyknosis, and TEM of diseased prawns revealed that icosahedral virus particles existed in hepatopancreas and gill, which confirmed the disease of the farmed prawns caused by the DIV1 infection. Besides, challenge tests showed LD50 of DIV1 to M. nipponense was determined to be 2.14 × 104 copies/mL, and real-time PCR revealed that M. nipponense had a very high DIV1 load in the hemocytes, gills and hepatopancreas after infection. Furthermore, qRT-PCR was undertaken to investigated the expression of six immune-related genes in DIV1-infected M. nipponense after different time points, and the results revealed UCHL3, Relish, Gly-Cru2, CTL, MyD88 and Hemocyanin were significantly up-regulated in hemocytes, gills and hepatopancreas, which revealed various expression patterns in response to DIV1 infection. This study revealed that DIV1 infection is responsible for the mass mortality of M. nipponense, one of the important crustacean species, indicating its high susceptibility to DIV1. Moreover, this study will contribute to exploring the interaction between the host and DIV1 infection, specifically in terms of understanding how M. nipponense recognizes and eliminates the invading of DIV1.

Immunomodulatory, antioxidant, and growth-promoting activities of dietary fermented Moringa oleifera in Nile tilapia (Oreochromus niloticus) with in-vivo protection against Aeromonas hydrophila.

BACKGROUND: Moringa oleifera, a well-known medicinal plant, has been used in aquafeed as a dietary supplement. Based on previous studies, insufficient research is available on the dietary supplementation of Nile tilapia with M. oleifera leaf and seed mixtures, specifically the fermented form. Therefore, this study aimed to investigate the efficacy of fermented (FMO) versus non-fermented M. oleifera (MO) leaf and seed mixtures on immunological parameters, antioxidant activity, growth performance, and resistance to A. hydrophila infection after a 30-day feeding trial on Nile tilapia. METHODS: A total of 180 fingerlings were randomly divided into four groups in addition to the control group (36 fish each, in triplicate). Fish in the tested groups were fed on basal diet supplemented with MO5%, MO10%, FMO5%, and FMO10%, while those in control were fed on basal diet only. After the feeding trial, fish were challenged with A. hydrophila. The immunomodulatory activity of M. oleifera was evaluated in terms of phagocytic and lysozyme activities, immune-related cytokines and IgM gene expression. Antioxidants, and growth-promoting activities were also assessed. RESULTS: The results revealed that fish supplemented FMO markedly in FMO10% group followed by FMO5%, exhibited significant (P < 0.05) improvement in the tested immunological, hepatic antioxidants, and growth performance parameters. Furthermore, the highest survival rate post-challenge with mild clinical symptoms, and the lowest A. hydrophila bacterial count were reported in these groups. Meanwhile, MO10%-supplementation exhibited the opposite trend. CONCLUSIONS: The study' conclusion suggests that fermented M. oleifera leaf and seed mixture is a promising growth-promoting and immunostimulatory feed-additive candidate for Nile tilapia and could reduce the losses caused by A. hydrophila infection.

Landscape of infiltrating immune cells and related genes in diabetic kidney disease.

INTRODUCTION: Diabetic kidney disease (DKD) is one of the prominent microvascular complications of diabetes and the leading cause of end-stage renal disease. Inflammation plays a crucial role in the development and progression of DKD. Currently, only a few studies depict the landscape of infiltrating immune cells and their potential regulatory network in DKD. To gain a better understanding of the role of immune cells in the renal microenvironment, we sought to reveal the profile of infiltrating immune cells and their potential regulatory network in DKD. METHODS: We obtained the transcriptomes and the corresponding clinical data of 19 DKD and 25 control samples from the Gene Expression Omnibus and Nephroseq databases, respectively. Thereafter, we conducted an analysis on the infiltrating immune cells and identified immune-related differentially expressed genes through bioinformatics. Finally, correlation analyses among immune cells, immune genes, and clinical manifestations were performed, and differentially infiltrating immune cell subsets were verified through multiplex immunofluorescence staining. RESULTS: We demonstrated the landscape of infiltrating immune cells in patients with DKD and identified the top five hub immune regulatory genes (C3, IL7R, TYROBP, BMP2, and CXCL6). Three of the core genes (C3, BMP2, and CXCL6) were significantly correlated with the estimated glomerular filtration rate. Through multiplex immunofluorescence staining, we verified that macrophage numbers were remarkably elevated, whereas Treg cells were remarkably reduced in diabetic kidney tissues. Th2 cells were scarce in the kidney tissue. CONCLUSION: Collectively, our findings shed light on new, possible therapeutic strategies for DKD, from an immune microenvironment perspective.

Osteosarcoma-Associated Immune Genes as Potential Immunotherapy and Prognosis Biomarkers.

Immune-modulating therapies exhibit abundant promise compared to traditional treatment for osteosarcoma. We aim to establish an immune-related prognostic signatures in osteosarcoma. We identified the differentially expressed genes in osteosarcoma compared with normal controls using the GEO dataset. The intersection with immune-related genes was considered as differentially expressed immune genes. Potential prognosis-related differentially expressed genes were first analyzed with the multifactor Cox regression and then the step function performed the iteration. The best model was finally chosen as the immunological risk score signature model. And finally, we evaluated the correlation of genes in the prognostic model with immune cells, common immune checkpoints, and immune checkpoint blockade responses. We identified 1527 significantly upregulated and 2407 significantly downregulated genes in osteosarcoma compared to normal samples. In the 258 differentially expressed immune genes, 20 genes with independent prognostic significance were included in the step function. Finally, we constructed a prognostic signature for overall survival based on five immune genes (JAG2, PLXNB1, CMKLR1, NUDT6, and PSMC4) in osteosarcoma. These five genes are closely related to immune infiltration. Osteosarcoma with high JAG2 expression or low CMKLR1 expression may be associated with better immune checkpoint blockade response. JAG2 overexpression or CMKLR1 inhibition induced sensitivity to PD-1 antibody in osteosarcoma cells. We constructed a prognosis prediction signature containing five immune-related genes (JAG2, PLXNB1, CMKLR1, NUDT6, and PSMC4) with a significant prognostic value in osteosarcoma. Significant differences in immune infiltration and immunotherapy responses were identified between groups with different levels of these genes.

Identifying immune-related prognostic biomarkers in osteosarcoma: Development and validation of the tumor immune microenvironment risk model based on analysis of TCGA.

OBJECTIVE: Osteosarcoma is a rare and aggressive malignancy with limited effective therapeutic options. This study aimed to identify immune-related prognostic biomarkers and develop a prognostic model for osteosarcoma. METHODS: We performed integrated analysis of transcriptomic data and immune cell infiltration profiles of 84 osteosarcoma samples from the Cancer Genome Atlas (TCGA) database. Time-dependent receiver operating characteristic (ROC) curve analysis was used to assess the prognostic value of the TIMErisk model. We also performed functional annotation and pathway enrichment analyses to explore the potential mechanisms underlying the TIMErisk model. RESULTS: We identified a seven-gene TIMErisk model (C2, APBB1IP, BST2, TRPV2, CCL5, GBP1, and F13A1) that was independently associated with overall survival of osteosarcoma patients. The TIMErisk model showed significant associations with immune cell infiltration and immunosuppressive gene expression. In addition, the TIMErisk model was associated with drug sensitivity, and we found that several immune checkpoint genes were significantly differentially expressed between high- and low-TIMErisk groups. Functional annotation and pathway enrichment analyses revealed that the TIMErisk model was associated with multiple immune-related pathways, including antigen processing and presentation, cytokine-cytokine receptor interaction, and T cell receptor signaling pathway. CONCLUSION: Our study identified a novel TIME-based prognostic model for osteosarcoma that incorporates immune-related genes and can be used to predict patient prognosis and response to immunotherapy. Our findings highlight the importance of the TIME microenvironment in osteosarcoma progression and suggest that immune-related biomarkers may have clinical significance in the management of osteosarcoma.

The immune landscape and prognostic analysis of CXCL8 immune-related genes in cervical squamous cell carcinoma.

Cervical squamous cell carcinoma (CESC), one of the most common malignancies in women, imposes a significant burden on women's health worldwide. Despite extensive research, the molecular and pathogenic mechanisms of cervical squamous cell carcinoma and CESC remain unclear. This study aimed to explore the immune-related genes, immune microenvironment infiltration, and prognosis of CESC, providing a theoretical basis for guiding clinical treatment. Initially, by mining four gene sets and immune-related gene sets from public databases, 14 immune-related genes associated with CESC were identified. Through univariate and multivariate COX regression analyses, as well as lasso regression analysis, four CESC-independent prognostic genes were identified, and a prognostic model was constructed, dividing them into high and low-risk groups. The correlation between these genes and immune cells and immune functions were explored through ssGSEA enrichment analysis, revealing a close association between the high-risk group and processes such as angiogenesis and epithelial-mesenchymal transition. Furthermore, using public databases and qRT-PCR experiments, significant differences in CXCL8 expression between normal cervical cells and cervical cancer cells were discovered. Subsequently, a CXCL8 knockdown plasmid was constructed, and the efficiency of CXCL8 knockdown was validated in two CESC cell lines, MEG-01 and HCE-1. Through CCK-8, scratch, and Transwell assays, it was confirmed that CXCL8 knockdown could inhibit the proliferation, invasion, and migration abilities of CESC cells. Targeting CXCL8 holds promise for personalized therapy for CESC, providing a strong theoretical basis for achieving clinical translation.

The Integrated Bioinformatic Approach Reveals the Prognostic Significance of LRP1 Expression in Ovarian Cancer.

A hyperactive tumour microenvironment (TME) drives unrestricted cancer cell survival, drug resistance, and metastasis in ovarian carcinoma (OC). However, therapeutic targets within the TME for OC remain elusive, and efficient methods to quantify TME activity are still limited. Herein, we employed an integrated bioinformatics approach to determine which immune-related genes (IRGs) modulate the TME and further assess their potential theragnostic (therapeutic + diagnostic) significance in OC progression. Using a robust approach, we developed a predictive risk model to retrospectively examine the clinicopathological parameters of OC patients from The Cancer Genome Atlas (TCGA) database. The validity of the prognostic model was confirmed with data from the International Cancer Genome Consortium (ICGC) cohort. Our approach identified nine IRGs, AKT2, FGF7, FOS, IL27RA, LRP1, OBP2A, PAEP, PDGFRA, and PI3, that form a prognostic model in OC progression, distinguishing patients with significantly better clinical outcomes in the low-risk group. We validated this model as an independent prognostic indicator and demonstrated enhanced prognostic significance when used alongside clinical nomograms for accurate prediction. Elevated LRP1 expression, which indicates poor prognosis in bladder cancer (BLCA), OC, low-grade gliomas (LGG), and glioblastoma (GBM), was also associated with immune infiltration in several other cancers. Significant correlations with immune checkpoint genes (ICGs) highlight the potential importance of LRP1 as a biomarker and therapeutic target. Furthermore, gene set enrichment analysis highlighted LRP1's involvement in metabolism-related pathways, supporting its prognostic and therapeutic relevance also in BLCA, OC, low-grade gliomas (LGG), GBM, kidney cancer, OC, BLCA, kidney renal clear cell carcinoma (KIRC), stomach adenocarcinoma (STAD), and stomach and oesophageal carcinoma (STES). Our study has generated a novel signature of nine IRGs within the TME across cancers, that could serve as potential prognostic predictors and provide a valuable resource to improve the prognosis of OC.

A signature of immune-related genes correlating with clinical prognosis and immune microenvironment in sepsis.

BACKGROUND: Immune-related genes (IRGs) remain poorly understood in their function in the onset and progression of sepsis. METHODS: GSE65682 was obtained from the Gene Expression Omnibus database. The IRGs associated with survival were screened for subsequent modeling using univariate Cox regression analysis and least absolute shrinkage and selection operator in the training cohort. Then, we assessed the reliability of the 7 IRGs signature's independent predictive value in the training and validation cohorts following the creation of a signature applying multivariable Cox regression analysis. After that, we utilized the E-MTAB-4451 external dataset in order to do an independent validation of the prognostic signature. Finally, the CIBERSORT algorithm and single-sample gene set enrichment analysis was utilized to investigate and characterize the properties of the immune microenvironment. RESULTS: Based on 7 IRGs signature, patients could be separated into low-risk and high-risk groups. Patients in the low-risk group had a remarkably increased 28-day survival compared to those in the high-risk group (P < 0.001). In multivariable Cox regression analyses, the risk score calculated by this signature was an independent predictor of 28-day survival (P < 0.001). The signature's predictive ability was confirmed by receiver operating characteristic curve analysis with the area under the curve reaching 0.876 (95% confidence interval 0.793-0.946). Moreover, both the validation set and the external dataset demonstrated that the signature had strong clinical prediction performance. In addition, patients in the high-risk group were characterized by a decreased neutrophil count and by reduced inflammation-promoting function. CONCLUSION: We developed a 7 IRGs signature as a novel prognostic marker for predicting sepsis patients' 28-day survival, indicating possibilities for individualized reasonable resource distribution of intensive care unit.

Screening and identification of the core immune-related genes and immune cell infiltration in severe burns and sepsis.

Severe burns often have a high mortality rate due to sepsis, but the genetic and immune crosstalk between them remains unclear. In the present study, the GSE77791 and GSE95233 datasets were analysed to identify immune-related differentially expressed genes (DEGs) involved in disease progression in both burns and sepsis. Subsequently, weighted gene coexpression network analysis (WGCNA), gene enrichment analysis, protein-protein interaction (PPI) network construction, immune cell infiltration analysis, core gene identification, coexpression network analysis and clinical correlation analysis were performed. A total of 282 common DEGs associated with burns and sepsis were identified. Kyoto Encyclopedia of Genes and Genomes pathway analysis identified the following enriched pathways in burns and sepsis: metabolic pathways; complement and coagulation cascades; legionellosis; starch and sucrose metabolism; and ferroptosis. Finally, six core DEGs were identified, namely, IL10, RETN, THBS1, FGF13, LCN2 and MMP9. Correlation analysis showed that some core DEGs were significantly associated with simultaneous dysregulation of immune cells. Of these, RETN upregulation was associated with a worse prognosis. The immune-related genes and dysregulated immune cells in severe burns and sepsis provide potential research directions for diagnosis and treatment.

Screening of the shared pathogenic genes of ulcerative colitis and colorectal cancer by integrated bioinformatics analysis.

Ulcerative colitis (UC) is one of the high-risk pathogenic factors for colorectal cancer (CRC). However, the shared gene and signalling mechanisms between UC and CRC remain unclear. The goal of this study was to delve more into the probable causal relationship between UC and CRC. CRC and UC datasets were downloaded from the Gene Expression Omnibus database. Using R software and Perl, differentially expressed genes (DEGs) in both UC and CRC tissues were re-annotated and screened. The biological activities and signalling pathways involved in DEGs were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The STRING database and Cytoscape software were used to construct the gene interaction network. A total of 384 DEGs were selected for further investigation, and functional analysis revealed that inflammatory and immunological responses were crucial in the development of the two diseases. Moreover, the top 15 key genes involved in the UC and CRC were screened using cytoHubba, including IL1B, CXCL10, CCL20, MMP9, ICAM1, CCL4, CXCR1, MMP3, TLR2, PTGS2, IL1RN, IL6, COL1A2, TIMP1 and CXCL1. The identification of these genes in the present study may provide a novel perspective for the prediction, prevention and personalized medicine of UC and CRC patients.

Identification of immune-related lncRNA in sepsis by construction of ceRNA network and integrating bioinformatic analysis.

BACKGROUND: Sepsis is a high mortality disease which seriously threatens human life and health, for which the pathogenetic mechanism still unclear. There is increasing evidence showed that immune and inflammation responses are key players in the development of sepsis pathology. LncRNAs, which act as ceRNAs, have critical roles in various diseases. However, the regulatory roles of ceRNA in the immunopathogenesis of sepsis have not yet been elucidated. RESULTS: In this study, we aimed to identify immune biomarkers associated with sepsis. We first generated a global immune-associated ceRNA (IMCE) network based on data describing interactions pairs of gene-miRNA and miRNA-lncRNA. Afterward, we excavated a dysregulated sepsis immune-associated ceRNA (SPIMC) network from the global IMCE network by means of a multi-step computational approach. Functional enrichment indicated that lncRNAs in SPIMC network have pivotal roles in the immune mechanism underlying sepsis. Subsequently, we identified module and hub genes (CD4 and STAT4) via construction of a sepsis immune-related PPI network. Then, we identified hub genes based on the modular structure of PPI network and generated a ceRNA subnetwork to analyze key lncRNAs associated with sepsis. Finally, 6 lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) that identified as immune biomarkers of sepsis. Moreover, the CIBERSORT algorithm and the infiltration of circulating immune cells types were performed to identify the inflammatory state of sepsis. Correlation analyses between immune cells and sepsis immune biomarkers showed that the LINC00265 was strongly positive correlated with the macrophages M2 (r = 0.77). CONCLUSION: Collectively, these results may suggest that these lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) played important roles in the immune pathogenesis of sepsis and provide potential therapeutic targets for further researches on immune therapy treatment in patients with sepsis.

Characterization and clinical verification of immune-related genes in hepatocellular carcinoma to aid prognosis evaluation and immunotherapy.

BACKGROUND: Immune-related genes (IRGs) have been confirmed to play an important role in tumorigenesis and tumor microenvironment formation in hepatocellular carcinoma (HCC). We investigated how IRGs regulates the HCC immunophenotype and thus affects the prognosis and response to immunotherapy. METHODS: We investigated RNA expression of IRGs and developed an immune-related genes-based prognostic index (IRGPI) in HCC samples. Then, the influence of the IRGPI on the immune microenvironment was comprehensively analysed. RESULTS: According to IRGPI, HCC patients are divided into two immune subtypes. A high IRGPI was characterized by an increased tumor mutation burden (TMB) and a poor prognosis. More CD8 + tumor infiltrating cells and expression of PD-L1 were observed in low IRGPI subtypes. Two immunotherapy cohorts confirmed patients with low IRGPI demonstrated significant therapeutic benefits. Multiplex immunofluorescence staining determined that there were more CD8 + T cells infiltrating into tumor microenvironment in IRGPI-low groups, and the survival time of these patients was longer. CONCLUSIONS: This study demonstrated that the IRGPI serve as a predictive prognostic biomarker and potential indicator for immunotherapy.

Immune-Related Genes' Prognostic, Therapeutic and Diagnostic Value in Ovarian Cancer Immune-Related Gene Biomarker in Ovarian Cancer.

OBJECTIVES: The abnormal expression of immune-related genes (IRGs) plays an important role in the occurrence and progression of ovarian cancer (OC), which is the main cause of mortality among gynecological cancer patients. This study aims to establish a prognostic risk model and comprehensively analyze the relationship between OC risk score and prognosis, immune cell infiltration (ICI) and therapeutic sensitivity in OC. METHODS: We retrospectively evaluated the clinicopathological characteristics of consecutive OC patients in the Cancer Genome Atlas (TCGA) database. First, the prognostic risk model was constructed by bioinformatics methods. And then, we systematically assessed model robustness, and correlations between risk score and prognosis, and immune cell infiltration. The ICGC cohort was used to verify the prognostic risk model. Finally, we evaluated their value in the treatment of OC immunotherapy and chemotherapy. RESULTS: A total of 10 IRGs were identified to construct the prognostic risk model. Survival analysis revealed that patients in the low-risk group had a better prognosis (P < .01), and the risk score might be considered an independent predictor for predicting the prognosis. In addition, risk scores and patient clinical information were used to construct clinical nomograms, improving the prediction's precision. We also explored the relationship between the risk score and ICI, immunotherapy and drug sensitivity. CONCLUSIONS: Collectively, we identified a novel ten IRGs signature that may be applied as a prognostic predictor of OC, thereby benefiting clinical decision-making and personalized treatment of patients.