Construction and validation of a prognostic and therapeutic cuproptosis- and immune-related gene signature in hepatocellular carcinoma.

Background: Abnormal accumulation of copper could induce cell death and tumor growth, and affect tumor immune escape by regulating programmed cell death ligand 1 (PD-L1) expression. This study aims to establish and verify a risk signature based on cuproptosis- and immune-related genes (CIRGs) for hepatocellular carcinoma (HCC) management. Methods: HCC RNA-seq and clinical data were obtained from open databases. Least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were utilized to screen CIRGs and develop a risk signature. The signature's value for clinical applications, functional enrichment, tumor mutation burden (TMB), and immune profile analyses were investigated systematically. Results: A risk signature was developed utilizing seven CIRGs, and it performed well in predicting the prognosis of HCC patients in both the training and external validation cohorts. The model's risk score was discovered to be related to important clinical features. Top 15 mutated genes in HCC were significantly different among different risk groups. High-risk patients showed higher TMB, and high TMB was closely identified with a poorer prognosis. Immune profile analyses showed that immune infiltration level was higher in low-risk patients than high-risk patients, and the level of immune checkpoint genes expression varied significantly between patients in two different risk groups. Low-risk patients responded well to immunotherapy treatment, whereas high-risk patients were more sensitive to sorafenib, doxorubicin, gemcitabine and AKT (also known as protein kinase B) inhibitors. Conclusions: The established risk signature based on CIRGs can not only well predict the prognosis of HCC patients but is also promising in evaluating TMB and treatment response to immunotherapy, targeted therapy and chemotherapy, which has the potential to assist in the clinical management of HCC.

Corrigendum: Identification of an immune-related gene prognostic index for predicting survival and immunotherapy efficacy in papillary renal cell carcinoma.

[This corrects the article DOI: 10.3389/fgene.2022.970900.].

Immune-related gene methylation prognostic instrument for stratification and targeted treatment of ovarian cancer patients toward advanced 3PM approach.

Background: DNA methylation is an important mechanism in epigenetics, which can change the transcription ability of genes and is closely related to the pathogenesis of ovarian cancer (OC). We hypothesize that DNA methylation is significantly different in OCs compared to controls. Specific DNA methylation status can be used as a biomarker of OC, and targeted drugs targeting these methylation patterns and DNA methyltransferase may have better therapeutic effects. Studying the key DNA methylation sites of immune-related genes (IRGs) in OC patients and studying the effects of these methylation sites on the immune microenvironment may provide a new method for further exploring the pathogenesis of OC, realizing early detection and effective monitoring of OC, identifying effective biomarkers of DNA methylation subtypes and drug targets, improving the efficacy of targeted drugs or overcoming drug resistance, and better applying it to predictive diagnosis, prevention, and personalized medicine (PPPM; 3PM) of OC. Method: Hypermethylated subtypes (cluster 1) and hypomethylated subtypes (cluster 2) were established in OCs based on the abundance of different methylation sites in IRGs. The differences in immune score, immune checkpoints, immune cells, and overall survival were analyzed between different methylation subtypes in OC samples. The significant pathways, gene ontology (GO), and protein-protein interaction (PPI) network of the identified methylation sites in IRGs were enriched. In addition, the immune-related methylation signature was constructed with multiple regression analysis. A methylation site model based on IRGs was constructed and verified. Results: A total of 120 IRGs with 142 differentially methylated sites (DMSs) were identified. The DMSs were clustered into a high-level methylation group (cluster 1) and a low-level methylation group (cluster 2). The significant pathways and GO analysis showed many immune-related and cancer-associated enrichments. A methylation site signature based on IRGs was constructed, including RORC|cg25112191, S100A13|cg14467840, TNF|cg04425624, RLN2|cg03679581, and IL1RL2|cg22797169. The methylation sites of all five genes showed hypomethylation in OC, and there were statistically significant differences among RORC|cg25112191, S100A13|cg14467840, and TNF|cg04425624 (p < 0.05). This prognostic model based on low-level methylation and high-level methylation groups was significantly linked to the immune microenvironment as well as overall survival in OC. Conclusions: This study provided different methylation subtypes for OC patients according to the methylation sites of IRGs. In addition, it helps establish a relationship between methylation and the immune microenvironment, which showed specific differences in biological signaling pathways, genomic changes, and immune mechanisms within the two subgroups. These data provide ones to deeply understand the mechanism of immune-related methylation genes on the occurrence and development of OC. The methylation-site signature is also to establish new possibilities for OC therapy. These data are a precious resource for stratification and targeted treatment of OC patients toward an advanced 3PM approach. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00359-3.

Identification Of Endothelial Cell Immune-related Gene Signature for Lung Adenocarcinoma by Integrated Analysis of Single-cell and Bulk RNA Sequencing Data.

Background: The role of endothelial cells in tumor progression is considerable, yet the effect of endothelial cell immune-related genes (EIRGs) is still unclear. This research aimed to scrutinize the prognostic value of EIRGs in lung adenocarcinoma (LUAD) and provide further insights into the abovementioned uncertainties. Methods: After single-cell RNA sequencing (scRNA-seq) samples were obtained from the Gene Expression Omnibus (GEO) database, they were integrated with bulk RNA sequencing data from The Cancer Genome Atlas (TCGA). Prognostic markers were determined and a prognostic model was developed. From this model, a nomogram was constructed. We analyzed the biological mechanism of the EIRGs in LUAD, including functional enrichment, tumor mutational burden (TMB), tumor microenvironment (TME) analyses and drug sensitivity. We validated the signature by validating the external cohort GSE31210 and RT-qPCR. Results: After analyzing the model constructed from eight EIRGs, we observed that high-risk group (HG) LUAD patients (a risk score exceeding 4.65) exhibited unfavorable outcomes according to Kaplan‒Meier survival curves. This outcome was confirmed by GSE31210. The nomogram based on the model demonstrated significant predictive value. HG was influenced primarily by steroid hormone biosynthesis and ECM receptor interactions. The TMB in HGs was greater than that in the LG. Analysis of drug sensitivity revealed the direction for individualized treatment for both risk cohorts. Variations in the expression of EIRGs have been confirmed via RT-qPCR in several LUAD cell lines. Conclusions: The prognostic model and nomogram above are valuable for determining the survival rate and treatment options for LUAD patients.

Identification of immune-related tumor antigens and immune subtypes in osteosarcoma.

Purpose: The development of tumor vaccines has become a hot topic in immunotherapy for osteosarcoma (OS); however, more tumor antigens with stronger immunogenicity need to be identified. Methods: We downloaded six sets of gene expression profile data from online databases. The overexpressed genes were analyzed, intersected, and used to calculate the immune infiltration abundance in the TARGET OS dataset based on their expression matrix. Potential tumor antigen genes were identified based on whether they exhibited a high correlation with the antigen-presenting cells (APCs). A total of 1330 immune-related genes (IRGs) from the ImmPort website were retrieved based on their expression, and the Consensus Cluster method was used to obtain immune subtypes of the OS samples. Prognosis, immune microenvironment, and sensitivity to drugs were compared among the immune subtypes. Results: In total, 680 genes were overexpressed in at least two datasets, of which TREM2, TNFRSF12A, and THY1 were positively correlated with different APCs. Based on the expression matrix of 1330 IRGs in TARGET-OS, two immune subtypes, IS1 and IS2, were identified. The prognosis of the IS1 subtype was better than that of IS2, the expression of immune checkpoint (ICP)-related genes was higher in patients with the IS1 subtype, and immune cell infiltration and sensitivity to 16 drugs were generally higher in IS1 subtype patients. Conclusion: We identified three APC-correlated genes that can be considered to code for potential novel tumor antigens for OS vaccines. Two immune subtypes in patients with OS were identified to implement personalized treatments using mRNA vaccines.

Identification of immune-related biomarkers for glaucoma using gene expression profiling.

Introduction: Glaucoma, a principal cause of irreversible vision loss, is characterized by intricate optic neuropathy involving significant immune mechanisms. This study seeks to elucidate the molecular and immune complexities of glaucoma, aiming to improve our understanding of its pathogenesis. Methods: Gene expression profiles from glaucoma patients were analyzed to identify immune-related differentially expressed genes (DEGs). Techniques used were weighted gene co-expression network analysis (WGCNA) for network building, machine learning algorithms for biomarker identification, establishment of subclusters related to immune reactions, and single-sample gene set enrichment analysis (ssGSEA) to explore hub genes' relationships with immune cell infiltration and immune pathway activation. Validation was performed using an NMDA-induced excitotoxicity model and RT-qPCR for hub gene expression measurement. Results: The study identified 409 DEGs differentiating healthy individuals from glaucoma patients, highlighting the immune response's significance in disease progression. Immune cell infiltration analysis revealed elevated levels of activated dendritic cells, natural killer cells, monocytes, and immature dendritic cells in glaucoma samples. Three hub genes, CD40LG, TEK, and MDK, were validated as potential diagnostic biomarkers for high-risk glaucoma patients, showing increased expression in the NMDA-induced excitotoxicity model. Discussion: The findings propose the three identified immune-related genes (IRGs) as novel diagnostic markers for glaucoma, offering new insights into the disease's pathogenesis and potential therapeutic targets. The strong correlation between these IRGs and immune responses underscores the intricate role of immunity in glaucoma, suggesting a shift in the approach to its diagnosis and treatment.

Construction of an immune-related gene prognostic model with experimental validation and analysis of immune cell infiltration in lung adenocarcinoma.

There is a correlation between tumors and immunity with the degree of immune cell infiltration in tumors being closely related to tumor growth and progression. Therefore, the present study identified immune-related prognostic genes and evaluated the immune infiltration level in lung adenocarcinoma (LUAD). This study performed Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and Gene Set Enrichment Analysis (GSEA) enrichment analyses on differential immune-associated genes. A risk model was created and validated using six immune-related prognostic genes. Reverse transcription-quantitative PCR was used to assess the prognostic gene expression in non-small cell lung cancer cells. Immune cell infiltration in LUAD was analyzed using the CIBERSORT method. Single sample GSEA was used to compare Tumor Immune Dysfunction and Exclusion (TIDE) scores between high and low-risk groups and to assess the activation of thirteen immune-related pathways. Multifactor Cox proportional hazards model analysis identified six prognostic risk genes (S100A16, FURIN, FGF2, LGR4, TNFRSF11A and VIPR1) to construct a risk model. The survival and receiver operating characteristic curves indicated that patients with higher risk scores had lower overall survival rates. The expression levels of prognostic genes S100A16, FURIN, LGR4, TNFRSF11A and VIPR1 were significantly increased in LUAD. B cells naive, plasma cells, T cells CD4 memory activated, T cells follicular helper, T cells regulatory, NK cells activated, macrophages M1, macrophages M2, and Dendritic cells resting cells showed elevated expression in LUAD. The prognostic genes were differentially associated with individual immune cells. Immune-related function scores, such as those for antigen presenting cell (APC) co-stimulation, APC co-inhibition, check-point, Cytolytic-activity, chemokine receptor, parainflammation, major histocompatibility complex-class-I, type-I-IFN-reponse and T-cell-co-inhibition, were higher in the high-risk group compared with the low-risk group. Furthermore, the TIDE score of the high-risk group was significantly lower than the low-risk group. This immune-related gene prognostic model has the potential to predict the prognosis of LUAD patients, supporting the development of a personalized clinical diagnosis and treatment plan.

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.

Prognostic implications of STK11 with different mutation status and its relationship with tumor-infiltrating immune cells in non-small cell lung cancer.

Background: Mutations in STK11 (STK11Mut) gene may present a negative impact on survival in Non-small Cell Lung Cancer (NSCLC) patients, however, its relationship with immune related genes remains unclear. This study is to unveil whether overexpressed- and mutated-STK11 impact survival in NSCLC and to explore whether immune related genes (IRGs) are involved in STK11 mutations. Methods: 188 NSCLC patients with intact formalin-fixed paraffin-embedded (FFPE) tissue available for detecting STK11 protein expression were included in the analysis. After immunohistochemical detection of STK11 protein, patients were divided into high STK11 expression group (STK11High) and low STK11 expression group (STK11Low), and then Kaplan-Meier survival analysis and COX proportional hazards model were used to compare the overall survival (OS) and progression-free survival (PFS) of the two groups of patients. In addition, the mutation data from the TCGA database was used to categorize the NSCLC population, namely STK11 Mutated (STK11Mut) and wild-type (STK11Wt) subgroups. The difference in OS between STK11Mut and STK11Wt was compared. Finally, bioinformatics analysis was used to compare the differences in IRGs expression between STK11Mut and STK11Wt populations. Results: The median follow-up time was 51.0 months (range 3.0 - 120.0 months) for real-life cohort. At the end of follow-up, 64.36% (121/188) of patients experienced recurrence or metastasis. 64.89% (122/188) of patients ended up in cancer-related death. High expression of STK11 was a significant protective factor for NSCLC patients, both in terms of PFS [HR=0.42, 95% CI= (0.29-0.61), P<0.001] and OS [HR=0.36, 95% CI= (0.25, 0.53), P<0.001], which was consistent with the finding in TCGA cohorts [HR=0.76, 95%CI= (0.65, 0.88), P<0.001 HR=0.76, 95%CI= (0.65, 0.88), P<0.001]. In TCGA cohort, STK11 mutation was a significant risk factor for NSCLC in both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) histology in terms of OS [HR=6.81, 95%CI= (2.16, 21.53), P<0.001; HR=1.50, 95%CI= (1.00, 2.26), P=0.051, respectively]. Furthermore, 7 IRGs, namely CALCA, BMP6, S100P, THPO, CGA, PCSK1 and MUC5AC, were found significantly overexpressed in STK11-mutated NSCLC in both LUSC and LUAD histology. Conclusions: Low STK11 expression at protein level and presence of STK11 mutation were associated with poor prognosis in NSCLC, and mutated STK11 might probably alter the expression IRGs profiling.

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.

Pathogenicity of Aeromonas veronii Isolated from Diseased Macrobrachium rosenbergii and Host Immune-Related Gene Expression Profiles.

Aeromonas veronii is widespread in aquatic environments and is responsible for infecting various aquatic animals. In this study, a dominant strain was isolated from the hepatopancreas of diseased Macrobrachium rosenbergii and was named JDM1-1. According to its morphological, physiological, and biochemical characteristics and molecular identification, isolate JDM1-1 was identified as A. veronii. The results of artificial challenge showed isolate JDM1-1 had high pathogenicity to M. rosenbergii with an LD50 value of 8.35 × 105 CFU/mL during the challenge test. Histopathological analysis revealed severe damage in the hepatopancreas and gills of the diseased prawns, characterized by the enlargement of the hepatic tubule lumen and gaps between the tubules as well as clubbing and degeneration observed at the distal end of the gill filament. Eight virulence-related genes, namely aer, ompA, lip, tapA, hlyA, flgA, flgM, and flgN, were screened by PCR assay. In addition, virulence factor detection showed that the JDM1-1 isolate produced lipase, lecithinase, gelatinase, and hemolysin. Furthermore, the mRNA expression profiles of immune-related genes of M. rosenbergii following A. veronii infection, including ALF1, ALF2, Crustin, C-lectin, and Lysozyme, were assessed, and the results revealed a significant upregulation in the hepatopancreas and intestines at different hours post infection. This study demonstrates that A. veronii is a causative agent associated with massive die-offs of M. rosenbergii and contributes valuable insights into the pathogenesis and host defense mechanisms of A. veronii invasion.

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.

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.

Tumor-infiltrating immune cells and survival in head and neck squamous cell carcinoma: a retrospective computational study.

The immune infiltration profiles of the tumor microenvironment have effects on the prognosis of head and neck squamous cell carcinoma (HNSCC). Whereas, HNSCC is a heterogeneous group of tumors, but past work has not taken this into consideration. Herein, we investigate the associations between survival and the function of immune cells in different tumorigenic sites of HNSCC. 1149 samples of HNSCC were collected from publicly accessible databases. Based on gene expression data, CIBERSORTx was applied to determine the proportion of 22 immune cell subpopulations. In the Cox regression model, the associations between overall survival, disease-free survival, and immune cells were examined, modeling gene expression and immune cell proportion as quartiles. Consensus cluster analysis was utilized to uncover immune infiltration profiles. Regardless of tumor sites, CD8+ T cells and activated CD4 memory T cells were associated with favorable survival, while eosinophils were the opposite. The survival of the hypopharynx, oral cavity, and larynx subsites was somewhat affected by immune cells, while the survival of the oropharynx subsite potentially was the most impacted. High expression of TIGIT, CIITA, and CXCR6 was linked to better survival, mainly in the oropharynx subsite. Immune cell clusters with four distinct survival profiles were discovered, of which the cluster with a high CD8+ T cell content had a better prognosis. The immune-infiltration pattern is related to the survival of HNSCC to varying degrees depending on the tumor sites; forthcoming studies into immune-mediated infiltration profiles will lay the groundwork for treating HNSCC with precision therapy.

Development and Validation of the novel Cuproptosis- and Immune-related Signature for Predicting Prognosis in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma often results in late-stage diagnosis, leading to decreased treatment success. To improve prognosis, this study integrates cuproptosis with immune risk scoring models for HCC patients. Method: We identified differentially expressed genes connected to cuproptosis and immune responses using Pearson correlation. A risk signature was then constructed via LASSO regression, and its robustness was validated in the International Cancer Genome Consortium dataset. Additionally, qPCR confirmed findings in tumor and normal tissues. Results: Eight genes emerged as key prognostic markers from the 110 differentially expressed genes linked to cuproptosis and immunity. A risk-scoring model was developed using gene expression, effectively categorizing patients into low- or high-risk groups. Validated in the ICGC dataset, high-risk patients had significantly reduced survival times. Multivariate Cox regression affirmed the risk signature's independent predictive capability. A clinical nomogram based on the risk signature was generated. Notably, low-risk patients might benefit more from immune checkpoint inhibitors. qPCR and western blotting results substantiated our bioinformatics findings. Conclusions: The genetic risk signature linked to cuproptosis and immunity holds potential as a vital prognostic biomarker for Hepatocellular carcinoma, providing avenues for tailored therapeutic strategies.

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.

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.

Exploring Immune-Related Gene Profiling and Infiltration of Immune Cells in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma.

Cervical cancer is a widespread malignancy among women, leading to a substantial global health impact. Despite extensive research, our understanding of the basic molecules and pathogenic processes of cervical squamous cell carcinoma is still insufficient. This investigation aims to uncover immune-related genes linked to CESC and delineate their functions. Leveraging data from the GEO and ImmPort databases, a total of 22 immune-related genes were identified. Multiple tools, including DAVID, the human protein atlas, STRING, GeneMANIA, and TCGA, were employed to delve into the expression and roles of these immune genes in CESC, alongside their connections to the disease's pathological features. Through RT-PCR, the study confirmed notable disparities in CXCL8 and CXCL10 mRNA expression between CESC and normal cervical tissue. The TCGA dataset's immune-related information reinforced the association of CXCL8 and CXCL10 with immune infiltration in CESC. This research sheds light on the potential of CXCL8 and CXCL10 as promising therapeutic targets and essential prognostic factors for individuals diagnosed with CESC.

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.