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• RNA-seq Analysis: Robust RNA-seq on 10 DFU patients and 11 controls identified 8800 DEGs. • Immune-Related DEGs: Intersection with ImmPort database revealed 526 immune-related DEGs. • Functional Analysis & PPI: Enrichment analysis and PPI network identified a significant module with 4 hub genes. • Immune Cell Insights: CIBERSORT showed distinct immune cell infiltration in DFU. • Hub Gene Validation: External scRNA-seq and RT-qPCR validations confirmed the identified hub genes. Diabetic foot ulcers (DFU), affecting a quarter of diabetic patients and leading to high rates of amputation and mortality, pose significant health and economic burdens. Wound healing in DFU is often compromised by chronic inflammation, underscoring the critical role of immune cells. However, the systematic investigation of immune-related genes (IRGs) in DFU pathogenesis remains elusive. To address this gap, our study aims to explore the association between IRGs and DFU. To explore biological changes in immune related gene expression in DFU, RNA-seq was performed on wound biopsies derived from 10 DFU patients and 11 healthy controls. Differentially expressed genes (DEGs) between DFU and normal samples were obtained by DEseq2. By intersecting the IRG list from the ImmPort database, the immune-related differentially expressed genes were identified. Function enrichment analysis and protein–protein interaction (PPI) analysis were applied by clusterProfiler and STRING database, and the hub genes of the PPI network were calculated by the cytoHubba plug-ins in Cytoscape. CIBERSORT algorithms was applied to analyze immune infiltration in DFU. And the correlation between immune cells infiltration and hub genes was explored by correlation analysis. Finally, to validate our findings, the transcriptional change of hub genes in DFU was confirmed using external scRNA-seq dataset and RT-qPCR. RNA-seq analysis detected 8,800 DEGs in DFUs, with 2,351 upregulated and 6,449 downregulated.526 differential IRGs were obtained from intersection of DEGs and IRGs. 526 differential IRGs were obtained from intersection of DEGs and IRGs. Enrichment function analysis of DEGs showed that they played a significant role in immune response. The PPI network was constructed, and the most significant module containing 4 hub genes was identified. CIBERSORT analysis showing that there was a significant difference between DFU and normal controls in the infiltration of immune cells. Compared with normal tissue, DFU tissue contained a higher proportion of resting NK cell, M0 macrophages, and activated mast cell, while resting dendritic cell, activated mast cell, and activated NK cell contributed to a relatively lower portion. Additionally, the analysis for M1/M2 polarization of macrophage cells shown that DFU tissue contained a higher M1/M2 ratio than normal group. Finally, the expression levels of 4 hub genes were confirmed by external scRNA-seq dataset and RT-qPCR. The immune related hub genes and the difference in immune infiltration between DFU tissue and normal controls might provide new insight for understanding DFU healing. [ABSTRACT FROM AUTHOR]

The cabbage webworm, Hellula undalis (Fabricius) (Lepidoptera: Pyralidae), is a significant pest of brassicas and other cruciferous plants in warm regions worldwide. Transcriptome analysis is valuable for investigation of molecular mechanisms underlying the insect development and reproduction. De novo assembly is particularly useful for acquiring complete transcriptome information of insect species when there is no reference genome available. In case of Hellula undalis , only 17 nucleotide records are currently available throughout NCBI nucleotide database. Genes associated with metabolic processes, general development, reproduction, defense and functional genomics were not previously predicted in the Hellula undalis at the genomic level. To address this issue, we constructed Hellula undalis transcriptome using Illumina NovaSeq6000 technology. Approximately 48 million 150 bp paired-end reads were obtained from sequencing. A total of 30,451 contigs were generated by de novo assembly of sample and were compared with the sequences in the NCBI non-redundant protein database (Nr). In total, 71 % of contigs were matched to known proteins in public databases including Nr, Gene Ontology (GO), and Cluster Orthologous Gene Database (COG), and then, contigs were mapped to 123 via functional annotation against the Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG). In addition, we compared the ortholog gene family of the Hullula undalis, transcriptome to Spodoptera frugiperda, spodotera litura and spodoptera littoralis and found that 391 orthologous gene families are specific to Hullula undalis. A total of 1,913 potential SSRs was discovered in Hullula undalis contigs. This study is the first transcriptome data for Hullula undalis. Additionally, it serves as a valuable resource for identifying target genes and developing effective and environmentally friendly strategies for pest control. [ABSTRACT FROM AUTHOR]

Clostridium butyricum is a butyrate-producing microorganism which has beneficial effects on various diseases, including obesity. In our previous study, the anti-obesity Clostridium butyricum strain CCFM1299 (C20_1_1) was selected, but its anti-obesity mechanism was not clarified. Herein, CCFM1299 was orally administrated to high-fat-diet-treated C57BL/6J mice for 12 weeks to uncover the way the strain alleviates obesity. The results indicated that CCFM1299 alleviated obesity through increasing the energy expenditure and increasing the expression of genes related to thermogenesis in brown adipose tissue (BAT). Moreover, strain CCFM1299 could also affect the expression of immune-related genes in epididymal white adipose tissue (eWAT). This immunomodulatory effect might be achieved through its influence on the complement system, as the expression of the complement factor D (CFD) gene decreased significantly. From the view of metabolites, CCFM1299 administration increased the levels of ursodeoxycholic acid (UDCA) in feces and taurohyodeoxycholic acid (THDCA) in serum. Together, the anti-obesity potential of CCFM1299 might be attributed to the increase in energy consumption, the regulation of immune-related gene expression in eWAT, and the alteration of bile acid metabolism in the host. These provided new insights into the potential application of anti-obesity microbial preparations and postbiotics.

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with a poor prognosis. Increasing evidence highlights the significant role of immune-related genes (IRGs) in ACC progression and immunotherapy, but the research is still limited. Based on the Cancer Genome Atlas (TCGA) database, immune-related molecular subtypes were identified by unsupervised consensus clustering. Univariate Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression were employed to further establish immune-related gene signatures (IRGS). An evaluation of immune cell infiltration, biological function, tumor mutation burden (TMB), predicted immunotherapy response, and drug sensitivity in ACC patients was conducted to elucidate the applicative efficacy of IRGS in precision therapy. ACC patients were divided into two molecular subtypes through consistent clustering. Furthermore, the 3-gene signature (including PRKCA, LTBP1, and BIRC5) based on two molecular subtypes demonstrated consistent prognostic efficacy across the TCGA and GEO datasets and emerged as an independent prognostic factor. The low-risk group exhibited heightened immune cell infiltration, TMB, and immune checkpoint inhibitors (ICIs), associated with a favorable prognosis. Pathways associated with drug metabolism, hormone regulation, and metabolism were activated in the low-risk group. In conclusion, our findings suggest IRGS can be used as an independent prognostic biomarker, providing a foundation for shaping future ACC immunotherapy strategies.

Hongqiong Meng,1 Qionghua Long,1 Ruiping Wang,1 Xian Zhou,1 Huipeng Su,1 Tingting Wang,1 Ya Li2 1Department of General Medicine, Yan’an Hospital Affiliated to Kunming Medical University, Kunming, People’s Republic of China; 2Department of Respiratory and Critical Care Medicine, Yan’an Hospital Affiliated to Kunming Medical University, Kunming, People’s Republic of ChinaCorrespondence: Ya LiDepartment of Respiratory and Critical Care Medicine, Yan’an Hospital Affiliated to Kunming Medical University, 245 Renmin East Road, Kunming, Yunnan Province, People’s Republic of ChinaEmail 563825085@qq.comPurpose: Chronic obstructive pulmonary disease (COPD) is a major cause of death and morbidity worldwide. A better understanding of new biomarkers for COPD patients and their complex mechanisms in the progression of COPD are needed.Methods: An algorithm was conducted to reveal the proportions of 22 subsets of immune cells in COPD samples. Differentially expressed immune-related genes (DE-IRGs) were obtained based on the differentially expressed genes (DEGs) of the GSE57148 dataset, and 1509 immune-related genes (IRGs) were downloaded from the ImmPort database. Functional enrichment analyses of DE-IRGs were conducted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and Ingenuity Pathway Analysis (IPA). We defined the DE-IRGs that had correlations with immune cells as hub genes. The potential interactions among the hub genes were explored by a protein–protein interaction (PPI) network.Results: The CIBERSORT results showed that lung tissue of COPD patients contained a greater number of resting NK cells, activated dendritic cells, and neutrophils than normal samples. However, the fractions of follicular helper T cells and resting dendritic cells were relatively lower. Thirty-eight DE-IRGs were obtained for further analysis. Functional enrichment analysis revealed that these DE-IRGs were significantly enriched in several immune-related biological processes and pathways. Notably, we also observed that DE-IRGs were associated with the coronavirus disease COVID-19 in the progression of COPD. After correlation analysis, six DE-IRGs associated with immune cells were considered hub genes, including AHNAK, SLIT2 TNFRRSF10C, CXCR1, CXCR2, and FCGR3B.Conclusion: In the present study, we investigated immune-related genes as novel diagnostic biomarkers and explored the potential mechanism for COPD based on CIBERSORT analysis, providing a new understanding for COPD treatment.Keywords: chronic obstructive pulmonary disease, COPD, immune-related genes, IRGs, CIBERSORT, diagnosis

Highlights A total of 309 CD8 T cell-related genes and 120 activated memory CD4 T cell-related genes were screened in liver cancer tumor samples. Forty-four chemical small-molecule–target interaction pairs associated with activated memory CD4 T cells and 276 pairs associated with CD8 T cells were screened. Upregulated expression of T cell-related genes including EOMES, CST7, and CD5L indicated the favorable prognosis of liver cancer.

Pancreatic cancer (PC) is one of the most fatal malignant tumors, and is commonly diagnosed at an advanced stage with no effective therapy. Metabolism-related genes (MRGs) and immune-related genes (IRGs) play considerable roles in the tumor microenvironment. Therefore, an effective prediction model based on MRGs and IRGs could aid in the prognosis of PC. In this study, differential expression analysis was performed to gain 25 intersectional genes from 857 differentially expressed MRGs (DEMRGs), and 1353 differentially expressed IRGs, from The Cancer Genome Atlas database of PC. Cox and Lasso regression were applied and a five-DEMRGs prognostic model constructed. Survival analysis, ROC values, risk curve and validation analysis showed that the model could independently predict PC prognosis. In addition, the correlation analysis suggested that the five-DEMRGs prognostic model could reflect the status of the immune microenvironment, including Tregs, M1 macrophages and Mast cell resting. Therefore, our study provides new underlying predictive biomarkers and associated immunotherapy targets.

IntroductionNight shift (NS) work has been associated with an increased risk of different conditions characterized by altered inflammatory and immune responses, such as cardio-metabolic and infectious diseases, cancer, and obesity. Epigenetic modifications, such as DNA methylation, might mirror alterations in biological processes that are influenced by NS work.MethodsThe present study was conducted on 94 healthy female workers with different working schedules and aimed at identifying whether NS was associated with plasmatic concentrations of the inflammatory proteins NLRP3 and TNF-alpha, as well as with DNA methylation levels of ten human endogenous retroviral (HERV) sequences, and nine genes selected for their role in immune and inflammatory processes. We also explored the possible role of the body mass index (BMI) as an additional susceptibility factor that might influence the effects of NS work on the tested epigenetic modifications.Results and discussionWe observed a positive association between NS and NLRP3 levels (p-value 0.0379). Moreover, NS workers retained different methylation levels for ERVFRD-1 (p-value = 0.0274), HERV-L (p-value = 0.0377), and HERV-P (p-value = 0.0140) elements, and for BIRC2 (p-value = 0.0460), FLRT3 (p-value = 0.0422), MIG6 (p-value = 0.0085), and SIRT1 (p-value = 0.0497) genes. We also observed that the BMI modified the relationship between NS and the methylation of ERVE, HERV-L, and ERVW-1 elements. Overall, our results suggest that HERV methylation could pose as a promising biomolecular sensor to monitor not only the effect of NS work but also the cumulative effect of multiple stressors.

Microplastics have become pervasive in ambient aquatic ecosystems over the last decade and are currently a serious global scale concern. To evaluate the potential toxic effects of PVC (polyvinyl chloride) microplastics on the immune functions of freshwater fish, this study undertook a conducted chronic 60-day dietary exposure experiment with Cyprinus carpio var. larvae. We exposed the fish to four microplastic treatments of different concentrations (food rationed diets): no-plastic (control), 10%, 20% and 30%. At the end of the experimental period the impacts of microplastics on the histology, biochemistry, ROS (reactive oxygen species) levels and gene transcription of immune organs were investigated. The results revealed that PVC microplastics induced cytoplasmic vacuolation in the liver, damaged villi in the intestine, inflammatory cell infiltration, hemosiderosis and vacuolar degeneration in the spleen, glomeruli tuft shrinkage and aggregation of melanin macrophage cells in the kidney. Moreover, following PVC microplastics exposure, ROS levels in the liver and protein levels of pro-inflammatory cytokines including IL-6, IL-8, and TNFα in the liver and serum were increased. Furthermore, modifications in the activities of non-specific immunoenzyme ACP (Acid phosphatase), AKP (alkaline phosphatase), LZM (lysozyme), and expression levels of a range of immune-related genes were observed. Using various techniques at the histological, biochemical and molecular levels, our findings demonstrated the effects of PVC microplastics on changes and imbalances in the immune status of carp. The results of this study provide basic toxicological data toward elucidating and quantifying the impacts of microplastics immunotoxicity on aquatic organisms.

Lemeng Zhang, Yongzhong Luo, Tianli Cheng, Jianhua Chen, Hua Yang, Xiaoping Wen, Zhou Jiang, Haitao Li, Changqie Pan Thoracic Medicine Department 1, Hunan Cancer Hospital, Changsha, Hunan Province, 410013, People’s Republic of ChinaCorrespondence: Yongzhong Luo Tel/Fax +86-731-89762220Email luoyongzhong@hnca.org.cnPurpose: The prognostic value of an N6-methyladenosine (m6A) methylation-related immune gene signature for lung adenocarcinoma (LUAD) was investigated.Patients and Methods: Gene expression and clinical phenotype data of LUAD patients were downloaded from The Cancer Genome Atlas database. A list of immune-related genes was retrieved from the InnateDB database. Correlation analysis, survival analysis, and univariate and multivariate Cox regression analyses were performed. After allocating patients into a high-risk or a low-risk group, the corresponding survival rates, immune microenvironment, expression of immune checkpoint genes, and modulation of Kyoto Encyclopedia of Genes and Genomes pathways were examined. Finally, the expression levels of prognostic biomarkers were assessed in the GSE126044 dataset.Results: Seven m6A-related immune prognostic genes were identified. High expression of PSMD10P1, DIDO1, ABCA5, and CIITA was associated with high survival rates, while that of PRC1, ZWILCH, and ANLN was associated with low survival rates. The high- and low-risk groups showed significant differences in terms of the abundance of six tumor-infiltrating immune cell types and expression of 12 immune checkpoint genes. The risk group acted as an independent prognostic factor (hazard ratio = 0.398, 95% confidence interval = 0.217– 0.729, P = 0.003). Finally, the developed nomogram could predict most efficiently the 1-, 2-, and 3-year survival probability of LUAD patients with a C-index of 0.833.Conclusion: A seven-gene risk signature, associated with the immune microenvironment in LUAD, showed independent prognostic value.Keywords: lung adenocarcinoma, N6-methyladenosine methylation, immune-related genes, immune microenvironment, prognostic signature

Background: Immunological-related genes (IRGs) play a critical role in the immune microenvironment of tumors. Our study aimed to develop an IRGbased survival prediction model for hepatocellular carcinoma (HCC) patients and to investigate the impact of IRGs on the immune microenvironment. Methods: Differentially expressed IRGs were obtained from The Genomic Data Commons Data Portal (TCGA) and the immunology database and analysis portal (ImmPort). The univariate Cox regression was used to identify the IRGs linked to overall survival (OS), and a Lasso-regularized Cox proportional hazard model was constructed. The International Cancer Genome Consortium (ICGC) database was used to verify the prediction model. ESTIMATE and CIBERSORT were used to estimate immune cell infiltration in the tumor immune microenvironment (TIME). RNA sequencing was performed on HCC tissue specimens to confirm mRNA expression. Results: A total of 401 differentially expressed IRGs were identified, and 63 IRGs were found related to OS on the 237 up-regulated IRGs by univariate Cox regression analyses. Finally, five IRGs were selected by the LASSO Cox model, including SPP1, BIRC5, STC2, GLP1R, and RAET1E. This prognostic model demonstrated satisfactory predictive value in the ICGC dataset. The risk score was an independent predictive predictor for OS in HCC patients. Immune-related analysis showed that the immune infiltration level in the high-risk group was higher, suggesting that the 5-IRG signature may play an important role in mediating immune escape and immune resistance in the TIME of HCC. Finally, we confirmed the 5-IRG signature is highly expressed in 65 HCC patients with good predictive power. Conclusion: We established and verified a new prognosis model for HCC patients based on survival-related IRGs, and the signature could provide new insights into the prognosis of HCC. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by communication and social interaction deficits, and by restricted interests and stereotyped, repetitive behavior patterns. ASD has a strong genetic component and a complex architecture characterized by the interplay of rare and common genetic variants. Recently, increasing evidence suggest a significant contribution of immune system dysregulation in ASD. The present paper reviews the latest updates regarding the altered immune landscape of this complex disorder highlighting areas with potential for biomarkers discovery as well as personalization of therapeutic approaches. Cross-talk between the central nervous system and immune system has long been envisaged and recent evidence brings insights into the pathways connecting the brain to the immune system. Disturbance of cytokine levels plays an important role in the establishment of a neuroinflammatory milieu in ASD. Several other immune molecules involved in antigen presentation and inflammatory cellular phenotypes are also at play in ASD. Maternal immune activation, the presence of brain-reactive antibodies and autoimmunity are other potential prenatal and postnatal contributors to ASD pathophysiology. Themolecular players involved in oxidative-stress response andmitochondrial system function, are discussed as contributors to the pro-inflammatory pattern. The gastrointestinal inflammation pathways proposed to play a role in ASD are also discussed. Moreover, the body of evidence regarding some of the genetic factors linked to the immune system dysregulation is reviewed and discussed. Last, but not least, the epigenetic traits and their interactions with the immune system are reviewed as an expanding field in ASD research. Understanding the immune-mediated pathways that influence brain development and function, metabolism, and intestinal homeostasis, may lead to the identification of robust diagnostic or predictive biomarkers for ASD individuals. Thus, novel therapeutic approaches could be developed, ultimately aiming to improve their quality of life. [ABSTRACT FROM AUTHOR]

Background: Colon adenocarcinoma (COAD) is one of the most common gastrointestinal tumors worldwide, and immunotherapy is one of the most promising treatments for it. Identifying immune genes involved in the development and maintenance of cancer is key to the use of tumor immunotherapy. This study aimed to determine the prognostic value of immune genes in patients with COAD and to establish an immune-related gene signature. Differentially expressed genes, immune-related genes (DEIGs), and transcription factors (DETFs) were screened using the following databases: Cistrome, The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and InnateDB. We constructed a network showing the regulation of DEIGs by DETFs. Using weighted gene co-expression network analysis, we prepared 5 co-expressed gene modules; 6 hub genes (CD1A, CD1B, FGF9, GRP, SERPINE1, and F2RL2) obtained using univariate and multivariate regression analysis were used to construct a risk model. Patients from TCGA database were divided into high- and low-risk groups based on whether their risk score was greater or less than the mean; the public dataset GSE40967, which contains gene expression profiles of 566 colon cancer patients, was used for validation. Results: Survival analysis, somatic gene mutations, and tumor-infiltrating immune cells differed significantly between the high- and low-risk groups. Conclusions: This immune-related gene signature could play an important role in guiding treatment, making prognoses, and potentially developing future clinical applications. [ABSTRACT FROM AUTHOR]

Background: Inflammatory responses have drawn more attention to atherosclerosis; however, the immune-related genes (IRGs) as a prognostic factor in atherosclerotic plaque remain to be fully elucidated. Here, the purpose of this study was to investigate whether the IRGs could be identified as a reliable biomarker for predicting ischemic events in patients undergoing carotid endarterectomy (CEA). Methods: Two datasets GSE97210 and GSE21545 were downloaded from the Gene Expression Omnibus (GEO) database. The dataset GSE97210 was used to explore the significant pathways and differentially expressed IRGs (DEIRGs) between plaques and controls, which were further screened to identify the prognostic DEIRGs in the GSE21545 dataset. The identification of molecular subgroups with the prognostic gene expression patterns was achieved through nonnegative matrix factorization (NMF) clustering. Functional analyses including GO, KEGG, GSVA, and GSEA analyses, and immune analyses including xCell and ssGSEA algorithms were conducted to elucidate the underlying mechanisms. The prognostic risk model was constructed using the LASSO algorithm and multivariate Cox regression analysis. Results: A total of 796 DEIRGs (including 588 upregulated and 208 downregulated) were identified. Nine prognostic DEIRGs were further screened with univariate Cox regression analysis. Two clusters with different prognosis were grouped based on the prognostic DEIRGs. Immune infiltration analysis shows that cluster 2 with a better prognosis presented with a higher immune response than cluster 1. A prognostic model based on seven IRGs (IL2RA, NR4A2, DES, ERAP2, SLPI, RASGRP1, and AGTR2) was developed and verified. Consistent with the immune analysis of the cluster, the immune infiltration in the low-risk group with a better prognosis was also more active than that in the high-risk group. Finally, a nomogram based on the seven genes was constructed, which might have future implications in clinical care. Conclusion: The expression of immune-related genes is correlated with the immune microenvironment of atherosclerotic patients and could be applied to predict the ischemic events in patients undergoing CEA accurately. [ABSTRACT FROM AUTHOR]

Intracranial aneurysm (IA), known as the intracranial "unscheduled bomb," is one of the most dangerous cerebrovascular diseases, with unclear pathogenesis. This study aimed to show the mechanisms and identify the new biological targets by applying bioinformatics analysis. Expression profiling for control superficial temporal artery and IA walls in GSE26969 and GSE75436 datasets were downloaded. By executing the LIMMA package in R software, the differentially expressed genes (DEGs) were filtered, and the functional enrichments were consequently performed. Further cross-linking with the 2483 immune-related genes (IRGs) from the ImmPort database, the differentially expressed IRGs were identified. Based on them, the least absolute shrinkage and selection operator logistic regression and support vector machine–recursive feature elimination algorithms were used to screen the biomarkers, which were validated in the GSE54083 datasets. The CIBERSORT algorithm was applied to evaluate the infiltration of immune cells in tissues. A total of 668 DEGs were obtained, and the functional enrichment suggested that they were closely related to the immune process. After intersecting them with the IRGs, 90 differentially expressed IRGs emerged, and ADIPOQ and ESM1 were identified as the biomarkers. Besides, we found that the infiltrated immune cells, such as the mast cells resting, might be associated with them. We explored the contributing factors involving IA, which may generate a better understanding of the complex interactions among them and inspire a promising strategy for clinical works. [ABSTRACT FROM AUTHOR]

Chinese perch (Siniperca chuatsi), an important fish for the aquaculture industry of China, is often affected by viral diseases. A stable and sensitive cell line can play an important role in virus identification and isolation, functional gene identification, virus pathogenic mechanism and antiviral immunity study. In the present study, a new cell line (S. chuatsi skin cell, SCSC) derived from the skin of S. chuatsi was established. The SCSC mainly consisted of fibroblastic‐like cells, which grew well in M199 medium supplemented with 10% foetal bovine serum at 25°C. Chromosome analysis revealed that the SCSC (44%) has a diploid chromosome number of 2n = 48. The SCSC can be transfected and expressed exogenous gene efficiently. It also showed high sensitivity to several aquatic animal viruses from different families including Rhabdoviridae, Iridoviridae and Reoviridae. In addition, RT‐PCR showed that S. chuatsi rhabdovirus (SCRV) started genome replication as early as 3 h post infection in the cells, which also induced the up‐regulation of a variety of immune‐related genes including these related to interleukin family, pattern recognition receptors, JAK–STAT pathway and interferon regulatory factors. In summary, current study provided a new tool in research of fish viruses and its interaction with host. [ABSTRACT FROM AUTHOR]

Background: As the most prevalent valvular heart disease, calcific aortic valve disease (CAVD) has become a primary cause of aortic valve stenosis and insufficiency. We aim to illustrate the roles of immune related genes (IRGs) and immune cells infiltration in the occurrence of CAVD. Methods: Integrative meta-analysis of expression data (INMEX) was adopted to incorporate multiple gene expression datasets of CAVD from Gene Expression Omnibus (GEO) database. By matching the differentially expressed genes (DEGs) to IRGs from "ImmPort" database, differentially expressed immune related genes (DEIRGs) were screened out. We performed enrichment analysis and found that DEIRGs in CAVD were closely related to inflammatory response and immune cells infiltration. We also constructed protein-protein interaction (PPI) network of DEIRGs and identified 5 key DEIRGs in CAVD according to the mixed character calculation results. Moreover, CIBERSORT algorithm was used to explore the profile of infiltrating immune cells in CAVD. Based on Spearman's rank correlation method, correlation analysis between key DEIRGs and infiltrating immune cells was performed. Results: A total of 220 DEIRGs were identified and the enrichment analysis of DEIRGs showed that they were significantly enriched in inflammatory responses. PPI network was constructed and PTPN11, GRB2, SYK, PTPN6 and SHC1 were identified as key DEIRGs. Compared with normal aortic valve tissue samples, the proportion of neutrophils, T cells CD4 memory activated and macrophages M0 was elevated in calcified aortic valves tissue samples, as well as reduced infiltration of macrophages M2 and NK cells activated. Furthermore, key DEIRGs identified in the present study, including PTPN11, GRB2, PTPN6, SYK, and SHC1, were all significantly correlated with infiltration of various immune cells. Conclusion: This meta-analysis suggested that PTPN11, GRB2, PTPN6, SYK, and SHC1 might be key DEIRGs associated with immune cells infiltration, which play a pivotal role in pathogenesis of CAVD. [ABSTRACT FROM AUTHOR]

With an almost global distribution, Varroa destuctor is the leading cause of weakening and loss of honey bee colonies. New substances are constantly being tested in order to find those that will exhibit high anti-Varroa efficacy at low doses/concentrations, without unwanted effects on bees. Lithium (Li) salts stood out as candidates based on previous research. The aims of this study were to evaluate Li citrate hydrate (Li-cit) for its contact efficacy against Varroa, but also the effect of Li-cit on honey bees by estimating loads of honey bee viruses, expression levels of immune-related genes and genes for antioxidative enzymes and oxidative stress parameters on two sampling occasions, before the treatment and after the treatment. Our experiment was performed on four groups, each consisting of seven colonies. Two groups were treated with the test compound, one receiving 5mM and the other 10 mM of Li-cit; the third received oxalic acid treatment (OA group) and served as positive control, and the fourth was negative control (C group), treated with 50% w/v pure sucrosewater syrup. Single trickling treatment was applied in all groups. Both tested concentrations of Li-cit, 5 and 10 mM, expressed high varroacidal efficacy, 96.85% and 96.80%, respectively. Load of Chronic Bee Paralysis Virus significantly decreased (p < 0.01) after the treatment in group treated with 5mM of Li-cit. In OA group, loads of Acute Bee Paralysis Virus and Deformed Wing Virus significantly (p < 0.05) increased, and in C group, loads of all viruses significantly (p < 0.01 or p < 0.001) increased. Transcript levels of genes for abaecin, apidaecin, defensin and vitellogenin were significantly higher (p < 0.05—p < 0.001), while all oxidative stress parameters were significantly lower (p < 0.05—p < 0.001) after the treatment in both groups treated with Li-cit. All presented results along with easy application indicate benefits of topical Li-cit treatment and complete the mosaic of evidence on the advantages of this salt in the control of Varroa. [ABSTRACT FROM AUTHOR]

Despite considerable progress has been made in the understanding of the genetics and molecular biology of renal cell carcinoma (RCC), therapeutic options of patients with papillary renal cell carcinoma (PRCC) are limited. Immunotherapy based on immune checkpoint inhibitors (ICIs) has become a hot point in researching new drug for tumor and been tested in a number of human clinical trials. In this study, an immune-related gene prognostic index (IRGPI) was developed and provided a comprehensive and systematic analysis of distinct phenotypic and molecular portraits in the recognition, surveillance, and prognosis of PRCC. The reliability of the IRGPI was evaluated using independent datasets from GEO database and the expression levels of the genes in the IRGPI detected by real-time PCR. Collectively, the currently established IRGPI could be used as a potential biomarker to evaluate the response and efficacy of immunotherapy in PRCC. [ABSTRACT FROM AUTHOR]

Background: Peripheral biomarkers are increasingly vital non-invasive methods for monitoring coronary artery disease (CAD) progression. Their superiority in early detection, prognosis evaluation and classified diagnosis is becoming irreplaceable. Nevertheless, they are still less explored. This study aimed to determine and validate the diagnostic and therapeutic values of differentially expressed immune-related genes (DE-IRGs) in CAD.Methods: We downloaded clinical information and RNA sequence data from the GEO database. We used R software, GO, KEGG and Cytoscape to analyze and visualize the data. A LASSO method was conducted to identify key genes for diagnostic model construction. The ssGSEA analysis was used to investigate the differential immune cell infiltration. Besides, we constructed CAD mouse model (low-density lipoprotein receptor deficient mice with high fat diet) to discover the correlation between the screened genes and severe CAD progress. We further uncovered the role of IL13RA1 might play in atherosclerosis.Results: A total of 762 differential genes were identified between the peripheral blood of 218 controls and 199 CAD patients, which were significantly associated with infection, immune response and neural activity. 58 DE-IRGs were obtained by overlapping the differentially expressed genes(DEGs) and immune-related genes downloaded from ImmpDb database. Through LASSO regression, CCR9, CER1, CSF2, IL13RA1, INSL5, MBL2, MMP9, MSR1, NTS, TNFRSF19, CXCL2, HTR3C, IL1A, and NR4A2 were distinguished as peripheral biomarkers of CAD with eligible diagnostic capabilities in the training set (AUC = 0.968) and test set (AUC = 0.859). The ssGSEA analysis showed that the peripheral immune cells had characteristic distribution in CAD and also close relationship with specific DE-IRGs. RT-qPCR test showed that CCR9, CSF2, IL13RA1, and NTS had a significant correlation with LDLR-/- mice. IL13RA1 knocked down in RAW264.7 cell lines decreased SCARB1 and ox-LDL-stimulated CD36 mRNA expression, TGF-β, VEGF-C and α-SMA protein levels and increased the production of IL-6, with downregulation of JAK1/STAT3 signal pathway.Conclusions: We constructed a diagnostic model of advanced-stage CAD based on the screened 14 DE-IRGs. We verified 4 genes of them to have a strong correlation with CAD, and IL13RA1 might participate in the inflammation, fibrosis, and cholesterol efflux process of atherosclerosis by regulating JAK1/STAT3 pathway. [ABSTRACT FROM AUTHOR]

(1) Objective: Identification of potential genetic biomarkers for various glomerulonephritis (GN) subtypes and discovering the molecular mechanisms of GN. (2) Methods: four microarray datasets of GN were downloaded from Gene Expression Omnibus (GEO) database and merged to obtain the gene expression profiles of eight GN subtypes. Then, differentially expressed immune-related genes (DIRGs) were identified to explore the molecular mechanisms of GN, and single-sample gene set enrichment analysis (ssGSEA) was performed to discover the abnormal inflammation in GN. In addition, a nomogram model was generated using the R package "glmnet", and the calibration curve was plotted to evaluate the predictive power of the nomogram model. Finally, deep learning (DL) based on a multilayer perceptron (MLP) network was performed to explore the characteristic genes for GN. (3) Results: we screened out 274 common up-regulated or down-regulated DIRGs in the glomeruli and tubulointerstitium. These DIRGs are mainly involved in T-cell differentiation, the RAS signaling pathway, and the MAPK signaling pathway. ssGSEA indicates that there is a significant increase in DC (dendritic cells) and macrophages, and a significant decrease in neutrophils and NKT cells in glomeruli, while monocytes and NK cells are increased in tubulointerstitium. A nomogram model was constructed to predict GN based on 7 DIRGs, and 20 DIRGs of each subtype of GN in glomeruli and tubulointerstitium were selected as characteristic genes. (4) Conclusions: this study reveals that the DIRGs are closely related to the pathogenesis of GN and could serve as genetic biomarkers in GN. DL further identified the characteristic genes that are essential to define the pathogenesis of GN and develop targeted therapies for eight GN subtypes. [ABSTRACT FROM AUTHOR]

The expression stability of four potential reference genes (EF1‐α, β‐actin, GAPDH and SubF0) was evaluated to normalize the expression of six immune‐related genes (proPO1, proPO2, MnSOD, PAP, Rab7 and NOS) in different tissues of black tiger shrimp (Penaeus monodon) following melanin injection and using the geNorm and NormFinder algorithms. The stability rankings of the reference genes were as follows: EF1‐α > β‐actin > SubF0 > GAPDH in the muscle, GAPDH > EF1‐α > SubF0 > β‐actin in the carapace and EF1‐α > GAPDH > β‐actin > SubF0 in the haemolymph. To normalize the expression of six immune‐related genes of P. monodon in different tissues under the effect of melanin injection, EF1‐α and GAPDH alone were the most suitable reference genes for the muscle and carapace, respectively, whereas the combination of EF1‐α + β‐actin was the most suitable for the haemolymph. The expression of these six immune‐related genes in P. monodon was upregulated in the haemolymph, downregulated in the carapace and nearly unchanged in the muscle of the melanin‐injected group compared to that in the control group. Our results provide reference genes for reverse transcription quantitative polymerase chain reaction to analyse the protective effects of melanin in black tiger shrimp. [ABSTRACT FROM AUTHOR]

Streptococcus agalactiae is common pathogenic bacteria in aquaculture and can cause mass mortality after fish infection. This study aimed to investigate the effects of S. agalactiae infection on the immune and antioxidant regulatory mechanisms of golden pompano (Trachinotus ovatus). Serum and liver samples were obtained at 0, 6, 12, 24, 48, 96, and 120 h after golden pompano infection with S. agalactiae for enzyme activity and gene expression analyses. After infection with S. agalactiae, the content of reactive oxygen species (ROS) in serum was significantly increased (p < 0.05). Serum levels of glucose (GLU), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and malondialdehyde (MDA) increased and then decreased (p < 0.05), reaching a maximum at 6 h. Serum antioxidant enzyme (LZM) activity increased significantly (p < 0.05) and reached a maximum at 120 h. In addition, the mRNA expression levels of antioxidant genes (SOD, CAT, and GPx) in the liver increased and then decreased, reaching the maximum at 24 h, 48 h, and 24 h, respectively. During the experimental period, the mRNA expression levels of NF-κB-related genes of the inflammatory signaling pathway inhibitory κB (IκB) showed an overall decreasing trend (p < 0.05) and the lowest expression at 120 h, whereas the mRNA expression levels of tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), IκB kinase (IKK), and nuclear factor NF-κB increased significantly (p < 0.05) and the highest expression was at 120 h. In conclusion, these results showed that S. agalactiae could activate internal regulatory signaling in the liver of golden pompano to induce defense and immune responses. This study is expected to lay a foundation to develop the healthy aquaculture of golden pompano and promote a more comprehensive understanding of its disease resistance mechanisms. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence supports that lactate plays an important role in tumor proliferation, invasion and within the tumor microenvironment (TME). This is particularly relevant in lung adenocarcinoma (LUAD). Therefore, there is a current need to investigate lactate metabolism in LUAD patients and how lactate metabolism is affected by different therapies. Methods: Data from LUAD patients were collected from The Cancer Genome Atlas (TCGA) and patients were divided into two subtypes according to 12 lactate metabolism-related genes to explore the effect of lactate metabolism in LUAD. We established a lactate-related prognostic indicator (LRPI) based on different gene expression profiles. Subsequently, we investigated associations between this LRPI and patient survival, molecular characteristics and response to therapy. Some analyses were conducted using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Results: The two LUAD subtypes exhibited different levels of lactate metabolism, in which patients that displayed high lactate metabolism also had a worse prognosis and a poorer immune environment. Indeed, LRPI was shown to accurately predict the prognosis of LUAD patients. Patients with a high LRPI showed a poor prognosis coupled with high sensitivity to chemotherapy using GDSC data. Meanwhile, these patients exhibited a high responsiveness to immunotherapy in TMB (Tumor mutation burden) and TIDE (Tumor Immune Dysfunction and Exclusion) analyses. Conclusion: We validated the effect of lactate metabolism on the prognosis of LUAD patients and established a promising biomarker. LRPI can predict LUAD patient survival, molecular characteristics and response to therapy, which can aid the individualized treatment of LUAD patients. [ABSTRACT FROM AUTHOR]

Background: Esophageal cancer is a tumor type with high invasiveness and low prognosis. As immunotherapy has been shown to improve the prognosis of esophageal cancer patients, we were interested in the establishment of an immune-associated gene prognostic index to effectively predict the prognosis of patients. Methods: To establish the immune-related gene prognostic index of esophageal cancer (EC), we screened 363 upregulated and 83 downregulated immune-related genes that were differentially expressed in EC compared to normal tissues. By multivariate Cox regression and weighted gene coexpression network analysis (WGCNA), we built a prognostic model based on eight immune-related genes (IRGs). We confirmed the prognostic model in both TCGA and GEO cohorts and found that the low-risk group had better overall survival than the high-risk group. Results: In this study, we identified 363 upregulated IRGs and 83 downregulated IRGs. Next, we found a prognostic model that was constructed with eight IRGs (OSM, CEACAM8, HSPA6, HSP90AB1, PCSK2, PLXNA1, TRIB2, and HMGB3) by multivariate Cox regression analysis and WGCNA. According to the Kaplan–Meier survival analysis results, the model we constructed can predict the prognosis of patients with esophageal cancer. This result can be verified by the Gene Expression Omnibus (GEO). Patients were divided into two groups with different outcomes. IRGPI-low patients had better overall survival than IRGPI-high patients. Conclusion: Our findings indicated the potential value of the IRGPI risk model for predicting the prognosis of EC patients [ABSTRACT FROM AUTHOR]

Immune dysfunction has been implicated in the pathogenesis of schizophrenia (SZ). Despite previous studies showing a broad link between immune dysregulation and the central nervous system of SZ, the exact relationship has not been completely elucidated. With immune infiltration analysis as an entry point, this study aimed to explore the relationship between schizophrenia and the immune system in more detail from brain regions, immune cells, genes, and pathways. Here, we comprehensively analyzed the hippocampus (HPC), prefrontal cortex (PFC), and striatum (STR) between SZ and control groups. Differentially expressed genes (DEGs) and functional enrichment analysis showed that three brain regions were closely related to the immune system. Compared with PFC and STR, there were 20 immune-related genes (IRGs) and 42 immune pathways in HPC. The results of immune infiltration analysis showed that the differential immune cells in HPC were effector memory T (Tem) cells. The correlation of immune-related DEGs (IDEGs) and immune cells further analysis showed that NPY, BLNK, OXTR, and FGF12, were moderately correlated with Tem cells. Functional pathway analysis indicated that these four genes might affect Tem by regulating the PI3K-AKT pathway and the neuroactive ligand-receptor interaction pathway. The receiver operating characteristic curve (ROC) analysis results indicated that these four genes had a high diagnostic ability (AUC=95.19%). Finally, the disease animal model was successfully replicated, and further validation was conducted using the real-time PCR and the western blot. These results showed that these gene expression changes were consistent with our previous expression profiling. In conclusion, our findings suggested that HPC in SZ may be more closely related to immune disorders and modulate immune function through Tem, PI3K-Akt pathway, and neuroactive ligand-binding receptor interactions. To the best of our knowledge, the Immucell AI tool has been applied for the first time to analyze immune infiltration in SZ, contributing to a better understanding of the role of immune dysfunction in SZ from a new perspective. [ABSTRACT FROM AUTHOR]

Aquaculture research has focused on polysaccharides as they are among the most promising new-generation immunostimulant used to control aquatic diseases. The aim of this study was to investigate the immunomodulatory effects of fermented wheat bran polysaccharides (FWBPs) on juvenile common carp (Cyprinus carpio). Carps were fed different FWBP amounts (0%, 0.1%, 0.2%, and 0.4%) for 8 weeks and then their skin mucus and serum immune parameters, hepatopancreas antioxidant indicators, and immune-related gene expression in the intestines, kidneys, and spleen were measured. The skin mucus IgM levels significantly increased in 0.1% FWBP group, but decreased in 0.4% FWBP group. The skin mucus protease and the serum alkaline phosphatase activities increased significantly in the 0.2%, 0.1%, and 0.4% FWBP groups, respectively. The serum total Ig levels increased noticeably in the 0.1% and 0.2% FWBP groups. The highest and lowest serum lysozyme activities were observed in the 0.1% and 0.4% FWBP groups, respectively. The hepatopancreatic total superoxide dismutase activity was higher in the 0.1% FWBP group than in the control. The malondialdehyde levels decreased significantly in the 0.2% and 0.4% groups. The intestinal mRNA levels of the LZM-C and IL-10 genes were significantly higher in the 0.2% than in the 0.4% FWBP group; TNF-α was significantly upregulated in the 0.1% group. The gene expression in the kidneys did not differ significantly among the treatments, except for a significant increase in the IL-10 expression in the 0.1% treatment. Significantly elevated expression of LZM-C in 0.2% group and IL-10 in 0.1% group was observed in the spleens. TNF-α and IL-1β were significantly downregulated in the 0.4% group. These results suggest that FWBPs could be used as immunostimulant feed additives in common carp cultures. [ABSTRACT FROM AUTHOR]

Tumor budding (TB) histology has become a critical biomarker for several solid cancers. Despite the accumulating evidence for the association of TB histology with poor prognosis, the biological characteristics of TB are little known about in the context related to the tumor immune microenvironment (TIME) in uterine cervical cancer (CC). Therefore, this study aimed to identify the transcriptomic immune profiles related to TB status and further provide robust medical evidence for clinical application. In our study, total RNA was extracted and sequenced from 21 CC tissue specimens. As such, 1494 differentially expressed genes (DEGs) between the high- and low-TB groups were identified by DESeq2. After intersecting the list of DEGs and public immune genes, we selected 106 immune-related DEGs. Then, hub genes were obtained using Least Absolute Shrinkage and Selection Operator regression. Finally, the correlation between the hub genes and immune cell types was analyzed and four candidate genes were identified (one upregulated (FCGR3B) and three downregulated (ROBO2, OPRL1, and NR4A2) genes). These gene expression levels were highly accurate in predicting TB status (area under the curve >80%). Interestingly, FCGR3B is a hub gene of several innate immune pathways; its expression significantly differed in the overall survival analysis (p = 0.0016). In conclusion, FCGR3B, ROBO2, OPRL1, and NR4A2 expression can strongly interfere with TB growth and replace TB to stratify CC patients. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular diseases, such as aortic valve calcification (AVC) and carotid atherosclerosis (CAS), impose substantial health challenges on a global scale. Both disorders have overlapping risk factors, which might trigger similar immune-inflammatory reactions in both diseases., Methods: Shared differentially expressed genes (DEGs) were identified in the AVC and CAS datasets from the Gene Expression Omnibus (GEO). Candidate hub genes associated with immunity were identified using LASSO and immune cell infiltration analysis, and single gene set enrichment analysis (GSEA) was performed on the datasets. Subsequently, the hub genes were confirmed by qRT‒PCR validation in tissue samples., Results: A total of 140 upregulated and 65 downregulated common genes were screened. Enrichment analyses highlighted immune system processes, response to stress, and cytokine pathways among the identified CEGs. LASSO identified candidate hub genes, including ANGPTL1, CX3CR1, and CCL4. Immune cell infiltration analysis emphasized the participation of immune cells, including macrophages, γδ T cells, and resting NK cells. The three hub genes were validated by qRT‒PCR analysis., Conclusion: Our study explored immunological processes, including immune-related genes and cells, involved in the development of AVC and CAS. In particular, the identified hub genes ANGPTL1, CX3CR1, and CCL4 play crucial roles in mediating immune-inflammatory responses, which are central to the pathogenesis of these cardiovascular diseases, and the involvement of these genes in key immune pathways suggests that they could serve as potential biomarkers for early diagnosis or as targets for therapeutic strategies., Competing Interests: The authors declare that this study was conducted in the absence of any commercial or financial relationship that could be construed as a potential conflict of interest., (© 2024 Wei et al.)

Lupus nephritis (LN) is a challenging condition with limited diagnostic and treatment options. In this study, we applied 12 distinct machine learning algorithms along with Non-negative Matrix Factorization (NMF) to analyze single-cell datasets from kidney biopsies, aiming to provide a comprehensive profile of LN. Through this analysis, we identified various immune cell populations and their roles in LN progression and constructed 102 machine learning-based immune-related gene (IRG) predictive models. The most effective models demonstrated high predictive accuracy, evidenced by Area Under the Curve (AUC) values, and were further validated in external cohorts. These models highlight six hub IRGs ( CD14 , CYBB , IFNGR1 , IL1B , MSR1 , and PLAUR ) as key diagnostic markers for LN, showing remarkable diagnostic performance in both renal and peripheral blood cohorts, thus offering a novel approach for noninvasive LN diagnosis. Further clinical correlation analysis revealed that expressions of IFNGR1, PLAUR , and CYBB were negatively correlated with the glomerular filtration rate (GFR), while CYBB also positively correlated with proteinuria and serum creatinine levels, highlighting their roles in LN pathophysiology. Additionally, protein-protein interaction (PPI) analysis revealed significant networks involving hub IRGs, emphasizing the importance of the interleukin family and chemokines in LN pathogenesis. This study highlights the potential of integrating advanced genomic tools and machine learning algorithms to improve diagnosis and personalize management of complex autoimmune diseases like LN., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Mou, Lu, Wu, Pu, Huang and Wang.)

Introduction: The tumor microenvironment and IRGs are highly correlated with tumor occurrence, progression, and prognosis. However, their roles in grade II and III gliomas, termed LGGs in this study, remain to be fully elucidated. Our research aims to develop immune-related features for risk stratification and prognosis prediction in LGG., Methods: Using the ssGSEA method, we assessed the immune characteristics of the LGG population. We conducted differential analysis using LGG samples from the TCGA database and normal samples from GTEx, identifying 412 differentially expressed immune-related genes (DEIRGs). Subsequently, we utilized univariate Cox, LASSO, and multivariate Cox regression analyses to establish both a gene predictive model and a nomogram predictive model., Results: Here, we found that the ESTIMATE score, immune score and stromal score of high-immunity, high-grade and isocitrate dehydrogenase (IDH) wild-type glioma were higher than those of the corresponding group, and the tumor purity was lower. Higher ESTIMATE scores, stromal scores and immune scores indicated a poor prognosis in patients with LGG. Our four-gene prognostic model demonstrated superior accuracy compared to other molecular features. Validation using the CGGA as a testing set and the combined TCGA and CGGA cohort confirmed its robust prognostic value. Additionally, a nomogram integrating the prognostic model and clinical variables showed enhanced predictive capability., Discussion: Our study highlights the prognostic significance of the identified four DEIRGs (KLRC3, MR1, PDIA2, and RFXAP) in LGG patients. The predictive model and nomogram developed herein offer valuable tools for personalized treatment strategies in LGG. Future research should focus on further validating these findings and exploring the functional roles of these DEIRGs within the LGG tumor microenvironment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Wang, Liu and Wu.)

Zhen Sun1,2 &ast;, Zhenhua Lu1 &ast;, Rui Li,1,2 Weiwei Shao,1,2 Yangyang Zheng,1,2 Xiaolei Shi,1 Yao Li,1 Jinghai Song1,2 1Department of General Surgery, Department of Hepato-Bilio-Pancreatic Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, People’s Republic of China; 2Graduate School of Peking Union Medical College, Beijing, 100730, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jinghai Song Email jhaisong2003@163.comBackground: The aim of this study was to screen and identify immunoautophagy-related genes (IARGs) in HCC patients and clarify their potential prognostic value in HCC patients.Methods: Immune-related genes and autophagy-related gene were downloaded from public databases. Cox regression analysis was used to selected several immunoautophagy-related genes to establish a prognostic model, and patients were divided into high- and low-risk groups based on median risk score. We analyzed the overall survival and clinicopathological characteristics between two groups. Meanwhile, internal validation dataset and external ICGC dataset were used to verify robustness of the model. Associations between six immune cells infiltrates and risk score were analyzed.Results: A prognostic model was established based on CANX and HDAC1. The prognoses of the high-risk group were worse than low-risk group in both TCGA and ICGC datasets. Multivariate Cox regression analysis showed that risk score was an independent prognostic factor for HCC patients. Results showed that the risk score in young group was higher than elderly group. Patients with poorly differentiated tumor may have high risk score and poor survival. The score was positively correlated with immune cells.Conclusion: Our study shows that immunoautophagy-related genes have potential prognostic value for patients with HCC and may provide new information and direction for targeted therapy.Keywords: hepatocellular carcinoma, immune-related genes, autophagy-related gene, overall survival

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by communication and social interaction deficits, and by restricted interests and stereotyped, repetitive behavior patterns. ASD has a strong genetic component and a complex architecture characterized by the interplay of rare and common genetic variants. Recently, increasing evidence suggest a significant contribution of immune system dysregulation in ASD. The present paper reviews the latest updates regarding the altered immune landscape of this complex disorder highlighting areas with potential for biomarkers discovery as well as personalization of therapeutic approaches. Cross-talk between the central nervous system and immune system has long been envisaged and recent evidence brings insights into the pathways connecting the brain to the immune system. Disturbance of cytokine levels plays an important role in the establishment of a neuroinflammatory milieu in ASD. Several other immune molecules involved in antigen presentation and inflammatory cellular phenotypes are also at play in ASD. Maternal immune activation, the presence of brain-reactive antibodies and autoimmunity are other potential prenatal and postnatal contributors to ASD pathophysiology. The molecular players involved in oxidative-stress response and mitochondrial system function, are discussed as contributors to the pro-inflammatory pattern. The gastrointestinal inflammation pathways proposed to play a role in ASD are also discussed. Moreover, the body of evidence regarding some of the genetic factors linked to the immune system dysregulation is reviewed and discussed. Last, but not least, the epigenetic traits and their interactions with the immune system are reviewed as an expanding field in ASD research. Understanding the immune-mediated pathways that influence brain development and function, metabolism, and intestinal homeostasis, may lead to the identification of robust diagnostic or predictive biomarkers for ASD individuals. Thus, novel therapeutic approaches could be developed, ultimately aiming to improve their quality of life.

With an almost global distribution, Varroa destuctor is the leading cause of weakening and loss of honey bee colonies. New substances are constantly being tested in order to find those that will exhibit high anti-Varroa efficacy at low doses/concentrations, without unwanted effects on bees. Lithium (Li) salts stood out as candidates based on previous research. The aims of this study were to evaluate Li citrate hydrate (Li-cit) for its contact efficacy against Varroa, but also the effect of Li-cit on honey bees by estimating loads of honey bee viruses, expression levels of immune-related genes and genes for antioxidative enzymes and oxidative stress parameters on two sampling occasions, before the treatment and after the treatment. Our experiment was performed on four groups, each consisting of seven colonies. Two groups were treated with the test compound, one receiving 5 mM and the other 10 mM of Li-cit; the third received oxalic acid treatment (OA group) and served as positive control, and the fourth was negative control (C group), treated with 50% w/v pure sucrose-water syrup. Single trickling treatment was applied in all groups. Both tested concentrations of Li-cit, 5 and 10 mM, expressed high varroacidal efficacy, 96.85% and 96.80%, respectively. Load of Chronic Bee Paralysis Virus significantly decreased (p < 0.01) after the treatment in group treated with 5 mM of Li-cit. In OA group, loads of Acute Bee Paralysis Virus and Deformed Wing Virus significantly (p < 0.05) increased, and in C group, loads of all viruses significantly (p < 0.01 or p < 0.001) increased. Transcript levels of genes for abaecin, apidaecin, defensin and vitellogenin were significantly higher (p < 0.05—p < 0.001), while all oxidative stress parameters were significantly lower (p < 0.05—p < 0.001) after the treatment in both groups treated with Li-cit. All presented results along with easy application indicate benefits of topical Li-cit treatment and complete the mosaic of evidence on the advantages of this salt in the control of Varroa.

Immune-related genes play a key role in regulating the cancer immune microenvironment, influencing the overall survival of patients with hepatocellular carcinoma (HCC). Along with the rapid development of immunotherapy, identifying immune-related genes with prognostic value in HCC has attracted increasing attention. Here, we aimed to develop a prognostic signature based on immune-related genes. By investigating the transcriptome landscape of 374 HCC and 160 non-HCC samples in silico, a total of 2251 differentially expressed genes were identified. Among which, 183 differentially expressed immune-related genes were subjected to a univariate Cox proportional hazard model to screen for genes with possible prognostic significance. A 10-gene prognostic signature, including HLA-G, S100A9, S100A10, DCK, CCL14, NRAS, EPO, IL1RN, GHR and RHOA, was generated employing a multivariate Cox proportional hazard model. Kaplan–Meier and Receiver Operator Characteristic (ROC) curves were used to evaluate the prognostic utility of the 10-gene signature. Moreover, the underlying mechanisms of these genes were analyzed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. According to the Tumor Immune Estimation Resource (TIMER) database, our prognostic signature was significantly associated with tumor-infiltrating B cells, CD4 T cells, dendritic cells, macrophages and neutrophils. Our study provides a novel prognostic signature based on immune-related genes associated with clinical outco mes of HCC.

Background: Glioblastoma multiforme (GBM) is a common malignant brain tumor with high mortality. It is urgently necessary to develop a new treatment because traditional approaches have plateaued. Purpose: Here, we identified an immune-related gene (IRG)-based prognostic signature to comprehensively define the prognosis of GBM. Methods: Glioblastoma samples were selected from the Chinese Glioma Genome Atlas (CGGA). We retrieved IRGs from the ImmPort data resource. Univariate Cox regression and LASSO Cox regression analyses were used to develop our predictive model. In addition, we constructed a predictive nomogram integrating the independent predictive factors to determine the one-, two-, and 3-year overall survival (OS) probabilities of individuals with GBM. Additionally, the molecular and immune characteristics and benefits of ICI therapy were analyzed in subgroups defined based on our prognostic model. Finally, the proteins encoded by the selected genes were identified with liquid chromatography-tandemmass spectrometry and western blotting (WB). Results: Six IRGs were used to construct the predictive model. The GBM patients were categorized into a high-risk group and a low-risk group. High-risk group patients had worse survival than low-risk group patients, and stronger positive associations with multiple tumor-related pathways, such as angiogenesis and hypoxia pathways, were found in the high-risk group. The high-risk group also had a low IDH1 mutation rate, high PTEN mutation rate, low 1p19q co-deletion rate and low MGMT promoter methylation rate. In addition, patients in the high-risk group showed increased immune cell infiltration, more aggressive immune activity, higher expression of immune checkpoint genes, and less benefit from immunotherapy than those in the low-risk group. Finally, the expression levels of TNC and SSTR2 were confirmed to be significantly associated with patient prognosis by proteinmass spectrometry and WB. Conclusion: Herein, a robust predictive model based on IRGs was developed to predict the OS of GBM patients and to aid future clinical research. [ABSTRACT FROM AUTHOR]

Clear Cell Renal Carcinoma (ccRCC) accounts for nearly 80% of renal carcinoma cases, and immunotherapy plays an important role in ccRCC therapy. However, the responses to immunotherapy and overall survival for ccRCC patients are still hard to predict. Here, we constructed an immune-related predictive signature using 19 genes based on TCGA datasets. We also analyzed its relationships between disease prognosis, infiltrating immune cells, immune subtypes, mutation load, immune dysfunction, immune escape, etc. We found that our signature can distinguish immune characteristics and predict immunotherapeutic response for ccRCC patients with better prognostic prediction value than other immune scores. The expression levels of prognostic genes were determined by RT-qPCR assay. This signature may help to predict overall survival and guide the treatment for patients with ccRCC. [ABSTRACT FROM AUTHOR]

Aeromonas are autochthonous bacteria of aquatic environments that are considered to be emerging pathogens to humans, producing diarrhea, bacteremia, and wound infections. Genetic identification shows that 95.4% of the strains associated with clinical cases correspond to the species Aeromonas caviae (37.26%), Aeromonas dhakensis (23.49%), Aeromonas veronii (21.54%), and Aeromonas hydrophila (13.07%). However, few studies have investigated the human immune response against some Aeromonas spp. such as A. hydrophila, Aeromonas salmonicida, and A. veronii. The present study aimed to increase the knowledge about the innate human immune response against six Aeromonas species, using, for the first time, an in vitro infection model with the monocytic human cell line THP-1, and to evaluate the intracellular survival, the cell damage, and the expression of 11 immune-related genes (TLR4, TNF-α, CCL2, CCL20, JUN, RELA, BAX, TP53, CASP3, NLRP3, and IL-1β). Transcriptional analysis showed an upregulated expression of a variety of the monocytic immune-related genes, with a variable response depending upon the Aeromonas species. The species that produced the highest cell damage, independently of the strain origin, coincidentally induced a higher expression of immune-related genes and corresponded to the more prevalent clinical species A. dhakensis, A. veronii, and A. caviae. Additionally, monocytic cells showed an overexpression of the apoptotic and pyroptotic genes involved in cell death after A. dhakensis, A. caviae, and Aeromonas media infection. However, the apoptosis route seemed to be the only way of producing cell damage and death in the case of the species Aeromonas piscicola and Aeromonas jandaei, while A. veronii apparently only used the pyroptosis route. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is one of the most common malignancies and its incidence and mortality are increasing yearly. 5-Fluorouracil (5-FU) has long been used as a standard first-line treatment for CRC patients. Although 5-FU-based chemotherapy is effective for advanced CRC, the consequent resistance remains a key problem and causes the poor prognosis of CRC patients. Thus, there is an urgent need to identify new biomarkers to predict the response to 5-FU-based chemotherapy. Methods: CRC samples were retrieved from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). The immune-related genes were retrieved from the ImmPort database. Single-cell sequencing results from colorectal cancer were obtained by the ArrayExpress database. 5-FU resistance-related genes were filtered and validated by R packages. ESTIMATE algorithms were used to assess the tumor microenvironment (TME). KEGG and GO analysis were performed to explore the biological signaling pathway for resistant-response patients and sensitive-response patients in the tumor microenvironment. pRRophetic algorithms were used to predict 5-FU sensitivity. GSEA and GSVA analysis was performed to excavate the biological signaling pathway of the RBP7 gene. Results: Nine immune-related genes were identified to be associated with 5-FU resistance and poor disease-free survival (DFS) of CRC patients and the signature of these genes was developed in a DFS-prognostic model. Four immune-related genes were determined to be associated with 5-FU resistance and overall survival (OS) of CRC patients. The signature of these genes was developed an OS-prognostic model. ESTIMATE scores showed a significant difference between 5-FU resistant and 5-FU sensitive CRC patients. Resistant-response patients and sensitive-response patients to 5-FU based chemotherapy showed different GO and KEGG enrichment on the tumor microenvironment. RBP7, as a tumor immune microenvironment (TIME) related gene, was found to have the potential of predicting chemotherapy resistance and poor prognosis of CRC patients. GSEA analysis showed multiple signaling differences between the high and low expression of RBP7 in CRC patients. Hypoxia and TNFα signaling via NFκB gene sets were significantly different between chemotherapy resistant (RBP7High) and chemotherapy sensitive (RBP7Low) patients. Single-cell RNA-seq suggested RBP7 was centrally distributed in endothelial stalk cells, endothelial tip cells, and myeloid cells. Conclusions: Immune-related genes will hopefully be potential prognostic biomarkers to predict chemotherapy resistance for CRC. RBP7 may function as a tumor microenvironment regulator to induce 5-FU resistance, thereby affecting the prognosis of CRC patients. [ABSTRACT FROM AUTHOR]

Breast cancer (BRCA) has the highest incidence rate among female tumours. The function of the immune system affects treatment efficacy and prognosis in patients with BRCA. However, the exact role of immune-related genes (IRGs) in stage N+M0 BRCA is unknown. We constructed a predictive risk scoring model with five IRGs (CDH1 , FGFR3 , INHBA , S100B , and SCG2) based on the clinical, mutation, and RNA sequencing data of individuals with stage N+M0 BRCA sourced from The Cancer Genome Atlas. Results from the Shandong Cancer Hospital and Institute validation cohort suggested that regardless of clinical stage, tumour size, or the number of lymph node metastases, this model was able to reliably discriminate low-risk patients from high-risk ones and assess the prognosis of patients with stage N+M0 BRCA, and low-risk patients could benefit more from immunotherapy than high-risk patients. In addition, significant inter-group variations in immunocyte infiltration and the tumour microenvironment were observed. Moreover, risk score and age were found to be independent factors in multivariate COX regression analysis, which influenced the outcome of patients with stage N+M0 BRCA. Based on the above findings, we plotted a prognostic nomogram. Finally, we constructed a lncRNA KCNQ1OT1-LINC00665-TUG1/miR-9-5p/CDH1 regulatory axis of the ceRNA network to explore the mechanism of BRCA progression. In summary, we conducted a systemic and extensive bioinformatics investigation and established an IRG-based prognostic scoring model. Finally, we constructed a ceRNA regulatory axis that might play a significant role in BRCA development. More research is required to confirm this result. Scoring system-based patient grouping can help predict the outcome of patients with stage N+M0 BRCA more effectively and determine their sensitivity to immunotherapies, which will aid the development of personalised therapeutic strategies and inspire the research and development of novel medications. [ABSTRACT FROM AUTHOR]

Background: Multiple myeloma (MM) is characterized by abnormal proliferation of bone marrow clonal plasma cells. Tumor immunotherapy, a new therapy that has emerged in recent years, offers hope to patients, and studying the expression characteristics of immune-related genes (IRGs) based on whole bone marrow gene expression profiling (GEP) in MM patients can help guide personalized immunotherapy. Methods: In this study, we explored the potential prognostic value of IRGs in MM by combining GEP and clinical data from the GEO database. We identified hub IRGs and transcription factors (TFs) associated with disease progression by Weighted Gene Co-expression Network Analysis (WGCNA), and modeled immune-related prognostic signature by univariate and multivariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis. Subsequently, the prognostic ability of signature was verified by multiple statistical methods. Moreover, ssGSEA and GSEA algorithm reveled different immunological characteristics and biological function variation in different risk groups. We mapped the hub IRGs by protein-protein interaction network (PPI) and extracted the top 10 ranked genes. Finally, we conducted vitro assays on two alternative IRGs. Results: Our study identified a total of 14 TFs and 88 IRGs associated with International Staging System (ISS). Ten IRGs were identified by Cox -LASSO regression analysis, and used to develop optimal prognostic signature for overall survival (OS) in MM patients. The 10-IRGs were BDNF, CETP, CD70, LMBR, LTBP1, NENF, NR1D1, NR1H2, PTK2B and SEMA4. In different groups, risk signatures showed excellent survival prediction ability, and MM patients also could be stratified at survival risk. In addition, IRF7 and SHC1 were hub IRGs in PPI network, and the vitro assays proved that they could promote tumor progression. Notably, ssGSEA and GSEA results confirmed that different risk groups could accurately indicate the status of tumor microenvironment (TME) and activation of biological pathways. Conclusion: Our study suggested that immune-related signature could be used as prognostic markers in MM patients. [ABSTRACT FROM AUTHOR]

Background: Prostatic cancer (PCa) is one of the most common malignant tumors in men worldwide. Emerging evidence indicates significance of hypoxia and immunity in PCa invasion and metastasis. This study aimed to develop a hypoxia- and immune-related gene risk signature and explore the molecular mechanisms to formulate a better prognostic tool for PCa patients.Methods: The hypoxia and immune scores of all PCa patients in The Cancer Genome Atlas (TCGA) dataset were calculated via the maximally selected rank statistics method and the ESTIMATE algorithm. From common genes identified overlapping hypoxia- and immune-related differentially expressed genes (DE-HRGs and DE-IRGs), a hypoxia- and immune-related gene risk signature was developed utilizing univariate and multivariate Cox regression analyses, and validated in the Memorial Sloan Kettering Cancer Centre (MSKCC) database. The immune cell infiltration level of PCa samples were evaluated with ssGSEA algorithm. Differential expression of prognostic genes was evidenced by immunohistochemistry and western blot (WB) in paired PCa samples. Expression levels of these genes and their variations under regular and hypoxic conditions were examined in cell lines. The functional effects of the prognostic gene on PCa cells were examined by wound healing and transwell assays.Results: A hypoxia- and immune-related gene risk signature constructed by ISG15 and ZFP36 displays significant predictive potency, with higher risk score representing worse survival. A nomogram based on independent prognostic factors including the risk score and Gleason score exhibited excellent clinical value in the survival prediction of PCa. Infiltration levels of eosinophils, neutrophils, Tcm, Tem, TFH, Th1 cells, and Th17 cells were significantly lower in the high-risk group. Conversely, aDC, pDC, T helper cells, and Tregs were significantly higher. Additionally, the two prognostic genes were closely correlated with the tumor-infiltrating immune cell subset in PCa progression. RT-qPCR and WB presented higher and lower expression of ISG15 and ZFP36 in PCa cells, respectively. They were correspondingly increased and decreased in PCa cells under hypoxic conditions. Wound healing and transwell assays showed that over-expression of ISG15 promoted the migration and invasion of PCa cells.Conclusion: Our study identified a novel hypoxia- and immune-related gene signature, contributing a new perspective to the treatment of PCa. [ABSTRACT FROM AUTHOR]

Background: Locally advanced rectal cancers (LARC) show a highly variable response to neoadjuvant chemoradiotherapy (nCRT), and the impact of the tumor immune response in this process is poorly understood. This study aimed to characterize the immune-related gene expression profiles (GEP), pathways, and cell types associated with response or resistance to neoadjuvant chemoradiotherapy. Methods: The transcriptomic and clinical data of Rectal carcinoma from the Gene Expression Omnibus database and Immune-related genes (IRGs) from ImmPort were downloaded to identify the differentially expressed immune-related genes (DEIRGs) between responder and non-responder to neoadjuvant chemoradiotherapy. Gene set enrichment analyses were performed to uncover significantly enriched GO terms and KEGG pathways. Immune cell infiltration was estimated from RNA-sequencing data using ImmuCellAI. Afterward, we constructed an immune-related gene-based predictive model (IRGPM) by Support Vector Machine and validated it in an external cohort. Result: A 15-gene signature (HLA-DPB1, HLA-DQA1, CXCL9, CXCL10, TAP2, INHBB, BMP2, CD74, IL33, CCL11, CXCL11, DEFB1, HLA-DPA1, CCN3, STAT1) was identified as DEIRGs and found to be significantly associated with nCRT outcomes. Gene set enrichment analyses indicated that the 15 genes play active roles in inflammation-related biological processes. In addition, ImmuCellAI revealed that CD4 naive T cells, Tex, Th1 were significantly up-regulated (p=0.035, p=0.02, p=0.0086, respectively), while Tfh were significantly down-regulated (p=0.015) in responder subgroup. Finally, a novel predictive model was developed by SVM based on DEIRGs with an AUC of 80% (internal validation) and 73.5% (external validation). Conclusion: Our team conducted a genomic study of the relationship between gene expression profile and response to nCRT in LARC. Our data suggested that the DEIRGs signature could help predict the efficacy of nCRT. And a DEIRGs‐based SVM model was developed to monitor the outcomes of nCRT in LARC. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitor (ICI) treatment is considered as an innovative approach for cancers. Since not every patient responded well to ICI therapy, it is imperative to screen out novel signatures to predict prognosis. Based on 407 gastric cancer (GC) samples retrieved from The Cancer Genome Atlas (TCGA), 36 immune-related hub genes were identified by weighted gene co-expression network analysis (WGCNA), and eight of them (RNASE2, CGB5, INHBE, DUSP1, APOA1, CD36, PTGER3, CTLA4) were used to formulate the Cox regression model. The obtained risk score was proven to be significantly correlated with overall survival (OS), consistent with the consequence of the Gene Expression Omnibus (GEO) cohort (n = 433). Then, the relationship between the risk score and clinical, molecular and immune characteristics was further investigated. Results showed that the low-risk subgroup exhibited higher mutation rate, more M1 macrophages, CD8+ and CD4+ T cells infiltrating, more active MHC-I, and bias to "IFN-γ Dominant" immune type, which is consistent with our current understanding of tumor prognostic risk. Furthermore, it is suggested that our model can accurately predict 1-, 2-, and 3-year OS of GC patients, and that it was superior to other canonical models, such as TIDE and TIS. Thus, these eight genes are probably considered as potential signatures to predict prognosis and to distinguish patient benefit from ICI, serving as a guiding individualized immunotherapy. [ABSTRACT FROM AUTHOR]

Background: Biliary atresia (BA) is the leading cause of pediatric liver failure and pediatric liver transplantation worldwide. Evidence suggests that the immune system plays a central role in the pathogenesis of BA. Methods: In this work, the novel immune-related genes between BA and normal samples were investigated based on weighted gene co-expression network analysis (WGCNA) and the deconvolution algorithm of CIBERSORT. Results: Specifically, 650 DEGs were identified between the BA and normal groups. The blue module was the most positively correlated with BA containing 3274 genes. Totally, 610 overlapping BA-related genes of DEGs and WGCNA were further used to identify IRGs. Three IRGs including VCAM1, HLA-DRA, and CD74 were finally identified as the candidate biomarkers. Particularly, the CD74 biomarker was discovered for the first as a potential immune biomarker for BA. Conclusions: Possibly, these 3 IRGs might serve as candidate biomarkers and guide the individualized treatment strategies for BA patients. Our results would provide great insights for a deeper understanding of both the occurrence and the treatment of BA. [ABSTRACT FROM AUTHOR]

Abstract Background Clear cell renal cell carcinoma (ccRCC) occupied most of renal cell carcinoma (RCC), which associated with poor prognosis. The purpose of this study is to screen novel and prognostic biomarkers for patients with ccRCC. Methods and results Firstly, Gene Expression Omnibus database was used to collect microarray data for weighted gene co-expression network construction. Gene modules related to prognosis which interest us most were picked out. 90 hub genes were further chosen in the key modules, two of which including gonadotropin releasing hormone 1 (GNRH1) and leukotriene B4 receptor (LTB4R) were screened and validated as immune-related prognostic biomarkers. Based on several public databases and ccRCC tissues collected by ourselves, we performed survival analysis, spearman correlation analysis, receiver operating characteristic (ROC) analysis, quantitative real-time PCR (qRT-PCR), western blotting, immunofluorescence (IF) and immunohistochemistry (IHC) staining for the validation of immune-related prognostic biomarkers. We further explored the relationship between immune-related prognostic biomarker expressions and immunocytes. Finally, gene set enrichment analysis (GSEA) demonstrated that the two immune-related prognostic biomarkers were significantly correlated with cell cycle. Conclusions Generally speaking, the present study has identified two novel prognostic biomarkers for patients with ccRCC, which showed strong correlation with prognosis of patients with ccRCC, could further be used as potential prognostic biomarkers in ccRCC.

Abstract Background Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid cancer. The effect of traditional anti-tumor therapy is not ideal for the patients with recurrence, metastasis and radioiodine resistance. The abnormal expression of immune-related genes (IRGs) has critical roles in the etiology of PTC. However, the effect of IRGs on PTC prognosis remains unclear. Methods Based on The Cancer Genome Atlas (TCGA) and ImmPort databases, we integrated IRG expression profiles and progression-free intervals (PFIs) of PTC patients. First, we identified the differentially expressed IRGs and transcription factors (TFs) in PTC. Subsequently, an IRG model that can predict the PFI was constructed by using univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses of the differentially expressed IRGs in the TCGA. Additionally, a protein–protein interaction (PPI) network showed the interactions between the differentially expressed genes (DEGs), and the top 30 genes with the highest degree were extracted from the network. Then, the key IRG was identified by the intersection analysis of the PPI network and univariate Cox regression, which was verified the differential expression of by western blotting and immunohistochemistry (IHC). ssGSEA was performed to understand the correlation between the key IRG expression level and immune activity. Results A total of 355 differentially expressed IRGs and 43 differentially expressed TFs were identified in PTC patients. Then, eight IRGs were finally utilized to construct an IRG model. The respective areas under the curve (AUCs) of the IRG model reached 0.948, 0.820, and 0.831 at 1, 3 and 5 years in the training set. In addition, lactotransferrin (LTF) was determined as the key IRG related to prognosis. The expression level of LTF in tumor tissues was significantly lower than that in normal tissues. And the results of ssGSEA showed the expression level of LTF is closely related to immune activity. Conclusions These findings show that the prognostic model and key IRG may become promising molecular markers for the prognosis of PTC patients.