Identification of Hub Biomarkers and Immune-Related Pathways Participating in the Progression of Antineutrophil Cytoplasmic Antibody-Associated Glomerulonephritis

BackgroundAntineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a systemic autoimmune disease that generally induces the progression of rapidly progressive glomerulonephritis (GN). The purpose of this study was to identify key biomarkers and immune-related pathways involved in the progression of ANCA-associated GN (ANCA-GN) and their relationship with immune cell infiltration.MethodsGene microarray data were downloaded from the Gene Expression Omnibus (GEO). Hub markers for ANCA-GN were mined based on differential expression analysis, weighted gene co-expression network analysis (WGCNA) and lasso regression, followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) of the differential genes. The infiltration levels of 28 immune cells in the expression profile and their relationship to hub gene markers were analysed using single-sample GSEA (ssGSEA). In addition, the accuracy of the hub markers in diagnosing ANCA-GN was subsequently evaluated using the receiver operating characteristic curve (ROC).ResultsA total of 651 differential genes were screened. Twelve co-expression modules were obtained via WGCNA; of which, one hub module (black module) had the highest correlation with ANCA-GN. A total of 66 intersecting genes were acquired by combining differential genes. Five hub genes were subsequently obtained by lasso analysis as potential biomarkers for ANCA-GN. The immune infiltration results revealed the most significant relationship among monocytes, CD4+ T cells and CD8+ T cells. ROC curve analysis demonstrated a prime diagnostic value of the five hub genes. According to the functional enrichment analysis of the differential genes, hub genes were mainly enhanced in immune- and inflammation-related pathways.ConclusionB cells and monocytes were closely associated with the pathogenesis of ANCA-GN. Hub genes (CYP3A5, SLC12A3, BGN, TAPBP and TMEM184B) may be involved in the progression of ANCA-GN through immune-related signal pathways.

Selection of Cashmere Fineness Functional Genes by Translatomics

Cashmere fineness is an important index to evaluate cashmere quality. Liaoning Cashmere Goat (LCG) has a large cashmere production and long cashmere fiber, but its fineness is not ideal. Therefore, it is important to find genes involved in cashmere fineness that can be used in future endeavors aiming to improve this phenotype. With the continuous advancement of research, the regulation of cashmere fineness has made new developments through high-throughput sequencing and genome-wide association analysis. It has been found that translatomics can identify genes associated with phenotypic traits. Through translatomic analysis, the skin tissue of LCG sample groups differing in cashmere fineness was sequenced by Ribo-seq. With these data, we identified 529 differentially expressed genes between the sample groups among the 27197 expressed genes. From these, 343 genes were upregulated in the fine LCG group in relation to the coarse LCG group, and 186 were downregulated in the same relationship. Through GO enrichment analysis and KEGG enrichment analysis of differential genes, the biological functions and pathways of differential genes can be found. In the GO enrichment analysis, 491 genes were significantly enriched, and the functional region was mainly in the extracellular region. In the KEGG enrichment analysis, the enrichment of the human papillomavirus infection pathway was seen the most. We found that the COL6A5 gene may affect cashmere fineness.

Based on Bioinformatics Studies on the Effect of a lpha1H on Key Genes, Pathways in Bladder Cancer and lncRNA on Patient Prognosis

Objective: To analyze the differential genes, lncRNA, signaling pathway and patient prognosis of bladder cancer after alpha1H treatment.Methods: Sequencing data GSE172112 for patients in clinical trials with a new bladder cancer drug were downloaded from the GEO database, The bladder cancer tissues using the new drug alpha1H (alpha1-oleate) and placebo were analyzed in the R language, The differentially expressed genes were selected; Differential genes were analyzed for KEGG pathway enrichment using the DAVID database, To explore the effect of a lpha1H treatment on pathways in patients with bladder cancer; at the same time, lncRNA expression data from the Bladder Cancer (BLCA) dataset were also downloaded through the TCGA database, First, screening for differential lncRNA expression, The screening results were then analyzed by univariate Cox regression to initially screen for lncRNA associated with prognosis, The key lncRNA affecting the prognosis were further screened out, The prognostic model was also constructed using multivariate Cox regression analysis. Results: There yielded 394 significantly upregulated genes and 385 significantly downregulated genes in bladder cancer tissue after a lpha1H treatment. Through gene signaling pathway enrichment analysis, the upregulated genes were mainly enriched in the signaling pathways regulating the pluripotent line of stem cell cells, the TGF-signaling pathways, and the cell cycle. The downregulated genes were mainly enriched in the MAPK signaling pathway, phagosomes, and the TNF signaling pathway. After a lpha1H treatment, of 119 differentially expressed lncRNA, from the lnc2cancer database, two genes were found to be potentially associated with bladder cancer prognosis, and the final analysis confirmed the key lncRNA affecting prognosis. The results of survival analysis showed that high expression of LINC00152 unfavorable unfavorable patient prognosis and the new drug alpha1H reduces LINC00152 favors patient prognosis. Conclusion: Alpha1H can cure bladder cancer by regulating hallmark signaling, TGF-beta signaling, and LINC00152.

Screening and Identification of Muscle-Specific Candidate Genes via Mouse Microarray Data Analysis

Muscle tissue is involved with every stage of life activities and has roles in biological processes. For example, the blood circulation system needs the heart muscle to transport blood to all parts, and the movement cannot be separated from the participation of skeletal muscle. However, the process of muscle development and the regulatory mechanisms of muscle development are not clear at present. In this study, we used bioinformatics techniques to identify differentially expressed genes specifically expressed in multiple muscle tissues of mice as potential candidate genes for studying the regulatory mechanisms of muscle development. Mouse tissue microarray data from 18 tissue samples was selected from the GEO database for analysis. Muscle tissue as the treatment group, and the other 17 tissues as the control group. Genes expressed in the muscle tissue were different to those in the other 17 tissues and identified 272 differential genes with highly specific expression in muscle tissue, including 260 up-regulated genes and 12 down regulated genes. is the genes were associated with the myofibril, contractile fibers, and sarcomere, cytoskeletal protein binding, and actin binding. KEGG pathway analysis showed that the differentially expressed genes in muscle tissue were mainly concentrated in pathways for AMPK signaling, cGMP PKG signaling calcium signaling, glycolysis, and, arginine and proline metabolism. A PPI protein interaction network was constructed for the selected differential genes, and the MCODE module used for modular analysis. Five modules with Score > 3.0 are selected. Then the Cytoscape software was used to analyze the tissue specificity of differential genes, and the genes with high degree scores collected, and some common genes selected for quantitative PCR verification. The conclusion is that we have screened the differentially expressed gene set specific to mouse muscle to provide potential candidate genes for the study of the important mechanisms of muscle development.

Bioinformatics prediction and experimental verification identify MAD2L1 and CCNB2 as diagnostic biomarkers of rhabdomyosarcoma

Background Rhabdomyosarcoma (RMS) is a malignant soft-tissue tumour. In recent years, the tumour microenvironment (TME) has been reported to be associated with the development of tumours. However, the relationship between the occurrence and development of RMS and TME is unclear. The purpose of this study is to identify potential tumor microenvironment-related biomarkers in rhabdomyosarcoma and analyze their molecular mechanisms, diagnostic and prognostic significance. Methods We first applied bioinformatics method to analyse the tumour samples of 125 patients with rhabdomyosarcoma (RMS) from the Gene Expression Omnibus database (GEO). Differential genes (DEGs) that significantly correlate with TME and the clinical staging of tumors were extracted. Immunohistochemistry (IHC) was applied to validate the expression of mitotic arrest deficient 2 like 1 (MAD2L1) and cyclin B2 (CCNB2) in RMS tissue. Then, we used cell function and molecular biology techniques to study the influence of MAD2L1 and CCNB2 expression levels on the progression of RMS. Results Bioinformatics results show that the RMS TME key genes were screened, and a TME-related tumour clinical staging model was constructed. The top 10 hub genes were screened through the establishment of a protein–protein interaction (PPI) network, and then Gene Expression Profiling Interactive Analysis (GEPIA) was conducted to measure the overall survival (OS) of the 10 hub genes in the sarcoma cases in The Cancer Genome Atlas (TCGA). Six DEGs of statistical significance were acquired. The relationship between these six differential genes and the clinical stage of RMS was analysed. Further analysis revealed that the OS of RMS patients with high expression of MAD2L1 and CCNB2 was worse and the expression of MAD2L1 and CCNB2 was related to the clinical stage of RMS patients. Gene set enrichment analysis (GSEA) revealed that the genes in MAD2L1 and CCNB2 groups with high expression were mainly related to the mechanism of tumour metastasis and recurrence. In the low-expression MAD2L1 and CCNB2 groups, the genes were enriched in the metabolic and immune pathways. Immunohistochemical results also confirmed that the expression levels of MAD2L1 (30/33, 87.5%) and CCNB2 (33/33, 100%) were remarkably higher in RMS group than in normal control group (0/11, 0%). Moreover, the expression of CCNB2 was related to tumour size. Downregulation of MAD2L1 and CCNB2 suppressed the growth, invasion, migration, and cell cycling of RMS cells and promoted their apoptosis. The CIBERSORT immune cell fraction analysis indicated that the expression levels of MAD2L1 and CCNB2 affected the immune status in the TME. Conclusions The expression levels of MAD2L1 and CCNB2 are potential indicators of TME status changes in RMS, which may help guide the prognosis of patients with RMS and the clinical staging of tumours.

Mechanism Of Leptin On Impaired Ovarian Reserve Function After Cold Exposure In Female Rats

Previous studies have shown that cold exposure can cause disturbance of estrus cycle in female rats. However, whether cold exposure can cause organic pathological damage to the reproductive system of female rats was undefined. Meanwhile there are few reports on the mechanism of decompensation in rat reproductive function after cold exposure. This study aims to further discuss how cold exposure impact female ovarian reserve function in rats. Female rats were randomly divided into control group and cold exposure group. Ovarian reserve function, differential genes in hypothalamus reproductive regulation center or peripheral were evaluated. After cold exposure, ovarian reserve function was impaired, follicle development was abnormal, the number of mature follicles decreased significantly, the key hypothalamic reproductive regulation molecule GnRH decreased significantly, the response of its regulatory receptor NPY-5R was down-regulated, and the peripheral hormone serum leptin, which is closely related to it, decreased significantly. Our results indicate that cold exposure can lead to impaired ovarian function in female rats, resulting from decrease in serum leptin cause by WAT leptin depletion, which can release the inhibitory of NPY in the hypothalamus, and further lead to the down-regulation of GnRH expression, resulting in the whole HPO axis.

Dimethyl itaconate alleviates the pyroptosis of macrophages through oxidative stress

Macrophages are involved in the pathophysiology of many diseases as critical cells of the innate immune system. Pyroptosis is a form of macrophage death that induces cytokinesis of phagocytic substances in the macrophages, thereby defending against infection. Dimethyl itaconate (DI) is an analog of itaconic acid with anti-inflammatory effects. However, the effect of dimethyl itaconate on macrophage pyroptosis has not been elucidated clearly. Thus, the present study aimed to analyze the effect of DI treatment on a macrophage pyroptosis model (Lipopolysaccharide, LPS + Adenosine Triphosphate, ATP). The results showed that 0.25 mM DI ameliorated macrophage pyroptosis and downregulated interleukin (IL)-1β expression. Then, real-time quantitative polymerase chain reaction (RT-qPCR) was used to confirm the result of RNA-sequencing of the upregulated oxidative stress-related genes (Gclc and Gss) and downregulated inflammation-related genes (IL-12β and IL-1β). In addition, Gene Ontology (GO) enrichment analysis showed that differential genes were associated with transcript levels and DNA replication. Kyoto encyclopedia of genes and genomes (KEGG) enrichment showed that signaling pathways, such as tumor necrosis factor (TNF), Jak, Toll-like receptor and IL-17, were altered after DI treatment. N-acetyl-L-cysteine (NAC) reversed the DI effect on the LPS + ATP-induced macrophage pyroptosis and upregulated the IL-1β expression. Oxidative stress-related protein Nrf2 is involved in the DI regulation of macrophage pyroptosis. Taken together, these findings suggested that DI alleviates the pyroptosis of macrophages through oxidative stress.

Integration of metabolomics and transcriptomics indicates changes in MRSA exposed to terpinen-4-ol

Background This study investigated the effects of terpinen-4-ol on methicillin-resistant Staphylococcus aureus (MRSA) and its biofilm, and the possible mechanisms governing this effect. Results We observed that terpinen-4-ol has good antibacterial activity and inhibits the formation of MRSA biofilm. The MIC and MBC values for terpinen-4-ol against S. aureus were 0.08% ~ 0.32%. And terpinen-4-ol at 0.32% could kill all bacteria and clear all biofilms. Untargeted metabolomic and transcriptomic analyses showed that terpinen-4-ol strongly inhibited DNA and RNA biosynthesis in MRSA at 2 h after treatment by affecting genes and metabolites related to purine and pyrimidine metabolic pathways. Some differential genes which play important roles in DNA synthesis and the production of eDNA from biofilm exposed to terpinen-4-ol was also significantly decreased compared with that of the control. Conclusions Terpinen-4-ol has good antibacterial activity and significantly inhibits the formation of MRSA biofilm by inhibiting purine and pyrimidine metabolism.

Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the most frequent and aggressive pancreatic tumor characterized by high metastatic risk and special tumor microenvironment. To comprehensively delineate the complex intra-tumoral heterogeneity and the underlying mechanism during metastatic lesions malignant progression, single-cell RNA sequencing (scRNA-seq) was employed. PCA and TSNE were used for dimensionality reduction analysis and cell clustering. Find All Markers function was used to calculate differential genes in each cluster, and Do Heatmap function was used to plot the distribution of differential genes in each cluster. GSVA was employed to assign pathway activity estimates to individual cells. Lineage trajectory progression was inferred by monocle. CNV status was inferred to compare the heterogeneity among patients and subtypes by infercnv. Ligand-receptor interactions were identified by CellPhoneDB, and regulons network of cells was analyzed by SCENIC. Through RNA-sequencing of 6236 individual cells from 5 liver metastatic PDAC lesions, 10 major cell clusters are identified by using unbiased clustering analysis of expression profiling and well-known cell markers. Cells with high CNV level were considered as malignant cells and pathway analyses were carried out to highlight intratumor heterogeneity in PDAC. Pseudotime trajectory analysis revealed that components of multiple tumor-related pathways and transcription factors (TFs) were differentially expressed along PDAC progression. The complex cellular communication suggested potential immunotherapeutic targets in PDAC. Regulon network identified multiple candidates for promising cell-specific transcriptional factors. Finally, metastatic-related genes expression levels and signaling pathways were validated in bulk RNA Sequencing data. This study contributed a comprehensive single-cell transcriptome atlas and contributed into novel insight of intratumor heterogeneity and molecular mechanism in metastatic PDAC.

USH2A Mutation is Associated With Tumor Mutation Burden and Antitumor Immunity in Patients With Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is one of the diseases with the highest morbidity and mortality in the world. At present, immunotherapy has become a valuable method for the treatment of COAD. Tumor mutational burden (TMB) is considered to be the most common biomarker for predicting immunotherapy. According to reports, the mutation rate of COAD ranks third. However, whether these gene mutations are related to TMB and immune response is still unknown. Here, COAD somatic mutation data were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Bioinformatics methods were used to study the relationships among gene mutations, COAD survival prognosis, and tumor immune response. A total of 22 of the top 40 mutations in TCGA and ICGC databases were the same. Among them, the USH2A mutation was associated with high TMB and poor clinical prognosis. According to Gene Set Enrichment Analysis (GSEA) and the CIBERSORT algorithm, we determined that the USH2A mutation upregulates signaling pathways involved in the immune system and the antitumor immune response. In cases with a USH2A mutation, the immune score and MSI score of TCGA samples increased, the expression of immune checkpoint genes decreased significantly, and the TIDE score decreased significantly. Dependent on the presence or absence of a USH2A mutation, TCGA COAD samples were analyzed for differentially expressed genes, 522 of which were identified. Using a univariate Cox analysis and LASSO COX analysis of these differential genes, a prediction model was established, which established significant differences in the infiltration of immune cells, immune checkpoint gene expression, immune score, MSI score, TMB, and TIDE in patients in high- and low-risk groups. In conclusion, mutation of USH2A is frequent in COAD and is related to an increase in TMB and the antitumor immunity. The differential genes screened by USH2A mutation allowed the construction of a risk model for predicting the survival and prognosis of cancer patients, in addition to providing new ideas for COAD immunotherapy.