IRF8 and its related molecules as potential diagnostic biomarkers or therapeutic candidates and immune cell infiltration characteristics in steroid-induced osteonecrosis of the femoral head.

PURPOSE: Steroid-induced osteonecrosis of the femoral head (SONFH) was a refractory orthopedic hip joint disease in the young and middle-aged people, but the pathogenesis of SONFH remained unclear. We aimed to identify the potential genes and screen potential therapeutic compounds for SONFH. METHODS: The microarray was obtained for blood tissue from the GEO database, and then it identifies differentially expressed genes (DEGs). The DEGs were analyzed to obtain the differences in immune cell infiltration. The gene functional enrichment analysis of SONFH was analyzed. The PPI of DEGs was identified through the STRING database, and the cluster modules and hub genes were ascertained using MCODE and CytoHubba, and the ROC curve of hub genes was analyzed, and the tissues distribution of hub genes was understood by the HPA, Bgee and BioGPS databases. The hub genes and target miRNAs and corresponding upstream lncRNAs were predicted by TargetScan, miRDB and ENCORI database. Subsequently, we used CMap, DGIdb and L1000FWD databases to identify several potential therapeutic molecular compounds for SONFH. Finally, the AutoDockTools Vina, PyMOL and Discovery Studio were employed for molecular docking analyses between compounds and hub genes. RESULTS: The microarray dataset GSE123568 was obtained related to SONFH. There were 372 DEGs including 197 upregulated genes and 175 downregulated genes by adjusted P value < 0.01 and |log2FC|> 1. Several significant GSEA enrichment analysis and biological processes and KEGG pathway associated with SONFH were identified, which were significantly related to cytoskeleton organization, nucleobase-containing compound catabolic process, NOD-like receptor signaling pathway, MAPK signaling pathway, FoxO signaling pathway, neutrophil-mediated immunity, neutrophil degranulation and neutrophil activation involved in immune response. Activated T cells CD4 memory, B cells naïve, B cells memory, T cells CD8 and T cells gamma delta might be involved in the occurrence and development of SONFH. Three cluster modules were identified in the PPI network, and eleven hub genes including FPR2, LILRB2, MNDA, CCR1, IRF8, TYROBP, TLR1, HCK, TLR8, TLR2 and CCR2 were identified by Cytohubba, which were differed in bone marrow, adipose tissue and blood, and which had good diagnostic performance in SONFH. We identified IRF8 and 10 target miRNAs that was utilized including Targetsan, miRDB and ENCORI databases and 8 corresponding upstream lncRNAs that was revealed by ENCORI database. IRF8 was detected with consistent expression by qRT-PCR. Based on the CMap, DGIdb and L1000FWD databases, the 11 small molecular compounds that were most strongly therapeutic correlated with SONFH were estradiol, genistein, domperidone, lovastatin, myricetin, fenbufen, rosiglitazone, sirolimus, phenformin, vorinostat and vinblastine. All of 11 small molecules had good binding affinity with the IRF8 in molecular docking. CONCLUSION: The occurrence of SONFH was associated with a "multi-target" and "multi-pathway" pattern, especially related to immunity, and IRF8 and its noncoding RNA were closely related to the development of SONFH. The CMap, DGIdb and L1000FWD databases could be effectively used in a systematic manner to predict potential drugs for the prevention and treatment of SONFH. However, additional clinical and experimental research is warranted.

Coexpression network analysis coupled with connectivity map database mining reveals novel genetic biomarkers and potential therapeutic drugs for polymyositis.

OBJECTIVE: Polymyositis (PM) is a chronic autoimmune connective tissue disease whose pathogenic mechanisms are unclear. This study aimed to identify the main genes and functionally enriched pathways involved in PM using weighted gene coexpression network analysis (WGCNA). METHODS: To identify the candidate genes of PM, microarray datasets GSE128470, GSE3112, GSE39454 and GSE125977 were obtained from the Gene Expression Omnibus database. The gene network of GSE128470 was constructed, and WGCNA was used to divide genes into different modules. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were applied to the most PM-related modules. The datasets were used to verify the expression profile and diagnostic capabilities of the hub genes. Additionally, gene set enrichment analysis (GSEA) was carried out. Moreover, gene signatures were then used as a search query to explore the connectivity map (CMap). RESULTS: A weighted gene coexpression network was constructed, and the genes were divided into 66 modules. The enriched functions and candidate pathway modules included interferon-γ, type I interferon, cellular response to interferon-γ, neutrophil activation, neutrophil degranulation, neutrophil-mediated immunity and neutrophil activation involved in the immune response. A total of 22 hub genes were identified. The Mann-Whitney U test was performed on these 22 genes using the three datasets of muscle samples and one dataset of whole blood samples, and two genes significantly differentially expressed in all datasets were obtained: VCAM1 and LY96. Receiver operating characteristic curve analysis determined that VCAM1 and LY96 gene expression can distinguish PM from healthy controls (the area under the curve [AUC] was greater than 0.75). Logistic regression analysis was performed on the combination of LY96 and VCAM1. The accuracy, sensitivity, specificity, and AUC of the combination reached 1.0. GSEA of VCAM1 and LY96 revealed their relation to 'inflammatory response', 'TNF-α signalling via NF-κB', 'complement' and 'myogenesis'. CMap research revealed a few compounds with the potential to counteract the effects of the dysregulated molecular signature in PM. CONCLUSIONS: We used WGCNA to observe all aspects of PM, which helped to elucidate the molecular mechanisms of PM onset and progression and provide candidate targets for the diagnosis and treatment of PM. Key Points • Four microarray datasets were analysed in patients with polymyositis and healthy controls, and VCAM1 and LY96 were significant genes in all datasets. • GSEA of VCAM1 and LY96 revealed that they were mainly related to 'inflammatory response', 'TNF-α signalling via NF-κB', 'complement' and 'myogenesis'. • CMap found a few compounds such as dimethyloxalylglycine and HNMPA-(AM)3 with the potential to counteract the effects of the dysregulated molecular signature in PM.

Weighted Correlation Network Analysis of Cancer Stem Cell-Related Prognostic Biomarkers in Esophageal Squamous Cell Carcinoma.

Background: The role of cancer stem cells in esophageal squamous cell carcinoma (ESCC) remains unclear. Methods: The mRNA stemness index (mRNAsi) of 179 ESCC patients (GSE53625) was calculated using a machine learning algorithm based on their mRNA expression. Stemness-related genes were identified by weighted correlation network analysis (WGCNA) and LASSO regression, whose associations with mutation status, immune cell infiltrations, and potential compounds were also analyzed. The role of these genes in proliferation and their expressions was assessed in ESCC cell lines and 112 samples from our center. Results: The ESCC samples had significantly higher mRNAsi than the normal tissues. Patients with high mRNAsi exhibited higher worse OS. Seven stemness-related genes were identified by WGCNA and LASSO regression, based on which a risk-predicted score model was constructed. Among them, CST1, CILP, PITX2, F2RL2, and RIOX1 were favorable for OS, which were adverse for DPP4 and ZFHX4 in the GSE53625 dataset. However, RIOX1 was unfavorable for OS in patients from our center. In vitro assays showed that CST1, CILP, PITX2, F2RL2, and RIOX1 were pro-proliferated, which were opposite for DDP4 and ZFHX4. In addition, SMARCA4, NOTCH3, DNAH5, and KALRN were more mutated in the low-score group. The low-score group had significantly more memory B cells, monocytes, activated NK cells, and Tregs and less macrophages M2, resting mast cells, and resting dendritic cells. Conclusions: Seven stemness-related genes are significantly related to the prognosis, gene mutations, and immune cell infiltration of ESCC. Some potential anticancer compounds may be favorable for OS.

Cyclin-Dependent Kinase Inhibitors Function as Potential Immune Regulators via Inducing Pyroptosis in Triple Negative Breast Cancer.

Background: Immunotherapy is the most promising treatment in triple-negative breast cancer (TNBC), and its efficiency is largely dependent on the intra-tumoral immune cells infiltrations. Thus, novel ways to assist immunotherapy by increasing immune cell infiltrations were highly desirable. Methods: To find key immune-related genes and discover novel immune-evoking molecules, gene expression profiles of TNBC were downloaded from Gene Expression Omnibus (GEO). Single-sample gene set enrichment analysis (ssGSEA) and Weighted Gene Co-expression Network Analysis (WGCNA) were conducted to identified hub genes. The CMap database was used subsequently to predicate potential drugs that can modulate the overall hub gene expression network. In vitro experiments were conducted to assess the anti-tumor activity and the pyroptosis phenotypes induced by GW-8510. Results: Gene expression profiles of 198 TNBC patients were downloaded from GEO dataset GSE76124, and ssGSEA was used to divide them into Immune Cell Proficiency (ICP) group and Immune Cell Deficiency (ICD) group. Hub differential expressed gene modules between two groups were identified by WGCNA and then annotated by Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A cyclin-dependent kinase (CDK) 2 inhibitor, GW-8510 was then identified by the CMap database and further investigated. Treatment with GW-8510 resulted in potent inhibition of TNBC cell lines. More importantly, in vitro and in vivo studies confirmed that GW-8510 and other CDK inhibitors (Dinaciclib, and Palbociclib) can induce pyroptosis by activating caspase-3 and GSDME, which might be the mechanism for their immune regulation potentials. Conclusion: GW-8510, as well as other CDK inhibitors, might serve as potential immune regulators and pyroptosis promotors in TNBC.

Identification and analysis of a prognostic ferroptosis and iron-metabolism signature for esophageal squamous cell carcinoma.

Background: The role of ferroptosis in esophageal squamous cell carcinoma (ESCC) is still unclear. Methods: The association of iron metabolism and ferroptosis-related genes with the prognosis, copy number variation (CNV), TMB, and immune cell infiltration of ESCC was explored using data from the GEO and TCGA database and validated by immunofluorescence in 112 ESCC patients from our center. The potential anti-cancer drugs and compounds from the GDSC and the Connectivity Map database were also screened. Results: A total of 117 iron metabolism and ferroptosis-related genes were identified. We found the expressions of PRNP, SLC3A2, SLC39A8, and SLC39A14 negatively related to the prognosis of ESCC patients, while ATP6V0A1 and LCN2 were opposite, which was validated in 112 ESCC samples from our center. And a prognostic signature was constructed based on their expressions and Cox regression coefficient (ß). The low-score group exhibited a significantly worse OS. Besides, analysis of 179 ESCC samples from GSE53625 revealed that patients of poorly differentiation, more than 60 years, T4 stage, advanced N stage, advanced stage, and adjuvant therapy also exhibited a significantly shorter OS, based on which a nomogram to predict the OS was established. Moreover, the low-score group exhibited significantly higher CNV and TMB and more frequent mutations of TP53, MUC16, and NOTCH1. Higher proportion of Macrophages M2, and lower proportion of T cells follicular helper were observed in the low-score group. We discovered that AZD7762, Sunitinib, Cytarabine, Docetaxel, Vinblastine, and Elesclomol exhibited lower IC50 in the low-score group. And 20 potential compounds were identified from the CMap database. Conclusions: Six iron metabolism and ferroptosis-related genes were associated with the prognosis, CNV, TMB, and immune cell infiltration of ESCC. Some potential anti-cancer drugs and compounds may be helpful for OS.

Identification of potential drugs for diffuse large b-cell lymphoma based on bioinformatics and Connectivity Map database.

Diffuse large B-cell lymphoma (DLBCL) is the most main subtype in non-Hodgkin lymphoma. After chemotherapy, about 30% of patients with DLBCL develop resistance and relapse. This study was to identify potential therapeutic drugs for DLBCL using the bioinformatics method. The differentially expressed genes (DEGs) between DLBCL and non-cancer samples were downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs were analyzed using the Database for Annotation, Visualization, and Integrated Discovery. The R software package (SubpathwayMiner) was used to perform pathway analysis on DEGs affected by drugs found in the Connectivity Map (CMap) database. Protein-protein interaction (PPI) networks of DEGs were constructed using the Search Tool for the Retrieval of Interacting Genes online database and Cytoscape software. In order to identify potential novel drugs for DLBCL, the DLBCL-related pathways and drug-affected pathways were integrated. The results showed that 1927 DEGs were identified from TCGA and GEO. We found 54 significant pathways of DLBCL using KEGG pathway analysis. By integrating pathways, we identified five overlapping pathways and 47 drugs that affected these pathways. The PPI network analysis results showed that the CDK2 is closely associated with three overlapping pathways (cell cycle, p53 signaling pathway, and small cell lung cancer). The further literature verification results showed that etoposide, rinotecan, methotrexate, resveratrol, and irinotecan have been used as classic clinical drugs for DLBCL. Anisomycin, naproxen, gossypol, vorinostat, emetine, mycophenolic acid and daunorubicin also act on DLBCL. It was found through bioinformatics analysis that paclitaxel in the drug-pathway network can be used as a potential novel drug for DLBCL.

Analysis of differentially expressed genes in placental tissues of preeclampsia patients using microarray combined with the Connectivity Map database.

Preeclampsia (PE), which affects 2-7% of human pregnancies, causes significant maternal and neonatal morbidity and mortality. To better understand the pathophysiology of PE, the gene expression profiles of placental tissue from 5 controls and 5 PE patients were assessed using microarray. A total of 224 transcripts were significantly differentially expressed (>2-fold change and q value <0.05, SAM software). Gene Ontology (GO) enrichment analysis indicated that genes involved in hypoxia and oxidative and reductive processes were significantly changed. Three differentially expressed genes (DEGs) involved in these biological processes were further verified by quantitative real-time PCR. Finally, the potential therapeutic agents for PE were explored via the Connectivity Map database. In conclusion, the data obtained in this study might provide clues to better understand the pathophysiology of PE and to identify potential therapeutic agents for PE patients.