scholarly journals Identification of Key Biomarkers and Immune Infiltration in Sciatic Nerve of Diabetic Neuropathy BKS-db/db Mice by Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Yixuan Lin ◽  
Fanjing Wang ◽  
Lianzhi Cheng ◽  
Zhaohui Fang ◽  
Guoming Shen
Keyword(s):  
Diabetic Neuropathy ◽  
Signaling Pathway ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Data Set ◽  
Immune Infiltration ◽  
P53 Signaling ◽  
Ppi Networks ◽  
Key Genes ◽  
P53 Signaling Pathway

Diabetic neuropathy (DN) is one of the chronic complications of diabetes which can cause severe harm to patients. In order to determine the key genes and pathways related to the pathogenesis of DN, we downloaded the microarray data set GSE27382 from Gene Expression Omnibus (GEO) and adopted bioinformatics methods for comprehensive analysis, including functional enrichment, construction of PPI networks, central genes screening, TFs-target interaction analysis, and evaluation of immune infiltration characteristics. Finally, we examined quantitative real- time PCR (qPCR) to validate the expression of hub genes. A total of 318 differentially expressed genes (DEGs) were identified, among which 125 upregulated DEGs were enriched in the mitotic nuclear division, extracellular region, immunoglobulin receptor binding, and p53 signaling pathway, while 193 downregulated DEGs were enriched in ion transport, membrane, synapse, sodium channel activity, and retrograde endocannabinoid signaling. GSEA plots showed that condensed nuclear chromosome kinetochore were the most significant enriched gene set positively correlated with the DN group. Importantly, we identified five central genes (Birc5, Bub1, Cdk1, Ccnb2, and Ccnb1), and KEGG pathway analysis showed that the five hub genes were focused on progesterone-mediated oocyte maturation, cell cycle, and p53 signaling pathway. The proportion of immune cells from DN tissue and normal group showed significant individual differences. In DN samples, T cells CD4 memory resting and dendritic cells resting accounted for a higher proportion, and macrophage M2 accounted for a lower proportion. In addition, all five central genes showed consistent correlation with immune cell infiltration levels. qPCR showed the same expression trend of five central genes as in our analysis. Our research identified key genes related to differential genes and immune infiltration related to the pathogenesis of DN and provided new diagnostic and potential therapeutic targets for DN.

scholarly journals Systematic Analysis Identifies NUF2 as an Immunological and Prognostic Biomarker for Non-small cell lung cancer

2021 ◽  
Author(s):  
xia li ◽  
zhongquan yi ◽  
lianlian zhang ◽  
jin zhou ◽  
wenchun song ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Signaling Pathway ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Functional Enrichment ◽  
Small Cell Lung ◽  
Hub Genes ◽  
P53 Signaling ◽  
P53 Signaling Pathway

Abstract Background Non-small cell lung cancer (NSCLC) is a part of the most common cancers in the world. A lot of efforts have been made to clarify the etiology of non-small cell lung cancer, but the molecular mechanism of non-small cell lung cancer is still unclear. Methods In order to identify candidate genes in the occurrence and progression of non-small cell lung cancer, GSE19804 GSE118370 GSE19188 GSE27262 and GSE33532 microarray data sets were downloaded from the Gene Expression General (GEO) database. Identify differentially expressed genes (DEGS) and perform functional enrichment analysis. The protein-protein interaction network (PPI) was constructed, and the module analysis was performed using STRING and Cytoscape. A total of 562 DEGS were identified, consisting of 98 downregulated genes and 464 upregulated genes. Abundant functions and pathways of DEGS include p53 signaling pathway, Cell adhesion molecules,Leukocyte transendothelial migration,Vascular smooth muscle contraction,Complement and coagulation cascades and Axon guidance. Tumor immunity was assessed to investigate the functions of hub genes. Results Totally 562 genes were found to be dysregulated. 12 genes were considered to be the hub genes. NUF2 was considered as the potential immunotherapeutic targets with future clinical significance.12 hub genes were detected, and biological process analysis showed that these genes are mainly enriched in p53 signaling pathway,Progesterone-mediated oocyte maturation,Cell cycle, Oocyte meiosis and Cellular senescence Survival analysis shows that NUF2 may be linked to the occurrence, invasion or recurrence of non-small cell lung cancer. Conclusion NUF2 genes discovered in this study help us include the molecular mechanisms of the occurrence and progression of non-small cell lung cancer, and provide candidate targets for the diagnosis and treatment of non-small cell lung cancer.

scholarly journals Identification of Molecular Mechanisms Underlying Sex-Associated Differences in the Chronic Obstructive Pulmonary Disease through Bioinformatics Analysis

2021 ◽  
Author(s):  
Fengshou Chen ◽  
Haijia Hou ◽  
Jie Han ◽  
Bing Tang
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Cholesterol Metabolism ◽  
Chronic Obstructive ◽  
Hub Genes ◽  
Obstructive Pulmonary Disease ◽  
P53 Signaling ◽  
Copd Patients ◽  
P53 Signaling Pathway

Abstract Background Accumulating evidence suggests the existence sex associated differences in the Chronic Obstructive Pulmonary Disease (COPD). However, limited knowledge exists on the molecular mechanisms underlying sex associated differences in COPD patients. Methods The GSE8581 dataset obtained from the GEO database was used to analyze differentially expressed genes (DEGs). Then enrichment analysis for DEGs were conducted through Metascape. PPI and the hub genes-pathway networks were constructed using the STRING database and Cytoscape software. Finally, the CTD was used to examine the relationships between the hub DEGs and COPD. Results The results revealed that different subsets of DEGs had different characteristics in GO functions and KEGG pathways. Different subsets of hub genes were obtained based on PPI network. The study then constructed the hub genes-pathway network for different subsets to explore the key signaling pathways and hub genes involved. The findings showed that NRAS and RAC1 functioned through “Rap1 signaling pathway” and “PI3K-Akt signaling pathway”, in male COPD patients. On the other hand, “Cholesterol metabolism” was among the important pathways in female COPD patients while the hub genes, APOE and APOC3 functioned through “Cholesterol metabolism”. Moreover, “Ubiquitin mediated proteolysis” and the “p53 signaling pathway” were shown to play more important roles in male COPD patients compared to their female counterparts. Furthermore, CDK2 and UBE2N were the hub genes involved in “p53 signaling pathway” and “Ubiquitin mediated proteolysis”, respectively. Finally the study identified the relationship between the hub genes and COPD in CTD. Conclusions The present study uncovered different molecular mechanisms in COPD patients based on sex. Additionally, distinct pathways and hub genes including NRAS, RAC1, APOE, APOC3, CDK2 and UBE2N were identified in the two genders of COPD patients. Further studies are needed to explore individualized treatment for COPD based on the findings.

scholarly journals Integrated Bioinformatics Analysis of Potential mRNA and miRNA Regulatory Networks in Mice With Ischemic Stroke Treated by Electroacupuncture

2021 ◽  
Vol 12 ◽  
Author(s):  
Chunxiao Wu ◽  
Lijun Zhao ◽  
Xinrong Li ◽  
Yingshan Xu ◽  
Hongji Guo ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Signaling Pathway ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Functional Enrichment ◽  
Neurological Deficits ◽  
Control Groups ◽  
Hub Genes ◽  
Key Genes ◽  
And Control

Background: The complicated molecular mechanisms underlying the therapeutic effect of electroacupuncture (EA) on ischemic stroke are still unclear. Recently, more evidence has revealed the essential role of the microRNA (miRNA)–mRNA networks in ischemic stroke. However, a systematic analysis of novel key genes, miRNAs, and miRNA–mRNA networks regulated by EA in ischemic stroke is still absent.Methods: We established a middle cerebral artery occlusion (MCAO) mouse model and performed EA therapy on ischemic stroke mice. Behavior tests and measurement of infarction area were applied to measure the effect of EA treatment. Then, we performed RNA sequencing to analyze differentially expressed genes (DEGs) and functional enrichment between the EA and control groups. In addition, a protein–protein interaction (PPI) network was built, and hub genes were screened by Cytoscape. Upstream miRNAs were predicted by miRTarBase. Then hub genes and predicted miRNAs were verified as key biomarkers by RT-qPCR. Finally, miRNA–mRNA networks were constructed to explore the potential mechanisms of EA in ischemic stroke.Results: Our analysis revealed that EA treatment could significantly alleviate neurological deficits in the affected limbs and reduce infarct area of the MCAO model mice. A total of 174 significant DEGs, including 53 upregulated genes and 121 downregulated genes, were identified between the EA and control groups. Functional enrichment analysis showed that these DEGs were associated with the FOXO signaling pathway, NF-kappa B signaling pathway, T-cell receptor signaling pathway, and other vital pathways. The top 10 genes with the highest degree scores were identified as hub genes based on the degree method, but only seven genes were verified as key genes according to RT-qPCR. Twelve upstream miRNAs were predicted to target the seven key genes. However, only four miRNAs were significantly upregulated and indicated favorable effects of EA treatment. Finally, comprehensive analysis of the results identified the miR-425-5p-Cdk1, mmu-miR-1186b-Prc1, mmu-miR-434-3p-Prc1, and mmu-miR-453-Prc1 miRNA–mRNA networks as key networks that are regulated by EA and linked to ischemic stroke. These networks might mainly take place in neuronal cells regulated by EA in ischemic stroke.Conclusion: In summary, our study identified key DEGs, miRNAs, and miRNA–mRNA regulatory networks that may help to facilitate the understanding of the molecular mechanism underlying the effect of EA treatment on ischemic stroke.

scholarly journals Elucidating the Key Biomarkers and Immune Infiltration in Acne by Integrated Bioinformatics Analysis

2021 ◽  
Author(s):  
Lu Yang ◽  
Yan-hong Shou ◽  
Yong-sheng Yang ◽  
Jin-hua Xu
Keyword(s):  
Mast Cells ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Acne Vulgaris ◽  
Interaction Network ◽  
Microarray Dataset ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Immune Infiltration

Abstract Background Acne vulgaris is a common inflammatory condition of skin. However, the landscape of immune infiltration in acne has not been entirely described. Objectives This study used a bioinformatics approach to investigate the inflammatory acne-related key biomarkers and signaling pathways, and immune infiltration in the acne lesion. Methods Two microarray datasets (GSE108110 and GSE53795) were downloaded from Gene Expression Omnibus. We used “limma” package from R software to identify the differentially expressed genes (DEGs) and perform the functional enrichment analyses. Then we built a protein-protein interaction network (PPI), performed the hub genes’ identification through STRING and Cytoscape. We applied the CIBERSORT algorithm to describe the immune infiltration in acne, and explored the correlation between biomarkers and immune infiltration. In the end, our findings in the study were verified by analyzing microarray dataset GSE6475. Results The differentially expressed genes (DEGs) including 292 upregulated genes and 150 downregulated genes in acne compared with non-lesional skin. The hub genes FPR1, C3AR1, CXCL1, CXCL8, FPR2, C3, CCR7, ITGB2 and pivotal pathways JAK-STAT signaling pathway, Toll-like receptor and NOD-like receptor signaling pathway were the most significantly associated with raising neutrophils, monocytes, activated mast cells, as well as reducing resting mast cells and Tregs. Conclusions Our study provides new insights into the pathogenesis and the targets which might be immunomodulatory potential for acne.

scholarly journals Identification of Key Genes and Pathways Associated With Irradiation in Breast Cancer Tissue and Breast Cancer Cell Lines

Dose-Response ◽  
2020 ◽  
Vol 18 (2) ◽  
pp. 155932582093125
Author(s):  
Changchun Zhu ◽  
Chang Ge ◽  
Junbo He ◽  
Xueying Zhang ◽  
Guoxing Feng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Signaling Pathway ◽  
Breast Cancer Cell Lines ◽  
Cancer Tissue ◽  
Interleukin 17 ◽  
Ppi Network ◽  
Hub Genes ◽  
Data Set ◽  
Key Genes

Radiotherapy is mainly a traditional treatment for breast cancer; however, the key genes and pathways in breast cancer associated with irradiation are not clear. In this study, we aimed to explore the messenger RNA expression changes between preradiation and postradiation breast cancer. The gene expression data set (GSE59733) was downloaded from Gene Expression Omnibus database. According to |log2FC (fold change) | ≥ 1 and with false discovery rate adjusted P value <.05, differentially expressed genes (DEGs) were screened and annotated by R programming software. The protein–protein interaction (PPI) network was conducted through STRING database, and subnetworks and hub genes were extracted by plug-in in Cytoscape. A total of 82 DEGs (74 upregulated and 8 downregulated genes) were identified. These DEGs mainly enriched in an intrinsic apoptotic signaling pathway and G-protein-coupled receptor binding. What’s more, tumor necrosis factor signaling pathway and interleukin 17 signaling pathway abnormally activated in postradiation tumor samples. Two characteristic subnetworks and 3 hub genes ( FOS, CCL2, and CXCL12) were strongly distinguished in PPI network. Moreover, the expression level of the hub genes was confirmed in irradiated MCF-7 cell and SUM-159 cell using quantitative real-time polymerase chain reaction assay. These findings imply that these hub genes may play momentous function in breast cancer to irradiation.

The Molecular Docking of Flavonoids Isolated from Daucus carota as a Dual Inhibitor of MDM2 and MDMX

2020 ◽  
Vol 15 (2) ◽  
pp. 154-164 ◽  
Author(s):  
Ijaz Muhammad ◽  
Noor Rahman ◽  
Gul E. Nayab ◽  
Sadaf Niaz ◽  
Mohibullah Shah ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Cancer Therapy ◽  
Natural Product ◽  
Signaling Pathway ◽  
In Silico ◽  
P53 Protein ◽  
Dual Inhibitor ◽  
P53 Signaling ◽  
In Silico Studies ◽  
P53 Signaling Pathway

Background: Cancer is characterized by overexpression of p53 associated proteins, which down-regulate P53 signaling pathway. In cancer therapy, p53 activity can be restored by inhibiting the interaction of MDMX (2N0W) and MDM2 (4JGR) proteins with P53 protein. Objective: In the current, study in silico approaches were adapted to use a natural product as a source of cancer therapy. Methods: In the current study in silico approaches were adapted to use a natural product as a source of cancer therapy. For in silico studies, Chemdraw and Molecular Operating Environment were used for structure drawing and molecular docking, respectively. Flavonoids isolated from D. carota were docked with cancerous proteins. Result: Based on the docking score analysis, we found that compound 7 was the potent inhibitor of both cancerous proteins and can be used as a potent molecule for inhibition of 2N0W and 4JGR interaction with p53. Conclusion: Thus the compound 7 can be used for the revival of p53 signaling pathway function however, intensive in vitro and in vivo experiments are required to prove the in silico analysis.

scholarly journals HEMGN and SLC2A1 might be potential diagnostic biomarkers of steroid-induced osteonecrosis of femoral head: study based on WGCNA and DEGs screening

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhixin Wu ◽  
Yinxian Wen ◽  
Guanlan Fan ◽  
Hangyuan He ◽  
Siqi Zhou ◽  
...  
Keyword(s):  
Femoral Head ◽  
Roc Curve ◽  
Enrichment Analysis ◽  
Diagnostic Value ◽  
Functional Enrichment ◽  
Pathway Enrichment Analysis ◽  
Overlapping Genes ◽  
Hub Genes ◽  
Diagnostic Biomarkers ◽  
Key Genes

Abstract Background Steroid-induced osteonecrosis of the femoral head (SONFH) is a chronic and crippling bone disease. This study aims to reveal novel diagnostic biomarkers of SONFH. Methods The GSE123568 dataset based on peripheral blood samples from 10 healthy individuals and 30 SONFH patients was used for weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) screening. The genes in the module related to SONFH and the DEGs were extracted for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Genes with |gene significance| > 0.7 and |module membership| > 0.8 were selected as hub genes in modules. The DEGs with the degree of connectivity ≥5 were chosen as hub genes in DEGs. Subsequently, the overlapping genes of hub genes in modules and hub genes in DEGs were selected as key genes for SONFH. And then, the key genes were verified in another dataset, and the diagnostic value of key genes was evaluated by receiver operating characteristic (ROC) curve. Results Nine gene co-expression modules were constructed via WGCNA. The brown module with 1258 genes was most significantly correlated with SONFH and was identified as the key module for SONFH. The results of functional enrichment analysis showed that the genes in the key module were mainly enriched in the inflammatory response, apoptotic process and osteoclast differentiation. A total of 91 genes were identified as hub genes in the key module. Besides, 145 DEGs were identified by DEGs screening and 26 genes were identified as hub genes of DEGs. Overlapping genes of hub genes in the key module and hub genes in DEGs, including RHAG, RNF14, HEMGN, and SLC2A1, were further selected as key genes for SONFH. The diagnostic value of these key genes for SONFH was confirmed by ROC curve. The validation results of these key genes in GSE26316 dataset showed that only HEMGN and SLC2A1 were downregulated in the SONFH group, suggesting that they were more likely to be diagnostic biomarkers of SOFNH than RHAG and RNF14. Conclusions Our study identified that two key genes, HEMGN and SLC2A1, might be potential diagnostic biomarkers of SONFH.

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