scholarly journals Bioinformatics Prediction and Experimental Verification Identify MAD2L1 and CCNB2 as Diagnostic Biomarkers of Rhabdomyosarcoma

2021 ◽  
Author(s):  
Tian Xia ◽  
Lian Meng ◽  
Zhijuan Zhao ◽  
Yujun Li ◽  
Hao Wen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Clinical Stage ◽  
Gene Set Enrichment Analysis ◽  
Clinical Staging ◽  
Control Group ◽  
Soft Tissue Tumour ◽  
Hub Genes ◽  
Expression Levels ◽  
Differential Genes

Abstract 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 187 patients with rhabdomyosarcoma (RMS) from the Gene Expression Omnibus database (GEO). Then, we used cell function and molecular biology techniques to study the progress 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 network, and then Gene Expression Profiling Interactive Analysis was conducted to measure the overall survival (OS) of the 10 hub genes in the sarcoma cases in The Cancer Genome Atlas (TCGA). Six differential genes of statistical significance were acquired. The correlation between these six differential genes and the clinical stage of RMS was analysed. Our data found that the expression levels of MAD2L1 and CCNB2 negatively correlated with the OS of RMS patients and positively correlated with the clinical stage of RMS patients. 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. Further gene set enrichment analysis 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. 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 may help guide the prognosis of patients with RMS and the clinical staging of tumours.

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

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Tian Xia ◽  
Lian Meng ◽  
Zhijuan Zhao ◽  
Yujun Li ◽  
Hao Wen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Stage ◽  
Gene Set Enrichment Analysis ◽  
High Expression ◽  
Clinical Staging ◽  
Soft Tissue Tumour ◽  
Hub Genes ◽  
Expression Levels ◽  
The Relationship ◽  
Differential Genes

Abstract 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.

scholarly journals Identification of novel biomarkers involved in pulmonary arterial hypertension based on multiple-microarray analysis

2020 ◽  
Vol 40 (9) ◽  
Author(s):  
Yi Ma ◽  
Shu-Shu Chen ◽  
Yan-Yan Feng ◽  
Huan-Liang Wang
Keyword(s):  
Gene Expression ◽  
Pulmonary Arterial Hypertension ◽  
Arterial Hypertension ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Control Group ◽  
Hub Genes ◽  
Gene Set ◽  
Pulmonary Arterial

Abstract Pulmonary arterial hypertension (PAH) is a life-threatening chronic cardiopulmonary disorder. However, studies providing PAH-related gene expression profiles are scarce. To identify hub genes involved in PAH, we investigate two microarray data sets from gene expression omnibus (GEO). A total of 150 differentially expressed genes (DEGs) were identified by limma package. Enriched Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of DEGs mostly included mitotic nuclear division, ATPase activity, and Herpes simplex virus one infection. Ten hub genes from three significant modules were ascertained by Cytoscape (CytoHubba). Gene set enrichment analysis (GSEA) plots showed that transcription elongation factor complex was the most significantly enriched gene set positively correlated with the PAH group. At the same time, solute proton symporter activity was the most significantly enriched gene set positively correlated with the control group. Correlation analysis between hub genes suggested that SMC4, TOP2A, SMC2, KIF11, KIF23, ANLN, ARHGAP11A, SMC3, SMC6 and RAD50 may involve in the pathogenesis of PAH. Then, the miRNA-target genes regulation network was performed to unveil the underlying complex association among them. Finally, RNA extracted from monocrotaline (MCT)-induced Rat-PAH model lung artery tissues were to conduct quantitative real-time PCR (qRT-PCR) to validate these hub genes. In conclusion, our study offers new evidence for the underlying molecular mechanisms of PAH as well as attractive targets for diagnosis and treatment of PAH.

scholarly journals Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data

2021 ◽  
Vol 12 ◽  
Author(s):  
Albert Martínez-Pinteño ◽  
Patricia Gassó ◽  
Llucia Prohens ◽  
Alex G. Segura ◽  
Mara Parellada ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Gene Set Enrichment Analysis ◽  
Metabolic Effects ◽  
First Episode ◽  
Hormone Regulation ◽  
Metabolic Abnormalities ◽  
Expression Levels ◽  
Cholesterol Levels ◽  
Mouse Tissues

Antipsychotics (APs) are associated with weight gain and other metabolic abnormalities such as hyperglycemia, dyslipidemia and metabolic syndrome. This translational study aimed to uncover the underlying molecular mechanisms and identify the key genes involved in AP-induced metabolic effects. An integrative gene expression analysis was performed in four different mouse tissues (striatum, liver, pancreas and adipose) after risperidone or olanzapine treatment. The analytical approach combined the identification of the gene co-expression modules related to AP treatment, gene set enrichment analysis and protein-protein interaction network construction. We found several co-expression modules of genes involved in glucose and lipid homeostasis, hormone regulation and other processes related to metabolic impairment. Among these genes, EP300, which encodes an acetyltransferase involved in transcriptional regulation, was identified as the most important hub gene overlapping the networks of both APs. Then, we explored the genetically predicted EP300 expression levels in a cohort of 226 patients with first-episode psychosis who were being treated with APs to further assess the association of this gene with metabolic alterations. The EP300 expression levels were significantly associated with increases in body weight, body mass index, total cholesterol levels, low-density lipoprotein cholesterol levels and triglyceride concentrations after 6 months of AP treatment. Taken together, our analysis identified EP300 as a key gene in AP-induced metabolic abnormalities, indicating that the dysregulation of EP300 function could be important in the development of these side effects. However, more studies are needed to disentangle the role of this gene in the mechanism of action of APs.

Validation of novel hub genes and molecular mechanisms in acute lung injury using an integrative bioinformatics approach

2021 ◽  
Author(s):  
Qingchun Liang ◽  
Qin Zhou ◽  
Jinhe Li ◽  
Zhugui Chen ◽  
Zhihao Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lung Injury ◽  
Lung Injury ◽  
Molecular Mechanisms ◽  
Molecular Biomarkers ◽  
Functional Enrichment ◽  
Lung Injury Score ◽  
Control Group ◽  
High Morbidity ◽  
Hub Genes

Abstract Acute lung injury (ALI) is an inflammatory pulmonary disease that can easily develop into serious acute respiratory distress syndrome, which has high morbidity and mortality. However, the molecular mechanism of ALI remains unclear, and few molecular biomarkers for diagnosis and treatment have been identified. In this study, we aimed to identify novel molecular biomarkers using a bioinformatics approach. Gene expression data were obtained from the Gene Expression Omnibus database, co-expressed differentially expressed genes (CoDEGs) were identified using R software, and further functional enrichment analyses were conducted using the online tool Database for Annotation, Visualization, and Integrated Discovery. A protein–protein interaction network was established using the STRING database and Cytoscape software. Lipopolysaccharide (LPS)-induced ALI mouse model was constructed and verified. The hub genes were screened and validated in vivo. The transcription factors (TFs) and miRNAs associated with the hub genes were predicted using the NetworkAnalyst database. In total, 71 CoDEGs were screened and found to be mainly involved in the cytokine–cytokine receptor interactions, and the tumor necrosis factor and malaria signaling pathways. Animal experiments showed that the lung injury score, bronchoalveolar lavage fluid protein concentration, and wet-to-dry weight ratio were higher in the LPS group than those in the control group. Real-time polymerase chain reaction analysis indicated that most of the hub genes such as colony-stimulating factor 2 (Csf2) were overexpressed in the LPS group. A total of 20 TFs including nuclear respiratory factor 1 (NRF1) and two miRNAs were predicted to be regulators of the hub genes. In summary, Csf2 may serve as a novel diagnostic and therapeutic target for ALI. NRF1 and mmu-mir-122-5p may be key regulators in the development of ALI.

scholarly journals Relevance of cancer cachexia models – muscle whole genome gene expression in human and animal cachexia

2020 ◽  
Author(s):  
Rogier L.C. Plas ◽  
Guido Hooiveld ◽  
Renger F. Witkamp ◽  
Klaske van Norren
Keyword(s):  
Gene Expression ◽  
Animal Models ◽  
Molecular Mechanisms ◽  
Gene Set Enrichment Analysis ◽  
The Other ◽  
Control Group ◽  
Whole Genome ◽  
Transport Pathway ◽  
Different Levels ◽  
Human Dataset

Abstract BackgroundCancer cachexia is a complex and multi-factorial syndrome. As currently available therapeutic options are limited, more in-depth knowledge on cachexia pathophysiology and the underlying molecular mechanisms remains warranted. Studies with animal models provide useful insights but they only mimic the human situation to a certain degree. Furthermore, there is heterogeneity in the design of published animal studies and outcomes. To further address this issue, we performed a comparative study analysing muscle whole genome gene expression of different cachexia studies in mice and human.MethodsWe selected data sets from the NCBI Gene Expression Omnibus database containing muscle gene expression data measured by micro-array or RNA-sequencing, at least comprising a cachectic/tumour bearing group (n>3) and a non-cachectic/control group (n>3). This provided 12 datasets; 9 from mouse models and 3 human datasets. All datasets were quality checked, normalised and annotated. Datasets were merged and compared at different levels. General similarity and differences in gene expression were determined using ordered list analysis and principal component analysis (PCA). Moreover, similarities and differences at pathway level were studied by applying gene set enrichment analysis (GSEA) of KEGG pathways.ResultsAnimal models displayed similarities to each other and to human datasets at different levels and with different processes. At the gene level, a similarity analysis indicated little similarity between the animal models and the human datasets, while animal models showed high similarity. Only one of the C26 mice models (GSE121972) showed significant similarity to more than one human dataset. Moreover, one human dataset comparing cachectic and non-cachectic cancer patients showed no similarity to any of the other datasets. PCA results indicated that a xenograft model showed most different expression from the other datasets and the Lewis lung carcinoma model to be least different from the human datasets. GSEA results showed four pathways clearly standing out across experiments with downregulation of oxidative phosphorylation and thermogenesis pathway, and upregulation of the proteasome and RNA transport pathway. However, these pathways were not consistently changed in the human datasets.ConclusionsOur comparative analysis showed that there is currently no basis to define a preferred animal model for human cachexia. More human datasets containing proper controls are needed. Repetition of the current analysis upon publication of additional human datasets is warranted.

scholarly journals Screen Key Genes Associated with Distraction-Induced Osteogenesis of Stem Cells Using Bioinformatics Methods

2021 ◽  
Vol 22 (12) ◽  
pp. 6505
Author(s):  
Jishizhan Chen ◽  
Jia Hua ◽  
Wenhui Song
Keyword(s):  
Stem Cells ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Negative Control ◽  
Gene Set Enrichment Analysis ◽  
Venn Diagram ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Two Samples ◽  
Key Genes

Applying mesenchymal stem cells (MSCs), together with the distraction osteogenesis (DO) process, displayed enhanced bone quality and shorter treatment periods. The DO guides the differentiation of MSCs by providing mechanical clues. However, the underlying key genes and pathways are largely unknown. The aim of this study was to screen and identify hub genes involved in distraction-induced osteogenesis of MSCs and potential molecular mechanisms. Material and Methods: The datasets were downloaded from the ArrayExpress database. Three samples of negative control and two samples subjected to 5% cyclic sinusoidal distraction at 0.25 Hz for 6 h were selected for screening differentially expressed genes (DEGs) and then analysed via bioinformatics methods. The Gene Ontology (GO) terms and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment were investigated. The protein–protein interaction (PPI) network was visualised through the Cytoscape software. Gene set enrichment analysis (GSEA) was conducted to verify the enrichment of a self-defined osteogenic gene sets collection and identify osteogenic hub genes. Results: Three hub genes (IL6, MMP2, and EP300) that were highly associated with distraction-induced osteogenesis of MSCs were identified via the Venn diagram. These hub genes could provide a new understanding of distraction-induced osteogenic differentiation of MSCs and serve as potential gene targets for optimising DO via targeted therapies.

scholarly journals Study on potential differentially expressed genes in stroke by bioinformatics analysis

2021 ◽  
Author(s):  
Xitong Yang ◽  
Pengyu Wang ◽  
Shanquan Yan ◽  
Guangming Wang
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Normal Control ◽  
Enrichment Analysis ◽  
Normal Control Group ◽  
Control Group ◽  
Ppi Network ◽  
Hub Genes ◽  
Pathway Enrichment ◽  
Key Genes

AbstractStroke is a sudden cerebrovascular circulatory disorder with high morbidity, disability, mortality, and recurrence rate, but its pathogenesis and key genes are still unclear. In this study, bioinformatics was used to deeply analyze the pathogenesis of stroke and related key genes, so as to study the potential pathogenesis of stroke and provide guidance for clinical treatment. Gene Expression profiles of GSE58294 and GSE16561 were obtained from Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) were identified between IS and normal control group. The different expression genes (DEGs) between IS and normal control group were screened with the GEO2R online tool. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed. Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), the function and pathway enrichment analysis of DEGS were performed. Then, a protein–protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. Cytoscape with CytoHubba were used to identify the hub genes. Finally, NetworkAnalyst was used to construct the targeted microRNAs (miRNAs) of the hub genes. A total of 85 DEGs were screened out in this study, including 65 upward genes and 20 downward genes. In addition, 3 KEGG pathways, cytokine − cytokine receptor interaction, hematopoietic cell lineage, B cell receptor signaling pathway, were significantly enriched using a database for labeling, visualization, and synthetic discovery. In combination with the results of the PPI network and CytoHubba, 10 hub genes including CEACAM8, CD19, MMP9, ARG1, CKAP4, CCR7, MGAM, CD79A, CD79B, and CLEC4D were selected. Combined with DEG-miRNAs visualization, 5 miRNAs, including hsa-mir-146a-5p, hsa-mir-7-5p, hsa-mir-335-5p, and hsa-mir-27a- 3p, were predicted as possibly the key miRNAs. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of ischemic stroke, and provide a new strategy for clinical therapy.

Repression of protocadherin 17 is correlated with elevated angiogenesis and hypoxia markers in female patients with breast cancer

2021 ◽  
pp. 1-10
Author(s):  
Sanaa A. El-Benhawy ◽  
Samia A. Ebeid ◽  
Nadia A. Abd El Moneim ◽  
Rabie R. Abdel Wahed ◽  
Amal R.R. Arab
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Clinical Stage ◽  
Suppressor Gene ◽  
Normal Breast ◽  
Vital Role ◽  
Control Group ◽  
Breast Cancer Patients ◽  
Cd34 Cells ◽  
Breast Tissues

BACKGROUND: Altered cadherin expression plays a vital role in tumorigenesis, angiogenesis and tumor progression. However, the function of protocadherin 17 (PCDH17) in breast cancer remains unclear. OBJECTIVE: Our target is to explore PCDH17 gene expression in breast carcinoma tissues and its relation to serum angiopoietin-2 (Ang-2), carbonic anhydrase IX (CAIX) and % of circulating CD34+ cells in breast cancer patients (BCPs). METHODS: This study included Fifty female BCPs and 50 healthy females as control group. Cancerous and neighboring normal breast tissues were collected from BCPs as well as blood samples at diagnosis PCDH17 gene expression was evaluated by RT-PCR. Serum Ang-2, CAIX levels were measured by ELISA and % CD34+ cells were assessed by flow cytometry. RESULTS: PCDH17 was downregulated in cancerous breast tissues and its repression was significantly correlated with advanced stage and larger tumor size. Low PCDH17 was significantly correlated with serum Ang-2, % CD34+ cells and serum CAIX levels. Serum CAIX, Ang-2 and % CD34+ cells levels were highly elevated in BCPs and significantly correlated with clinical stage. CONCLUSIONS: PCDH17 downregulation correlated significantly with increased angiogenic and hypoxia biomarkers. These results explore the role of PCDH17 as a tumor suppressor gene inhibiting tumor growth and proliferation.

scholarly journals Genes associated with inflammation and bone remodeling are highly expressed in the bone of patients with the early-stage cam-type femoroacetabular impingement

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Guanying Gao ◽  
Ruiqi Wu ◽  
Rongge Liu ◽  
Jianquan Wang ◽  
Yingfang Ao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Tissue ◽  
Bone Remodeling ◽  
Femoroacetabular Impingement ◽  
Early Stage ◽  
Control Group ◽  
Tissue Samples ◽  
Expression Levels ◽  
Normal Bone ◽  
Impingement Zone

Abstract Background Recent studies have shown high expression levels of certain inflammatory, anabolic, and catabolic genes in the articular cartilage from the impingement zone of the hips with femoroacetabular impingement (FAI), representing an increased metabolic state. Nevertheless, little is known about the molecular properties of bone tissue from the impingement zone of hips with FAI. Methods Bone tissue samples from patients with early-stage cam-type FAI were collected during hip arthroscopy for treatment of cam-type FAI. Control bone tissue samples were collected from six patients who underwent total hip replacement because of a femoral neck fracture. Quantitative real-time polymerase chain reaction (PCR) was performed to determine the gene expression associated with inflammation and bone remodeling. The differences in the gene expression in bone tissues from the patients with early-stage cam-type FAI were also evaluated based on clinical parameters. Results In all, 12 patients with early-stage cam-type FAI and six patients in the control group were included in this study. Compared to the control samples, the bone tissue samples from patients with FAI showed higher expression levels of interleukin-6 (IL-6), alkaline phosphatase (ALP), receptor activator of nuclear factor-kB ligand (RANKL), and osteoprotegerin (OPG) (P < 0.05). IL-1 expression was detected only in the control group. On the other hand, there was no significant difference in IL-8 expression between the patients with FAI and the control group. The patients with FAI having a body mass index (BMI) of >24 kg/m2 showed higher ALP expression (P < 0.05). Further, the expression of IL-6 and ALP was higher in the patients with FAI in whom the lateral center-edge angle was >30° (P < 0.05). Conclusions Our results indicated the metabolic condition of bone tissues in patients with early-stage cam-type FAI differed from that of normal bone in the femoral head-neck junction. The expression levels of the genes associated with inflammation and bone remodeling were higher in the bone tissue of patients with early-stage cam-type FAI than in the patients with normal bone tissue.

scholarly journals Identification of Pathways and Key Genes in Venous Remodeling After Arteriovenous Fistula by Bioinformatics Analysis

2020 ◽  
Vol 11 ◽  
Author(s):  
Kong Jie ◽  
Wang Feng ◽  
Zhao Boxiang ◽  
Gong Maofeng ◽  
Zhang Jianbin ◽  
...  
Keyword(s):  
Arteriovenous Fistula ◽  
Pathway Analysis ◽  
Kegg Pathway ◽  
Function Analysis ◽  
Gene Set Enrichment Analysis ◽  
Control Group ◽  
Hub Genes ◽  
Molting Cycle ◽  
Kegg Pathway Analysis ◽  
First Choice

The arteriovenous fistula (AVF) is the first choice for vascular access for hemodialysis of renal failure patients. Venous remodeling after exposure to high fistula flow is important for AVF to mature but the mechanism underlying remodeling is still unknown. The objective of this study is to identify the molecular mechanisms that contribute to venous remodeling after AVF. To screen and identify the differentially expressed genes (DEGs) that may involve venous remodeling after AVF, we used bioinformatics to download the public microarray data (GSE39488) from the Gene Expression Omnibus (GEO) and screen for DEGs. We then performed gene ontology (GO) function analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and gene set enrichment analysis (GSEA) for the functional annotation of DEGs. The protein-protein interaction (PPI) network was constructed and the hub genes were carried out. Finally, we harvested 12 normal vein samples and 12 AVF vein samples which were used to confirm the expressions of the hub genes by immunohistochemistry. A total of 45 DEGs were detected, including 32 upregulated and 13 downregulated DEGs. The biological process (BP) of the GO analysis were enriched in the extrinsic apoptotic signaling pathway, cGMP-mediated pathway signaling, and molting cycle. The KEGG pathway analysis showed that the upregulated DEGs were enriched in glycosaminoglycan biosynthesis and purine metabolism, while the downregulated DEGs were mainly enriched in pathways of glycosaminoglycan biosynthesis, antifolate resistance, and ABC transporters. The GSEA analysis result showed that the top three involved pathways were oxidative phosphorylation, TNFA signaling via NF-K B, and the inflammatory response. The PPI was constructed and the hub genes found through the method of DMNC showed that INHBA and NR4A2 might play an important role in venous remodeling after AVF. The integrated optical density (DOI) examined by immunohistochemistry staining showed that the expression of both INHBA and NR4A2 increased in AVF compared to the control group. Our research contributes to the understanding of the molecular mechanism of venous remodeling after exposure to high fistula flow, which may be useful in treating AVF failure.

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