scholarly journals Identification of Potential Autophagy-Related Genes in Steroid-Induced Osteonecrosis of the Femoral Head

2021 ◽  
Author(s):  
XueZhen LIANG ◽  
Di LUO ◽  
Yan-Rong CHEN ◽  
Jia-Cheng LI ◽  
Bo-Zhao YAN ◽  
...  
Keyword(s):  
Femoral Head ◽  
Correlation Analysis ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
R Software ◽  
Pathway Enrichment

Abstract Purpose: Steroid-induced osteonecrosis of the femoral head (SONFH) was a refractory orthopedic hip joint disease in the young and middle-aged people. Previous experimental studies had shown that autophagy might be involved in the pathological process of SONFH, but the pathogenesis of autophagy in SONFH remained unclear. We aim to identify and validate the key potential autophagy-related genes of SONFH to further illustrate the mechanism of autophagy in SONFH through bioinformatics analysis. Methods: The mRNA expression profile dataset GSE123568 was download from Gene Expression Omnibus (GEO) database, including 10 non-SONFH (following steroid administration) samples and 30 SONFH samples. The autophagy-related genes were obtained from the Human Autophagy Database (HADb). The autophagy-related genes of SONFH were screened by intersecting GSE123568 dataset with autophagy genes. The differentially expressed autophagy-related genes of SONFH were identified by R software. Besides, the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted for the differentially expressed autophagy-related genes of SONFH by R software. Then, the correlation analysis between the expression levels of differentially expressed autophagy-related genes of SONFH was confirmed by R software. Moreover, the protein–protein interaction (PPI) network were analyzed by the Search Tool for the Retrieval of Interacting Genes (STRING), and the significant gene cluster modules were identified by the MCODE Cytoscape plugin, and hub genes of differentially expressed autophagy-related genes of SONFH were screened by the CytoHubba Cytoscape plugin. Finally, the expression levels of hub genes of differentially expressed autophagy-related genes of SONFH was validated in hip articular cartilage specimens from necrosis femur head (NFH) by GSE74089 dataset. Results: A total of 34 differentially expressed autophagy-related genes were identified between the peripheral blood of SONFH samples and non-SONFH Samples based on the defined criteria, including 25 up-regulated genes and 9 down-regulated genes. The GO and KEGG pathway enrichment analysis revealed that these 34 differentially expressed autophagy-related genes of SONFH were concentrated in death domain receptors, FOXO signaling pathway and apoptosis. The correlation analysis revealed a significant correlation among the 34 differentially expressed autophagy-related genes of SONFH. The PPI results demonstrated that the 34 differentially expressed autophagy-related genes interacted with each other. There were 10 hub genes identified by the MCC algorithms of Cytohubba. The results of GSE74089 dataset showed TNFSF10, PTEN and CFLAR were significantly upregulated while BCL2L1 were significantly downregulated in the hip cartilage specimens, which were consistent with the GSE123568 dataset. Conclusions: There were 34 potential autophagy-related genes of SONFH identified using bioinformatics analysis. TNFSF10, PTEN, CFLAR and BCL2L1 might serve as potential drug targets and biomarkers by regulating autophagy. These results would expand new insights into the autophagy-related understanding of SONFH and might be useful in the diagnosis and prognosis of SONFH.

scholarly journals Transcriptomic analysis of Procambarus clarkii affected by “Black May” disease

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Guoqing Shen ◽  
Xiao Zhang ◽  
Jie Gong ◽  
Yang Wang ◽  
Pengdan Huang ◽  
...  
Keyword(s):  
Procambarus Clarkii ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Apoptosis Pathway ◽  
Pathway Enrichment ◽  
Cellular Processes ◽  
Expression Of Genes ◽  
Muscle Tissues

AbstractEach year from April to May, high mortality rates are reported in red swamp crayfish (Procambarus clarkii) cultured in Jiangsu and other regions, in China, and this phenomenon has come to be known as “Black May” disease (BMD). Therefore, in order to investigate the possible causes of this disease, this study gathered BMD-affected P. clarkii samples and performed transcriptome analysis on hepatopancreas, gill, and muscle tissues. A total of 19,995,164, 149,212,804, and 222,053,848 clean reads were respectively obtained from the gills, muscle, and hepatopancreas of BMD-affected P. clarkii, and 114,024 unigenes were identified. The number of differentially expressed genes (DEGs) in gill, muscle, and hepatopancreas was 1703, 964, and 476, respectively. GO and KEGG enrichment analyses of the DEGs were then conducted. Based on KEGG pathway enrichment analysis, the most significantly differentially expressed pathways were mainly those involved with metabolism, human disease, and cellular processes. Further analysis of the significantly DEGs revealed that they were mainly related to the mitochondrial-mediated apoptosis pathway and that the expression of these DEGs was mostly down-regulated. Moreover, the expression of genes related to immune and metabolism-related pathways was also significantly down-regulated, and these significantly-inhibited pathways were the likely causes of P. clarkii death. Therefore, our results provide a basis for the identification of BMD causes.

scholarly journals Immunological analysis and differential genes screening of venous thromboembolism

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Li-Na Gao ◽  
Qiang Li ◽  
Jian-Qin Xie ◽  
Wan-Xia Yang ◽  
Chong-Ge You
Keyword(s):  
Venous Thromboembolism ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
R Software ◽  
Pathway Enrichment ◽  
Protein Protein Interaction ◽  
New Ideas ◽  
Gene Expression Profile Data ◽  
Differential Genes

Abstract Purpose To explore the pathogenesis of venous thromboembolism (VTE) and provide bioinformatics basis for the prevention and treatment of VTE. Methods The R software was used to obtain the gene expression profile data of GSE19151, combining with the CIBERSORT database, obtain immune cells and differentially expressed genes (DEGs) of blood samples of VTE patients and normal control, and analyze DEGs for GO analysis and KEGG pathway enrichment analysis. Then, the protein-protein interaction (PPI) network was constructed by using the STRING database, the key genes (hub genes) and immune differential genes were screened by Cytoscape software, and the transcription factors (TFs) regulating hub genes and immune differential genes were analyzed by the NetworkAnalyst database. Results Compared with the normal group, monocytes and resting mast cells were significantly expressed in the VTE group, while regulatory T cells were significantly lower. Ribosomes were closely related to the occurrence of VTE. 10 hub genes and immune differential genes were highly expressed in VTE. MYC, SOX2, XRN2, E2F1, SPI1, CREM and CREB1 can regulate the expressions of hub genes and immune differential genes. Conclusions Ribosomal protein family genes are most relevant to the occurrence and development of VTE, and the immune differential genes may be the key molecules of VTE, which provides new ideas for further explore the pathogenesis of VTE.

scholarly journals Deciphering Expression Profiling and Functional Signatures of Individualized Obesity-Associated Genes in Ossification of Ligamentum Flavum Through RNA-Sequence Data Mining

2021 ◽  
Author(s):  
Baoliang Zhang ◽  
Lei Yuan ◽  
Guanghui Chen ◽  
Xi Chen ◽  
Xiaoxi Yang ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Immune Cells ◽  
Ligamentum Flavum ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Ossification Of Ligamentum Flavum

Abstract Background: Obese individuals predispose to ossification of ligamentum flavum (OLF), whereas the underlying connections between obesity phenotype and OLF pathomechanism are not fully understood, especially during early life. This study aimed to explore obesity-associated genes and their functional signatures in OLF. Methods: Gene microarray expression data related to OLF were downloaded from the GSE106253 dataset in the Gene Expression Omnibus (GEO) database. The potential obesity-related differentially expressed genes (ORDEGs) in OLF were screened. Then, gene-ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied for these genes. Furthermore, protein-protein interactions (PPI) were used to identify hub ORDEGs, and Metascape was used to further verify the key signaling pathways and immune-related function signatures of hub ORDEGs. Finally, correlation analysis of hub ORDEGs and identified OLF-related infiltrating immune cells (OIICs) was constructed to understand the possible mechanical link among obesity, immune response and OLF. Results: OLF-related differentially expressed genes and 2051 obesity-related genes from four databases were intersected to obtain 99 ORDEGs, including 54 upregulated and 55 downregulated genes. GO and KEGG analysis revealed that these genes were mainly involved in metabolism, inflammation and immune-related biological functions and pathways. A PPI network was established to determine 14 hub genes (AKT1, CCL2, CCL5, CXCL2, ICAM1, IL10, MYC, PTGS2, SAA1, SOCS1, SOCS3, STAT3, TNFRSF1B and VEGFA). The co-expression network demonstrated that this module was associated with cellular response to biotic stimulus, regulation of inflammatory response, regulation of tyrosine phosphorylation of STAT protein. Furthermore, Metascape functional annotations showed that hub genes were mainly involved in receptor signaling pathway via JAK-STAT, response to TNF and regulation of defense response, and their representative enriched pathways were TNF, adipocytokine and JAK-STAT signaling pathways. Subgroup analysis indicated that T cell activation might be potential immune function processes involved, and correlation analysis revealed that cDCs, memory B-cells and preadipocytes were highly correlated infiltrating immune cells. Conclusions: Our study deciphered individualized obesity-associated gene signature for the first time, which may facilitate exploring the underlying cellular and molecular pathogenesis and novel therapeutic targets of obesity-related early-onset OLF.

scholarly journals Construction of a circRNA-miRNA-mRNA network based on competitive endogenous RNA reveals the key pathways and central genes of osteosarcoma in vivo

2021 ◽  
Author(s):  
Zhihao Chen ◽  
Xi Wang ◽  
Liubing Li ◽  
Mingxiao Han ◽  
Min Wang ◽  
...  
Keyword(s):  
Protein Modification ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Micro Rna ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Go Annotation ◽  
Pathway Enrichment ◽  
Ppi Networks

Abstract Circular RNAs (circRNAs) play important roles in a variety of pathological functions. However, the potential functions and detailed mechanisms of circRNAs in osteosarcoma (OS) have not been fully elucidated. In this study, the circRNA, micro RNA (miRNA), and messenger RNA (mRNA) expression profile of human OS was investigated based on the raw microarray data GSE140256, GSE65071 and GSE16088 in Gene Expression Omnibus (GEO) datasets, and seven differentially-expressed circRNAs (DEcircRNAs), 166 differentially-expressed miRNAs (DEmiRNAs), and 175 differentially-expressed mRNAs (DEmRNAs) were identified in total. FunRich was employed to analyze the differentially-expressed transcription factors on the basis of identified DEmiRNAs. In addition, the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to further study biological functions of the DEmRNAs. Interestingly, post-translational protein modification, collagen-containing extracellular matrix, and single-stranded DNA binding were the most significant pathways enriched for DEmRNAs in GO annotation analysis. Meanwhile, in KEGG pathway enrichment analysis, complement and coagulation cascades, RNA transport and drug metabolism − other enzymes were the most significantly enriched pathways of DEmRNAs in OS. We constructed circRNA-miRNA-mRNA and protein–protein interaction (PPI) networks that may be associated with pathological processes of OS. Finally, we also revealed the pattern of tumor-infiltrating immune cells in OS and further explored the ceRNA networks we constructed in which we found that COL1A1 and RAN were significantly correlated with overall survival in patients with osteosarcoma (p < 0.05). To our knowledge, this study provides the first profile analysis of DEcircRNAs, DEmiRNAs, and DEmRNAs with OS in vivo and reveals a novel idea for understanding the pathogenesis of OS.

scholarly journals Screening of Osteoarthritis-Related Genes and Function Determination Based on Bioinformatics Tools

2021 ◽  
Author(s):  
Zheng Fu ◽  
Weiqian Jiang ◽  
Wenlong Yan ◽  
Fei Xie ◽  
Yu Chen ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Experimental Studies ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Pathway Enrichment ◽  
Early Diagnostic

Abstract Background:Osteoarthritis(OA), commonly seen in the middle-aged and elderly population, imposes a heavy burden on patients from the clinical, humanistic and economic aspects. Our work aims at the discovery of early diagnostic and therapeutic targets for OA and new candidate biomarkers for experimental studies on OA via bioinformatics analysis.Methods:The dataset GSE114007 was downloaded from GEO to identify differentially expressed genes(DEGs) in R using 3 different algorithms. Overlapping DEGs were subject to GO and KEGG pathway enrichment analysis and functional annotation. Following the identification of DEGs, a protein-protein interaction(PPI) network was established and imported into Cytoscape to screen for hubgenes. The expression of each hubgene was verified in two other datasets and create miRNA-mRNA regulatory networks.Results:174 upregulated genes and 117 downregulated genes were identified among the overlapping DEGs. According to the results of GO enrichment analysis,MF enrichment was basically found in ECM degradation and collagen breakdown; enrichment was also present in the development, ossification, and differentiation of cells. The KEGG pathway enrichment analysis suggested significant enrichment in such pathways as PI3K-AKT, P53, TNF, and FoxO. 23 hubgenes were obtained from the PPI network, and 11 genes were identified as DEGs through verification. 8 genes were used for the establishment of miRNA-mRNA regulatory networks.Conclusion:OA-related genes, proteins, pathways and miRNAs that were identified through bioinformatics analysis may provide a reference for the discovery of early diagnostic and therapeutic targets for OA, as well as candidate biomarkers for experimental studies on OA.

scholarly journals Immunological Analysis and Differential Genes Screening of Venous Thromboembolism

2020 ◽  
Author(s):  
Li-Na Gao ◽  
Qiang Li ◽  
Jian-Qin Xie ◽  
Wan-Xia Yang ◽  
Chong-Ge You
Keyword(s):  
Venous Thromboembolism ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
R Software ◽  
Pathway Enrichment ◽  
Protein Protein Interaction ◽  
New Ideas ◽  
Gene Expression Profile Data ◽  
Differential Genes

Abstract Purpose: To explore the pathogenesis of venous thromboembolism (VTE) and provide bioinformatics basis for the prevention and treatment of VTE. Methods: The R software was used to obtain the gene expression profile data of GSE19151, combining with the CIBERSORT database, obtain immune cells and differentially expressed genes (DEGs) of blood samples of VTE patients and normal control, and analyze DEGs for GO analysis and KEGG pathway enrichment analysis. Then, the protein-protein interaction (PPI) network was constructed by using the STRING database, the key genes (hub genes) and immune differential genes were screened by Cytoscape software, and the transcription factors (TFs) regulating hub genes and immune differential genes were analyzed by the NetworkAnalyst database. Results: Compared with the normal group, monocytes and resting mast cells were significantly expressed in the VTE group, while regulatory T cells were significantly lower. Ribosomes were closely related to the occurrence of VTE. 10 hub genes and immune differential genes were highly expressed in VTE. MYC, SOX2, XRN2, E2F1, SPI1, CREM and CREB1 can regulate the expressions of hub genes and immune differential genes. Conclusions: Ribosomal protein family genes are most relevant to the occurrence and development of VTE, and the immune differential genes may be the key molecules of VTE, which provides new ideas for further explore the pathogenesis of VTE.

Identification of Differentially Expressed Genes and Signaling Pathways Related to Ovarian Endometriosis by Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Kainan Lin ◽  
Zhenyan Pan ◽  
Renke He ◽  
Hanchu Wang ◽  
Kai Zhou ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Go Analysis ◽  
Pathway Enrichment

Abstract Purpose: Endometriosis was a common gynecological disease, however, the specific mechanism and the key molecules of endometriosis remained uncertain. This study aimed to single out key genes associated with poor prognosis, and further uncover underlying mechanisms.Methods: Data regarding mRNA expression profiles used in this study were retrieved from the Gene Expression Omnibus (GEO) database, a total of three mRNA expression profiles were included for subsequent analysis (GSE31515, GSE58178 and GSE120103). Then, we conducted Gene Ontology analysis (GO analysis), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) analysis by the software R.Results: A total of 304 differentially expressed genes (DEGs) between endometriosis tissues and normal endometrium tissues were identified in integrated analysis, including 185 up-regulated genes and 119 down-regulated genes. GO analysis reveals that the DEGs of endometriosis were closely associated with molecular origin of bacteria. KEGG pathway enrichment analysis indicates that the DEGs were mainly involved in AGE-RAGE signaling pathway in diabetic complications. In addition, PPI of these DEGs was visualized by Cytoscape platform with utilization of Search Tool for the Retrieval of Interacting Genes (STRING). PPI analysis identifies 10 potential DEGs-related protein targets, including CCND1, IL6, CCL2, COL1A2, PTGS2, VCAM1, COL3A1, ELN, SERPINE1, HSP90B1. Conclusion: In conclusion, the present study reveals that bacterial contamination, defect of female reproductive system development, retrograde menstruation and the AGE-RAGE signaling pathway may be involved in the development of endometriosis In addition, these identified DEGs may be of clinical significance for the diagnosis and treatment of the endometriosis.

scholarly journals Comprehensive Analyses of miRNA-mRNA Network and Potential Drugs in Idiopathic Pulmonary Arterial Hypertension

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Chan Li ◽  
Zeyu Zhang ◽  
Qian Xu ◽  
Ruizheng Shi
Keyword(s):  
Pulmonary Arterial Hypertension ◽  
Arterial Hypertension ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Idiopathic Pulmonary Arterial Hypertension ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Pulmonary Arterial

Introduction. Idiopathic pulmonary arterial hypertension (IPAH) is a severe cardiopulmonary disease with a relatively low survival rate. Moreover, the pathogenesis of IPAH has not been fully recognized. Thus, comprehensive analyses of miRNA-mRNA network and potential drugs in IPAH are urgent requirements. Methods. Microarray datasets of mRNA and microRNA (miRNA) in IPAH were searched and downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMIs) were identified. Then, the DEMI-DEG network was conducted with associated comprehensive analyses including Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis, while potential drugs targeting hub genes were investigated using L1000 platform. Results. 30 DEGs and 6 DEMIs were identified in the lung tissue of IPAH. GO and KEGG pathway analyses revealed that these DEGs were mostly enriched in antimicrobial humoral response and African trypanosomiasis, respectively. The DEMI-DEG network was conducted subsequently with 4 DEMIs (hsa-miR-34b-5p, hsa-miR-26b-5p, hsa-miR-205-5p, and hsa-miR-199a-3p) and 16 DEGs, among which 5 DEGs (AQP9, SPP1, END1, VCAM1, and SAA1) were included in the top 10 hub genes of the PPI network. Nimodipine was identified with the highest CMap connectivity score in L1000 platform. Conclusion. Our study conducted a miRNA-mRNA network and identified 4 miRNAs as well as 5 mRNAs which may play important roles in the pathogenesis of IPAH. Moreover, we provided a new insight for future therapies by predicting potential drugs targeting hub genes.

scholarly journals Weighted gene co-expression network analysis identifies modules and functionally enriched pathways in the lactation process

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mohammad Farhadian ◽  
Seyed Abbas Rafat ◽  
Bahman Panahi ◽  
Christopher Mayack
Keyword(s):  
Network Analysis ◽  
Regulatory Networks ◽  
Kegg Pathway ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Phenotypic Traits ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Pathway Enrichment ◽  
Dependent Protein

AbstractThe exponential growth in knowledge has resulted in a better understanding of the lactation process in a wide variety of animals. However, the underlying genetic mechanisms are not yet clearly known. In order to identify the mechanisms involved in the lactation process, various mehods, including meta-analysis, weighted gene co-express network analysis (WGCNA), hub genes identification, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment at before peak (BP), peak (P), and after peak (AP) stages of the lactation processes have been employed. A total of 104, 85, and 26 differentially expressed genes were identified based on PB vs. P, BP vs. AP, and P vs. AP comparisons, respectively. GO and KEGG pathway enrichment analysis revealed that DEGs were significantly enriched in the “ubiquitin-dependent ERAD” and the “chaperone cofactor-dependent protein refolding” in BP vs. P and P vs. P, respectively. WGCNA identified five significant functional modules related to the lactation process. Moreover, GJA1, AP2A2, and NPAS3 were defined as hub genes in the identified modules, highlighting the importance of their regulatory impacts on the lactation process. The findings of this study provide new insights into the complex regulatory networks of the lactation process at three distinct stages, while suggesting several candidate genes that may be useful for future animal breeding programs. Furthermore, this study supports the notion that in combination with a meta-analysis, the WGCNA represents an opportunity to achieve a higher resolution analysis that can better predict the most important functional genes that might provide a more robust bio-signature for phenotypic traits, thus providing more suitable biomarker candidates for future studies.

scholarly journals BioinformaticsAnalysis of the Muscle-invasive Bladder Cancer Subtypes

1970 ◽  
Vol 2 (2) ◽  
Author(s):  
Wenbin Xu ◽  
Weiying Zheng ◽  
Hong Xia ◽  
Lin Hua
Keyword(s):  
Extracellular Matrix ◽  
Bladder Cancer ◽  
Inflammatory Response ◽  
Differentially Expressed Genes ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Cancer Subtypes ◽  
Pathway Enrichment

Objective In order to improve the accuracy in distinguishing subtypes of bladder cancer and to explore its potential therapeutic targets, we identify differences between two kinds of bladder cancer subtypes (basal-like and luminal) in molecular mechanism and molecular characteristics based on the bioinformatics analysis. Methods In this study, the RMA (robust multichip averaging) was applied to normalize the mRNA profile which included 22 samples from basal-like subtype and 132 from luminal subtype, and the differential expression analysis of genes with top 1000 highest standard deviation was performed. Then, the Gene Ontology and KEGG pathway enrichment analysis of differentially expressed genes was performed. In addition, the protein-protein interactions networks analysis for the top 100 most significant differentially expressed genes was performed. Results A total of 742 differentially expressed genes distinguishing basal-like and luminal subtypes were found, of which 405 were up-regulated and 337 genes were down-regulated in basal-like subtype. GO enrichment analysis showed that differentially expressed genes were significantly enriched in the extracellular matrix, chemotaxis and inflammatory response. KEGG pathway enrichment analysis showed that the differentially expressed genes were significantly enriched in the pathway of extracellular matrix receptor interaction. The hub proteins we founded in protein-protein interaction networks were LNX1, MSN and PPARG. Conclusion In this study, the mainly difference of molecular mechanism between basal-like and luminal subtypes are alteration in extracellular matrix region, cell chemotaxis and inflammatory response. Genes such as LNX1, MSN and PPARG were forecast to play important roles in the classification of bladder carcinoma subtypes.

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