scholarly journals Identification of four key prognostic genes and three potential drugs in human papillomavirus negative head and neck squamous cell carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guocai Tian ◽  
You Fu ◽  
Dahe Zhang ◽  
Jiang Li ◽  
Zhiyuan Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Gene Set Enrichment ◽  
Therapeutic Value ◽  
Hpv Status ◽  
Hnscc Cell

Abstract Background Head and neck squamous cell carcinoma (HNSCC) is a common tumor worldwide with poor prognosis. The pathogenesis of human papillomavirus (HPV)-positive and HPV-negative HNSCCs differs. However, few studies have considered the HPV status when identifying biomarkers for HNSCC. Thus, the identification of biomarkers for HPV-positive and HPV-negative HNSCCs is urgently needed. Methods Three microarray datasets from Gene Expression Omnibus (GEO) were analyzed, and the differentially expressed genes (DEGs) were obtained. Then, functional enrichment pathway analysis was performed and protein–protein interaction (PPI) networks were constructed. The expression of hub genes at both the mRNA and protein level was determined in Oncomine, The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA). In addition, survival analysis of the patient stratified by HPV status and the expression levels of key genes were performed based on TCGA data. The role of AREG, STAG3, CAV1 and C19orf57 in cancer were analyzed through Gene set enrichment analysis (GSEA). The top ten small molecule drugs were identified and the therapeutic value of zonisamide, NVP-AUY922, PP-2 and fostamatinib was further evaluated in six HPV-negative HNSCC cell lines. Finally, the therapeutic value of NVP-AUY922 was tested in vivo based on three HPV-negative HNSCC models, and statistical analysis was performed. Results In total, 47 DEGs were obtained, 11 of which were identified as hub genes. Biological process analysis indicated that the hub genes were associated with the G1/S transition of the mitotic cell cycle. Survival analysis uncovered that the prognostic value of AREG, STAG3, C19orf57 and CAV1 differed between HPV-positive and HPV-negative patients. Gene set enrichment analysis (GSEA) showed the role of AREG, STAG3 and CAV1 in dysregulated pathways of tumor. Ten small molecules were identified as potential drugs specifically for HPV-positive or HPV-negative patients; three—NVP-AUY922, fostamatinib and PP-2—greatly inhibited the proliferation of six HPV-negative HNSCC cell lines in vitro, and NVP-AUY922 inhibited three HPV-negative HNSCC xenografts in vivo. Conclusions In conclusion, AREG, STAG3, C19orf57 and CAV1 are key prognostic factors and potential therapeutic targets in HPV-negative HNSCC. NVP-AUY922, fostamatinib and PP-2 may be effective drugs for HPV-negative HNSCC.

scholarly journals Identification of AREG, STAG3, C19orf57 and CAV1 as key prognostic factors in HPV- negative head and neck squamous cell carcinoma

2020 ◽  
Author(s):  
Guocai Tian ◽  
You Fu ◽  
Jiang Li ◽  
Zhiyuan Zhang ◽  
Xi Yang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Prognostic Factors ◽  
Cell Carcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Gene Set Enrichment ◽  
Hpv Status ◽  
Hnscc Cell

Abstract Background Head and neck squamous cell carcinoma (HNSCC) is a common tumor worldwide with poor prognosis. The pathogenesis of human papillomavirus (HPV)-positive and HPV-negative HNSCCs differs. However, few studies have considered the HPV status when identifying biomarkers for HNSCC. Thus, the identification of biomarkers for HPV-positive and HPV-negative HNSCCs is urgently needed. Methods Three microarray datasets from Gene Expression Omnibus (GEO) were analyzed, and the differentially expressed genes (DEGs) were obtained. Then, functional enrichment pathway analysis was performed and protein-protein interaction (PPI) networks were constructed. The expression of hub genes at both the mRNA and protein level was determined in Oncomine, The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA). In addition, survival analyses of the patient stratified by HPV status and the expression levels of key genes were performed based on TCGA data. The role of AREG, STAG3, CAV1 and C19orf57 in cancer were analyzed through Gene set enrichment analysis (GSEA). Finally, the top ten small molecule drugs were identified and the therapeutic value of zonisamide, NVP-AUY922, PP-2 and fostamatinib was further evaluated in six HPV-negative HNSCC cell lines. Results In total, 47 DEGs were obtained, 11 of which were identified as hub genes. Biological process analysis indicated that the hub genes were associated with the G1/S transition of the mitotic cell cycle. Survival analysis uncovered that the prognostic value of AREG, STAG3, C19orf57 and CAV1 differed between HPV-positive and HPV-negative patients. Gene set enrichment analysis (GSEA) showed the role of AREG, STAG3 and CAV1 in dysregulated pathways of tumor. Ten small molecules were identified as potential drugs specifically for HPV-positive or HPV-negative patients; three—NVP-AUY922, fostamatinib and PP-2—greatly inhibited the proliferation of six HPV-negative HNSCC cell lines in vitro. Conclusions In conclusion, AREG, STAG3, C19orf57 and CAV1 are key prognostic factors and potential therapeutic targets in HPV-negative HNSCC. NVP-AUY922, fostamatinib and PP-2 may be effective drugs for HPV-negative HNSCC.

scholarly journals Identification of Four Key Prognostic Genes and Three Potential Drugs in Human Papillomavirus Negative Head and Neck Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Guocai Tian ◽  
You Fu ◽  
Dahe Zhang ◽  
Jiang Li ◽  
Zhiyuan Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Survival Analysis ◽  
Human Papillomavirus ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Gene Set Enrichment ◽  
Hpv Status ◽  
Hnscc Cell

Abstract BackgroundHead and neck squamous cell carcinoma (HNSCC) is a common tumor worldwide with poor prognosis. The pathogenesis of human papillomavirus (HPV)-positive and HPV-negative HNSCCs differs. However, few studies have considered the HPV status when identifying biomarkers for HNSCC. Thus, the identification of biomarkers for HPV-positive and HPV-negative HNSCCs is urgently needed.MethodsThree microarray datasets from Gene Expression Omnibus (GEO) were analyzed, and the differentially expressed genes (DEGs) were obtained. Then, functional enrichment pathway analysis was performed and protein-protein interaction (PPI) networks were constructed. The expression of hub genes at both the mRNA and protein level was determined in Oncomine, The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA). In addition, survival analysis of the patient stratified by HPV status and the expression levels of key genes were performed based on TCGA data. The role of AREG, STAG3, CAV1 and C19orf57 in cancer were analyzed through Gene set enrichment analysis (GSEA). Finally, the top ten small molecule drugs were identified and the therapeutic value of zonisamide, NVP-AUY922, PP-2 and fostamatinib was further evaluated in six HPV-negative HNSCC cell lines.ResultsIn total, 47 DEGs were obtained, 11 of which were identified as hub genes. Biological process analysis indicated that the hub genes were associated with the G1/S transition of the mitotic cell cycle. Survival analysis uncovered that the prognostic value of AREG, STAG3, C19orf57 and CAV1 differed between HPV-positive and HPV-negative patients. Gene set enrichment analysis (GSEA) showed the role of AREG, STAG3 and CAV1 in dysregulated pathways of tumor. Ten small molecules were identified as potential drugs specifically for HPV-positive or HPV-negative patients; three—NVP-AUY922, fostamatinib and PP-2—greatly inhibited the proliferation of six HPV-negative HNSCC cell lines in vitro, and NVP-AUY922 inhibited three HPV-negative HNSCC xenografts in vivo.ConclusionsIn conclusion, AREG, STAG3, C19orf57 and CAV1 are key prognostic factors and potential therapeutic targets in HPV-negative HNSCC. NVP-AUY922, fostamatinib and PP-2 may be effective drugs for HPV-negative HNSCC.

scholarly journals Identification of potential therapeutic targets for atherosclerosis by analysing the gene signature related to different immune cells and immune regulators in atheromatous plaques

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yang Shen ◽  
Li-rong Xu ◽  
Xiao Tang ◽  
Chang-po Lin ◽  
Dong Yan ◽  
...  
Keyword(s):  
Immune Cells ◽  
Plasma Cells ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gamma Delta ◽  
Hub Genes ◽  
Gene Set Enrichment ◽  
Bioinformatics Analyses ◽  
Immune Infiltration ◽  
Atheromatous Plaques

Abstract Background Atherosclerosis is a chronic inflammatory disease that affects multiple arteries. Numerous studies have shown the inherent immune diversity in atheromatous plaques and suggest that the dysfunction of different immune cells plays an important role in atherosclerosis. However, few comprehensive bioinformatics analyses have investigated the potential coordinators that might orchestrate different immune cells to exacerbate atherosclerosis. Methods Immune infiltration of 69 atheromatous plaques from different arterial beds in GSE100927 were explored by single-sample-gene-set enrichment analysis (presented as ssGSEA scores), ESTIMATE algorithm (presented as immune scores) and CIBERSORT algorithm (presented as relative fractions of 22 types of immune cells) to divide these plaques into ImmuneScoreL cluster (of low immune infiltration) and ImmuneScoreH cluster (of high immune infiltration). Subsequently, comprehensive bioinformatics analyses including differentially-expressed-genes (DEGs) analysis, protein–protein interaction networks analysis, hub genes analysis, Gene-Ontology-terms and KEGG pathway enrichment analysis, gene set enrichment analysis, analysis of expression profiles of immune-related genes, correlation analysis between DEGs and hub genes and immune cells were conducted. GSE28829 was analysed to cross-validate the results in GSE100927. Results Immune-related pathways, including interferon-related pathways and PD-1 signalling, were highly enriched in the ImmuneScoreH cluster. HLA-related (except for HLA-DRB6) and immune checkpoint genes (IDO1, PDCD-1, CD274(PD-L1), CD47), RORC, IFNGR1, STAT1 and JAK2 were upregulated in the ImmuneScoreH cluster, whereas FTO, CRY1, RORB, and PER1 were downregulated. Atheromatous plaques in the ImmuneScoreH cluster had higher proportions of M0 macrophages and gamma delta T cells but lower proportions of plasma cells and monocytes (p < 0.05). CAPG, CECR1, IL18, IGSF6, FBP1, HLA-DPA1 and MMP7 were commonly related to these immune cells. In addition, the advanced-stage carotid plaques in GSE28829 exhibited higher immune infiltration than early-stage carotid plaques. Conclusions Atheromatous plaques with higher immune scores were likely at a more clinically advanced stage. The progression of atherosclerosis might be related to CAPG, IGSF6, IL18, CECR1, FBP1, MMP7, FTO, CRY1, RORB, RORC, PER1, HLA-DPA1 and immune-related pathways (IFN-γ pathway and PD-1 signalling pathway). These genes and pathways might play important roles in regulating immune cells such as M0 macrophages, gamma delta T cells, plasma cells and monocytes and might serve as potential therapeutic targets for atherosclerosis.

scholarly journals The Relationship Between Gene Expression Pattern and the Severity of Asthma

2020 ◽  
Author(s):  
Shuang Lin ◽  
Bin Luo ◽  
Liping Cheng ◽  
Xiaohong Yang
Keyword(s):  
Gene Expression Pattern ◽  
Enrichment Analysis ◽  
Research Direction ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Gene Set Enrichment ◽  
Incidence And Mortality ◽  
New Research ◽  
High Degree ◽  
The Relationship

Abstract Background Because of heterogeneity, complexity of diagnosis and diversity of pathogenesis, the incidence and mortality of asthma are increased seriously. A structured and specific approach to assess and treat asthma may help clinicians. Results A total of 838 common genes were found from quietness to exacerbation then to recovery of asthma. PPI network analysis identified 7 modules, and found 7 hub genes with high degree. Then, we verified the expression of hub genes in patients by quantitative real-time polymerase chain reaction (qRT-PCR). Enrichment analysis and gene set enrichment analysis (GSEA) showed that exacerbation related genes were significantly related to immune and inflammatory response. Transcriptional regulators factor STAT1 had a significant regulatory effect on exacerbation related genes. Conclusions These results indicated that seven hub genes were potential biomarkers and targets of asthma exacerbation. they were involved in the development of asthma through immune inflammatory signaling pathway. The results of this study not only provide a new research direction and theoretical basis for the exacerbation mechanism of asthma, but also provide a new target for clinical treatment.

scholarly journals Increased Expression of FN1 in Head and Neck Squamous Cell Carcinoma Predicts Poor Prognosis

2021 ◽  
Author(s):  
Hung-Sheng Shih ◽  
Li-Yu Hung ◽  
Ming-Yu Hsieh
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Neck Squamous Cell Carcinoma ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Kaplan Meier

Abstract Background: A few recent studies have addressed the function of FN1 (Fibronectin 1) in head and neck cancer. The clinical information from 500 HNSCC (Head and neck squamous cell carcinoma) patients with FN1 gene expression data set was published by The Cancer Genome Atlas (TCGA). The correlation between clinicopathologic characteristics and FN1 expression was analyzed by Logistic regression and Wilcoxon signed rank test. Survival function was performed employing Kaplan-Meier estimator, and the relationship between clinicopathological characteristics, prognostic outcome, and FN1 expression were examined by using Cox regression analysis. As Gene set enrichment analysis (GSEA) was performed, we investigated the correlation between FN1 expression and immune cell infiltrates with single-sample gene set enrichment analysis (ssGSEA). Results: Patients with high FN1 expression revealed a significantly decreased overall survival (OS), and disease-specific survival (DSS) than those with low FN1 expression in Kaplan-Meier survival analyses. According to the above results, univariate and multivariate analysis revealed that patients with high FN1 expression had lower OS than those with low FN1 expression.Conclusions: The findings of this research provide insights for FN1 may be potential prognostic biomarkers for diagnosis as well as therapeutic targets in HNSCC patients.

Construction of a Competitive Endogenous RNA Network Associated with Angiogenesis in Ischemic Stroke Using a Bioinformatics Approach

2021 ◽  
Author(s):  
Jia Wang ◽  
Xuxiang Zhang ◽  
Yibo Xie ◽  
Jiachen Li ◽  
Xiaokun Wang ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Gene Set Enrichment ◽  
Differentially Expressed Mirnas ◽  
New Biomarkers ◽  
Competitive Endogenous Rna

Abstract Ischemic stroke (IS) is one of the leading causes of death and disability worldwide, and angiogenesis is an important target for its treatment. However, the mechanism of angiogenesis of endogenous RNA (ceRNA) in IS remains poorly understood. This study aims to explore the role of ceRNA in the angiogenesis of IS, to provide a possible target for the treatment of IS. First, GSE22255 (mRNA), GSE55937 (miRNA) and GSE102541 (lncRNA) were downloaded from the Gene Expression Omnibus (GEO) database. Then, a total of 21 mRNA modules were identified by WGCNA analysis, among which NR4A1, PTGS2, ERG3, and VEGFA in cyan module were identified as key genes for angiogenesis. Subsequently, 1454 differentially expressed lncRNAs (DELs) were screened and a lncRNA-mRNA co-expression network consisting of 40 lncRNAs and 4 mRNAs was constructed by correlation analysis. Then, 16 differentially expressed miRNAs (DEMs) were screened and the online database was used to predict the interaction information between miRNAs, lncRNAs and mRNAs. The angiogenesis-related ceRNA network was finally constructed based on ceRNA theory, in which 1 DEL was predicted as a ceRNA for 2 DEMs to regulate 4 hub genes, specifically, HCG18-has-let-7i-5p-NR4A1/PTGS2/ERG3, HCG18-miR-148a-3p-PTGS2/ERG3/VEGFA interaction axis. The results of gene set enrichment analysis (GSEA) suggest that HCG18 may regulate angiogenesis through NF-kB-TNFA signaling pathway, hypoxia and other pathways. In conclusion, the above genes may be new biomarkers and potential targets for the treatment of IS.

scholarly journals Downregulation of NEDD4L by EGFR Signaling Promotes the Development of Lung Adenocarcinoma

2021 ◽  
Author(s):  
Guoyin Li ◽  
Zewen Song ◽  
Changjing Wu ◽  
XiaoYan Li ◽  
Liping Zhao ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Data Sets ◽  
Egfr Signaling ◽  
Gene Set Enrichment ◽  
Mtorc1 Pathway ◽  
Cumulative Evidence

Abstract Cumulative evidence indicates that the abnormal regulation of the NEDD4 family of E3-ubiquitin ligases participates in the tumorigenesis and development of cancer. However, their role in lung adenocarcinoma (LUAD) remains unclear. This study comprehensively analyzed the NEDD4 family in LUAD data sets from public databases and found only NEDD4L was associated with the overall survival of LUAD patients. Gene set enrichment analysis (GSEA) indicated that NEDD4L might be involved in the regulation of mTORC1 pathway. Both cytological and clinical assays showed that NEDD4L inhibited the activity of the mTOR signaling pathway. In vivo and in vitro experiments showed that NEDD4L could significantly inhibit the proliferation of LUAD cells. In addition, this study also found that the expression of NEDD4L was regulated by EGFR signaling. These findings firstly revealed that NEDD4L mediates an interplay between EGFR and mTOR pathways in LUAD, and suggest that NEDD4L held great potential as a novel biomarker and therapeutic target for LUAD.

scholarly journals Identification of Hub Genes in Tuberculosis via Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Tiancheng Zhang ◽  
Guihua Rao ◽  
Xiwen Gao
Keyword(s):  
Gene Expression ◽  
Pulmonary Tuberculosis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Gene Set Enrichment ◽  
Data Set ◽  
Hub Gene ◽  
The World

Background. Tuberculosis (TB) is a serious chronic bacterial infection caused by Mycobacterium tuberculosis (MTB). It is one of the deadliest diseases in the world and a heavy burden for people all over the world. However, the hub genes involved in the host response remain largely unclear. Methods. The data set GSE11199 was studied to clarify the potential gene network and signal transduction pathway in TB. The subjects were divided into latent tuberculosis and pulmonary tuberculosis, and the distribution of differentially expressed genes (DEGs) was analyzed between them using GEO2R. We verified the enriched process and pathway of DEGs by making use of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The construction of protein-protein interaction (PPI) network of DEGs was achieved through making use of the Search Tool for the Retrieval of Interacting Genes (STRING), aiming at identifying hub genes. Then, the hub gene expression level in latent and pulmonary tuberculosis was verified by a boxplot. Finally, through making use of Gene Set Enrichment Analysis (GSEA), we further analyzed the pathways related to DEGs in the data set GSE11199 to show the changing pattern between latent and pulmonary tuberculosis. Results. We identified 98 DEGs in total in the data set GSE11199, 91 genes upregulated and 7 genes downregulated included. The enrichment of GO and KEGG pathways demonstrated that upregulated DEGs were mainly abundant in cytokine-mediated signaling pathway, response to interferon-gamma, endoplasmic reticulum lumen, beta-galactosidase activity, measles, JAK-STAT signaling pathway, cytokine-cytokine receptor interaction, etc. Based on the PPI network, we obtained 4 hub genes with a higher degree, namely, CTLA4, GZMB, GZMA, and PRF1. The box plot showed that these 4 hub gene expression levels in the pulmonary tuberculosis group were higher than those in the latent group. Finally, through Gene Set Enrichment Analysis (GSEA), it was concluded that DEGs were largely associated with proteasome and primary immunodeficiency. Conclusions. This study reveals the coordination of pathogenic genes during TB infection and offers the diagnosis of TB a promising genome. These hub genes also provide new directions for the development of latent molecular targets for TB treatment.

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