scholarly journals ARHGAP11A Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Gastric Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Biao Fan ◽  
Ke Ji ◽  
Zhaode Bu ◽  
Ji Zhang ◽  
Heli Yang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
Prognostic Biomarker ◽  
Lymphocyte Activation ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Gene Markers ◽  
Division Cell

Background: ARHGAP11A, belongs to RhoGAPs family, is vital for cell motility. However, the role of ARHGAP11A in gastric cancer is obscure.Methods: The expression level of ARHGAP11A was analyzed by Oncomine database. The correlation of ARHGAP11A expression with immune infiltrates and associated gene markers was clarified by Tumor IMmune Estimation Resource and Gene Expression Profiling Interactive Analysis database. The correlation between ARHGAP11A expression and the patient prognosis was identified by Kaplan-Meier plotter and PrognoScan. Genetic changes of ARHGAP11A were analyzed by cBioPortal. The protein-protein interaction network and gene functional enrichment analysis were constructed and performed by GeneMANIA and Metascape.Results: We found that the expression levels of ARHGAP11A were elevated in various cancers including gastric cancer when compared with normal tissues. High expression of ARHGAP11A was significantly correlated with a better prognosis in gastric cancer. We revealed that the expression of ARHGAP11A was negatively associated with infiltration levels of CD8+ T cells, CD4+ T cells, macrophages and dendritic cells. In addition, ARHGAP11A expression was significantly correlated with gene markers of these immune cells. Lastly, gene functional enrichment analysis indicated that ARHGAP11A involved in regulating lymphocyte activation, cell division, cell killing, myeloid leukocyte differentiation and leukocyte apoptosis.Conclusion: Our findings demonstrated that ARHGAP11A was a valuable prognostic biomarker in gastric cancer. Further work is needed to validate its role and underlying mechanisms in regulating immune infiltrates.

scholarly journals ITGA5 Is a Prognostic Biomarker and Correlated with Immune Infiltration In Gastrointestinal Cancers

2020 ◽  
Author(s):  
Hai Zhu ◽  
Gang Wang ◽  
Haixing Zhu ◽  
Aman Xu
Keyword(s):  
Gastric Cancer ◽  
Immune Cell ◽  
Prognostic Biomarker ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Th2 Cells ◽  
Integrin Subunit ◽  
Expression Levels ◽  
Immune Infiltration

Abstract Background: Integrin Subunit Alpha 5 (ITGA5) belongs to the integrin alpha chain family, is vital for promoting cancer cell invasion, metastasis. However, the correlation between ITGA5 expression and immune infiltration in gastrointestinal (GI) tumors remain unclear.Methods: The expression levels of ITGA5 were detected by Oncomine and Tumor Immune Estimation Resource (TIMER). The association between ITGA5 and prognosis of patients was identified by Kaplan–Meier plotter, Gene Expression Profiling Interactive Analysis 2(GEPIA2) and PrognoScan. We evaluated the correlation between ITGA5 expression and immune infiltrating level via TIMER. Besides, TIMER and immunohistochemistry (IHC) staining were used to explore correlations between ITGA5 expression and markers of immune infiltrates cells. Furthermore, we constructed protein-protein interaction (PPI) network and performed functional enrichment by GeneMANIA and Metascape.Results: ITGA5 was generally overexpressed and correlated with worse prognosis in multiple types of GI tumors. In addition, ITGA5 expression levels was significantly associated with tumor purity and immune infiltration levels of different immune cells in GI tumors. Interestingly, Immune markers for monocytes, tumor - associated macrophages (TAMs), macrophages 2 (M2) cells and T-helper 2 (Th2) cells were found to be significantly and positively correlated with ITGA5 expression levels in colon and gastric cancer. Results from IHC staining further proved that markers of Th2 and M2 cell were significantly increased in gastric cancer patients with high ITGA5 expression levels. Lastly, interaction network and function enrichment analysis revealed ITGA5 were mainly involved in “integrin mediated signaling pathway”, “leukocyte migration”, “cell-substrate adhesion”.Conclutions: our study demonstrated that ITGA5 may act as an essential regulator of tumor immune cell infiltration and a valuable prognostic biomarker in GI tumors. Additional work is needed to fully elucidate the underlying mechanisms behind these observations.

scholarly journals Investigation and Functional Enrichment Analysis of the Human Host Interaction Network with Common Gram-Negative Respiratory Pathogens Predicts Possible Association with Lung Adenocarcinoma

2021 ◽  
Vol 28 (1) ◽  
pp. 20-33
Author(s):  
Lydia-Eirini Giannakou ◽  
Athanasios-Stefanos Giannopoulos ◽  
Chrissi Hatzoglou ◽  
Konstantinos I. Gourgoulianis ◽  
Erasmia Rouka ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Junctions ◽  
Respiratory Pathogens ◽  
Gram Negative ◽  
Human Proteins ◽  
Apoptotic Pathways

Haemophilus influenzae (Hi), Moraxella catarrhalis (MorCa) and Pseudomonas aeruginosa (Psa) are three of the most common gram-negative bacteria responsible for human respiratory diseases. In this study, we aimed to identify, using the functional enrichment analysis (FEA), the human gene interaction network with the aforementioned bacteria in order to elucidate the full spectrum of induced pathogenicity. The Human Pathogen Interaction Database (HPIDB 3.0) was used to identify the human proteins that interact with the three pathogens. FEA was performed via the ToppFun tool of the ToppGene Suite and the GeneCodis database so as to identify enriched gene ontologies (GO) of biological processes (BP), cellular components (CC) and diseases. In total, 11 human proteins were found to interact with the bacterial pathogens. FEA of BP GOs revealed associations with mitochondrial membrane permeability relative to apoptotic pathways. FEA of CC GOs revealed associations with focal adhesion, cell junctions and exosomes. The most significantly enriched annotations in diseases and pathways were lung adenocarcinoma and cell cycle, respectively. Our results suggest that the Hi, MorCa and Psa pathogens could be related to the pathogenesis and/or progression of lung adenocarcinoma via the targeting of the epithelial cellular junctions and the subsequent deregulation of the cell adhesion and apoptotic pathways. These hypotheses should be experimentally validated.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

scholarly journals Demethylation alters transcriptome profiling of buds and leaves in ‘Kyoho’ grape

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Haoran Jia ◽  
Zibo Zhang ◽  
Ehsan Sadeghnezhad ◽  
Qianqian Pang ◽  
Shangyun Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Epigenetic Modification ◽  
Deep Understanding ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Glutathione Metabolism ◽  
Endogenous Factors

Abstract Background Grape buds and leaves are directly associated with the physiology and metabolic activities of the plant, which is monitored by epigenetic modifications induced by environment and endogenous factors. Methylation is one of the epigenetic regulators that could be involved in DNA levels and affect gene expression in response to stimuli. Therefore, changes of gene expression profile in leaves and bud through inhibitors of DNA methylation provide a deep understanding of epigenetic effects in regulatory networks. Results In this study, we carried out a transcriptome analysis of ‘Kyoho’ buds and leaves under 5-azacytidine (5-azaC) exposure and screened a large number of differentially expressed genes (DEGs). GO and KEGG annotations showed that they are mainly involved in photosynthesis, flavonoid synthesis, glutathione metabolism, and other metabolic processes. Functional enrichment analysis also provided a holistic perspective on the transcriptome profile when 5-azaC bound to methyltransferase and induced demethylation. Enrichment analysis of transcription factors (TFs) also showed that the MYB, C2H2, and bHLH families are involved in the regulation of responsive genes under epigenetic changes. Furthermore, hormone-related genes have also undergone significant changes, especially gibberellin (GA) and abscisic acid (ABA)-related genes that responded to bud germination. We also used protein-protein interaction network to determine hub proteins in response to demethylation. Conclusions These findings provide new insights into the establishment of molecular regulatory networks according to how methylation as an epigenetic modification alters transcriptome patterns in bud and leaves of grape.

scholarly journals System Analysis of MIRNAs in Maize Internode Elongation

Biomolecules ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 417
Author(s):  
Chuanxi Peng ◽  
Xing Wang ◽  
Tianyu Feng ◽  
Rui He ◽  
Mingcai Zhang ◽  
...  
Keyword(s):  
Target Genes ◽  
System Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Internode Elongation ◽  
Differentially Expressed Mirnas ◽  
Post Transcriptional Regulation

MicroRNAs (miRNAs), the post-transcriptional gene regulators, are known to play an important role in plant development. The identification of differentially expressed miRNAs could better help us understand the post-transcriptional regulation that occurs during maize internode elongation. Accordingly, we compared the expression of MIRNAs between fixed internode and elongation internode samples and classified six differentially expressed MIRNAs as internode elongation-responsive miRNAs including zma-MIR160c, zma-MIR164b, zma-MIR164c, zma-MIR168a, zma-MIR396f, and zma-MIR398b, which target mRNAs supported by transcriptome sequencing. Functional enrichment analysis for predictive target genes showed that these miRNAs were involved in the development of internode elongation by regulating the genes respond to hormone signaling. To further reveal how miRNA affects internode elongation by affecting target genes, the miRNA–mRNA–PPI (protein and protein interaction) network was constructed to summarize the interaction of miRNAs and these target genes. Our results indicate that miRNAs regulate internode elongation in maize by targeting genes related to cell expansion, cell wall synthesis, transcription, and regulatory factors.

scholarly journals Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

2020 ◽  
Vol 9 (2) ◽  
pp. LMT30
Author(s):  
Chuanli Ren ◽  
Weixiu Sun ◽  
Xu Lian ◽  
Chongxu Han
Keyword(s):  
Lung Adenocarcinoma ◽  
Differentially Expressed Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Kaplan Meier ◽  
Key Genes ◽  
Core Genes

Aim: To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD). Materials & methods: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID. Results: Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD. Conclusion: 23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

scholarly journals Identification of novel genes and pathways in carotid atheroma using integrated bioinformatic methods

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Wenqing Nai ◽  
Diane Threapleton ◽  
Jingbo Lu ◽  
Kewei Zhang ◽  
Hongyuan Wu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Transforming Growth Factor ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Transforming Growth Factor Β ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Atheromatous Plaques

Abstract Atherosclerosis is the primary cause of cardiovascular events and its molecular mechanism urgently needs to be clarified. In our study, atheromatous plaques (ATH) and macroscopically intact tissue (MIT) sampled from 32 patients were compared and an integrated series of bioinformatic microarray analyses were used to identify altered genes and pathways. Our work showed 816 genes were differentially expressed between ATH and MIT, including 443 that were up-regulated and 373 that were down-regulated in ATH tissues. GO functional-enrichment analysis for differentially expressed genes (DEGs) indicated that genes related to the “immune response” and “muscle contraction” were altered in ATHs. KEGG pathway-enrichment analysis showed that up-regulated DEGs were significantly enriched in the “FcεRI-mediated signaling pathway”, while down-regulated genes were significantly enriched in the “transforming growth factor-β signaling pathway”. Protein-protein interaction network and module analysis demonstrated that VAV1, SYK, LYN and PTPN6 may play critical roles in the network. Additionally, similar observations were seen in a validation study where SYK, LYN and PTPN6 were markedly elevated in ATH. All in all, identification of these genes and pathways not only provides new insights into the pathogenesis of atherosclerosis, but may also aid in the development of prognostic and therapeutic biomarkers for advanced atheroma.

scholarly journals Identification of Latent Diagnostic Biomarkers and Biological Pathways in Dermatomyositis Based on WGCNA

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shaxi Ouyang ◽  
Yifang Liu ◽  
Changjuan Xiao ◽  
Qinghua Zeng ◽  
Xun Luo ◽  
...  
Keyword(s):  
Cell Lines ◽  
Differentially Expressed Gene ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Interferon Α ◽  
Pathway Enrichment Analysis ◽  
Oligoadenylate Synthetase

Introduction. Dermatomyositis (DM) is a chronic autoimmune disease of predominantly lymphocytic infiltration mainly involving the transverse muscle. Its pathogenesis is remaining unknown. This research is designed to probe the latent pathogenesis of dermatomyositis, identify potential biomarkers, and reveal the pathogenesis of dermatomyositis through information biology analysis of gene chips. Methods. In this study, we utilised the GSE14287 and GSE11971 datasets rooted in the Gene Expression Omnibus (GEO) databank, which included a total of 62 DM samples and 9 normal samples. The datasets were combined, and the differentially expressed gene sets were subjected to weighted gene coexpression network analysis, and the hub gene was screened using a protein interaction network from genes in modules highly correlated with dermatomyositis progression. Results. A total of 3 key genes—myxovirus resistance-2 (MX2), oligoadenylate synthetase 1 (OAS1), and oligoadenylate synthetase 2 (OAS2)—were identified in combination with cell line samples, and the expressions of the 3 genes were verified separately. The results showed that MX2, OAS1, and OAS2 were highly expressed in LPS-treated cell lines compared to normal cell lines. The results of pathway enrichment analysis of the genes indicated that all 3 genes were enriched in the cytosolic DNA signalling and cytokine and cytokine receptor interaction signalling pathways; the results of functional enrichment analysis showed that all 3 were enriched in interferon-α response and interferon-γ response functions. Conclusions. This is important for the study of the pathogenesis and objective treatment of dermatomyositis and provides important reference information for the targeted therapy of dermatomyositis.

scholarly journals SPP1 is a Prognostic Related Biomarker and Correlated With Tumor-Infiltrating Immune Cells in Ovarian Cancer

2021 ◽  
Author(s):  
Wen Gao ◽  
Sheng Yin ◽  
Haiyan Sun ◽  
Zhuyan Shao ◽  
Peipei Shi ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
T Cells ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Vital Role ◽  
Functional Enrichment ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Secreted Phosphoprotein 1

Abstract Background: Secreted phosphoprotein 1 (SPP1) plays a vital role in tumor progression of some cancer types, but little is known whether it is a bystander or an actual player on driving immune infiltration in ovarian cancer.Methods: In this study, the expression of SPP1 was identified by Oncomine, GEPIA and TIMER databases, and SPP1 immumohistochemical staining analysis was assessed by The HPA database. The clinical outcomes between SPP1 expression and ovarian cancer patients were evaluated via Kaplan-Meier Plotter and PrognoScan dataset. Immune infiltration analyses were explored using TIMER and TISIDB dataset. In addition, Functional enrichment analyses were performed with Metascape and GeneMANIA database.Results: SPP1 was found overexpressed in ovarian tumor tissues and high SPP1 expression was correlated with shorter OS and PFS survivals. Particularly, elevated SPP1 expression was significantly associated with stage III ovarian cancer. Notably, SPP1 expression was positively correlated with infiltrating levels of CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells. Furthermore, SPP1 expression showed strong correlations with diverse immune hallmark sets in ovarian cancer. Of particular importance, functional enrichment analysis suggested that SPP1 strong related with immune response.Conclusions: These findings imply that SPP1 is correlated with prognosis and immune cell infiltrating, offering a new potential immunotherapeutic target in ovarian cancer.Trial registration: Not applicable.

scholarly journals Co-expression network analysis identifies specific hub genes in association with developmental neuronal remodeling in Drosophila melanogaster

2019 ◽  
Author(s):  
Yunze Liu ◽  
Xiaojie Sun ◽  
Aijun Qu
Keyword(s):  
Drosophila Melanogaster ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Neuronal Remodeling ◽  
Gene Modules

As an evolutionarily conserved mechanism, developmental neuronal remodeling is needed for the proper wiring of the nervous system and is critical for understanding the neurodevelopment mechanisms. Previous studies have shown that during metamorphosis lots of Drosophila melanogaster mushroom body neurons experience stereotypic remodeling. However, the related regulators and downstream executors of pathways are yet unclear, especially studies of transcriptional gene co-expression analysis of nervous systems remain insufficient. In this study, we develop a weighted gene co-expression network (WGCNA) to classify gene modules associated with neuronal remodeling. Moreover, functional and pathway enrichment analysis with protein-protein network construction is applied to detect high informative hub genes in the targeted gene module. Thus, we select a total of five hub genes that play critical roles in neuronal remodeling and identify them with functional enrichment analysis and protein-protein interaction network. Overall, this study provides insight into the underlying molecular mechanism of developmental neuronal remodeling in Drosophila melanogaster.

Sign in / Sign up

Export Citation Format

Share Document