Bioinformatics analysis of SOX2 gene expression in gliogenesis

2020 ◽  
Vol 3 (1) ◽  
pp. 26
Author(s):  
Shouhartha Choudhury
Keyword(s):  
Gene Expression ◽  
Bioinformatics Analysis ◽  
Sox2 Gene

scholarly journals Distinct diagnostic and prognostic values of Glypicans gene expression in patients with hepatocellular carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jian-Yao Wang ◽  
Xiang-Kun Wang ◽  
Guang-Zhi Zhu ◽  
Xin Zhou ◽  
Jun Yao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Tumor Tissue ◽  
Bioinformatics Analysis ◽  
Mrna Level ◽  
Normal Liver ◽  
Predictive Index ◽  
Expression Levels ◽  
Interactive Analysis ◽  
Diagnostic Values

Abstract Backgroud In our current work, we aimed to investigate the expressions of glypican (GPC) family genes at the mRNA level and assess their prognostic significances in patients with hepatocellular carcinoma (HCC). Methods The pathological roles of GPC family genes were examined using bioinformatics analysis. The diagnostic values of GPC genes were explored with the Gene Expression Profiling Interactive Analysis. Moreover, the mRNA expression and prognostic values of GPC genes were assessed via the KM plotter database. Results Our data showed that the expression of GPC-3 was dramatically increased in the liver tumor tissue. Moreover, the expressions of the other five GPC family members were not significantly different between the tumor and normal liver tissues (P > 0.05). Furthermore, the up-regulation of GPC-1 at the mRNA level was dramatically correlated to the reduced overall survival (OS) for all HCC patients (hazard ratio = 2.03, 95% confidence intervals =1.44–2.87, P = 4.1e-05) compared with its low-expression group. Besides, the prognosis of the Caucasians was related to most GPC family genes, while the prognosis of the Asian race was only related to the expression of GPC-2. Besides, for pathological factors, including stage, grade, AJCC, and vascular invasion, the higher the pathological grade and vascular invasiveness, the lower the expression levels of GPC family genes (P < 0.05). Finally, the expression levels of GPC-1, 2, and 3 in the hepatitis group were related to the poor prognosis of HCC in the risk factor (alcohol consumption and hepatitis) subgroup (P < 0.05). Conclusions Our findings indicated that GPC-3 was dysregulated in HCC compared with paracancerous tissues. The expression of GPC-1 could be used as a potent predictive index for the general prognosis of HCC. The pathology, patients, and risk factors might affect the prognostic value of GPC family genes in HCC.

scholarly journals 975. Why Sex Make a Difference in HIV Clinical Course? Bioinformatics Analysis of Differential Expressed Gene in Females and Males with HIV Disease

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S516-S517
Author(s):  
Kulachanya Suwanwongse ◽  
Nehad Shabarek
Keyword(s):  
Gene Expression ◽  
Bioinformatics Analysis ◽  
Underlying Mechanism ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Gender Inequalities ◽  
Hiv Disease ◽  
Go Analysis ◽  
Hiv Progression ◽  
Pathway Analyses

Abstract Background Human immunodeficiency virus (HIV) disease progression are different among genders, in which women usually progress to acquired immunodeficiency syndrome (AIDS) faster than men. The mechanisms resulting in the gender biases of HIV progression are unclear. We conducted a bioinformatics analysis of differentially expressed genes (DEGs) in women and men with HIV disease to understand the sex-based differences in HIV pathogenesis. Methods We obtained microarray data from the Gene Expression Omnibus (GEO) database using our pre-defined search strategy and analyzed data using the GEO2R platform. The t-test was done to compare DEGs between females and males with HIV diseases. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was implemented to systematically extract biological features and processes of retrieving DEGs via gene ontology (GO) analysis. A Systemic search was performed to evaluate each DEG function and its possible association with HIV. Results One gene expression profiling data were retrieved: GSE 140713, composed of 40 males and 10 females with HIV1 infected samples. A GEO2R analysis yielded 19 DEGs (Table 1). The GO analysis result was demonstrated in Tables 2 and 3. Following a systemic search, we found two DEGs, which have previous studies reported an association with HIV: DDX3X (20 studies) and PDS5 (1 study). We proposed DDX3X (t 5.3, p 0.0037) is responsible for gender inequalities of HIV progression because of: 1. DDX3X is needed in the HIV1 life cycle. 2. Several studies confirmed a positive correlation between DDX3X expression and HIV1 replication. 3. Our study found an up-regulated DDX3X expression in women corresponded to the fact that women progress to AIDS faster than men. 4. Our GO analysis showed female up-regulated genes were enriched in positive regulation of the gene expression pathway, which can be explained by DDX3X and its underlying mechanism. Table 1: DEGs in women and men with HIV1 disease Table 2: GO functional enrichment pathway analyses of overall retrieving DEGs Table 3: GO functional enrichment pathway analyses of down- and up-regulated clusters of DEGs Conclusion Aberrant DDX3X expression may contribute to sex-based differences in HIV disease. Drugs modifying DDX3X gene expression will be beneficial in the treatment of HIV especially resolving the HIV drug resistance problem because current anti-HIV drugs target viral components posed the risk of viral mutation. Disclosures All Authors: No reported disclosures

scholarly journals Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Gu ◽  
Ying Sun ◽  
Xiong Zheng ◽  
Jin Ma ◽  
Xiao-Ying Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Microarray Analysis ◽  
Cancer Progression ◽  
Pathway Analysis ◽  
Bioinformatics Analysis ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Circular Rnas ◽  
Target Mrnas

Gastric cancer is one of the common malignant tumors worldwide. Increasing studies have indicated that circular RNAs (circRNAs) play critical roles in the cancer progression and have shown great potential as useful markers and therapeutic targets. However, the precise mechanism and functions of most circRNAs are still unknown in gastric cancer. In the present study, we performed a microarray analysis to detect circRNA expression changes between tumor samples and adjacent nontumor samples. The miRNA expression profiles were obtained from the National Center of Biotechnology Information Gene Expression Omnibus (GEO). The differentially expressed circRNAs and miRNAs were identified through fold change filtering. The interactions between circRNAs and miRNAs were predicted by Arraystar’s home-made miRNA target prediction software. After circRNA-related miRNAs and dysregulated miRNAs were intersected, 23 miRNAs were selected. The target mRNAs of miRNAs were predicted by TarBase v7.0. Gene ontology (GO) enrichment analysis and pathway analysis were performed using standard enrichment computational methods for the target mRNAs. The results of pathway analysis showed that p53 signaling pathway and hippo signal pathway were significantly enriched and CCND2 was a cross-talk gene associated with them. Finally, a circRNA-miRNA-mRNA regulation network was constructed based on the gene expression profiles and bioinformatics analysis results to identify hub genes and hsa_circRNA_101504 played a central role in the network.

scholarly journals Cyclin-Dependent Kinase Inhibitor p21 Controls Adult Neural Stem Cell Expansion by Regulating Sox2 Gene Expression

2013 ◽  
Vol 12 (1) ◽  
pp. 88-100 ◽  
Author(s):  
M. Ángeles Marqués-Torrejón ◽  
Eva Porlan ◽  
Ana Banito ◽  
Esther Gómez-Ibarlucea ◽  
Andrés J. Lopez-Contreras ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cell ◽  
Neural Stem Cell ◽  
Cell Expansion ◽  
Kinase Inhibitor ◽  
Cyclin Dependent Kinase ◽  
Adult Neural Stem Cell ◽  
Stem Cell Expansion ◽  
Cyclin Dependent Kinase Inhibitor ◽  
Sox2 Gene

Bioinformatics Analysis of The Expression of ATP Binding Cassette Transporters and The Screening of Regulatory Genes in PTEN/PI3K/Akt/mTOR Signaling Pathway in The Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Tingdan Zheng ◽  
Wuqi Song ◽  
Aiying Yang
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Bioinformatics Analysis ◽  
Wilcoxon Test ◽  
Rank Test ◽  
Short Term ◽  
Term Survival ◽  
Log Rank Test ◽  
Short Term Survival

Abstract Objective Here we performed the Bioinformatics analysis on the data from The Cancer Genome Atlas (TCGA), in order to find the correlation between the expression of ATP Binding Cassette (ABC) Transporters’ genes and hepatocellular carcinoma (HCC) prognosis; Methods Transcriptome profiles and clinical data of HCC were obtained from TCGA database. Package edgeR was used to analyze differential gene expression. Patients were divided into low-ABC expression and high-ABC expression groups based on the median expression level of ABC genes in cancer. The overall survival and short-term survival (n= 341) of the two groups was analyzed using the log-rank test and Wilcoxon test; Results We found that ABC gene expression was correlated with the expression of PIK3C2B (p<0.001, ABCC1: r=0.27; ABCC10: r=0.57; ABCC4: r=0.20; ABCC5: r=0.28; ABCB9: r=0.17; ABCD1: r=0.21). All patients with low-ABC expression showed significantly increased overall survival. Significantly decreased overall survival (Log-rank test: p<0.05, Wilcoxon test: p<0.05) was found in patients with high expression of ABCC1 (HR=1.58), ABCD1 (HR=1.45), ABCC4 (HR=1.56), and ABCC5 (HR=1.64), while decreased short-term survival (Log-rank test: p>0.05, Wilcoxon test: p<0.05) was correlated with the increased expression of ABCC10 (HR=1.29), PIK3C2B (HR=1.29) and ABCB9 (HR=1.23); Conclusions Our findings indicate that the specific ABC gene expression correlates with the prognosis of HCC. Therefore, ABC expression profile could be a potential indicator for HCC patients.

scholarly journals LASSO and Bioinformatics Analysis in the Identification of Key Genes for Prognostic Genes of Gynecologic Cancer

2021 ◽  
Vol 11 (11) ◽  
pp. 1177
Author(s):  
Shao-Hua Yu ◽  
Jia-Hua Cai ◽  
De-Lun Chen ◽  
Szu-Han Liao ◽  
Yi-Zhen Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Endometrial Cancer ◽  
Pathway Analysis ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gynecologic Cancer ◽  
Functional Enrichment ◽  
Lasso Regression ◽  
Potential Biomarker ◽  
Study Gene Expression

The aim of this study is to identify potential biomarkers for early diagnosis of gynecologic cancer in order to improve survival. Cervical cancer (CC) and endometrial cancer (EC) are the most common malignant tumors of gynecologic cancer among women in the world. As the underlying molecular mechanisms in both cervical and endometrial cancer remain unclear, a comprehensive and systematic bioinformatics analysis is required. In our study, gene expression profiles of GSE9750, GES7803, GES63514, GES17025, GES115810, and GES36389 downloaded from Gene Expression Omnibus (GEO) were utilized to analyze differential gene expression between cancer and normal tissues. A total of 78 differentially expressed genes (DEGs) common to CC and EC were identified to perform the functional enrichment analyses, including gene ontology and pathway analysis. KEGG pathway analysis of 78 DEGs indicated that three main types of pathway participate in the mechanism of gynecologic cancer such as drug metabolism, signal transduction, and tumorigenesis and development. Furthermore, 20 diagnostic signatures were confirmed using the least absolute shrink and selection operator (LASSO) regression with 10-fold cross validation. Finally, we used the GEPIA2 online tool to verify the expression of 20 genes selected by the LASSO regression model. Among them, the expression of PAMR1 and SLC24A3 in tumor tissues was downregulated significantly compared to the normal tissue, and found to be statistically significant in survival rates between the CC and EC of patients (p < 0.05). The two genes have their function: (1.) PAMR1 is a tumor suppressor gene, and many studies have proven that overexpression of the gene markedly suppresses cell growth, especially in breast cancer and polycystic ovary syndrome; (2.) SLC24A3 is a sodium–calcium regulator of cells, and high SLC24A3 levels are associated with poor prognosis. In our study, the gene signatures can be used to predict CC and EC prognosis, which could provide novel clinical evidence to serve as a potential biomarker for future diagnosis and treatment.

scholarly journals Investigation of the Mechanism of Complement System in Diabetic Nephropathy via Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Bojun Xu ◽  
Lei Wang ◽  
Huakui Zhan ◽  
Liangbin Zhao ◽  
Yuehan Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Diabetic Nephropathy ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Topological Analysis ◽  
Gene Expression Omnibus ◽  
Complement Cascade ◽  
Hub Genes ◽  
Novel Biomarkers

Objectives. Diabetic nephropathy (DN) is a major cause of end-stage renal disease (ESRD) throughout the world, and the identification of novel biomarkers via bioinformatics analysis could provide research foundation for future experimental verification and large-group cohort in DN models and patients. Methods. GSE30528, GSE47183, and GSE104948 were downloaded from Gene Expression Omnibus (GEO) database to find differentially expressed genes (DEGs). The difference of gene expression between normal renal tissues and DN renal tissues was firstly screened by GEO2R. Then, the protein-protein interactions (PPIs) of DEGs were performed by STRING database, the result was integrated and visualized via applying Cytoscape software, and the hub genes in this PPI network were selected by MCODE and topological analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to determine the molecular mechanisms of DEGs involved in the progression of DN. Finally, the Nephroseq v5 online platform was used to explore the correlation between hub genes and clinical features of DN. Results. There were 64 DEGs, and 32 hub genes were identified, enriched pathways of hub genes involved in several functions and expression pathways, such as complement binding, extracellular matrix structural constituent, complement cascade related pathways, and ECM proteoglycans. The correlation analysis and subgroup analysis of 7 complement cascade-related hub genes and the clinical characteristics of DN showed that C1QA, C1QB, C3, CFB, ITGB2, VSIG4, and CLU may participate in the development of DN. Conclusions. We confirmed that the complement cascade-related hub genes may be the novel biomarkers for DN early diagnosis and targeted treatment.

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