scholarly journals Investigation of differentially-expressed microRNAs and genes in cervical cancer using an integrated bioinformatics analysis

2017 ◽  
Vol 13 (4) ◽  
pp. 2784-2790 ◽  
Author(s):  
Zhanzhan Xu ◽  
Yu Zhou ◽  
Fang Shi ◽  
Yexuan Cao ◽  
Thi Lan Anh Dinh ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Bioinformatics Analysis ◽  
Differentially Expressed

scholarly journals Identification of crucial aberrantly methylated and differentially expressed genes related to cervical cancer using an integrated bioinformatics analysis

2020 ◽  
Vol 40 (5) ◽  
Author(s):  
Xiaoling Ma ◽  
Jinhui Liu ◽  
Hui Wang ◽  
Yi Jiang ◽  
Yicong Wan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Functional Analysis ◽  
Estrogen Receptor ◽  
Differentially Expressed Genes ◽  
Bioinformatics Analysis ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Venn Diagram ◽  
Hub Genes

Abstract Methylation functions in the pathogenesis of cervical cancer. In the present study, we applied an integrated bioinformatics analysis to identify the aberrantly methylated and differentially expressed genes (DEGS), and their related pathways in cervical cancer. Data of gene expression microarrays (GSE9750) and gene methylation microarrays (GSE46306) were gained from Gene Expression Omnibus (GEO) databases. Hub genes were identified by ‘limma’ packages and Venn diagram tool. Functional analysis was conducted by FunRich. Search Tool for the Retrieval of Interacting Genes Database (STRING) was used to analyze protein–protein interaction (PPI) information. Gene Expression Profiling Interactive Analysis (GEPIA), immunohistochemistry staining, and ROC curve analysis were conducted for validation. Gene Set Enrichment Analysis (GSEA) was also performed to identify potential functions.We retrieved two upregulated-hypomethylated oncogenes and eight downregulated-hypermethylated tumor suppressor genes (TSGs) for functional analysis. Hypomethylated and highly expressed genes (Hypo-HGs) were significantly enriched in cell cycle and autophagy, and hypermethylated and lowly expressed genes (Hyper-LGs) in estrogen receptor pathway and Wnt/β-catenin signaling pathway. Estrogen receptor 1 (ESR1), Erythrocyte membrane protein band 4.1 like 3 (EPB41L3), Endothelin receptor B (EDNRB), Inhibitor of DNA binding 4 (ID4) and placenta-specific 8 (PLAC8) were hub genes. Kaplan–Meier method was used to evaluate survival data of each identified gene. Lower expression levels of ESR1 and EPB41L3 were correlated with a shorter survival time. GSEA results showed that ‘cell adhesion molecules’ was the most enriched item. This research inferred the candidate genes and pathways that might be used in the diagnosis, treatment, and prognosis of cervical cancer.

Bioinformatics Analysis and Validation of Differentially Expressed MicroRNAs with Their Target Genes Involved in GLP-1RA Facilitated Osteogenesis

2020 ◽  
Vol 15 ◽  
Author(s):  
Na Wang ◽  
Yukun Li ◽  
Sijing Liu ◽  
Liu Gao ◽  
Chang Liu ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Target Genes ◽  
Bioinformatics Analysis ◽  
Differentially Expressed ◽  
Functional Study ◽  
Regulation Network ◽  
Glucagon Like Peptide 1 ◽  
G Protein Coupled ◽  
Lower Expression

Background: Recent studies revealed that the hypoglycemic hormone, glucagon-like peptide-1 (GLP-1), acted as an important modulator in osteogenesis of bone marrow derived mesenchymal stem cells (BMSCs). Objectives: The aim of this study was to identify the specific microRNA (miRNA) using bioinformatics analysis and validate the presence of differentially expressed microRNAs with their target genes after GLP-1 receptor agonist (GLP-1RA) administration involved in ostogenesis of BMSCs. Methods: MiRNAs were extracted from BMSCs after 5 days’ treatment and sent for high-throughput sequencing for differentially expressed (DE) miRNAs analyses. Then the expression of the DE miRNAs verified by the real-time RT-PCR analyses. Target genes were predicted, and highly enriched GOs and KEGG pathway analysis were conducted using bioinformatics analysis. For the functional study, two of the target genes, SRY (sex determining region Y)-box 5 (SOX5) and G protein-coupled receptor 84 (GPR84), were identified. Results: A total of 5 miRNAs (miRNA-509-5p, miRNA-547-3p, miRNA-201-3p, miRNA-201-5p, and miRNA-novel-272-mature) were identified differentially expressed among groups. The expression of miRNA-novel-272-mature were decreased during the osteogenic differentiation of BMSCs, and GLP-1RA further decreased its expression. MiRNA-novel-272-mature might interact with its target mRNAs to enhance osteogenesis. The lower expression of miRNA-novel-272-mature led to an increase in SOX5 and a decrease in GPR84 mRNA expression, respectively. Conclusions: Taken together, these results provide further insights to the pharmacological properties of GLP-1RA and expand our knowledge on the role of miRNAs-mRNAs regulation network in BMSCs’ differentiation.

scholarly journals Integrative Systems Biology Approaches to Identify Potential Biomarkers and Pathways of Cervical Cancer

2021 ◽  
Vol 11 (5) ◽  
pp. 363
Author(s):  
Arafat Rahman Oany ◽  
Mamun Mia ◽  
Tahmina Pervin ◽  
Salem Ali Alyami ◽  
Mohammad Ali Moni
Keyword(s):  
Cervical Cancer ◽  
Systems Biology ◽  
Differentially Expressed Genes ◽  
Inflammatory Responses ◽  
Profile Analysis ◽  
Target Identification ◽  
Regulatory Genes ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Potential Biomarkers

Nowadays, cervical cancer (CC) is treated as the leading cancer among women throughout the world. Despite effective vaccination and improved surgery and treatment, CC retains its fatality rate of about half of the infected population globally. The major screening biomarkers and therapeutic target identification have now become a global concern. In the present study, we have employed systems biology approaches to retrieve the potential biomarkers and pathways from transcriptomic profiling. Initially, we have identified 76 of each up-regulated and down-regulated gene from a total of 4643 differentially expressed genes. The up-regulatory genes mainly concentrate on immune-inflammatory responses, and the down-regulatory genes are on receptor binding and gamma-glutamyltransferase. The involved pathways associated with these genes were also assessed through pathway enrichment, and we mainly focused on different cancer pathways, immunoresponse, and cell cycle pathways. After the subsequent enrichment of these genes, we have identified 12 hub genes, which play a crucial role in CC and are verified by expression profile analysis. From our study, we have found that genes LILRB2 and CYBB play crucial roles in CC, as reported here for the first time. Furthermore, the survivability of the hub genes was also assessed, and among them, finally, CXCR4 has been identified as one of the most potential differentially expressed genes that might play a vital role in the survival of CC patients. Thus, CXCR4 could be used as a prognostic and/or diagnostic biomarker and a drug target for CC.

scholarly journals Activating NK cell receptor ligands are differentially expressed during progression to cervical cancer

2008 ◽  
Vol 123 (10) ◽  
pp. 2343-2353 ◽  
Author(s):  
Sonja Textor ◽  
Matthias Dürst ◽  
Lars Jansen ◽  
Rosita Accardi ◽  
Massimo Tommasino ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Nk Cell ◽  
Cell Receptor ◽  
Differentially Expressed ◽  
Receptor Ligands ◽  
Nk Cell Receptor

The novel serine protease tumor-associated differentially expressed gene-14 (KLK8/Neuropsin/Ovasin) is highly overexpressed in cervical cancer

2004 ◽  
Vol 190 (1) ◽  
pp. 60-66 ◽  
Author(s):  
Stefania Cane' ◽  
Eliana Bignotti ◽  
Stefania Bellone ◽  
Michela Palmieri ◽  
Luis De Las Casas ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Serine Protease ◽  
Differentially Expressed Gene ◽  
Differentially Expressed ◽  
The Novel

Identification of differentially expressed microRNAs in outgrowth embryos compared with blastocysts and non-outgrowth embryos in mice

2019 ◽  
Vol 31 (4) ◽  
pp. 645 ◽  
Author(s):  
Jihyun Kim ◽  
Jaewang Lee ◽  
Jin Hyun Jun
Keyword(s):  
Bioinformatics Analysis ◽  
Preimplantation Embryo ◽  
Expression Profiles ◽  
In Silico Analysis ◽  
Differentially Expressed ◽  
Recurrent Implantation Failure ◽  
Preimplantation Embryo Development ◽  
Mirna Expression Profiles ◽  
Differentially Expressed Mirnas ◽  
Silico Analysis

Recurrent implantation failure (RIF) is one of the main causes for the repeated failure of IVF, and the major reason for RIF is thought to be a miscommunication between the embryo and uterus. However, the exact mechanism underlying embryo–uterus cross-talk is not fully understood. The aim of the present study was to identify differentially expressed microRNAs (miRNAs) among blastocysts, non-outgrowth and outgrowth embryos in mice using microarray analysis. A bioinformatics analysis was performed to predict the potential mechanisms of implantation. The miRNA expression profiles differed significantly between non-outgrowth and outgrowth embryos. In all, 3163 miRNAs were detected in blastocysts and outgrowth embryos. Of these, 10 miRNA candidates (let-7b, miR-23a, miR-27a, miR-92a, miR-183, miR-200c, miR-291a, miR-425, miR-429 and miR-652) were identified as significant differentially expressed miRNAs of outgrowth embryos by in silico analysis. The expression of the miRNA candidates was markedly changed during preimplantation embryo development. In particular, let-7b-5p, miR-200c-3p and miR-23a-3p were significantly upregulated in outgrowth embryos compared with non-outgrowth blastocysts. Overall, differentially expressed miRNAs in outgrowth embryos compared with blastocysts and non-outgrowth embryos could be involved in embryo attachment, and interaction between the embryo proper and maternal endometrium during the implantation process.

scholarly journals Expression profiling analysis of autophagy-related genes in cervical cancer

2021 ◽  
Author(s):  
Zhiyuan Huang ◽  
He Wang ◽  
Min Liu ◽  
Xinrui Li ◽  
Lei Zhu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cervical Cancer ◽  
Overall Survival ◽  
Risk Score ◽  
Roc Curve ◽  
Normal Tissue ◽  
Cox Regression ◽  
Risk Group ◽  
Differentially Expressed ◽  
Tissue Samples

Abstract Background: It has been demonstrated by studies globally that autophagy took part in the development of cervical cancer (CC). Few studies concentrated on the correlation between overall survival and CC patients. We retrieved significant autophagy-related genes (ARGs) correlated to the process of cervical cancer. They may be used as prognosis marker or treatment target for clinical application.Methods: Expressions level of genes in cervical cancer and normal tissue samples were obtained from GTEx and TCGA database. Autophagy-related genes (ARGs) were retrieved accroding to the gene list from HaDB. Differentially expressed autophagy related genes (DE-ARGs) related to cervical cancer were identified by Wilcoxon signed-rank test. ClusterProfiler package worked in R software was used to perform GO and KEGG enrichment analyses. Univariate propotional hazard cox regression and multivariate propotional hazard cox regressions were applied to identify DE-ARGs equipped with prognostic value and other clinical independent risk factors. ROC curve was drawn for comparing the survival predict feasibility of risk score with other risk factors in CC patients. Nomogram was drawn to exhibit the prediction model constructed accroding to multivariate cox regression. Correlations between Differentially expressed autophagy related genes (DE-ARGs) and other clinical features were investigated by t test or Cruskal wallis analysis. Correlation between Immune and autophagy in cervical cancer was investigated by ssGSEA and TIMER database. Results: Fifty-six differentially expressed ARGs (DE-ARGs) were retrieved from cervical cancer tissue and normal tissue samples. GO enrichment analysis showed that these ARGs involved in autophagy, ubiquitination of protein and apoptosis. Cox regression medel showed that there were six ARGs significantly associated with overall survival of cervical caner patients. VAMP7 (HR = 0.599, P= 0.033) and TP73 (HR = 0.671, P= 0.014) played protective roles in survival among these six genes. Stage (Stage IV vs Stage I HR = 3.985, P<0.001) and risk score (HR = 1.353, P< 0.001) were sorted as independent prognostic risk factors based on multivariate cox regression. ROC curve validated that risk score was preferable to predict survival of CC patients than other risk factors. Additionally, we found some of these six predictor ARGs were correlated significantly in statistic with tumor grade or stage, clinical T stage, clinical N stage, pathology or risk score (all P< 0.05). The immune cells and immune functions showed a lower activity in high risk group than low risk group which is distincted by median risk score. Conclusion: Our discovery showed that autophagy genes involved in the progress of cervical cancer. Many autophagy-related genes could probably serve as prognostic biomarkers and accelerate the discovery of treatment targets for CC patients.

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