scholarly journals Screening and Bioinformatics Analysis of Competitive Endogenous RNA Regulatory Network ––Related to Circular RNA in Breast Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Tao Wang ◽  
Yi Zhang ◽  
Yan He ◽  
Yang Liu ◽  
Peng Qi
Keyword(s):  
Breast Cancer ◽  
Survival Analysis ◽  
Regulatory Network ◽  
Circular Rna ◽  
Differentially Expressed ◽  
Tgf Beta ◽  
Qrt Pcr ◽  
Kegg Analysis ◽  
Competitive Endogenous Rna ◽  
Geo Database

Purpose. Circular RNA as a competitive endogenous RNA (ceRNA) plays a significant role in the pathogenesis and progression of breast cancer. In this study, a circular RNA-related ceRNA regulatory network was constructed, which provides new biomarkers and therapeutic targets for the treatment of breast cancer. Materials and methods. The expression profile datasets (GSE101123, GSE143564, GSE50428) of circRNAs, miRNAs, and mRNAs were downloaded from the GEO database, and then differentially expressed RNAs (DEcircRNAs, DEmiRNAs, DEmRNAs) were obtained through the CSCD, TargetScan, miRDB, and miRTarBase databases. CircRNA-miRNA pairs and miRNA-mRNA pairs were constructed. Finally, a ceRNA regulatory network was established. Downstream analysis of the ceRNA network included GO, KEGG analysis, survival analysis, sub-network construction, the BCIP, and qRT-PCR verification. Results. In total, 144 differentially expressed (DE) DEcircRNA, 221 DEmiRNA, and 1211 DEmRNA were obtained, and 96 circRNA-miRNA pairs and 139 miRNA-mRNA pairs were constructed by prediction. The ceRNA regulatory network (circRNA-miRNA-mRNA) was constructed, which included 42 circRNA, 36miRNA, and 78 mRNA. GO function annotation showed genes were mainly enriched in receptor activity activated by transforming growth factor beta (TGF-beta) and in the regulation of epithelial cell apoptosis. KEGG analysis showed genes were mainly enriched in the TGF-beta signaling, PI3K-Akt signaling, and Wnt signaling pathways. Four genes associated with survival and prognosis of breast cancer were obtained by survival analysis, the prognostic sub-network included 4 circRNA, 4 miRNA, and 4 mRNA. BCIP analysis and qRT-PCR verification confirmed that relative mRNA expression levels were consistent with those in the GEO database. Conclusion. A circRNA-related ceRNA regulatory network was constructed for breast cancer in this study and key genes affecting pathogenesis and progression were identified. These findings may help better understand and further explore the molecular mechanisms that affect the progression and pathogenesis of breast cancer.

scholarly journals Integrated Analysis of Circular RNA Associated Cerna Network Reveals Potential CircRNA Biomarkers in Human Breast Cancer

2020 ◽  
Author(s):  
Hui Shen ◽  
Huan Pan ◽  
Jianju Lu ◽  
Jianfen Shen ◽  
Longsheng Xu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Survival Analysis ◽  
Correlation Analysis ◽  
Mrna Expression ◽  
Circular Rna ◽  
Comprehensive Analysis ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Cerna Network ◽  
Competitive Endogenous Rna

Abstract BackgroundThere is increasing evidence that circular RNA (circRNA) is closely related to tumorigenesis and cancer progression. circRNA has been identified as a sponge of microRNA (miRNA) in a competitive endogenous RNA (ceRNA) network and is involved in the regulation of mRNA expression. However, the roles of cancer specific circRNAs in circRNA-related ceRNA network of breast cancer (BRCA) are still unclear. This study aims to construct a ceRNA network associated with circRNA and to explore new therapeutic and prognostic targets and biomarkers for breast cancer.MethodsWe downloaded the circRNA expression profile of BRCA from Gene Expression Omnibus (GEO) microarray datasets and downloaded the miRNA and mRNA expression profiles of BRCA from The Cancer Genome Atlas (TCGA) database, these data were included in the study for comprehensive analysis. Differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs) and differentially expressed circRNAs (DEcircRNAs) were identified and a competitive endogenous RNA (ceRNA) regulatory network was constructed based on circRNA–miRNA pairs and miRNA–mRNA pairs. Gene ontology and pathway enrichment analysis were performed on mRNAs regulated by circRNAs in ceRNA networks. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network were performed. The STRING search tool was used to predict the interaction between proteins, and the hub genes were screened by the MCODE plugin in Cytoscape.ResultsA total of 72 DEcircRNAs, 158 DEmiRNAs and 2762 DE mRNAs were identified. The constructed ceRNA network contains 60 circRNA-miRNA pairs and 140 miRNA-mRNA pairs, including 40 circRNAs, 30 miRNAs and 100 mRNAs. Functional enrichment indicated that DEmRNAs regulated by DEcircRNAs in ceRNA networks were significantly enriched in PI3K-Akt signaling pathway, MicroRNAs in cancer and Proteoglycans in cancer. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network showed that a total of 13 mRNAs and 6 miRNAs were significantly associated with overall survival, and 48 miRNA-mRNA interaction pairs had a significant negative correlation. A PPI network was established and 21 hub genes were determined from the network. After comprehensive analysis, four potential ceRNA regulatory axes were constructed based on three circRNAs, two miRNAs, and three mRNAs.ConclusionsThis study provides an effective bioinformatics basis for further understanding the molecular mechanisms and predictions of breast cancer. A better understanding of the circRNA-related ceRNA network in BRCA will help identify potential biomarkers for diagnosis and prognosis.

scholarly journals Integrated Analysis of Circular RNA-Associated ceRNA Network Reveals Potential circRNA Biomarkers in Human Breast Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Han Sheng ◽  
Huan Pan ◽  
Ming Yao ◽  
Longsheng Xu ◽  
Jianju Lu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Survival Analysis ◽  
Correlation Analysis ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Circular Rna ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Cerna Network

Circular RNA (circRNA) is closely related to tumorigenesis and cancer progression. Yet, the roles of cancer-specific circRNAs in the circRNA-related ceRNA network of breast cancer (BRCA) remain unclear. The aim of this study was to construct a ceRNA network associated with circRNA and to explore new therapeutic and prognostic targets and biomarkers for breast cancer. We downloaded the circRNA expression profile of BRCA from Gene Expression Omnibus (GEO) microarray datasets and downloaded the miRNA and mRNA expression profiles of BRCA from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed circRNAs (DEcircRNAs) were identified, and a competitive endogenous RNA (ceRNA) regulatory network was constructed based on circRNA–miRNA pairs and miRNA–mRNA pairs. Gene ontology and pathway enrichment analyses were performed on mRNAs regulated by circRNAs in ceRNA networks. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network were performed. A total of 72 DEcircRNAs, 158 DEmiRNAs, and 2762 DE mRNAs were identified. The constructed ceRNA network contains 60 circRNA–miRNA pairs and 140 miRNA–mRNA pairs, including 40 circRNAs, 30 miRNAs, and 100 mRNAs. Functional enrichment indicated that DEmRNAs regulated by DEcircRNAs in ceRNA networks were significantly enriched in the PI3K-Akt signaling pathway, microRNAs in cancer, and proteoglycans in cancer. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network showed that 13 mRNAs and 6 miRNAs were significantly associated with overall survival, and 48 miRNA–mRNA interaction pairs had a significant negative correlation. A PPI network was established, and 21 hub genes were determined from the network. This study provides an effective bioinformatics basis for further understanding of the molecular mechanisms and predictions of breast cancer. A better understanding of the circRNA-related ceRNA network in BRCA will help identify potential biomarkers for diagnosis and prognosis.

scholarly journals Construction and Investigation of circRNA-miRNA-mRNA ceRNA regulatory network in breast cancer

2020 ◽  
Author(s):  
Ming Wu ◽  
Meijie Sang ◽  
Shuo Pan ◽  
Fei Liu ◽  
Meixiang Sang
Keyword(s):  
Breast Cancer ◽  
Survival Analysis ◽  
Real Time ◽  
Real Time Pcr ◽  
Regulatory Network ◽  
Target Genes ◽  
Differentially Expressed ◽  
Venn Diagram ◽  
Circular Rnas ◽  
Hub Genes

Abstract Background Circular RNAs (circRNAs) have drawn lots of attention in tumorigenesis and progression. However, circRNAs as crucial regulators in multitudinous biological processes have not been systematically identified in breast cancer (BC). Our research aims to explore novel circRNAs in BC and their mechanisms of action. Methods The circRNA expression profile data, as well as RNA-sequencing data of BC, were downloaded from public database, respectively. The differentially expressed circRNAs, miRNA, and mRNA were determined via fold change filtering. The competing endogenous RNAs (ceRNAs) network were established on the foundation of the relationship between circular RNAs, miRNAs and mRNAs. GO and KEGG analysis of the overlapped genes were performed to predict the potential functions and mechanisms of circRNAs in BC. The CytoHubba was used to determine the hub genes from the PPI regulatory network. Morever, we further used Kaplan–Meier plotter to perform survival analysis of these hub genes. Real-time PCR was used to validate the expression of the circRNAs in BC tissues. Results A total of seven differential expressed circRNAs were screened. After the predicted target miRNA and DEmiRNA were intersected, four circRNA-miRNA interactions including three circRNAs and four miRNAs were determined. Furthermore, the Venn diagram was used to intersect the predicted target genes and the downregulated differentially expressed genes, and screened 149 overlapped genes. Moreover, we constructed a PPI network, and selecting six hub genes, including DGAT2, ACSL1, ADIPOQ, LPL, LEP, PCK1. Moreover, the survival analysis results revealed that low expression of ADIPOQ, LPL, LEP were obviously correlated with poor prognosis of BC patients. The real-time PCR results demonstrated that, the levels of circ_0028899, circ_0000375, and circ_0000376 were significantly down-regulated in breast cancer tissues. Conclusions Our study constructed and analyzed a circRNA-associated ceRNA regulatory network and discovered that circ_0028899, circ_0000375, and circ_0000376 may function as ceRNAs to serve key roles in BC.

scholarly journals Construction and Investigation of circRNA-miRNA-mRNA ceRNA Regulatory Network in Breast Cancer

2020 ◽  
Author(s):  
Ming Wu ◽  
Meijie Sang ◽  
Shuo Pan ◽  
Fei Liu ◽  
Meixiang Sang
Keyword(s):  
Breast Cancer ◽  
Survival Analysis ◽  
Real Time ◽  
Real Time Pcr ◽  
Regulatory Network ◽  
Target Genes ◽  
Differentially Expressed ◽  
Venn Diagram ◽  
Circular Rnas ◽  
Hub Genes

Abstract Background: Circular RNAs (circRNAs) have drawn lots of attention in tumorigenesis and progression. However, circRNAs as crucial regulators in multitudinous biological processes have not been systematically identified in breast cancer (BC). Our research aims to explore novel circRNAs in BC and their mechanisms of action.Methods: The circRNA expression profile data, as well as RNA-sequencing data of BC, were downloaded from public database, respectively. The differentially expressed circRNAs, miRNA, and mRNA were determined via fold change filtering. The competing endogenous RNAs (ceRNAs) network were established on the foundation of the relationship between circular RNAs, miRNAs and mRNAs. GO and KEGG analysis of the overlapped genes were performed to predict the potential functions and mechanisms of circRNAs in BC. The CytoHubba was used to determine the hub genes from the PPI regulatory network. Morever, we further used Kaplan–Meier plotter to perform survival analysis of these hub genes. Real-time PCR was used to validate the expression of the circRNAs in BC tissues.Results: A total of seven differential expressed circRNAs were screened. After the predicted target miRNA and DEmiRNA were intersected, four circRNA-miRNA interactions including three circRNAs and four miRNAs were determined. Furthermore, the Venn diagram was used to intersect the predicted target genes and the downregulated differentially expressed genes, and screened 149 overlapped genes. Moreover, we constructed a PPI network, and selecting six hub genes, including DGAT2, ACSL1, ADIPOQ, LPL, LEP, PCK1. Moreover, the survival analysis results revealed that low expression of ADIPOQ, LPL, LEP were obviously correlated with poor prognosis of BC patients. The real-time PCR results demonstrated that, the levels of circ_0028899, circ_0000375, and circ_0000376 were significantly down-regulated in breast cancer tissues.Conclusions: Our study constructed and analyzed a circRNA-associated ceRNA regulatory network and discovered that circ_0028899, circ_0000375, and circ_0000376 may function as ceRNAs to serve key roles in BC.

scholarly journals Circular RNA Expression Profiling Identifies Prostate Cancer- Specific circRNAs in Prostate Cancer

2018 ◽  
Vol 50 (5) ◽  
pp. 1903-1915 ◽  
Author(s):  
Qianlin Xia ◽  
Tao Ding ◽  
Guihong Zhang ◽  
Zehuan Li ◽  
Ling Zeng ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Polymerase Chain Reaction Analysis ◽  
Circular Rna ◽  
Differentially Expressed ◽  
Pcr Analysis ◽  
High Morbidity ◽  
Qrt Pcr ◽  
Diagnosis And Prognosis ◽  
Novel Biomarkers ◽  
Rna Expression Profiling

Background/Aims: Prostate cancer (PCa) is one of the main cancers that damage males’ health severely with high morbidity and mortality, but there is still no ideal molecular marker for the diagnosis and prognosis of prostate cancer. Methods: To determine whether the differentially expressed circRNAs in prostate cancer can serve as novel biomarkers for prostate cancer diagnosis, we screened differentially expressed circRNAs using SBC-ceRNA array in 4 pairs of prostate tumor and paracancerous tissues. A circRNA-miRNA-mRNA regulatory network for the differential circRNAs and their host genes was constructed by Cytoscape3.5.1 software. Quantitative real-time polymerase chain reaction analysis (qRT-PCR) was performed to confirm the microarray data. Results: We found 1021 differentially expressed circRNAs in PCa tumor using SBC-ceRNA array and confirmed the expression of circ_0057558, circ_0062019 and SLC19A1 in PCa cell lines and tumor tissues through qRT-PCR analysis. We demonstrated that combination of PSA level and two differentially expressed circRNAs showed significantly increased AUC, sensitivity and specificity (0.938, 84.5% and 90.9%, respectively) than PSA alone (AUC of serum PSA was 0.854). Moreover, circ_0057558 was correlated positively with total cholesterol. The functional network of circRNA-miRNA-mRNA analysis showed that circ_0057558 and circ_0034467 regulated miR-6884, and circ_0062019 and circ_0060325 regulated miR-5008. Conclusion: Our results demonstrated that differentially expressed circRNAs (circ_0062019 and circ_0057558) and host gene SLC19A1 of circ_0062019 could be used as potential novel biomarkers for prostate cancer.

scholarly journals Prognostic Biomarkers on a Competitive Endogenous RNA Network Reveals Overall Survival in Triple-Negative Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Wenxing Qin ◽  
Feng Qi ◽  
Jia Li ◽  
Ping Li ◽  
Yuan-Sheng Zang
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Triple Negative Breast Cancer ◽  
Prognostic Model ◽  
Triple Negative ◽  
Cox Regression ◽  
Critical Role ◽  
Differentially Expressed ◽  
Cerna Network ◽  
Competitive Endogenous Rna

The objective of this study was to construct a competitive endogenous RNA (ceRNA) regulatory network using differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in patients with triple-negative breast cancer (TNBC) and to construct a prognostic model for predicting overall survival (OS) in patients with TNBC. Differentially expressed lncRNAs, miRNAs, and mRNAs in TNBC patients from the TCGA and Metabric databases were examined. A prognostic model based on prognostic scores (PSs) was established for predicting OS in TNBC patients, and the performance of the model was assessed by a recipient that operated on a distinctive curve. A total of 874 differentially expressed RNAs (DERs) were screened, among which 6 lncRNAs, 295 miRNAs and 573 mRNAs were utilized to construct targeted and coexpression ceRNA regulatory networks. Eight differentially expressed genes (DEGs) associated with survival prognosis, DBX2, MYH7, TARDBP, POU4F1, ABCB11, LHFPL5, TRHDE and TIMP4, were identified by multivariate Cox regression and then used to establish a prognostic model. Our study shows that the ceRNA network has a critical role in maintaining the aggressiveness of TNBC and provides comprehensive molecular-level insight for predicting individual mortality hazards for TNBC patients. Our data suggest that these prognostic mRNAs from the ceRNA network are promising therapeutic targets for clinical intervention.

scholarly journals CircRNA-miRNA-mRNA Regulatory Network in Colorectal Cancer

2021 ◽  
Author(s):  
Liyuan Liu ◽  
Shan Wu ◽  
Dan Jiang ◽  
Yuliang Qu ◽  
Hongxia Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Regulatory Network ◽  
Research Direction ◽  
Differentially Expressed ◽  
Circular Rnas ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Qrt Pcr ◽  
Cancer Tissues ◽  
Chip Analysis

Abstract Background: Abnormal expression of Circular RNAs (circRNAs) occurs in the occurrence and progression of colorectal cancer (CRC) and plays an important role in the pathogenesis of tumors. We combined bioinformatics and laboratory-validated methods to search for key circRNAs and possible potential mechanisms. Methods: Colorectal cancer tissues and normal paracancerous tissues were detected by microarray analysis and qRT-PCR validation, and differentially expressed circRNAs were screened and identified. The circRNA-miRNA-mRNA regulatory network (cirReNET) was constructed, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to ascertain the functions of circRNAs in CRCs. In addition, a protein-protein interaction (PPI) network of hub genes which acquired by string and plugin app CytoHubba in cytoscape was established. Validation of expression of hub genes was identified by GEPIA database. Results: 564 differentially expressed circRNAs which include 207 up-regulated and 357 down-regulated circRNAs were detected. The top 3 up-regulated circRNAs (hsa_circRNA_100833, hsa_circRNA_103828, hsa_circRNA_103831) and the top 3 down-regulated circRNAs (hsa_circRNA_103752, hsa_circRNA_071106, hsa_circRNA_102293) in chip analysis were chosen to be verified in 33 pairs of CRCs by qRT-PCR. The cirReNET include of 6 circRNAs, 19 miRNAs and 210 mRNA. And the targeted mRNAs were associated with cellular metabolic process, cell cycle and glandular epithelial cell differentiation and so on. 12 and 10 target hub genes were shown separately in upregulated circRNA-downregulated miRNA-upregulated mRNA (UcDiUm-RNA) group and downregulated circRNA-upregulated miRNA-downregulated mRNA (DcUiDm-RNA) group. Finally, we may have predicted and discovered several critical circRNA-miRNA-mRNA regulatory axes (cirReAXEs) which may play important roles in colorectal cancer. Conclusion: We constructed a cirReNET including 6 candidate circRNAs, which were crucial in CRCs, may become potential diagnostic markers and predictive indicators of CRCs, and we may provide a research direction for the pathogenesis of colorectal cancer.

scholarly journals Identification of Differentially Expressed Genes and miRNAs Associated with Esophageal Squamous Cell Carcinoma by Integrated Analysis of Microarray Data

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Lemeng Zhang ◽  
Jianhua Chen ◽  
Tianli Cheng ◽  
Hua Yang ◽  
Changqie Pan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Survival Analysis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Microarray Data ◽  
Regulatory Network ◽  
Differentially Expressed ◽  
Pathway Enrichment

To identify candidate key genes and miRNAs associated with esophageal squamous cell carcinoma (ESCC) development and prognosis, the gene expression profiles and miRNA microarray data including GSE20347, GSE38129, GSE23400, and GSE55856 were downloaded from the Gene Expression Omnibus (GEO) database. Clinical and survival data were retrieved from The Cancer Genome Atlas (TCGA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes (DEGs) was analyzed via DAVID, while the DEG-associated protein-protein interaction network (PPI) was constructed using the STRING database. Additionally, the miRNA target gene regulatory network and miRNA coregulatory network were constructed, using the Cytoscape software. Survival analysis and prognostic model construction were performed via the survival (version 2.42-6) and rbsurv R packages, respectively. The results showed a total of 2575, 2111, and 1205 DEGs, and 226 differentially expressed miRNAs (DEMs) were identified. Pathway enrichment analyses revealed that DEGs were mainly enriched in 36 pathways, such as the proteasome, p53, and beta-alanine metabolism pathways. Furthermore, 448 nodes and 1144 interactions were identified in the PPI network, with MYC having the highest random walk score. In addition, 7 DEMs in the microarray data, including miR-196a, miR-21, miR-205, miR-194, miR-103, miR-223, and miR-375, were found in the regulatory network. Moreover, several reported disease-related miRNAs, including miR-198a, miR-103, miR-223, miR-21, miR-194, and miR-375, were found to have common target genes with other DEMs. Survival analysis revealed that 85 DEMs were related to prognosis, among which hsa-miR-1248, hsa-miR-1291, hsa-miR-421, and hsa-miR-7-5p were used for a prognostic survival model. Taken together, this study revealed the important roles of DEGs and DEMs in ESCC development, as well as DEMs in the prognosis of ESCC. This will provide potential therapeutic targets and prognostic predictors for ESCC.

scholarly journals Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Xinhong Liu ◽  
Feng Chen ◽  
Fang Tan ◽  
Fang Li ◽  
Ruokun Yi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcription Factors ◽  
Target Genes ◽  
Differential Expression Analysis ◽  
Mirna Gene ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Epithelial Tissue ◽  
Hub Genes ◽  
Geo Database

Background. Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive breast cancer-miRNA-gene interaction map. Methods. Three miRNA microarray datasets (GSE26659, GSE45666, and GSE58210) were obtained from the GEO database. Then, the R software “LIMMA” package was used to identify differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The BRCA GE-mRNA datasets (GSE109169 and GSE139038) were downloaded from the GEO database for identifying differentially expressed genes (DE-genes). Next, GO annotation and KEGG pathway enrichment analysis were conducted. A PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes were further evaluated. Results. We found 6 upregulated differentially expressed- (DE-) miRNAs and 18 downregulated DE-miRNAs by analyzing 3 Gene Expression Omnibus databases, and we predicted the upstream transcription factors and downstream target genes for these DE-miRNAs. Then, we used the GEO database to perform differential analysis on breast cancer mRNA and obtained differentially expressed mRNA. We found 10 hub genes of upregulated DE-miRNAs and 10 hub genes of downregulated DE-miRNAs through interaction analysis. Conclusions. In this study, we have performed an integrated bioinformatics analysis to construct a more comprehensive BRCA-miRNA-gene network and provide new targets and research directions for the treatment and prognosis of BRCA.

scholarly journals Identification of lncRNA–mRNA Regulatory Network Associated With Isolated Systolic Hypertension and Atherosclerotic Cerebral Infarction

2021 ◽  
Author(s):  
jie Yang ◽  
Yan-Nan Tao ◽  
Fang-Xiao Hu ◽  
Yong-Zhi Chen ◽  
Xue-Song Yang ◽  
...  
Keyword(s):  
Cerebral Infarction ◽  
Regulatory Network ◽  
Systolic Hypertension ◽  
Expression Profiles ◽  
Pearson Correlation ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Isolated Systolic Hypertension ◽  
Hub Genes ◽  
Qrt Pcr

Abstract Background: Increasing evidences uncover that lncRNAs play an important role in Isolated systolic hypertension (ISH). However, a systematic lncRNA-mRNA regulatory network is still absent in isolated systolic hypertension and atherosclerotic cerebral infarction patients (ISH & ACI).Aim:This research aims to establish a lncRNA-mRNA co-expression network in patients with ISH & ACI, to probe into the potential functions of lncRNA in those patients.Design and Setting:Expression profiles of lncRNA and mRNAs are collected and compared respectively from 8 patients with ISH and 8 patients with ISH & ACI by RNA-seq data.Methods: Differentially expressed lncRNAs and mRNAs were screened out via high-throughput sequencing in the plasma of ISH/ACI patients and control ISH patients. Then, a lncRNA-mRNA interaction network was built using the Pearson correlation coefficient by Cytoscape software. The expression levels of the hub genes and lncRNAs were verified by qRT-PCR in another 10 ISH/ACI patients and 10 control patients. Results: 2768 differentially expressed lncRNAs and 747 differentially expressed mRNAs were identified. 2 hub genes (CD226 and PARVB) and 11 lncRNAs were identified in the lncRNA-mRNA interaction network. qRT-PCR and cell assay results verified that lncRNAs ENST00000590604 and CD226 are highly expressed in patients of ISH & ACI. CD226 was associated with vascular endothelial cells growth and stability through platelet activation and focal adhesion pathway.Conclusion: We established a novel mRNA-lncRNA interaction network. lncRNAs ENST00000590604 and CD226 might be the potential biomarkers of ISH & ACI.

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