scholarly journals Construction and analysis of the lncRNA-miRNA-mRNA network based on competitive endogenous RNA reveal functional lncRNAs in oral cancer

2020 ◽  
Author(s):  
Junhao Yin ◽  
Xiaoli Zeng ◽  
Zexin Ai ◽  
Miao Yu ◽  
Yang’ou Wu ◽  
...  
Keyword(s):  
Oral Cancer ◽  
Expression Profiles ◽  
Topological Analysis ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Expression Omnibus ◽  
Mirna Sponge ◽  
Cerna Network ◽  
Function Enrichment Analysis ◽  
Competitive Endogenous Rna

Abstract Background There is a growing body of evidence suggesting that long non-coding RNAs(lncRNAs) can function as a microRNA(miRNA) sponge in various diseases including oral cancer. However, we are still not very clear about the pathophysiological function of lncRNAs. Methods We constructed a lncRNA-miRNA-mRNA network in oral cancer based on the competitive endogenous RNA(ceRNA) theory with the human expression profiles GSE74530 from the Gene Expression Omnibus (GEO) database and used topological analysis to determine the hub lncRNAs in the regulatory ceRNA network. Then, function enrichment analysis was performed by R package Cluster Profiler. Results A total of 238 potential co-dysregulated competing triples were obtained in the lncRNA-assoicated ceRNA network of oral cancer, which consisted of 10 lncRNA nodes, 41 miRNA nodes, and 122 mRNA nodes. Additionally, we found three lncRNAs( HCP5 , AGAP11 , HCG22 ) exhibiting superior potential as diagnostic and prognostic markers of oral cancer. Conclusions Our findings will provide novel insights for understanding the ceRNA regulation in oral cancer and identify three novel lncRNAs as potential molecular biomarkers.

scholarly journals Construction and analysis of the lncRNA-miRNA-mRNA network based on competitive endogenous RNA reveal functional lncRNAs in oral cancer

2020 ◽  
Author(s):  
Junhao Yin ◽  
Xiaoli Zeng ◽  
Zexin Ai ◽  
Miao Yu ◽  
Yang’ou Wu ◽  
...  
Keyword(s):  
Oral Cancer ◽  
Expression Profiles ◽  
Topological Analysis ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
R Package ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cerna Network ◽  
Competitive Endogenous Rna

Abstract Background: A growing evidence suggests that long non-coding RNAs (lncRNAs) can function as a microRNA (miRNA) sponge in various diseases including oral cancer. However, the pathophysiological function of lncRNAs remains unclear. Methods: Based on the competitive endogenous RNA (ceRNA) theory, we constructed a lncRNA-miRNA-mRNA network in oral cancer with the human expression profiles GSE74530 from the Gene Expression Omnibus (GEO) database. We used topological analysis to determine the hub lncRNAs in the regulatory ceRNA network. Then, function enrichment analysis was performed using the clusterProfiler R package. Clinical information was downloaded from The Cancer Genome Atlas (TCGA) database and survival analysis was performed with Kaplan-Meier analysis. Results: A total of 238 potential co-dysregulated competing triples were obtained in the lncRNA-associated ceRNA network in oral cancer, which consisted of 10 lncRNA nodes, 41 miRNA nodes and 122 mRNA nodes. Additionally, we found lncRNA HCG22 exhibiting superior potential as a diagnostic and prognostic marker of oral cancer. Conclusions: Our findings provide novel insights to understand the ceRNA regulation in oral cancer and identify a novel lncRNA as a potential molecular biomarker.

scholarly journals Identification and analysis of lncRNA, microRNA and mRNA expression profiles and construction of ceRNA network in Talaromyces marneffei-infected THP-1 macrophage

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10529
Author(s):  
Yueqi Li ◽  
Wudi Wei ◽  
Sanqi An ◽  
Junjun Jiang ◽  
Jinhao He ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
R Package ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Next Generation Sequencing Technology ◽  
Talaromyces Marneffei ◽  
Kegg Analysis ◽  
Cerna Network

Background Competitive endogenous RNA (ceRNA) reveals new mechanisms for interactions between RNAs, which have been considered to play a significant role in pathogen-host innate immune response. However, knowledge of ceRNA regulatory networks in Talaromyces marneffei (TM)-macrophages is still limited. Methods Next-generation sequencing technology (NGS) was used to obtain mRNA, miRNA and lncRNA expression profiles in TM-infected macrophages. The R package DESeq2 was used to identify differentially expressed lncRNA, miRNA and mRNA. The R package GOseq was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and the ceRNA network of lncRNA–miRNA–mRNA interaction was constructed in Cytoscape. Similarly, functional enrichment analysis on mRNA in the ceRNA network. Finally, two mRNAs and four lncRNAs in the ceRNA network were randomly selected to verify the expression using qRT-PCR. Results In total, 119 lncRNAs, 28 miRNAs and 208 mRNAs were identified as differentially expressed RNAs in TM-infected macrophages. The constructed ceRNA network contains 38 lncRNAs, 10 miRNAs and 45 mRNAs. GO and KEGG analysis of mRNA in the ceRNA network indicated that activated pathways in TM-infected macrophages were related to immunity, inflammation and metabolism. The quantitative validation of the expression of four randomly selected differentially expressed lncRNAs, AC006252.1, AC090197.1, IL6R-AS1, LINC02009 and two mRNAs, CSF1, NR4A3 showed that the expression levels were consistent with those in the RNA-sequencing. Conclusions The ceRNA network related to immunity, inflammation and metabolism plays an important role in TM-macrophage interaction. This study may provide effective and novel insights for further understanding the underlying mechanism of TM infection.

The relationship between LncRNAs and lung adenocarcinoma as well as their ceRNA network

2021 ◽  
pp. 1-12
Author(s):  
Yuxin Zhao ◽  
Shuwen Ma ◽  
Zhigang Cui ◽  
Sixuan Li ◽  
Yao Chen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Pathway Enrichment Analysis ◽  
Lung Cancer Patients ◽  
Protein Protein Interaction ◽  
Normal Tissues ◽  
Cerna Network ◽  
Downstream Analysis

BACKGROUND: More and more studies have shown that long non-coding RNA (LncRNA) as a competing endogenous RNA (ceRNA) plays an important role in lung cancer. Therefore, we analyzed the RNA expression profiles of 82 lung cancer patients which were all from Gene Expression Omnibus (GEO). METHODS: Firstly, we used BLASTN (evalue = 1e-10) to annotate the gene sets, performed in-group correction and batched normalization of the four data sets with R. Secondly, we used the limma and sva packages to compare tumor tissues with normal tissues. Then through WGCNA, we obtained the 4 gene modules most related to the trait. RESULTS: We intersected the genes of above 4 modules with the differential expression genes: 28 LncRNAs (up: 5, down: 23) and 265 mRNAs (up:11, down: 254). Based on these genes, we picked up 6 LncRNAs (CCDC39, FAM182A, SRGAP3-AS2, ADAMTS9-AS2, AC020907.2, SFTA1P), then set and visualized the LncRNA-miRNA-mRNA ceRNA network with 12 miRNAs related to 12 mRNAs. Finally, we performed downstream analysis of 265 mRNAs by Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Protein-Protein Interaction (PPI) network. CONCLUSION: After analyzing, we think this study provides a new direction for basic and clinical research related to LAD, and is expected to provide new targets for early diagnosis, prognostic evaluation and clinical treatment of lung cancer.

scholarly journals The characteristics of circRNA as competing endogenous RNA in pathogenesis of acute myeloid leukemia

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Siyuan Zhang
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Expression Profiles ◽  
Gene Expression Omnibus ◽  
The Novel ◽  
Competing Endogenous Rna ◽  
Regulatory Modules ◽  
Cerna Network ◽  
Regulatory Module ◽  
Acute Myeloid

Abstract Background As one of the novel molecules, circRNA has been identified closely involved in the pathogenesis of many diseases. However, the function of circRNA in acute myeloid leukemia (AML) still remains unknown. Methods In the current study, the RNA expression profiles were obtained from Gene Expression Omnibus (GEO) datasets. The differentially expressed RNAs were identified using R software and the competing endogenous RNA (ceRNA) network was constructed using Cytoscape. Functional and pathway enrichment analyses were performed to identify the candidate circRNA-mediated aberrant signaling pathways. The hub genes were identified by MCODE and CytoHubba plugins of Cytoscape, and then a subnetwork regulatory module was established. Results A total of 27 circRNA-miRNA pairs and 208 miRNA-mRNA pairs, including 12 circRNAs, 24 miRNAs and 112 mRNAs were included in the ceRNA network. Subsequently, a subnetwork, including 4 circRNAs, 5 miRNAs and 6 mRNAs, was established based on related circRNA-miRNA-mRNA regulatory modules. Conclusions In summary, this work analyzes the characteristics of circRNA as competing endogenous RNA in AML pathogenesis, which would provide hints for developing novel prognostic, diagnostic and therapeutic strategy for AML.

scholarly journals Bioinformatics Analysis of the Molecular Mechanism and Potential Treatment Target of Ankylosing Spondylitis

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Fanyan Meng ◽  
Ningna Du ◽  
Daoming Xu ◽  
Li Kuai ◽  
Lanying Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ankylosing Spondylitis ◽  
Molecular Mechanism ◽  
Soft Tissues ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Expression Omnibus ◽  
Treatment Targets ◽  
Protein Protein Interaction

Ankylosing spondylitis (AS) is an autoimmune disease that mainly affects the spinal joints, sacroiliac joints, and adjacent soft tissues. We conducted bioinformatics analysis to explore the molecular mechanism related to AS pathogenesis and uncover novel potential molecular targets for the treatment of AS. The profiles of GSE25101, containing gene expression data extracted from the blood of 16 AS patients and 16 matched controls, were acquired from the Gene Expression Omnibus (GEO) database. The background correction and standardization were carried out utilizing the transcript per million (TPM) method. After analysis of AS patients and the normal groups, we identified 199 differentially expressed genes (DEGs) with upregulation and 121 DEGs with downregulation by the limma R package. The results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) biological process enrichment analysis revealed that the DEGs with upregulation were mainly associated with spliceosome, ribosome, RNA-catabolic process, electron transport chain, etc. And the DEGs with downregulation primarily participated in T cell-associated pathways and processes. After analysis of the protein-protein interaction (PPI) network, our data revealed that the hub genes, comprising MRPL13, MRPL22, LSM3, COX7A2, COX7C, EP300, PTPRC, and CD4, could be the treatment targets in AS. Our data furnish new hints to uncover the features of AS and explore more promising treatment targets towards AS.

Predicting functional circular RNA-based competitive endogenous RNA network in gastric carcinoma using novel bioinformatics analysis

2021 ◽  
pp. 153537022110487
Author(s):  
Zirui Zhu ◽  
Rui Huang ◽  
Baojun Huang
Keyword(s):  
Messenger Rna ◽  
Expression Profiles ◽  
Clinical Stage ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Rank Aggregation ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Competitive Endogenous Rna

Gastric cancer (GC) remains one of the most prevalent types of malignancies worldwide, and also one of the most reported lethal tumor-related diseases. Circular RNAs (circRNAs) have been certified to be trapped in multiple aspects of GC pathogenesis. Yet, the mechanism of this regulation is mostly undefined. This research is designed to discover the vital circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in GC. Expression profiles with diverse levels including circRNAs, miRNAs, and mRNAs were all determined using microarray public datasets from Gene Expression Ominous (GEO). The differential circRNAs expressions were recognized against the published robust rank aggregation algorithm. Besides, a circRNA-based competitive endogenous RNA (ceRNA) interaction network was visualized via Cytoscape software (version 3.8.0). Functional and pathway enrichment analysis associated with differentially expressed targeted mRNAs were conducted using Cytoscape and an online bioinformatics database. Furthermore, an interconnected protein–protein interaction association network which consisted of 51 mRNAs was predicted, and hub genes were screened using STRING and CytoHubba. Then, several hub genes were chosen to explore their expression associated with survival rate and clinical stage in GEPIA and Kaplan-Meier Plotter databases. Finally, a carefully designed circRNA-related ceRNA regulatory subnetwork including four circRNAs, six miRNAs, and eight key hub genes was structured using the online bioinformatics tool.

scholarly journals Integrative Analysis of Three Novel Competing Endogenous RNA Biomarkers with a Prognostic Value in Lung Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Juan Tan ◽  
Weimin Wang ◽  
Bin Song ◽  
Yingjian Song ◽  
Zili Meng
Keyword(s):  
High Risk ◽  
Lung Adenocarcinoma ◽  
Prognostic Value ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Function Enrichment Analysis ◽  
Pathway Function ◽  
Function Enrichment

Increasing evidence has shown competitive endogenous RNAs (ceRNAs) play key roles in numerous cancers. Nevertheless, the ceRNA network that can predict the prognosis of lung adenocarcinoma (LUAD) is still lacking. The aim of the present study was to identify the prognostic value of key ceRNAs in lung tumorigenesis. Differentially expressed (DE) RNAs were identified between LUAD and adjacent normal samples by limma package in R using The Cancer Genome Atlas database (TCGA). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function enrichment analysis was performed using the clusterProfiler package in R. Subsequently, the LUAD ceRNA network was established in three steps based on ceRNA hypothesis. Hub RNAs were identified using degree analysis methods based on Cytoscape plugin cytoHubba. Multivariate Cox regression analysis was implemented to calculate the risk score using the candidate ceRNAs and overall survival information. The survival differences between the high-risk and low-risk ceRNA groups were determined by the Kaplan-Meier and log-rank test using survival and survminer package in R. A total of 2,989 mRNAs, 185 lncRNAs, and 153 miRNAs were identified. GO and KEGG pathway function enrichment analysis showed that DE mRNAs were mainly associated with “sister chromatid segregation,” “regulation of angiogenesis,” “cell adhesion molecules (CAMs),” “cell cycle,” and “ECM-receptor interaction.” LUAD-related ceRNA network was constructed, which comprised of 54 nodes and 78 edges. Top ten hub RNAs (hsa-miR-374a-5p, hsa-miR-374b-5p, hsa-miR-340-5p, hsa-miR-377-3p, hsa-miR-21-5p, hsa-miR-326, SNHG1, RALGPS2, and PITX2) were identified according to their degree. Kaplan-Meier survival analyses demonstrated that hsa-miR-21-5p and RALGPS2 had a significant prognostic value. Finally, we found that a high risk of three novel ceRNA interactions (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) was positively associated with worse prognosis. Three novel ceRNAs (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) might be potential biomarkers for the prognosis and treatment of LUAD.

scholarly journals Identification of Potential Key Genes and Molecular Mechanisms of Medulloblastoma Based on Integrated Bioinformatics Approach

2022 ◽  
Vol 2022 ◽  
pp. 1-17
Author(s):  
Md. Rakibul Islam ◽  
Lway Faisal Abdulrazak ◽  
Mohammad Khursheed Alam ◽  
Bikash Kumar Paul ◽  
Kawsar Ahmed ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Gene Expression Omnibus ◽  
Hub Genes ◽  
New Treatments

Background. Medulloblastoma (MB) is the most occurring brain cancer that mostly happens in childhood age. This cancer starts in the cerebellum part of the brain. This study is designed to screen novel and significant biomarkers, which may perform as potential prognostic biomarkers and therapeutic targets in MB. Methods. A total of 103 MB-related samples from three gene expression profiles of GSE22139, GSE37418, and GSE86574 were downloaded from the Gene Expression Omnibus (GEO). Applying the limma package, all three datasets were analyzed, and 1065 mutual DEGs were identified including 408 overexpressed and 657 underexpressed with the minimum cut-off criteria of ∣ log   fold   change ∣ > 1 and P < 0.05 . The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways enrichment analyses were executed to discover the internal functions of the mutual DEGs. The outcomes of enrichment analysis showed that the common DEGs were significantly connected with MB progression and development. The Search Tool for Retrieval of Interacting Genes (STRING) database was used to construct the interaction network, and the network was displayed using the Cytoscape tool and applying connectivity and stress value methods of cytoHubba plugin 35 hub genes were identified from the whole network. Results. Four key clusters were identified using the PEWCC 1.0 method. Additionally, the survival analysis of hub genes was brought out based on clinical information of 612 MB patients. This bioinformatics analysis may help to define the pathogenesis and originate new treatments for MB.

scholarly journals Integrated analysis of lncRNA-miRNA-mRNA ceRNA network and the potential prognosis indicators in sarcomas

2021 ◽  
Author(s):  
Lu Gao ◽  
Yu Zhao ◽  
Xuelei Ma ◽  
Ling Zhang
Keyword(s):  
Survival Analysis ◽  
Kegg Pathway ◽  
Gene Prediction ◽  
Expression Profiles ◽  
Gene Expression Omnibus ◽  
Integrated Analysis ◽  
Ppi Network ◽  
Tissue Samples ◽  
Pathway Enrichment ◽  
Cerna Network

Abstract Background: Competitive endogenous RNA (ceRNA) has revealed a new mechanism of interaction between RNAs and been demonstrated to play crucial roles in multiple biological processes and in the development of neoplasms that potentially serve as diagnostic and prognosis markers as well as therapeutic targets.Methods：In this work, we identified differentially expressed mRNAs (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcoma by comparing the genes expression profiles between sarcoma samples and normal tissue samples in Gene Expression Omnibus (GEO) datasets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were applied to investigate the primary functions of the overlapped DEGs. Then, lncRNA-miRNA and miRNA-mRNA interactions were predicted, and the ceRNA regulatory network was constructed in Cytoscape. In addition, the protein-protein interaction (PPI) network was constructed and survival analysis was performed.Results: A total of 1296 DEGs were identified in sarcoma samples by combining the GO and KEGG pathway enrichment analyses, 338 DELs were discovered after the probes were reannotated, and 36 DEMs were ascertained through intersecting two different expression miRNAs sets. Further, through target gene prediction, a lncRNA-miRNA-mRNA ceRNA network that contained 113 mRNAs, 69 lncRNAs and 29 miRNAs was constructed. The PPI network identified the six most significant hub proteins. Survival analysis revealed that seven mRNAs, four miRNAs and one lncRNA were associated with overall survival of sarcoma patients.Conclusions: Overall, we constructed a ceRNA network in sarcomas, which likely provides insights for further research on the molecular mechanism and potential prognosis biomarkers.

scholarly journals Integrated analysis of lncRNA-miRNA-mRNA ceRNA network and the potential prognosis indicators in sarcomas

2020 ◽  
Author(s):  
Ling Zhang ◽  
Lu Gao ◽  
Yu Zhao ◽  
Xuelei Ma
Keyword(s):  
Survival Analysis ◽  
Protein Interactions ◽  
Sequence Data ◽  
Gene Prediction ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Integrated Analysis ◽  
Pathway Enrichment Analysis ◽  
Tissue Samples ◽  
Cerna Network

Abstract The ceRNA network has been demonstrated to play crucial roles in multiple biological processes and the development of neoplasms, which have the potential to become diagnostic and prognosis markers and therapeutic targets. In this work, we comparing the expression profiles between sarcoma identified differentially expressed genes (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcomas and normal tissue samples in GEO datasets. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied to investigate the major functions of the overlapping DEGs. Then, lncRNA-miRNA interactions and miRNA-mRNA interactions were predicted, and a ceRNA regulatory network was constructed. In addition, the mRNAs included in ceRNA network were used to construct the protein-protein interactions network, and the survival analysis of sarcomas was performed according to the biomarkers included in the ceRNA network. According to the RNA sequence data from GEO dataset, 1296 DEGs were identified in sarcoma samples by combining the GO and Pathway enrichment analysis, 338 DELs were discovered after re-annotating the probes, and 36 DEGs were ascertained through intersecting two different expression miRNAs sets. Further, 448 miRNA-mRNA interactions and 454 miRNA-lncRNA interactions were obtained through target gene prediction, and then, we constructed a lncRNA-miRNA-mRNA ceRNA network containing 9 miRNAs, 69 lncRNAs and 113 mRNAs. PPI network showed that the hub up-regulated nodes include IGF1, PRKCB and GNAI3, and the hub down-regulated nodes include AR, CYCS and PPP1CB. Survival analysis revealed that the expression levels of 12 RNAs involved in the ceRNA network were associated with overall survival of sarcoma patients. Our study showed that the ceRNA network in sarcomas based on that lncRNA could serve as ceRNA and discovered the potential indicators for prognosis of sarcoma patients.

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