FAM201A, a Long Noncoding RNA Potentially Associated With Atrial Fibrillation Identified by ceRNA Network Analyses and WGCNA

Abstract Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia that contributes to various complications. However, little is known about lncRNAs associated with AF susceptibility. In the present study, we aim to identify lncRNAs involved in pathogenesis of AF based on competing endogenous RNA (ceRNA) network analyses and weighted gene co-expression network analysis (WGCNA).Methods: Two lncRNA and mRNA microarray datasets GSE41177 and GSE79768 were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed lncRNAs (DElncRNAs), mRNAs (DEmRNAs) between AF patients and patients with sinus rhythm (SR) were identified from dataset GSE41177. Then, those DElncRNAs associated target miRNAs were predicted. The ceRNA network was constructed based on DElncRNAs, predicted miRNAs and DEmRNAs. To validate the role of AF-related lncRNAs, all lncRNAs form dataset GSE79768 were selected to perform WGCNA. LncRNA modules relevant to AF were identified. Crucial lncRNAs in the module that was most relevant to AF were screened according to the criteria of | Gene significance (GS)| > 0.6 and |Module membership (MM)| > 0.5. Results: A total of 18 DElncRNAs and 350 DEmRNAs were identified between AF patients and SR patients. The final ceRNA network contained 5 lncRNAs, 10 miRNAs, and 21 mRNAs. According to the ceRNA theory, combined with the comparative toxicogenomics database (CTD) database, the ceRNA axis FAM201A-miR-33a-3p-RAC3 was considered associated with AF susceptibility. By WGCNA, the blue module was detected most highly relevant with AF. The lncRNA FAM201A was proved in the blue module and highly related to AF. Conclusions: These results demonstrated that FAM201A might have great potential for susceptibility of AF based on ceRNA network analyses and WGCNA. FAM201A may function, at least partly, as ceRNA to regulate RAC3 in AF susceptibility.

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Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer

10.21203/rs.2.17512/v1 ◽

2019 ◽

Author(s):

ChenChen Yang ◽

Aifeng Gong

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Differentially Expressed Genes ◽

Kegg Pathway ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Mrna Levels ◽

Pcr Assay ◽

Microarray Datasets ◽

Geo Database

Abstract Background Gastric cancer (GC) has a high mortality rate in cancer-related deaths worldwide. Here, we identified several vital candidate genes related to gastric cancer development and revealed the potential pathogenic mechanisms using integrated bioinformatics analysis.Methods Two microarray datasets from Gene Expression Omnibus (GEO) database integrated. Limma package was used to analyze differentially expressed genes (DEGs) between GC and matched normal specimens. DAVID was utilized to conduct Gene ontology (GO) and KEGG enrichment analysis. The relative expression of OLFM4, IGF2BP3, CLDN1and MMP1were analyzed based on TCGA database provided by UALCAN. Western blot and quantitative real time PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1and MMP1 in GC tissues and cell lines, respectively.Results We downloaded the expression profiles of GSE103236 and GSE118897 from the Gene Expression Omnibus (GEO) database. Two integrated microarray datasets were used to obtain differentially expressed genes (DEGs), and bioinformatics methods were used for in-depth analysis. After gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analysis, we identified 61 DEGs in common, of which the expression of 34 genes were elevated and 27 genes were decreased. GO analysis displayed that the biological functions of DEGs mainly focused on negative regulation of growth, fatty acid binding, cellular response to zinc ion and calcium-independent cell-cell adhesion. KEGG pathway analysis demonstrated that these DEGs mainly related to the Wnt and tumor signaling pathway. Interestingly, we found 4 genes were most significantly upregulated in the DEGs, which were OLFM4, IGF2BP3, CLDN1 and MMP1.Then, we confirmed the upregulation of these genes in STAD based on sample types. In the final, western blot and qRT-PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines.Conclusion In our study, using integrated bioinformatics to screen DEGs in gastric cancer could benefit us for understanding the pathogenic mechanism underlying gastric cancer progression. Meanwhile, we also identified four significantly upregulated genes in DEGs from both two datasets, which might be used as the biomarkers for early diagnosis and prevention of gastric cancer.

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Integrated analysis of cancer stem cells-associated lncRNA-miRNA-mRNA network for ovarian cancer via microarray and Gene Expression Omnibus database

10.21203/rs.3.rs-106454/v1 ◽

2020 ◽

Author(s):

Zheng Li ◽

Zhijiao Wang ◽

Yingying Zhou

Keyword(s):

Gene Expression ◽

Ovarian Cancer ◽

Stem Cells ◽

Stem Cell ◽

Cancer Stem Cells ◽

Signaling Pathway ◽

Gene Expression Omnibus ◽

Integrated Analysis ◽

Cerna Network ◽

Geo Database

Abstract Background: Cancer stem cells (CSCs) are associated with the recurrence, metastasis and chemoresistance of epithelial ovarian cancer. Competing endogenous RNAs (CeRNAs) play an important role in maintenance of ovarian cancer stem cell-like cells (OCSCs) characteristics. To construct a ceRNA regulatory network for OCSCs, microarray technology and Gene Expression Omnibus (GEO) database had been used. Human serous epithelial ovarian carcinoma cell line COC1 cells were treated with cisplatin and paclitaxel then maintained in stem cell conditions for 6 days to obtain CD117+/CD133+ cells (OCSCs). We identified the differentially expressed miRNAs (DEMs), lncRNA (DELs) and mRNA (DEGs) between OCSCs and COC1 by microarray and combined them with representative microarray profiles in GEO Database. Results: According to the combination, 28 DEMs were identified at first, and 452 DEGs were obtained combining with the predicted targets of these miRNAs and our mRNA microarray results. Up-regulated DEGs of them were significantly enriched in ‘p53 signaling pathway’, ‘FoxO signaling pathway’ and ‘MicroRNAs in cancer’, whereas down-regulated DEGs were significantly enriched in ‘Adherens junction’ and ‘Hepatitis C’ pathway. 29 transcripts of 17 lncRNAs should be the ceRNAs of 10 of these miRNAs according to bioinformatics predicted results and lncRNA microarray. Finally, we obtained ceRNA network with 10 DEMs, 21 DEGs, and 25 transcripts of 13 DELs which should play an important role in maintenance of OCSCs characteristics. LINC00665-miR-146a-5p-NRP2 should be one of ceRNA pathways of the network. The qPCR results indicated that the expression of miR-146a-5p in OCSCs was lower than that in COC1, and LINC00665 shows the opposite trend. These results were consistent with the results of microarray partially. When LINC00665 expression was up-regulated in COC1, the cell proliferation ability enhanced, apoptosis rate reduced, and the percentage of G2/M phase cells increased. Conclusions: The ceRNA network we constructed may be involved in the stem cell characteristics maintenance of OCSCs and provide directions for further OCSCs research in the future, so as to assist the development and treatment of ovarian cancer.

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Construction and Investigation of an LINC00284-Associated Regulatory Network in Serous Ovarian Carcinoma

Disease Markers ◽

10.1155/2020/9696285 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Shasha Wang ◽

Lu Zhang ◽

Lin Tao ◽

Lijuan Pang ◽

Ruiting Fu ◽

...

Keyword(s):

Ovarian Carcinoma ◽

Expression Profiles ◽

Ovarian Tissue ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Prognostic Scores ◽

Qrt Pcr ◽

Cerna Network ◽

Serous Ovarian Carcinoma ◽

Geo Database

The low survival rate associated with serous ovarian carcinoma (SOC) is largely due to the lack of relevant molecular markers for early detection and therapy. Increasing experimental evidence has demonstrated that long noncoding RNAs (lncRNAs) are involved in cancer initiation and development, and a competitive endogenous RNA (ceRNA) hypothesis has been formulated. Therefore, the characterization of new lncRNA and lncRNA-related networks is crucial for early diagnosis and targeted therapy of SOC. Data on lncRNAs, mRNAs, and miRNAs with differential expression in SOC, compared to normal ovarian tissue, were obtained from the Gene Expression Omnibus (GEO) database. Data on lncRNA expression and clinical data in SOC were obtained from The Cancer Genome Atlas (TCGA). lncRNA-miRNA interactions were predicted by the miRBase database. Different online tools, i.e., TargetScan, RNA22, miRmap, microT, miRanda, StarBase, and PicTar, were cooperatively utilized to predict the mRNAs targeted by miRNAs. The plugin of BiNGO in Cytoscape and KOBAS 3.0 were used to conduct the functional and pathway enrichment analyses. The lncRNA, miRNAs, and mRNAs identified to be expressed at statistically significant and different levels between SOC and healthy fallopian tube tissues were further validated using qRT-PCR. A total of 4 lncRNAs (LINC00284, HAGLR, HCAT158, and BLACAT1) and 111 mRNAs were found to be upregulated in SOC tissues compared to normal tissues, based on the GEO database. LINC00284 was found to be highly expressed in SOC, in association with the upregulation of the transcription factor SOX9. The high LINC00284 expression was associated with poor prognosis and proved to be an independent risk factor in patients with SOC, based on TCGA database. The qRT-PCR validation results closely recapitulated the expression profiles and prognostic scores of the aforementioned bioinformatic analyses. The LINC00284-related ceRNA network was found to be associated with SOC carcinogenesis by biofunctional analysis. In conclusion, the LINC00284-related ceRNA network may provide valuable information on the mechanisms of SOC initiation and progression. Importantly, LINC00284 proved to be a new potential prognostic biomarker for SOC.

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miR-628-5p promotes growth and migration of osteosarcoma by targeting IFI44L

Biochemistry and Cell Biology ◽

10.1139/bcb-2019-0001 ◽

2020 ◽

Vol 98 (2) ◽

pp. 99-105 ◽

Cited By ~ 1

Author(s):

Ju-Yong Wang ◽

Ju-Qiang Wang ◽

Shi-Bao Lu

Keyword(s):

Untranslated Region ◽

Poor Prognosis ◽

Luciferase Activity ◽

Gene Expression Omnibus ◽

Migration And Invasion ◽

Activity Assay ◽

Luciferase Activity Assay ◽

And Migration ◽

Geo Database

This study investigated the role of miR-628-5p and interferon-induced protein 44-like (IFI44L) in osteosarcoma (OS) and determined whether miR-628-5p modulated OS growth by regulating IFI44L. Based on the data downloaded from Gene Expression Omnibus (GEO) database, we revealed that the expression of IFI44L was downregulated in OS and low expression of IFI44L was correlated with better prognosis of patients with OS. Biological prediction of its upstream regulatory miRNAs on the miRWalk website found that miR-628-5p is a possible upstream regulatory miRNA of IFI44L. Luciferase activity assay demonstrated that miR-628-5p could bind to the 3′ untranslated region (UTR) of IFI44L, which proved the above prediction. The expression of miR-628-5p is upregulated in OS and high expression of miR-628-5p is correlated with poor prognosis of patients with OS. The results of RT-qPCR showed that the expression of miR-628-5p in MG-63, U2OS, Saos-2, and SW1353 cells was significantly higher than that in the hFOB1.19 cells. Downregulation of miR-628-5p by miR-628-5p inhibitor significantly inhibited the proliferation, migration, and invasion of MG-63 cells. By rescue assay, we found that knockdown of IFI44L rescued the proliferation and motility of miR-628-5p depleted MG-63 cells. Collectively, our present data illustrated that miR-628-5p promoted the growth and motility of OS at least partly by targeting IFI44L. Moreover, miR-628-5p and IFI44L might be proposed as promising biomarkers in OS diagnosis and treatment.

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Mechanism and Role of the Neuropeptide LGI1 Receptor ADAM23 in Regulating Biomarkers of Ferroptosis and Progression of Esophageal Cancer

Disease Markers ◽

10.1155/2021/9227897 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Chen Chen ◽

Jun Zhao ◽

Jing-ni Liu ◽

Chenyu Sun

Keyword(s):

Esophageal Cancer ◽

Cell Lines ◽

Noncoding Rna ◽

The Cancer Genome Atlas ◽

Cell Counting ◽

Luciferase Reporter ◽

Cerna Network ◽

And Migration ◽

Proliferation And Migration

Background. According to recent studies, ferroptosis is closely related to the efficacy and prognosis of tumour treatment. However, the role of ferroptosis in esophageal squamous cell carcinoma (ESCC) has not been explored comprehensively. Materials and Methods. The esophageal cancer (EC) transcriptome data was downloaded from The Cancer Genome Atlas (TCGA), then analyzed, to obtain the differentially expressed messenger RNA (mRNA), microRNA (miRNA), and long noncoding RNA (lncRNA) between groups with the low and high Ferroptosis Potential Index (FPI) and construct a ferroptosis-associated ceRNA network. In addition, the expression of ARHGEF26-AS1 and miR-372-3p in ESCC cell lines was assessed, and the appropriate cell lines were selected. The interaction between ARHGEF26-AS1, miR-372-3p, and ADAM23 was also determined through a dual-luciferase reporter assay. Moreover, the Western blot, Cell Counting Kit-8 (CCK-8), wound healing, cell viability, and cell death assays were conducted to establish the biological functions of the ARHGEF26-AS1/miR-372-3p/ADAM23 pathway in ESCCs. Results. An FPI scoring model reflecting the activity of the ferroptosis pathway was constructed, and a ferroptosis-associated ceRNA network was established. The findings revealed that low expression of ADAM23 and ARHGEF26-AS1 as well as high expression of miR-372-3p was associated with poor prognosis and a lower FPI score in EC patients. Functionally, overexpression of ADAM23 and ARHGEF26-AS1 and the miR-372-3p inhibitor not only promoted ferroptosis in ESCC cells in vitro but also inhibited the proliferation and migration of cells. Mechanistically, ARHGEF26-AS1 upregulated the expression of ADAM23 by competitively binding to miR-372-3p. Conclusions. The study showed that the lncRNA, ARHGEF26-AS1 acts as a miR-372-3p sponge that regulates the neuropeptide LGI1 receptor ADAM23 expression. This in turn not only inhibits the proliferation and migration of ESCC cells but also upregulates the ferroptosis pathway. A neuropeptide-related ferroptosis regulatory pathway was identified in this study.

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Exploring the Mechanism of Quercetin for the Treatment of Atrial Fibrillation by GEO Gene Chip Combined with Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-1229124/v1 ◽

2022 ◽

Author(s):

Xin Tan ◽

Wei Xian ◽

Xiaorong Li ◽

Yongfeng Chen ◽

Jiayi Geng ◽

...

Keyword(s):

Atrial Fibrillation ◽

Molecular Docking ◽

Signaling Pathway ◽

Target Prediction ◽

Mapk Signaling ◽

Differentially Expressed ◽

Network Pharmacology ◽

Therapeutic Drug ◽

Geo Database

Abstract Atrial fibrillation (AF) is a common atrial arrhythmia for which there is no specific therapeutic drug. Quercetin (Que) has been used to treat cardiovascular diseases such as arrhythmias. In this study, we explored the mechanism of action of Que in AF using network pharmacology and molecular docking. The chemical structure of Que was obtained from Pubchem. TCMSP, Swiss Target Prediction, Drugbank, STITCH, Binding DB, Pharmmapper, CTD, GeneCards, DISGENET and TTD were used to obtain drug component targets and AF-related genes, and extract AF and normal tissue by GEO database differentially expressed genes by GEO database. The top targets were IL6, VEGFA, JUN, MMP9 and EGFR, and Que for AF treatment might involve the lipid and atherosclerosis pathway, the role of AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway and IL-17 signaling pathway. In addition, molecular docking showed that Que binds strongly to key targets and is differentially expressed in AF. This study systematically elucidated the key targets of Que treatment for AF and the specific mechanisms, providing a new direction for further basic experimental exploration and clinical treatment.

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Identification of Functional lncRNAs Associated With Ovarian Endometriosis Based on a ceRNA Network

Frontiers in Genetics ◽

10.3389/fgene.2021.534054 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jian Bai ◽

Bo Wang ◽

Tian Wang ◽

Wu Ren

Keyword(s):

Gene Expression Omnibus ◽

Reproductive Age ◽

Differentially Expressed ◽

Rna Seq ◽

Ovarian Endometriosis ◽

Diagnostic Biomarkers ◽

Cerna Network ◽

Competing Endogenous Rnas ◽

Gynecological Disease ◽

Geo Database

BackgroundEndometriosis is a common gynecological disease affecting women of reproductive age; however, the mechanisms underlying this condition are not fully clear. The aim of this study was to identify functional long non-coding RNAs (lncRNAs) associated with ovarian endometriosis for potential use as biomarkers and therapeutic targets.MethodsRNA-seq profiles of paired ectopic (EC) and eutopic (EU) endometrial samples from patients with ovarian endometriosis were downloaded from the publicly available Gene Expression Omnibus (GEO) database. Bioinformatics algorithms were used to construct a network of ovarian endometriosis-related competing endogenous RNAs (ceRNAs) and to detect functional lncRNAs.ResultsA total of 4,213 mRNAs, 1,474 lncRNAs, and 221 miRNAs were identified as being differentially expressed between EC and EU samples, and an ovarian endometriosis-related ceRNA network was constructed through analysis of these differentially expressed RNAs. H19 and GS1-358P8.4 were identified as key ovarian endometriosis-related lncRNAs through topological feature analysis, and RP11-96D1.10 was identified using a random walk with restart algorithm.ConclusionBased on bioinformatics analysis of a ceRNA network, we identified the lncRNAs H19, GS1-358P8.4, and RP11-96D1.10 as being strongly associated with ovarian endometriosis. These three lncRNAs hold potential as targets for medical therapy and as diagnostic biomarkers. Further studies are needed to elucidate the detailed biological function of these lncRNAs in the pathogenesis of endometriosis.

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Identification of Functional Genes in Pterygium Based on Bioinformatics Analysis

BioMed Research International ◽

10.1155/2020/2383516 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Yuting Xu ◽

Chen Qiao ◽

Siying He ◽

Chen Lu ◽

Shiqi Dong ◽

...

Keyword(s):

Protein Interaction ◽

Growth Regulation ◽

Interaction Network ◽

Gene Expression Omnibus ◽

Node Degree ◽

Hub Genes ◽

Protein Protein Interaction ◽

Cerna Network ◽

R Programming ◽

Geo Database

Purpose. The competing endogenous RNA (ceRNA) network regulatory has been investigated in the occurrence and development of many diseases. This research aimed at identifying the key RNAs of ceRNA network in pterygium and exploring the underlying molecular mechanism. Methods. Differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs were obtained from the Gene Expression Omnibus (GEO) database and analyzed with the R programming language. LncRNA and miRNA expressions were extracted and pooled by the GEO database and compared with those in published literature. The lncRNA-miRNA-mRNA network was constructed of selected lncRNAs, miRNAs, and mRNAs. Metascape was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses on mRNAs of the ceRNA network and to perform Protein-Protein Interaction (PPI) Network analysis on the String website to find candidate hub genes. The Comparative Toxicogenomic Database (CTD) was used to find hub genes closely related to pterygium. The differential expressions of hub genes were verified using the reverse transcription-real-time fluorescent quantitative PCR (RT-qPCR). Result. There were 8 lncRNAs, 12 miRNAs, and 94 mRNAs filtered to construct the primary ceRNA network. A key lncRNA LIN00472 ranking the top 1 node degree was selected to reconstruct the LIN00472 network. The GO and KEGG pathway enrichment showed the mRNAs in ceRNA networks mainly involved in homophilic cell adhesion via plasma membrane adhesion molecules, developmental growth, regulation of neuron projection development, cell maturation, synapse assembly, central nervous system neuron differentiation, and PID FOXM1 PATHWAY. According to the Protein-Protein Interaction Network (PPI) analysis on mRNAs in LINC00472 network, 10 candidate hub genes were identified according to node degree ranking. Using the CTD database, we identified 8 hub genes closely related to pterygium; RT-qPCR verified 6 of them were highly expressed in pterygium. Conclusion. Our research found LINC00472 might regulate 8 hub miRNAs (miR-29b-3p, miR-183-5p, miR-138-5p, miR-211-5p, miR-221-3p, miR-218-5p, miR-642a-5p, miR-5000-3p) and 6 hub genes (CDH2, MYC, CCNB1, RELN, ERBB4, RB1) in the ceRNA network through mainly PID FOXM1 PATHWAY and play an important role in the development of pterygium.

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Identification and Validation of Glomerulotubular Crosstalk Genes Mediating IgA Nephropathy by Integrated Bioinformatics

10.21203/rs.3.rs-1154101/v1 ◽

2021 ◽

Author(s):

Yawen Bai ◽

Yajing Li ◽

Yali Xi ◽

Chunjie Ma

Keyword(s):

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Diagnostic Significance ◽

Function Enrichment Analysis ◽

Gene Modules ◽

Key Genes ◽

End Stage ◽

Microarray Datasets ◽

Geo Database ◽

Function Enrichment

Abstract BackgroundIgA nephropathy (IgAN), which has been reported as the most prevalent glomerulonephritis globally, is the major contributor to end-stage renal illness. This bioinformatics study aimed to explore glomeruli-tubulointerstitial crosstalk genes and dysregulated pathways relating to the pathogenesis of IgAN. MethodsThe microarray datasets from the Gene Expression Omnibus (GEO) database were searched. Weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) of both glomeruli and tubulointerstitial were conducted individually. The co-expression gene modules of tubulointerstitial and glomeruli were compared via gene function enrichment analysis. Subsequently, the crosstalk co-expression network was constructed via the STRING database and key genes were mined from the crosstalk network. Results583 DEGs and eight modules were identified in glomeruli samples, while 272 DEGs and four modules were in tubulointerstitial samples. There were 119 overlapping DEGs of the two groups. Among the distinctive modules, four modules in glomeruli and one module in tubulointerstitial were positively associated with IgAN. While four modules in glomeruli and two modules in tubulointerstitial were negatively associated with IgAN. The top ten key genes screened by CytoHubba were ITGAM, ALB, TYROBP, ITGB2, CYBB, HCK, CSF1R, LAPTM5, FN1and CTSS. The above genes were all validated using another two datasets, and all of the key genes demonstrated possible diagnostic significance. Conclusionshe crosstalk genes confirmed in this study may provide novel insight into the pathogenesis of IgAN. Immune-related pathways are associated with both glomerular and tubulointerstitial injuries in IgAN. The glomerulotubular crosstalk might perform a role in the pathogenesis of IgAN.

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Construction and Analysis of a circRNA-Mediated ceRNA Network in Lung Adenocarcinoma

10.21203/rs.3.rs-32720/v1 ◽

2020 ◽

Author(s):

Zhaojun Wang ◽

Haifeng Li ◽

Li Wei ◽

Junhang Zhang

Keyword(s):

Lung Adenocarcinoma ◽

Patient Survival ◽

Gene Prediction ◽

Differential Expression Analysis ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Circular Rnas ◽

Cerna Network ◽

Intersection Analysis ◽

Microarray Datasets

Abstract Background: Circular RNAs (circRNAs), a new class of regulatory noncoding RNAs, are involved in gene regulation and may play a role in cancer development. This study aimed to identify circRNAs involved in lung adenocarcinoma (LUAD) using bioinformatics analysis.Methods: CircRNA (GSE101684, GSE101586), miRNA (GSE135918), and mRNA (GSE130779) microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed circRNAs (DECs), miRNAs (DEMs), and mRNAs (DEGs) in LUAD. Circinteractome and StarBase were used to predict miRNAs and mRNAs, respectively. A circRNA-miRNA-mRNA-ceRNA network was constructed. Patient survival was analyzed using UALCAN, and a sub-network was established.Results: Hsa_circ_0072088 was identified as a differentially expressed (upregulated) circRNA in the two datasets. Intersection analysis identified hsa-miR-532-3p and hsa-miR-942 as the two miRNAs with the highest potential for binding to hsa_circ_0072088. Differential expression analysis and target gene prediction were performed to build a ceRNA network of hsa_circ_0072088 using Circinteractome/StarBase 3.0. Intersection analysis showed that TMEM52, IL24, POF1B, KIF1A, NHS, LBH, HIST2H2BE, ABCC3, PYCR1, CD79A, IGF2BP3, ANKRD17, GTSE1, MKI67, CLSPN, PLAU, LUC7L, MAGIX, GPATCH4, and ABAT were potential downstream mRNAs. The association between the expression level of 20 DEGs and LUAD patient survival was analyzed using UALCAN, which showed that IGF2BP3, MKI67, CD79A, and ABAT were related to patient survival.Conclusion: The circRNA hsa_circ_0072088, the miRNAs hsa-miR-532-3p and hsa-miR-942-5p, and the genes IGF2BP3, MKI67, CD79A, and ABAT may serve as prognostic markers in LUAD.

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