Dataset Information

Bioinformatics-based analysis of the lncRNA-miRNA-mRNA and TF regulatory networks reveals functional genes in esophageal squamous cell carcinoma.

ABSTRACT: Esophageal squamous cell carcinoma (ESCC) is a 5-year survival rate unsatisfied malignancies. The study aimed to identify the novel diagnostic and prognostic targets for ESCC. Expression profiling (GSE89102, GSE97051, and GSE59973) data were downloaded from the GEO database. Then, differentially expressed (DE) lncRNAs, DEmiRNAs, and genes (DEGs) with P-values < 0.05, and |log2FC| ? 2, were identified using GEO2R. Functional enrichment analysis of miRNA-related mRNAs and lncRNA co-expressed mRNA was performed. LncRNA-miRNA-mRNA, protein-protein interaction of miRNA-related mRNAs and DEGs, co-expression, and transcription factors-hub genes network were constructed. The transcriptional data, the diagnostic and prognostic value of hub genes were estimated with ONCOMINE, receiver operating characteristic (ROC) analyses, and Kaplan-Meier plotter, respectively. Also, the expressions of hub genes were assessed through qPCR and Western blot assays. The CDK1, VEGFA, PRDM10, RUNX1, CDK6, HSP90AA1, MYC, EGR1, and SOX2 used as hub genes. And among them, PRDM10, RUNX1, and CDK6 predicted worse overall survival (OS) in ESCC patients. Our results showed that the hub genes were significantly up-regulated in ESCA primary tumor tissues and cell lines, and exhibited excellent diagnostic efficiency. These results suggest that the hub genes may server as potential targets for the diagnosis and treatment of ESCC.

SUBMITTER: Ye Z

PROVIDER: S-EPMC7441485 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Bioinformatics-based analysis of the lncRNA-miRNA-mRNA and TF regulatory networks reveals functional genes in esophageal squamous cell carcinoma.

Ye Zhimin Z Fang Jun J Wang Zhun Z Wang Lei L Li Bin B Liu Tongxin T Wang Yuezhen Y Hua Jianfeng J Wang FangZheng F Fu Zhenfu Z

Bioscience reports 20200801 8

Esophageal squamous cell carcinoma (ESCC) is a 5-year survival rate unsatisfied malignancies. The study aimed to identify the novel diagnostic and prognostic targets for ESCC. Expression profiling (GSE89102, GSE97051, and GSE59973) data were downloaded from the GEO database. Then, differentially expressed (DE) lncRNAs, DEmiRNAs, and genes (DEGs) with P-values < 0.05, and |log2FC| ≥ 2, were identified using GEO2R. Functional enrichment analysis of miRNA-related mRNAs and lncRNA co-expressed mRNA ...[more]

PMID: 32662828

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Project description:PURPOSE:Prostate cancer (PCa) causes a common male urinary system malignant tumour, and the molecular mechanisms of PCa are related to the abnormal regulation of various signalling pathways. An increasing number of studies have suggested that mRNAs, miRNAs, lncRNAs, and TFs could play important roles in various biological processes that are associated with cancer pathogenesis. This study aims to reveal functional genes and investigate the underlying molecular mechanisms of PCa with bioinformatics. METHODS:Original gene expression profiles were obtained from the GSE64318 and GSE46602 datasets in the Gene Expression Omnibus (GEO). We conducted differential screens of the expression of genes (DEGs) between two groups using the online tool GEO2R based on the R software limma package. Interactions between differentially expressed miRNAs, mRNAs and lncRNAs were predicted and merged with the target genes. Co-expression of miRNAs, lncRNAs and mRNAs was selected to construct mRNA-miRNA-lncRNA interaction networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for the DEGs. Protein-protein interaction (PPI) networks were constructed, and transcription factors were annotated. Expression of hub genes in the TCGA datasets was verified to improve the reliability of our analysis. RESULTS:The results demonstrate that 60 miRNAs, 1578 mRNAs and 61 lncRNAs were differentially expressed in PCa. The mRNA-miRNA-lncRNA networks were composed of 5 miRNA nodes, 13 lncRNA nodes, and 45 mRNA nodes. The DEGs were mainly enriched in the nuclei and cytoplasm and were involved in the regulation of transcription, related to sequence-specific DNA binding, and participated in the regulation of the PI3K-Akt signalling pathway. These pathways are related to cancer and focal adhesion signalling pathways. Furthermore, we found that 5 miRNAs, 6 lncRNAs, 6 mRNAs and 2 TFs play important regulatory roles in the interaction network. The expression levels of EGFR, VEGFA, PIK3R1, DLG4, TGFBR1 and KIT were significantly different between PCa and normal prostate tissue. CONCLUSION:Based on the current study, large-scale effects of interrelated mRNAs, miRNAs, lncRNAs, and TFs established a new prostate cancer network. In addition, we conducted functional module analysis within the network. In conclusion, this study provides new insight for exploration of the molecular mechanisms of PCa and valuable clues for further research into the process of tumourigenesis and its development in PCa.

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Project description:Uterine fibroids (UF) are the most common benign gynecologic tumors and lead to heavy menstrual bleeding, severe anemia, abdominal pain, and infertility, which seriously harm a women's health. Unfortunately, the regulatory mechanisms of UF have not been elucidated. Recent studies have demonstrated that miRNAs play a vital role in the development of uterine fibroids. As a high-throughput technology, microarray is utilized to identify differentially expressed genes (DEGs) and miRNAs (DEMs) between UF and myometrium. We identified 373 candidate DEGs and the top 100 DEMs. Function enrichment analysis showed that candidate DEGs were mainly enriched in biological adhesion, locomotion and cell migration, and collagen-containing extracellular matrix. Subsequently, protein-protein interaction (PPI) networks are constructed to analyze the functional interaction between DEGs and screen hub DEGs. Subsequently, the expression levels of hub DEGs were validated by real-time PCR of clinical UF samples. The DGIdb database was used to select candidate drugs for hub DEGs. Molecular docking was applied to test the affinity between proteins and drugs. Furthermore, target genes for 100 candidate DEMs were predicted by miRwalk3.0. After overlapping with 373 candidate DEGs, 28 differentially expressed target genes (DEGTs) were obtained. A miRNA-mRNA network was constructed to investigate the interactions between miRNA and mRNA. Additionally, two miRNAs (hsa-miR-381-3p and hsa-miR-181b-5p) were identified as hub DEMs and validated through RT-PCR. In order to better elucidate the pathogenesis of UF and the synergistic effect between miRNA and transcription factor (TF), we constructed a miRNA-TF-mRNA regulatory network. Meanwhile, in vitro results suggested that dysregulated hub DEMs were associated with the proliferation, migration, and apoptosis of UF cells. Our findings provided a novel horizon to reveal the internal mechanism and novel targets for the diagnosis and treatment of UF.

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Dataset Information

Bioinformatics-based analysis of the lncRNA-miRNA-mRNA and TF regulatory networks reveals functional genes in esophageal squamous cell carcinoma.

Publications

Bioinformatics-based analysis of the lncRNA-miRNA-mRNA and TF regulatory networks reveals functional genes in esophageal squamous cell carcinoma.

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