Dataset Information

Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) accounts for a significant proportion of liver cancer, which has become the second most common cause of cancer-related mortality worldwide. To investigate the potential mechanisms of invasion and progression of HCC, bioinformatics analysis and validation by qRT-PCR were performed. We found 237 differentially expressed genes (DEGs) including EGR1, FOS, and FOSB, which were three cancer-related transcription factors. Subsequently, we constructed TF-gene network and miRNA-TF-mRNA network based on data obtained from mRNA and miRNA expression profiles for analysis of HCC. We found that 42 key genes from the TF-gene network including EGR1, FOS, and FOSB were most enriched in the p53 signaling pathway. The qRT-PCR data confirmed that mRNA levels of EGR1, FOS, and FOSB all were decreased in HCC tissues. In addition, we confirmed that the mRNA levels of CCNB1, CCNB2, and CHEK1, three key markers of the p53 signaling pathway, were all increased in HCC tissues by bioinformatics analysis and qRT-PCR validation. Therefore, we speculated that miR-181a-5p, which was upregulated in HCC tissues, could regulate FOS and EGR1 to promote the invasion and progression of HCC by p53 signaling pathway. Overall, the study provides support for the possible mechanisms of progression in HCC.

SUBMITTER: Liu S

PROVIDER: S-EPMC6136478 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma.

Liu Shui S Yao Xiaoxiao X Zhang Dan D Sheng Jiyao J Wen Xin X Wang Qingyu Q Chen Gaoyang G Li Zhaoyan Z Du Zhenwu Z Zhang Xuewen X

BioMed research international 20180829

Hepatocellular carcinoma (HCC) accounts for a significant proportion of liver cancer, which has become the second most common cause of cancer-related mortality worldwide. To investigate the potential mechanisms of invasion and progression of HCC, bioinformatics analysis and validation by qRT-PCR were performed. We found 237 differentially expressed genes (DEGs) including EGR1, FOS, and FOSB, which were three cancer-related transcription factors. Subsequently, we constructed TF-gene network and m ...[more]

PMID: 30228980

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Project description:ObjectiveThe aim of the current research was to construct a miRNA-transcription factor (TF)-target gene regulatory network in order to investigate the mechanism underlying choriocarcinoma and to verify the network through the overexpression or silencing of hub miRNAs in vitro.Materials and methodsA mRNA expression dataset and two miRNA expression datasets were analysed to identify differentially expressed genes (DEGs) and miRNAs (DEMs) between normal cells and choriocarcinoma cells. The top 400 upregulated and downregulated DEGs were identified as candidate DEGs, which were then mapped to construct protein-protein interaction (PPI) networks and select hub genes. Moreover, the DGIdb database was utilized to select candidate drugs for hub genes. Moreover, DEM target genes were predicted through the miRWalk2.0 database and overlaid with candidate DEGs to identify the differentially expressed target genes (DETGs). Furthermore, we established miRNA-TF-target gene regulatory networks and performed functional enrichment analysis of hub DEMs. Finally, we transfected mimics or inhibitors of hub DEMs into choriocarcinoma cells and assessed cell proliferation and migration to verify the vital role of hub DEMs in choriocarcinoma.ResultsA total of 140 DEMs and 400 candidate DEGs were screened from choriocarcinoma cells and normal cells. A PPI network of 400 candidate DEGs was established. Twenty-nine hub genes and 99 associated small molecules were identified to provide potential target drugs for choriocarcinoma treatment. We obtained 70 DETGs of DEMs derived from the intersection between predicted miRNA target genes and candidate DEGs. Subsequently, 3 hub DEMs were selected, and miRNA-TF-target gene regulatory networks containing 4 TFs, 3 TFs and 3 TFs for each network were constructed. The RT-PCR results confirmed that miR-29b-3p was highly expressed and that miR-519c-3p and miR-520a-5p were expressed at low levels in choriocarcinoma cells. The overexpression or silencing results suggested that 3 dysregulated hub DEMs jointly accelerated the proliferation and migration of choriocarcinoma.ConclusionAssociation of miRNA-TF-target gene regulatory networks may help us explore the underlying mechanism and provide potential targets for the diagnosis and treatment of choriocarcinoma.

Project description:BackgroundAbnormal miRNA and mRNA expression and dysregulated immune microenvironment have been found to frequently induce the progression of hepatocellular carcinoma (HCC) in recent reports. In particular, the immune-related competing endogenous RNAs (ceRNA) mechanism plays a crucial role in HCC progression. However, the underlying mechanisms remain unclear.MethodsDifferentially expressed immune-related genes were obtained from the Immport, GEO, and TCGA databases. The mRNA and protein expression levels in HCC tissues and adjacent normal tissues were confirmed, and we further investigated the methylation levels of these biomarkers to explore their function. Then, the TIMER and TISCH databases were used to assess the relationship between immune infiltration and hub genes. Survival analysis and univariate and multivariate Cox models were used to evaluate the association between hub genes and HCC diagnosis. Hub gene expression was experimentally validated in six HCC cell lines and 15 HCC samples using qRT-PCR and immunohistochemistry. The hub genes were uploaded to DSigDB for drug prediction enrichment analysis.ResultsWe identified that patients with abnormal miRNAs (hsa-miR-125b-5p and hsa-miR-21-5p) and their targeted genes (NTF3, PSMD14, CD320, and SORT1) had a worse prognosis. Methylation analysis of miRNA-targeted genes suggested that alteration of methylation levels is also a factor in the induction of tumorigenesis. We also found that the development of HCC progression caused by miRNA-mRNA interactions may be closely correlated with the infiltration of immunocytes. Moreover, the GSEA, GO, and KEGG analysis suggested that several common immune-related biological processes and pathways were related to miRNA-targeted genes. The results of qRT-PCR, immunohistochemistry, and western blotting were consistent with our bioinformatics results, suggesting that abnormal miRNAs and their targeted genes may affect HCC progression.ConclusionsBriefly, our study systematically describes the mechanisms of miRNA-mRNA interactions in HCC and predicts promising biomarkers that are associated with immune filtration for HCC progression.

Project description:PurposeNasopharyngeal carcinoma (NPC) is one of the most common malignant tumors of the head and neck. This study aimed to investigate the crucial genes and regulatory networks involved in the carcinogenesis of NPC using a bioinformatics approach.MethodsFive mRNA and two miRNA expression datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and miRNAs (DEMs) between NPC and normal samples were analyzed using R software. The WebGestalt tool was used for functional enrichment analysis, and protein-protein interaction (PPI) network analysis of DEGs was performed using STRING database. Transcription factors (TFs) were predicted using TRRUST and Transcriptional Regulatory Element Database (TRED). Kinases were identified using X2Kgui. The miRNAs of DEGs were predicted using miRWalk database. A kinase-TF-mRNA-miRNA integrated network was constructed, and hub nodes were selected. The hub genes were validated using NPC datasets from the GEO and Oncomine databases. Finally, candidate small-molecule agents were predicted using CMap.ResultsA total of 122 DEGs and 44 DEMs were identified. DEGs were associated with the immune response, leukocyte activation, endoplasmic reticulum stress in GO analysis, and the NF-κB signaling pathway in KEGG analysis. Four significant modules were identified using PPI network analysis. Subsequently, 26 TFs, 73 kinases, and 2499 miRNAs were predicted. The predicted miRNAs were cross-referenced with DEMs, and seven overlapping miRNAs were selected. In the kinase-TF-mRNA-miRNA integrated network, eight genes (PTGS2, FN1, MMP1, PLAU, MMP3, CD19, BMP2, and PIGR) were identified as hub genes. Hub genes were validated with consistent results, indicating the reliability of our findings. Finally, six candidate small-molecule agents (phenoxybenzamine, luteolin, thioguanosine, reserpine, blebbistatin, and camptothecin) were predicted.ConclusionWe identified DEGs and an NPC regulatory network involving kinases, TFs, mRNAs, and miRNAs, which might provide promising insight into the pathogenesis, treatment, and prognosis of NPC.

Project description:OBJECTIVE:Colorectal cancer (CRC) is an extremely common gastrointestinal malignancy. The present study aimed to identify microRNAs (miRNAs) and transcription factors (TFs) associated with tumor development. METHODS:Three miRNA profile datasets were integrated and analyzed to elucidate the potential key candidate miRNAs in CRC. The starBase database was used to identify the potential targets of common differentially expressed miRNAs (DEMs). Transcriptional Regulatory Element Database and Transcriptional Regulatory Relationships Unraveled by Sentence-based Text databases were used to identify cancer-related TFs and the TF-regulated target genes. Functional and pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integration Discovery (DAVID) database, and the miRNA-TF-gene networks were constructed by Cytoscape. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to detect the expression of genes and miRNAs. RESULTS:In total, 14 DEMs were found in CRC. By bioinformatics analysis, 5 DEMs (miR-145, miR-497, miR-30a, miR-31, and miR-20a) and 8 TFs (ELK4 (ETS-family transcription factor), myeloblastosis proto-oncogene like (MYBL)1, MYBL2, CEBPA, PPARA, PPARD, PPARG, and endothelial PAS domain protein (EPAS1)) appeared to be associated with CRC and were therefore used to construct miRNA-TF-gene networks. From the networks, we found that miR-20a might play the most important role as an miRNA in the networks. By qRT-PCR, we demonstrated that miR-20a was significantly upregulated in CRC tissues. We also performed qRT-PCR to identify the expression of miR-20a-related TFs (PPARA, PPARD, PPARG, EPAS1). Three of them, PPARA, PPARG, and EPAS1, were downregulated in CRC tissues, with statistically significant differences, while the downregulation of PPARD in CRC tissues was not significantly different. Pathway enrichment analyses indicated that the phosphoinositide 3-kinase (PI3K)-Akt signaling pathway was the most significantly enriched pathway. Two main elements of the PI3K-Akt signaling pathway, phosphatase and tensin homolog deleted on chromosome 10 and B-cell lymphoma 2-associated agonist of cell death, were demonstrated to be downregulated in CRC. CONCLUSION:The present study identified hub miRNAs and miRNA-related TF regulatory networks in CRC, which might be potential targets for the diagnosis and treatment of CRC.

Project description:BackgroundMacrophage play a crucial role in regulating tumor progression. This study intended to investigate the circular RNA (circRNA) regulatory network associated with macrophage infiltration in hepatocellular carcinoma (HCC).MethodsThe immune cell fractions of HCC from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium were calculated by Estimation of the Proportion of Immune and Cancer cells algorithm. The differentially expressed mRNAs (DEmRNAs), microRNAs (DEmiRNAs) and circRNAs (DEcircRNAs) were identified from HCC and adjacent non-tumor cases of TCGA or Gene Expression Omnibus database. The DEmRNAs related to macrophage were selected by weighted gene co-expression network analysis and then utilized to generate the circRNA-miRNA-mRNA network. A hub circRNA regulatory network was established based on the co-expressed DEmiRNAs and DEmRNAs owning contrary correlation with the clinical characteristics, survival and macrophage infiltration level. A gene signature based on the DEmRNAs in hub network was also generated for further evaluation. The circRNA binding bite for miRNA was detected by luciferase assay.ResultsHigh macrophage fraction predicted good survival for HCC. A circRNA-miRNA-mRNA network was constructed by 27 macrophage related DEmRNAs, 21 DEmiRNAs, and 15 DEcircRNAs. Among this network, the expression of hsa-miR-139-5p was negatively correlated with CDCA8, KPNA2, PRC1 or TOP2A. Hsa-miR-139-5p low or targeted DEmRNA high expression was associated with low macrophage infiltration, high grade, advanced stage and poor prognosis of HCC. Additionally, the risk score generated by 4-DEmRNA signature could reflect the macrophage infiltration status and function as an independent prognostic factor for HCC. Finally, hsa_circ_0007456 acting on hsa-miR-139-5p related network was viewed as the hub circRNA regulatory network. Taken together, some circRNA regulatory networks may be associated with macrophage infiltration, which provides clues for mechanism study and therapeutic strategies of HCC.

Project description:Background: In vitro induction of spermatogonial stem cells (SSCs) from embryonic stem cells (ESCs) provides a promising tool for the treatment of male infertility. A variety of molecules are involved in this complex process, which needs to be further clarified. Undoubtedly, the increased knowledge of SSC formation will be beneficial to facilitate the currently complex induction process. Methods: Based on ATAC-seq, DNase-seq, RNA-seq, and microarray data from GEO datasets, chromatin property data (ATAC-seq, DNase-seq) and gene expression data (RNA-seq, microarray data) were combined to search for SSC-specific transcription factors (TFs) and hub SSC-specific genes by using the WGCNA method. Then, we applied RNA-seq and microarray data screening for key SSC-specific TFs and constructed key SSC-specific TF-mediated gene regulatory networks (GRNs) using ChIP-seq data. Results: First, after analysis of the ATAC-seq and DNase-seq data of mouse ESCs, primordial germ cells (PGCs), and SSCs, 33 SSC-specific TFs and 958 targeting genes were obtained. RNA-seq and WGCNA revealed that the key modules (turquoise and red) were the most significantly related to 958 SSC-specific genes, and a total of 10 hub SSC-specific genes were identified. Next, when compared with the cell-specific TFs in human ESCs, PGCs, and SSCs, we obtained five overlapping SSC-specific TF motifs, including the NF1 family TF motifs (NFIA, NFIB, NFIC, and NFIX), GRE, Fox:Ebox, PGR, and ARE. Among these, Nfib and Nfix exhibited abnormally high expression levels relative to mouse ESCs and PGCs. Moreover, Nfib and Nfix were upregulated in the testis sample with impaired spermatogenesis when compared with the normal group. Finally, the ChIP-seq data results showed that NFIB most likely targeted the hub SSC-specific genes of the turquoise module (Rpl36al, Rps27, Rps21, Nedd8, and Sec61b) and the red module (Vcam1 and Ccl2). Conclusion: Our findings preliminarily revealed cell-specific TFs and cell-specific TF-mediated GRNs in the process of SSC formation. The hub SSC-specific genes and the key SSC-specific TFs were identified and suggested complex network regulation, which may play key roles in optimizing the induction efficiency of the differentiation of ESCs into SSCs in vitro.

Dataset Information

Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma.

Publications

Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma.

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