Interaction Network Of Target Genes Research Articles

Establishment and verification of potential biomarkers for cholangiocarcinoma.

Cholangiocarcinoma (CCA) is a malignancy arising from multiple locations along the biliary tree, which is still lacking effective diagnostic biomarkers. The present study aimed to provide a comprehensive differential gene expression profile for the disease. The differentially expressed genes (DEGs) for CCA were explored in-depth using a Gene Expression Omnibus (GEO) dataset, an internal cohort of clinical participants as well as in vitro experiments with the HUCCT1 cell line. Based on the GEO dataset, potential biomarker genes were proposed and the enriched biological processes as well as signaling pathways were further investigated. A protein-protein interaction network of target genes was established. In the clinical specimens, the functions of the primary candidate, FBJ murine osteosarcoma viral oncogene homolog B (FOSB), were evaluated by reverse transcription-quantitative (RT-q)PCR and western blot analysis. A Cell Counting Kit-8 (CCK-8) assay was used for a functional study on FOSB. The results indicated that, compared with non-tumor bile duct tissues, primary CCA samples had 676 differentially expressed genes, including 277 downregulated and 399 upregulated ones. Among these, HBD, FOSB, HBB, ITIH2, FCGBP, MT1JP, PIJR, SLC38A1, COL10A1 and MMP19 were determined to be the most significant DEGs. At the same time, upregulated genes were enriched in ‘vasculature development’ and ‘IL-17 signaling pathways’. Downregulated genes were enriched in ‘extracellular matrix progress’ and ‘glucuronate signaling pathway’. The patients with CCA displayed decreased levels of hemoglobin. Compared with paracancerous tissues, CCA cancerous tissues exhibited increased RNA and protein expression levels of FOSB according to RT-qPCR and western blot analysis, respectively. Furthermore, FOSB expression influenced the proliferation/viability of the CCA cell line HUCCT1. In conclusion, the present study suggested that the FOSB gene may serve as a primary biomarker candidate for CCA, providing a valuable reference for its clinical implementation.

Establishment of a 7-microRNA prognostic signature and identification of hub target genes in colorectal carcinoma.

BackgroundColorectal cancer (CRC) is a malignant tumor with high morbidity and mortality, but there is still no recognized prognostic prediction model to better predict and intervene its prognosis. Our aim is to establish a novel microRNA (miRNA) signature and identify hub target genes for simply and accurately predicting survival risk for CRC patients and to provide therapeutic targets.MethodsThe miRNA expression profiles along with clinical data of 512 CRC patients were downloaded from the Cancer Genome Atlas (TCGA) database and randomly divided into training set and validation set. The signature was generated from the training set after a series of Cox regression analyses, including least absolute shrinkage and selectionator operator (LASSO)-Cox regression, and verified in the test set and the whole set. Furthermore, the signature was compared with clinical risk factors. Interaction network of target genes of the seven micoRNAs was established. Functional enrichment analysis was performed to reveal the biological processes and pathways. GEPIA2 was used for prognostic analysis.ResultsA 7-micoRNA prognostic signature was generated from the training set with the areas under the receiver operating characteristic (ROC) curve (AUC) of 5-year survival rate was 0.889. Its performance was well verified both in the test set and the entire set by Kaplan-Meier analysis (P value <0.05). Further analysis demonstrated that the signature was an independent prognostic risk factor for CRC patients and its predictive ability was superior to age and tumor-node-metastasis (TNM) stage. Interaction network found two major gene modules, and they might be involved in the activation of PI3K-Akt-mTOR and p53 signaling pathways, which related to epidermal growth factor receptor (EGFR) resistance. The GEPIA2 revealed that CDKN1A, eIF4E and SNAI1 were associated with CRC prognosis.ConclusionsOur study demonstrated the potential of this novel 7-micoRNA signature to independently predict overall survival in patients with CRC and provided potential therapeutic targets.

The potential value of microRNA-145 for predicting prognosis in patients with ovarian cancer: A protocol for systematic review and meta-analysis.

Background:As an anticancer gene, microRNA-145 (miRNA-145) inhibits the growth, migration, and invasion of cancer cells, and inhibits tumorigenesis by targeting various genes that are abnormally expressed in tumors. However, whether miRNA-145 can be applied as a biomarker for potential prognosis of ovarian cancer still remains controversial. Therefore, this study further explored the prognostic value and mechanism of miRNA-145 in ovarian cancer through meta-analysis and bioinformatics analysis.Methods:Eligible studies were identified by searching the China National Knowledge Infrastructure, Chinese Biomedical literature Database, Chinese Scientific and Journal Database, Wan Fang database, PubMed, EMBASE, and Web of Science up to July 2021. Pooled hazard ratios with 95% confidence intervals for patient survival were calculated to investigate the effects of miRNA-145 on the prognosis of ovarian cancer. Survival curves of differential expression of miRNA-145 were analyzed by Oncomir. The target genes of miRNA-145 were predicted by miRTARbase and Diana-Tarbase V7.0 database. Enrichr database was applied to analyze the target genes by gene ontology and Kyoto Encyclopedia of Genes and Genomes pathways. Protein–protein interaction network of target genes was constructed from STRING database. Cytoscape software was used to screen the hub genes to meet the requirements. The Gene Expression Profiling Interactive Analysis database was applied to analyze the survival outcomes of hub genes.Results:The results of this meta-analysis would be submitted to peer-reviewed journals for publication.Conclusion:This study provides high-quality evidence to support the relationship between miRNA-145 expression and ovarian cancer prognosis. Through bioinformatics analysis, we further explored the mechanism of miRNA-145 in ovarian cancer and related pathways.

Identification of Potential Diagnostic and Prognostic Pseudogenes in Hepatocellular Carcinoma Based on Pseudogene-miRNA-mRNA Competitive Network.

BackgroundIt is widely known that hepatocellular carcinoma (HCC) has high rates of morbidity and mortality. A large number of studies have indicated that pseudogenes have an important effect on the carcinogenesis of HCC. Pseudogenes can play a role through the ceRNA network. There have been numerous studies on lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA networks. However, the pseudogene-miRNA-mRNA network in HCC has rarely been researched or reported on.Material/MethodsThe Cancer Genome Atlas (TCGA) database was researched and differences between selected genes were studied. A pseudogene-miRNA-mRNA network was then constructed and clustering of pseudogenes was studied. The diagnostic value of the selected pseudogenes, their functions, and pathways were investigated using available databases to understand their possible pathogenic mechanism in HCC. The protein-protein interaction network of target genes was found and the top 10 hub genes were identified. Expression of hub genes in HCC tissues was then detected by RT-qPCR.ResultsBy analyzing the gene difference and clinical data of HCC, we constructed a ceRNA network composed of 4 pseudogenes, 8 miRNAs, and 30 mRNAs. The pseudogenes AP000769.1, KRT16P1, KRT16P3, and RPLP0P2 were all correlated with the diagnosis and prognosis of HCC. Functional analyses through the Kyoto Encyclopedia of Genes and Genomes and the Gene Ontology databases indicated that pseudogenes can affect the physiological process of HCC through the p53 pathway. The top 10 hub genes identified were all highly expressed in HCC tissues and affected the patient survival rate.ConclusionsIn this study, 4 pseudogenes related to the diagnosis and prognosis of liver cancer were found through the construction of a ceRNA network. These 4 pseudogenes might constitute new therapeutic targets for liver cancer patients.

Identification of key microRNAs and genes associated with abdominal aortic aneurysm based on the gene expression profile.

What is the central question of this study? The aim was to identify abdominal aortic aneurysm (AAA)-associated microRNAs and their target genes in AAA using microarray analysis. What is the main finding and its importance? The main finding was that miR-145 and miR-30c-2* were found to be downregulated microRNAs in AAA, which could exert suppressive effects on AAA progression, and that miR-145 might target RAC2, whereas miR-30c-2* might target PIK3CD, IL1B and RAC2. The findings obtained from the study provide an enhanced understanding of microRNA as a therapeutic target to limit AAA. The aim of the study was to identify abdominal aortic aneurysm (AAA)-associated microRNAs (miRNAs) and genes potentially contributing to AAA. Differential analysis was performed to screen out differentially expressed genes (DEGs) and miRNAs in expression datasets of AAA-related miRNAs [GSE51226 (mouse)] and genes [GSE51227 (mouse) and GSE7084 (human)]. Then, gene ontology (GO) enrichment analysis of DEGs was compared with aneurysm-related GO to screen out DEGs related to the disease. The target genes of differential miRNAs were predicted and used to construct a miRNA-DEG regulatory network, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of target genes. Moreover, the protein-protein interaction network of target genes of miRNAs in the core position (hub-miRNA) with AAA-related genes was constructed to screen out hub genes. Finally, the target relationship between hub-miRNAs and their target genes was verified. There were 20 upregulated miRNAs and 20 downregulated miRNAs in AAA screened from the GSE51226 dataset (mouse). In addition, there were 1154 upregulated genes and 821 downregulated genes in the GSE51227 dataset (mouse), of which 246 DEGs were enriched in aneurysm-related GO entries in AAA. miR-145 and miR-30c-2* were the key miRNAs of AAA, both of which were downregulated in AAA and influenced pathways so as to affect AAA by regulating their respective target genes. The disease-related gene ACTA2 was downregulated, whereas DEGs including PIK3CD, IL1B, RAC2 and SELL were upregulated in AAA. Finally, it was proved that miR-145 targeted RAC2 and SELL, whereas miR-30c-2* targeted PIK3CD, IL1B and RAC2. Taken together, miR-145 and miR-30c-2*, downregulated in AAA, could potentially affect AAA, and miR-145 might target RAC2, whereas miR-30c-2* might target PIK3CD, IL1B and RAC2.

The identification and preliminary study of lncRNA TUG1 and its related genes in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common malignant tumour of the digestive system, which is a threat to public health. The purpose of this study was to investigate the featured genes and pathways of HCC from a bioinformatics database, and verify their correlation with diagnosis and prognosis of HCC. We downloaded the gene expression profile on HCC from the Gene Expression Omnibus (GEO), and software R was used to identify differentially expressed lncRNA (DEL). The target genes of the lncRNA were further predicted by using a cluster database and molecular interaction database. Subsequently, a combined interaction network of target genes was constructed using the Cytoscape platform with preliminary verification at the level of different databases, cell lines, and tissues. Finally, we explored the effectiveness of TUG1 and its target genes on the diagnosis and prognosis of HCC by univariate Cox analysis and survival analysis. A total of four DELs were identified and the most remarkably up-regulated lncRNA was TUG1, which included 12 high-confidence target genes. Moreover, we found that the expression changes of TUG1 and its target genes in different databases, cell lines, and liver cancer tissues were consistent with the prediction. The high expression of TUG1 and its target genes could significantly predict the shorter survival time of HCC patients, among which NCAPG, MCM6, PIGC, PEA15, and RACGAP1 have significant diagnostic value for HCC (AUC > 0.9). This study provides a starting point for the screening of therapeutically relevant targets in HCC. Further experiment should be conducted to verify our findings.

A systematic investigation based on microRNA-mediated gene regulatory network reveals that dysregulation of microRNA-19a/Cyclin D1 axis confers an oncogenic potential and a worse prognosis in human hepatocellular carcinoma

MicroRNAs (miRNAs) contribute to a wide variety of human diseases by regulating gene expression, leading to imbalances in gene regulatory networks. To discover novel hepatocellular carcinoma (HCC)-related miRNA-target axes and to elucidate their functions, we here performed a systematic investigation combining biological data acquisition and integration, miRNA-target prediction, network construction, functional assay and clinical validation. As a result, a total of 117 HCC differentially expressed miRNAs were identified, and 728 high confident target genes of these miRNAs were collected. Then, the interaction network of target genes was constructed and 221 key nodes with topological importance in the network were identified according to their topological features including degree, node-betweenness, closeness and K-coreness. Among these key nodes, Cyclin D1 had the highest node-betweenness, implying its bottleneck role in the network. Luciferase reporter assay confirmed that miRNA-19a, which was one of HCC downregulated miRNAs, directly targeted Cyclin D1 in HCC cells. Moreover, miR-19a might play inhibitory roles in HCC malignancy via regulating Cyclin D1 expression. Further clinical evidence also highlighted the prognostic potential of miR-19a/Cyclin D1 axis in HCC. In conclusion, this systematic investigation provides a framework to identify featured miRNAs and their target genes which are potent effectors in the occurrence and development of HCC. More importantly, miR-19a/Cyclin D1 axis might have promising applications as a therapeutic target and a prognostic marker for patients with HCC.

Identification of the typical miRNAs and target genes in hepatocellular carcinoma.

The aim of the present study was to identify miRNAs that were differentially expressed in hepatocellular carcinoma (HCC) by comparing normal and cancer tissue samples and to analyze the correlation of the target genes and HCC. The gene expression profile of GSE31383 was downloaded from the Gene Expression Omnibus database, including 19samples, 9normal and 10from HCC tissue samples. The differentially‑expressed miRNAs were identified with packages in R language and further analyzed using bioinformatics methods. Firstly, the verified targets of miRNAs were integrated in two miRNA databases: miRecords and miRTarBase, and the targets of the differentially‑expressed miRNAs were obtained. The software STRING was then used to construct the interaction network of target genes. Finally, a functional enrichment analysis of the genes in the interaction network was conducted using the software Gestalt. Typical miR‑224 and miR‑214 were identified by comparing normal and cancer samples, each of which obtained 14 and 8target genes, respectively. The functional enrichment analysis of the targets in the two groups highlighted the intracellular signaling cascade. In conclusion, the featured miRNAs (the upregulated miRNA‑224 and downregulated miRNA‑214) and their target genes are significant in the occurrence and development of HCC, which is likely to be significant for the identification of therapeutic targets and biomarkers to aid in the treatment of HCC.

Screening Biomarkers of Prostate Cancer by Integrating microRNA and mRNA Microarrays

In this study, we screened microRNA (miRNA) target genes of prostate cancer by integrating miRNA and mRNA expression profiles after target prediction and performed function enrichment analysis for selected candidate genes. The miRNA expression profile (GSE36802) and mRNA expression profile (GSE36801) were downloaded from the Gene Expression Omnibus database. We processed data and identified the differentially expressed miRNAs and mRNAs with R packages. Verified targets of miRNAs were identified through miRecods and miRTarBase. Then, software of Search Tool for the Retrieval of Interacting Genes was used to construct the interaction network of target genes. Finally, we performed function enrichment analysis for genes in the interaction network with the Functional Classification Tool. A total of 22 upregulated and 8 downregulated miRNAs were detected in this study, of which, hsa-mir-31 was the most overexpressed miRNA in prostate cancer. Both ITGA5 and RDX, two target genes of hsa-mir-31, were found to be differentially expressed from mRNA profiles by overexpressing hsa-mir-31. The cell adhesion molecule was found to be the most significant pathway enriched by ITGA5 and RDX. Overexpression of hsa-mir-31 can be a significant marker to distinguish cancer tissues from benign tissues. The targets such as ITGA5 and RDX regulated by hsa-mir-31 are candidate genes of prostate cancer, which provide new treatment strategies for its gene therapy.