Dataset Information

Analysis of Differential Expression of microRNAs and Their Target Genes in Prostate Cancer: A Bioinformatics Study on Microarray Gene Expression Data.

ABSTRACT: Early diagnosis of prostate cancer (PCa) as the second most common cancer in men is not associated with precise and specific results. Thus, alternate methods with high specificity and sensitivity are needed for accurate and timely detection of PCa. MicroRNAs regulate the molecular pathways involved in cancer by targeting multiple genes. The aberrant expression of the microRNAs has been reported in different cancer types including PCa. In this bioinformatics study, we studied differential expression profiles of microRNAs and their target genes in four PCa gene expression omnibus (GEO) databases. PCa diagnostic biomarker candidates were investigated using bioinformatics tools for analysis of gene expression data, microRNA target prediction, pathway and GO annotation, as well as ROC curves. The results of this study revealed significant changes in the expression of 14 microRNAs and 40 relevant target genes, which ultimately composed four combination panels (miR- 375+96+663/ miR- 133b+143- 3p + 205/ C2ORF72 + ENTPD5 + GLYAT11/LAMB3 + NTNG2+TSLP) as candidate biomarkers capable to distinguish between PCa tumor samples and normal prostate tissue samples. These biomarkers may be suggested for a more accurate early diagnosis of PCa patients along with current diagnostic tests.

SUBMITTER: Khorasani M

PROVIDER: S-EPMC7081080 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Analysis of Differential Expression of microRNAs and Their Target Genes in Prostate Cancer: A Bioinformatics Study on Microarray Gene Expression Data.

Khorasani Maryam M Shahbazi Shirin S Hosseinkhan Nazanin N Mahdian Reza R

International journal of molecular and cellular medicine 20191029 2

Early diagnosis of prostate cancer (PCa) as the second most common cancer in men is not associated with precise and specific results. Thus, alternate methods with high specificity and sensitivity are needed for accurate and timely detection of PCa. MicroRNAs regulate the molecular pathways involved in cancer by targeting multiple genes. The aberrant expression of the microRNAs has been reported in different cancer types including PCa. In this bioinformatics study, we studied differential express ...[more]

PMID: 32215262

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Project description:Polycystic ovary syndrome (PCOS) is the most common endocrine disease in women of reproductive age. MicroRNAs (miRNAs or miRs) serve important roles in the physiological and pathological process of PCOS. To identify PCOS‑associated miRNAs, the dataset GSE84376 was extracted from the Gene Expression Omnibus database. Differentially expressed miRNAs (DE‑miRNAs) were obtained from Gene‑Cloud Biotechnology Information and potential target genes were predicted using TargetScan, DIANA‑microT‑CDS, miRDB and miRTarBase tools. Gene Ontology enrichment analysis was performed using Metascape and a protein‑protein interaction network was constructed using Cytoscape. Transcription factors were obtained from FunRich. DE‑miRNAs were verified by reverse transcription‑quantitative PCR. At the screening phase, there were seven DE‑miRNAs in the PCOS group not present in the control group. In total, 935 target genes were identified, which are involved in the development and maturation of oocytes. Mitogen‑activated protein kinase 1, phosphatase and tensin homolog, cAMP responsive element binding protein 1, signal transducer and activator of transcription 3, interferon γ, Fms‑related tyrosine kinase 1, transcription factor p65, insulin receptor substrate 1, DnaJ homolog superfamily C member 10 and casein kinase 2 α 1 were identified as the top 10 hub genes in the protein‑protein interaction network. Specificity protein 1 was the most enriched transcription factor. At the validation phase, the levels of Homo sapiens (hsa)‑miR‑3188 and hsa‑miR‑3135b were significantly higher in the PCOS group than in the control group. In addition, the expression level of hsa‑miR‑3135b was significantly correlated with the number of oocytes retrieved, the fertilization rate and the cleavage rate (P<0.05). The present bioinformatics study on miRNAs may offer a novel understanding of the mechanism of PCOS, and may serve to identify novel miRNA therapeutic targets.

Dataset Information

Analysis of Differential Expression of microRNAs and Their Target Genes in Prostate Cancer: A Bioinformatics Study on Microarray Gene Expression Data.

Publications

Analysis of Differential Expression of microRNAs and Their Target Genes in Prostate Cancer: A Bioinformatics Study on Microarray Gene Expression Data.

Similar Datasets

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