Dataset Information

MiRNA signature identification of retinoblastoma and the correlations between differentially expressed miRNAs during retinoblastoma progression.

ABSTRACT: Retinoblastoma (RB) is a common pediatric cancer. The study aimed to uncover the mechanisms of RB progression and identify novel therapeutic biomarkers.The miRNA expression profile GSE7072, which includes three RB samples and three healthy retina samples, was used. After data normalization using the preprocessCore package, differentially expressed miRNAs (DE-miRs) were selected by the limma package. The targets of the DE-miRs were predicted based on two databases, followed by construction of the miRNA-target network. Pathway enrichment analysis was conducted for the targets of the DE-miRNAs using DAVID. The CTD database was used to predict RB-related genes, followed by clustering analysis using the pvclust package. The correlation network of DE-miRs was established. MiRNA expression was validated in another data set, GSE41321.In total, 24 DE-miRs were identified whose targets were correlated with the cell cycle pathway. Among them, hsa-miR-373, hsa-miR-125b, and hsa-miR-181a were highlighted in the miRNA-target regulatory network; 14 DE-miRs, including hsa-miR-373, hsa-miR-125b, hsa-miR-18a, hsa-miR-25, hsa-miR-20a, and hsa-let-7 (a, b, c), were shown to distinguish RB from healthy tissue. In addition, hsa-miR-25, hsa-miR-18a, and hsa-miR-20a shared the common target BCL2L11; hsa-let-7b and hsa-miR-125b targeted the genes CDC25A, CDK6, and LIN28A. Expression of three miRNAs in GSE41321 was consistent with that in GSE7072.Several critical miRNAs were identified in RB progression. Hsa-miR-373 might regulate RB invasion and metastasis, hsa-miR-181a might involve in the CDKN1B-mediated cell cycle pathway, and hsa-miR-125b and hsa-let-7b might serve as tumor suppressors by coregulating CDK6, CDC25A, and LIN28A. The miRNAs hsa-miR-25, hsa-miR-18a, and hsa-miR-20a might exert their function by coregulating BCL2L1.

SUBMITTER: Yang Y

PROVIDER: S-EPMC4688417 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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miRNA signature identification of retinoblastoma and the correlations between differentially expressed miRNAs during retinoblastoma progression.

Yang Yang Y Mei Qi Q

Molecular vision 20151214

<h4>Purpose</h4>Retinoblastoma (RB) is a common pediatric cancer. The study aimed to uncover the mechanisms of RB progression and identify novel therapeutic biomarkers.<h4>Methods</h4>The miRNA expression profile GSE7072, which includes three RB samples and three healthy retina samples, was used. After data normalization using the preprocessCore package, differentially expressed miRNAs (DE-miRs) were selected by the limma package. The targets of the DE-miRs were predicted based on two databases, ...[more]

PMID: 26730174

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Project description:Retinoblastoma (RB), the most common intraocular malignancy, typically occurs in pediatric patients under the age of 6 years. The present study aimed to explore the long noncoding RNA (lncRNA) expression profile in RB and identify novel lncRNA biomarkers to facilitate the investigation of molecular mechanisms of RB and improve clinical therapy. Raw microarray data for the comparison of gene expression between three RB and three adjacent normal tissue samples were downloaded from Gene Expression Omnibus (dataset no. GSE111168). After identification of differentially expressed lncRNAs (DELs) and differentially expressed mRNAs (DEMs) in RB, functional enrichment analyses and a DEL-DEM weighted correlation network analysis were performed. A total of 3,915 DELs (1,774 upregulated and 2,141 downregulated) and 3,715 DEMs (1,492 upregulated and 2,223 downregulated) were identified in RB. The DEL-targeted DEMs were highly enriched by genes involved in hexose transport, muscle tissue morphogenesis, the stereocilium membrane, endothelin B receptor binding and γ-filamin/ABP-L, α-actinin and telethonin binding protein of the Z-disc binding. Furthermore, associations of the DELs and DEMs with several pathways were determined, including PI3K/AKT, Hippo and cancer signaling, as well as extracellular matrix-receptor interaction pathways. Coexpression network analysis revealed that the top three DELs, lnc-DAZ1-161, lnc-HDAC7-21 and lnc-OR52A1-55, formed coexpression modules with 181, 156 and 210 DEMs, respectively. In addition, the top three DEMs, namely EIF1AY, GSTM1 and NLRP11, formed coexpression modules with 33, 50 and 41 DELs, respectively. Validation using reverse transcription-quantitative PCR indicated that the expression of representative lncRNAs (lnc-DAZ1-161 and lnc-HDAC7-21) in RB cells in vitro was consistent with that in RB tissues in the database, while the expression of lnc-OR52A1-55 was not consistent with the database. These results suggested that the aberrant lncRNA expression profile in RB is related to the differential regulation of numerous physiological and pathological processes. The lncRNA and mRNA profiles in RB identified may provide novel targets for the investigation of its molecular mechanisms and thus lead to improvements in clinical therapy for RB.

Project description:BACKGROUND: The miRNAs, a class of short approximately 22-nucleotide non-coding RNAs, often act post-transcriptionally to inhibit mRNA expression. In effect, they control gene expression by targeting mRNA. They also help in carrying out normal functioning of a cell as they play an important role in various cellular processes. However, dysregulation of miRNAs is found to be a major cause of a disease. It has been demonstrated that miRNA expression is altered in many human cancers, suggesting that they may play an important role as disease biomarkers. Multiple reports have also noted the utility of miRNAs for the diagnosis of cancer. Among the large number of miRNAs present in a microarray data, a modest number might be sufficient to classify human cancers. Hence, the identification of differentially expressed miRNAs is an important problem particularly for the data sets with large number of miRNAs and small number of samples. RESULTS: In this regard, a new miRNA selection algorithm, called ?HEM, is presented based on rough hypercuboid approach. It selects a set of miRNAs from a microarray data by maximizing both relevance and significance of the selected miRNAs. The degree of dependency of sample categories on miRNAs is defined, based on the concept of hypercuboid equivalence partition matrix, to measure both relevance and significance of miRNAs. The effectiveness of the new approach is demonstrated on six publicly available miRNA expression data sets using support vector machine. The.632+ bootstrap error estimate is used to minimize the variability and biasedness of the derived results. CONCLUSIONS: An important finding is that the ?HEM algorithm achieves lowest B.632+ error rate of support vector machine with a reduced set of differentially expressed miRNAs on four expression data sets compare to some existing machine learning and statistical methods, while for other two data sets, the error rate of the ?HEM algorithm is comparable with the existing techniques. The results on several microarray data sets demonstrate that the proposed method can bring a remarkable improvement on miRNA selection problem. The method is a potentially useful tool for exploration of miRNA expression data and identification of differentially expressed miRNAs worth further investigation.

Dataset Information

MiRNA signature identification of retinoblastoma and the correlations between differentially expressed miRNAs during retinoblastoma progression.

Publications

miRNA signature identification of retinoblastoma and the correlations between differentially expressed miRNAs during retinoblastoma progression.

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