Integrative molecular bioinformatics study of human adrenocortical tumors : microRNA, tissue-specific target prediction, and pathway analysis.

Details

Serval ID
serval:BIB_B6554E4D489E
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Integrative molecular bioinformatics study of human adrenocortical tumors : microRNA, tissue-specific target prediction, and pathway analysis.
Journal
Endocrine-Related Cancer
Author(s)
Tombol Zsofia, Szabo Peter M., Molnar Viktor, Wiener Zoltan, Tolgyesi Gergely, Horanyi Janos, Riesz Peter, Reismann Peter, Patocs Attila, Liko Istvan, Gaillard Rolf-Christian, Falus Andras, Racz Karoly, Igaz Peter
ISSN
1479-6821[electronic]
Publication state
Published
Issued date
2009
Volume
16
Number
3
Pages
895-906
Language
english
Abstract
MicroRNAs (miRs) are involved in the pathogenesis of several neoplasms; however, there are no data on their expression patterns and possible roles in adrenocortical tumors. Our objective was to study adrenocortical tumors by an integrative bioinformatics analysis involving miR and transcriptomics profiling, pathway analysis, and a novel, tissue-specific miR target prediction approach. Thirty-six tissue samples including normal adrenocortical tissues, benign adenomas, and adrenocortical carcinomas (ACC) were studied by simultaneous miR and mRNA profiling. A novel data-processing software was used to identify all predicted miR-mRNA interactions retrieved from PicTar, TargetScan, and miRBase. Tissue-specific target prediction was achieved by filtering out mRNAs with undetectable expression and searching for mRNA targets with inverse expression alterations as their regulatory miRs. Target sets and significant microarray data were subjected to Ingenuity Pathway Analysis. Six miRs with significantly different expression were found. miR-184 and miR-503 showed significantly higher, whereas miR-511 and miR-214 showed significantly lower expression in ACCs than in other groups. Expression of miR-210 was significantly lower in cortisol-secreting adenomas than in ACCs. By calculating the difference between dCT(miR-511) and dCT(miR-503) (delta cycle threshold), ACCs could be distinguished from benign adenomas with high sensitivity and specificity. Pathway analysis revealed the possible involvement of G2/M checkpoint damage in ACC pathogenesis. To our knowledge, this is the first report describing miR expression patterns and pathway analysis in sporadic adrenocortical tumors. miR biomarkers may be helpful for the diagnosis of adrenocortical malignancy. This tissue-specific target prediction approach may be used in other tumors too.
Keywords
Adenoma/diagnosis, Adenoma/genetics, Adrenal Cortex Neoplasms/diagnosis, Adrenal Cortex Neoplasms/genetics, Adrenocortical Carcinoma/diagnosis, Adrenocortical Carcinoma/genetics, Adult, Algorithms, Computational Biology/methods, Drug Delivery Systems/methods, Female, Forecasting/methods, Gene Expression Profiling/methods, Gene Expression Regulation, Neoplastic, Humans, Male, MicroRNAs/analysis, MicroRNAs/genetics, Middle Aged, Models, Biological, Organ Specificity/genetics, Signal Transduction/genetics, Tumor Markers, Biological/analysis, Tumor Markers, Biological/genetics
Pubmed
Web of science
Open Access
Yes
Create date
06/01/2010 11:56
Last modification date
20/08/2019 15:24
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