Dataset Information

MicroRNA expression signatures of stage, grade, and progression in clear cell RCC.

ABSTRACT: Clear cell RCC is the most common, and more likely to metastasize, of the three main histological types of RCC. Pathologic stage is the most important prognostic indicator and nuclear grade can predict outcome within stages of localized RCC. Epithelial tumors are thought to accumulate a series of genetic and epigenetic changes as they progress through well-defined clinical and histopathological changes. MicroRNAs (miRNAs) are involved in the regulation of mRNA expression from many human genes and miRNA expression is dysregulated in cancer. To better understand the contribution of dysregulated miRNA expression to the progression and biology of ccRCC, we examined the differences in expression levels of 723 human miRNAs through a series of analyses by stage, grade, and disease progression status in a large series of 94 ccRCC. We found a consistent signature that included significant upregulation of miR-21-5p, 142-3p, let-7g-5p, let-7i-5p and 424-5p, as well as downregulation of miR-204-5p, to be associated with ccRCC of high stage, or high grade, or progression. Discrete signatures associated with each of stage, grade, or progression were also identified. The let-7 family was significantly downregulated in ccRCC compared with normal renal parenchyma. Expression of the 6 most significantly differentially expressed miRNAs between ccRCC was verified by stem-loop qRT-PCR. Pathways predicted as targets of the most significantly dysregulated miRNAs included signaling, epithelial cancers, metabolism, and epithelial to mesenchymal transition. Our studies help to further elucidate the biology underlying the progression of ccRCC and identify miRNAs for potential translational application.

SUBMITTER: Gowrishankar B

PROVIDER: S-EPMC3974834 | biostudies-other | 2014 Mar

REPOSITORIES: biostudies-other

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MicroRNA expression signatures of stage, grade, and progression in clear cell RCC.

Gowrishankar Banumathy B Ibragimova Ilsiya I Zhou Yan Y Slifker Michael J MJ Devarajan Karthik K Al-Saleem Tahseen T Uzzo Robert G RG Cairns Paul P

Cancer biology & therapy 20131218 3

Clear cell RCC is the most common, and more likely to metastasize, of the three main histological types of RCC. Pathologic stage is the most important prognostic indicator and nuclear grade can predict outcome within stages of localized RCC. Epithelial tumors are thought to accumulate a series of genetic and epigenetic changes as they progress through well-defined clinical and histopathological changes. MicroRNAs (miRNAs) are involved in the regulation of mRNA expression from many human genes an ...[more]

PMID: 24351440

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Project description:BackgroundClear cell renal cell carcinoma (ccRCC) represents the most invasive and common adult kidney neoplasm. Mounting evidence suggests that microRNAs (miRNAs) are important regulators of gene expression. But their function in tumourigenesis in this tumour type remains elusive. With the development of high throughput technologies such as microarrays and NGS, aberrant miRNA expression has been widely observed in ccRCC. Systematic and integrative analysis of multiple microRNA expression datasets may reveal potential mechanisms by which microRNAs contribute to ccRCC pathogenesis.MethodsWe collected 5 public microRNA expression datasets in ccRCC versus non-matching normal renal tissues from GEO database and published literatures. We analyzed these data sets with an integrated bioinformatics framework to identify expression signatures. The framework incorporates a novel statistic method for abnormal gene expression detection and an in-house developed predictor to assess the regulatory activity of microRNAs. We then mapped target genes of DE-miRNAs to different databases, such as GO, KEGG, GeneGo etc, for functional enrichment analysis.ResultsUsing this framework we identified a consistent panel of eleven deregulated miRNAs shared by five independent datasets that can distinguish normal kidney tissues from ccRCC. After comparison with 3 RNA-seq based microRNA profiling studies, we found that our data correlated well with the results of next generation sequencing. We also discovered 14 novel molecular pathways that are likely to play a role in the tumourigenesis of ccRCC.ConclusionsThe integrative framework described in this paper greatly improves the inter-dataset consistency of microRNA expression signatures. Consensus expression profile should be identified at pathway or network level to address the heterogeneity of cancer. The DE-miRNA signature and novel pathways identified herein could provide potential biomarkers for ccRCC that await further validation.

Dataset Information

MicroRNA expression signatures of stage, grade, and progression in clear cell RCC.

Publications

MicroRNA expression signatures of stage, grade, and progression in clear cell RCC.

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