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MicroRNA profiling in primary clear cell renal cell carcinoma

ABSTRACT: Renal cell carcinoma (RCC) is the most common neoplasm of the adult kidney. Currently, there are no biomarkers for the diagnostic, prognostic, or predictive applications in RCC. MicroRNAs (miRNAs) are short non protein-coding RNAs that negatively regulate gene expression and have been shown to be involved in cancer. We analyzed a total of 70 matched pairs of clear cell RCC (ccRCC) and normal kidney tissues from the same patients by microarray analysis and validated our results by quantitative real time PCR. We identified 166 miRNAs significantly dysregulated in ccRCC. MiR-122, miR-155 and miR-210 had the highest fold changes of overexpression while miR-200c, miR-335, and miR-218 were the most downregulated. We performed extensive bioinformatics analysis including a combinatorial analysis of previously reported miRNAs dysregulated in RCC and extensive target prediction analysis. Many miRNAs were predicted to target a number of genes involved in RCC pathogenesis. Our results showed that miRNA dysregulation in RCC can be attributed in part, to chromosomal aberrations, the co-regulation of miRNA clusters, and co-expression with host genes. We also correlated miRNA expression with clinical characteristics and found miR-155 expression was correlated with ccRCC tumor size. In conclusion, our analysis showed that a number of miRNAs are dysregulated in ccRCC and may contribute to kidney cancer pathogenesis by targeting more than one key molecule. We identified mechanisms that may contribute to miRNA dysregulation in ccRCC. Dysregulated miRNAs represent potential biomarkers for kidney cancer.

ORGANISM(S): Homo sapiens

PROVIDER: GSE23085 | GEO | 2010/07/22

SECONDARY ACCESSION(S): PRJNA131881

REPOSITORIES: GEO

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Project description:Renal cell carcinoma (RCC) is the most common neoplasm of the adult kidney. Currently, there are no biomarkers for the diagnostic, prognostic, or predictive applications in RCC. MicroRNAs (miRNAs) are short non protein-coding RNAs that negatively regulate gene expression and have been shown to be involved in cancer. We analyzed a total of 70 matched pairs of clear cell RCC (ccRCC) and normal kidney tissues from the same patients by microarray analysis and validated our results by quantitative real time PCR. We identified 166 miRNAs significantly dysregulated in ccRCC. MiR-122, miR-155 and miR-210 had the highest fold changes of overexpression while miR-200c, miR-335, and miR-218 were the most downregulated. We performed extensive bioinformatics analysis including a combinatorial analysis of previously reported miRNAs dysregulated in RCC and extensive target prediction analysis. Many miRNAs were predicted to target a number of genes involved in RCC pathogenesis. Our results showed that miRNA dysregulation in RCC can be attributed in part, to chromosomal aberrations, the co-regulation of miRNA clusters, and co-expression with host genes. We also correlated miRNA expression with clinical characteristics and found miR-155 expression was correlated with ccRCC tumor size. In conclusion, our analysis showed that a number of miRNAs are dysregulated in ccRCC and may contribute to kidney cancer pathogenesis by targeting more than one key molecule. We identified mechanisms that may contribute to miRNA dysregulation in ccRCC. Dysregulated miRNAs represent potential biomarkers for kidney cancer. We preformed a miRNA microarray on 20 pairs of matched primary clear cell renal cell carcinoma (ccRCC) and normal kidney tissue from the same patient (St. Michael's Hospital, Toronto, Canada). One matched pair was used per array for a total of 20 arrays. Microarray results were validated by quantitative real time PCR using an independent set of 50 matched pairs of ccRCC and normal kidney tissue from the same patient.

Project description:We investigated the expression profiles of microRNAs (miRNA) in 26 renal cell carcinoma (RCC) FFPE tissues (3 chRCC, 5 papRCC and 18 ccRCC), 4 urothelial cell carcinomas of the upper urinary tract (UT-UCs) and 20 normal kidneys by using the miRCURY LNA™ microRNA Array, 6th gen (Exiqon, Woburn MA), containing capture probes that target all miRNAs for all species registered in the miRBASE version 16.0. Real-time PCR (qRT-PCR) using appropriate endogenous controls was performed in order to validate the microarray results of the 27 most differentially expressed (DE) miRNAs. We identified 434 miRNAs that were significantly deregulated in all tumours compared to the normal kidney tissues. Overall, 126 miRNAs (29%) showed increased expression and 303 miRNAs (69.8%) had decreased expression in RCCs and UT-UCs vs. the normal kidneys. Specifically, 374, 420, 421 and 409 miRNAs were 90% consistently down-regulated in ccRCC, papRCC, chRCC and UT-UC, respectively. Unsupervised two-way hierarchical clustering (HCL) with Euclidian distance accurately discriminated between RCC and UT-UC. Apart from one chRCC sample that was clustered with ccRCCs, HCL also managed to successfully classify the 3 RCC subtypes among them. Furthermore, it showed that ccRCC is more closely related to papRCC and that both are distinct from chRCC or UT-UC. Ninety-four miRNAs were co-upregulated among ccRCC, papRCC and chRCC; and 11, 44 and 24 miRNAs were specifically up-regulated in each one of the three RCC subtypes (ccRCC, chRCC and papRCC), respectively. On the other hand, 222 miRNAs were co-down-regulated in the three RCC subtypes, whereas 16, 18 and 5 miRNAs were specifically down-regulated in ccRCC, chRCC and papRCC, respectively. When the DE miRNAs in each RCC subtype were combined with those in UT-UC, we identified 89 and 206 miRNAs, respectively, that were up- and down-regulated in all tumor types. miRNA profiling can distinguish between RCC and UT-UC as well as among distinct RCC subtypes. Our data validicate that miRNA expression tends to be down-regulated in RCC versus the normal kidney tissue.

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MicroRNA profiling in primary clear cell renal cell carcinoma

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