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Clear cell and chromophobe renal cell carcinoma samples

ABSTRACT: Background: Clear cell renal cell carcinoma (ccRCC) and chromophobe renal cell carcinoma (chRCC) can usually be distinguished by histologic characteristics. Occasionally, diagnosis proves challenging and diagnostic difficulty will likely increase as needle biopsies of renal lesions become more common. Method: To identify markers that aid in differentiating ccRCC from chRCC, we used gene expression profiles to identify candidate markers that correlate with histology. 39 antisera and antibodies, including 35 for transcripts identified from gene expression profiling, were evaluated. Promising markers were tested on a tissue microarray (TMA) containing 428 renal neoplasms. Strength of staining of each core on the TMA was formally scored and the distribution of staining across different types of renal neoplasms was analyzed. Results: Based on results from initial immunohistochemical staining of multitissue titer arrays, 23 of the antisera and antibodies were selected for staining of the TMA. For 7 of these markers, strength of staining of each core on the TMA was formally scored. Vimentin (positive in ccRCC) and CD9 (positive in chRCC) best distinguished ccRCC from chRCC. The combination of vimentin negativity and CD9 positivity was found to distinguish chRCC from ccRCC with a sensitivity of 100.0% and a specificity of 95.2%. Conclusions: Based on gene expression analysis, we identify CD9 and vimentin as candidate markers for distinguishing between ccRCC and chRCC. In difficult cases and particularly when the amount of diagnostic tissue is limited, vimentin and CD9 staining could serve as a useful adjunct in the differential diagnosis of ccRCC and chRCC. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: Stage of Clear Cell renal cell carcinoma (I - V))

ORGANISM(S): Homo sapiens

PROVIDER: GSE17746 | GEO | 2010/08/20

SECONDARY ACCESSION(S): PRJNA118347

REPOSITORIES: GEO

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Project description:We investigated the expression profiles of microRNAs (miRNA) in 27 renal cell carcinoma (RCC) FFPE tissues (3 chRCC, 5 papRCC and 18 ccRCC), 4 upper urinary tract-urothelial cell carcinomas of the renal pelvis-ureter (UUT-UCCs) and 20 normal kidneys by using the miRCURY LNAM-bM-^DM-" 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 kidney tumours compared to the normal tissues. A total of 126 miRNAs (29%) had increased expression while 303 (69.8%) had decreased expression in RCC. Out of the 434 DE miRNAs, we detected 94 co-up-regulated and 218 co-down-regulated microRNAs among chRCC, papRCC and ccRCC. Of these, 89 and 203 were co-up- and co-down-regulated between RCCs and UUT-UCCs, respectively. We detected 11, 44 and 24 up-regulated miRNAs, which were specific for ccRCC, chRCC and papRCC, respectively. Moreover, 19, 18 and 8 miRNAs were uniquelly down-regulated in ccRCC, chRCC and papRCC, respectively. We also detected 89 and 203 co-up- and co-down-regulated miRNAs between kidney cancer and UUT-UCCs. Five miRNAs were up-regulated specifically in renal tumours and 49 in UUT-UCCs, whereas 15 miRNAs were down-regulated specifically in renal tumours and 89 in UUT-UCCs, respectively. Our data validicate that expression of miRNAs tends to be down-regulated renal cell carcinomas compared with normal kidney. We used 18 ccRCC, 3 chRCC, 5 papRCC, 4 UUT-UCC, 1 undifferentiated carcinoma and 19 normal tissue samples for miRNA profiling. Total RNA (0.5 M-BM-5g) from each sample and reference was labeled with Hy3M-bM-^DM-" fluorescent label, using the miRCURY LNAM-bM-^DM-" microRNA Hi-Power Labeling Kit (Exiqon, Woburn MA). The Hy3M-bM-^DM-\"-labeled samples were hybridized to the miRCURY LNAM-bM-^DM-" microRNA Array, 6th gen (Exiqon, Woburn MA), using an Agilent hybridization SureHyb chamber and gasket slide kits. After hybridization, the microarray slides were scanned at 10 M-NM-<m using the High-Resolution Microarray Scanner (Agilent Technologies) and stored in an ozone free environment. The image analysis was carried out using the ImaGene 8.0 software (BioDiscovery, Inc., USA). Raw microarray data were filtered, background corrected and quantile normalizated. Normalized data were further extracted, pre-processed and sorted with Microsoft ExcelM-BM-.. MicroRNAs were considered to be significantly differentially expressed if they obtained a p-value<0.05 and a FDRM-bM-^IM-$0.05.

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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Clear cell and chromophobe renal cell carcinoma samples

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