MicroRNA expression of clear cell papillary renal cell carcinoma
Ontology highlight
ABSTRACT:
ORGANISM(S): synthetic construct Homo sapiens
PROVIDER: GSE51554 | GEO | 2013/10/23
SECONDARY ACCESSION(S): PRJNA223405
REPOSITORIES: GEO
Similar Datasets
Project description:to see if CCPRCC has a distinct miRNA profile from CCRCC and PRCC miRNA v.2.0 chips on two portions of five CCPRCC cases (total 10 samples), three portions of two CCRCC cases and a further three CCRCC cases (total 9 samples), and five type I PRCC samples; a total of 24 samples
2013-10-23 | E-GEOD-51554 | biostudies-arrayexpress
Project description:Clear cell papillary renal cell carcinoma (CCPRCC) is a low-grade renal neoplasm with morphological characteristics mimicking both clear cell renal cell carcinoma (CCRCC) and papillary renal cell carcinoma (PRCC). However, despite some overlapping features, their morphological, immunohistochemical, and molecular profiles are distinct. To better understand the biology of this tumor, we analyze the miRNA expression profiles of a set of CCPRCC by microarrays.
2017-02-28 | GSE95385 | GEO
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.
2010-07-22 | E-GEOD-23085 | biostudies-arrayexpress
Project description:We present three mouse models of kidney cancer that recapitulate the genomic alterations found in human papillary (pRCC) and clear cell RCC (ccRCC), the most common RCC subtypes. MYC activation results in highly penetrant pRCC tumors (MYC), while MYC activation, when combined with Vhl and Cdkn2a (Ink4a/Arf) deletion (VIM), produce kidney tumors that approximate human ccRCC.
2017-04-12 | GSE97654 | GEO
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.
2010-07-22 | GSE23085 | GEO
Project description:To identify microRNA (miRNA) profiles of small, pathologically confirmed stage 1 clear cell renal cell carcinoma (ccRCC) tumors that could predict progression to metachronous metastatic disease. : Fifty-five pathologic stage 1 ccRCC tumors ≤5cm from two institutions were examined in an initial miRNA screening, followed by a validation study. This investigation identified miRNA biomarkers that may differentiate between non-progressive ccRCC tumors and those that progress to metastatic disease in this group of stage I tumors. The data presented in this workbook are for the samples analyzed in the custom array analysis. The data were normalized to the average of the insignificant control miRNA: miRs-28-5p, -125-5p, and -191-5p, selected from the screening array dataset using NormFinder©. Prior to normalization each value was scaled by the corresponding internal plate calibrator value (see below).
2020-06-01 | GSE131960 | GEO
Project description:Renal cell carcinoma is the most common neoplasm of the adult kidney. A few subtypes of RCC include papillary RCC (pRCC), chromophobe RCC (chRCC) and the benign oncocytoma tumor. In some cases, distinguishing between the RCC subyptes is difficult. We performed a mircroRNA (miRNA) microarray to determine differential miRNA expression between pRCC, chRCC, and oncocytoma. We performed a miRNA microarray on 10 tumor samples of each papillary renal cell carcinoma (pRCC), chromophobe renal cell carcinoma (chRCC), and oncocytoma.
2012-08-13 | E-GEOD-39790 | biostudies-arrayexpress
Project description:Renal cell carcinoma is the most common neoplasm of the adult kidney. A few subtypes of RCC include papillary RCC (pRCC), chromophobe RCC (chRCC) and the benign oncocytoma tumor. In some cases, distinguishing between the RCC subyptes is difficult. We performed a mircroRNA (miRNA) microarray to determine differential miRNA expression between pRCC, chRCC, and oncocytoma.
2012-08-14 | GSE39790 | GEO
Project description:The proteome of clinical tissue samples diagnosed with clear cell renal cell carcinoma (ccRCC) and papillary renal cell carcinoma (pRCC) were evaluated analyzed along with the dataset identifier PXD022018 to establish a potential discriminative biomarker panel of proteins for these tumors subtypes.
2021-12-15 | PXD023296 | Pride
Project description:To identify microRNA (miRNA) profiles of small, pathologically confirmed stage 1 clear cell renal cell carcinoma (ccRCC) tumors that could predict progression to metachronous metastatic disease. : Fifty-five pathologic stage 1 ccRCC tumors ≤5cm from two institutions were examined in an initial miRNA screening, followed by a validation study. This investigation identified miRNA biomarkers that may differentiate between non-progressive ccRCC tumors and those that progress to metastatic disease in this group of stage I tumors. The data presented in this workbook are for the 20 samples analyzed in the screening analysis. The data were normalized to the global mean of all targets with a Cq<35. Prior to normalization each value was scaled by the corresponding internal plate calibrator value.
2020-06-01 | GSE131959 | GEO