Project description:Genome wide DNA methylation profiling of clear cell renal cell carcinoma (ccRCC) tissue versus matched normal kidney tissue. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 450,000 CpGs in tumor and adjacent normal kidney tissue samples from ccRCC patients. Samples included 46 paired fresh frozen ccRCC tumor and adjacent normal kidney tissues.
Project description:Genome wide DNA methylation profiling of clear cell renal cell carcinoma (ccRCC) tissue versus matched normal kidney tissue. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 450,000 CpGs in tumor and adjacent normal kidney tissue samples from ccRCC patients. Samples included 46 paired fresh frozen ccRCC tumor and adjacent normal kidney tissues. Bisulphite converted DNA from the 92 samples were hybridised to the Illumina Infinium 450 Human Methylation Beadchip v1.2
Project description:Aberrant DNA methylation is common in cancer. To associate DNA methylation with gene function, we performed RNAseq upon tumor tissue and matched normal tissues of two ccRCC (clear cell renal cell carcinoma) patients. To quantify 5mC and 5hmC level in each CG site at genome-wide level, we performed BS-seq and TAB-seq upon tumor tissue and matched normal tissues of two ccRCC (clear cell renal cell carcinoma) patients, respectively. mRNA profiles of tumor and matched normal tissues from two ccRCC patients were generated by deep sequencing, using Hiseq 2000. Single-nucleotide-resolution, whole-genome, 5mC and 5hmC profiles of tumor and matched normal tissues from two ccRCC (clear cell renal cell carcinoma) patients were generated by deep sequencing, using Hiseq 2000.
Project description:Aberrant DNA methylation is common in cancer. To associate DNA methylation with gene function, we performed RNAseq upon tumor tissue and matched normal tissues of two ccRCC (clear cell renal cell carcinoma) patients. To quantify 5mC and 5hmC level in each CG site at genome-wide level, we performed BS-seq and TAB-seq upon tumor tissue and matched normal tissues of two ccRCC (clear cell renal cell carcinoma) patients, respectively.
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:Uncovering a protein abundance-based gene panel specific to clear cell Renal Cell Carcinoma (ccRCC) could provide support for the everyday clinical decision-making process. We used proteomic data to differentiate between normal kidney and ccRCC tissues. By using datasets of patients with paired normal tissue samples from gene array cohorts, we uncovered the top genes over-expressed in ccRCC. We collected surgically resected ccRCC specimens at Semmelweis University to validate the strongest genes. Differential expression was evaluated at the protein level using targeted mass spectrometry (MS).
Project description:In order to clarify the molecular mechanism involved in renal carcinogenesis, and identify molecular targets for diagnosis and treatment, we analyzed genome-wide gene expression profiles of 15 surgical specimens of clear cell renal cell carcinoma (RCC), compared to normal renal cortex, using a combination of laser microbeam microdissection (LMM) with a cDNA microarray representing 27,648 genes. Tissue samples of surgically-resected clear cell renal cell carcinoma (ccRCC) and their corresponding clinical information were obtained from patients with written informed consent. The total of 15 cancer patients (6 women and 9 men; median age, 66; range, 36-75 years) that had been confirmed histologically as ccRCC were selected for this study. Two to three pieces of cancer tissue had been taken from each patient at the time of radical nephrectomy. Normal tissue had been obtained from the distant region from cancer area in the resected kidney tissue. These samples were immediately embedded in TissueTek OCT compound (Sakura, Tokyo, Japan), frozen, and stored at -80°C. The frozen tissues were sliced into 8-μm sections using a cryostat (Sakura) and then stained with H&E for histological examination. We used LMM technology to collect pure populations of ccRCC cells as well as non-cancerous renal cortex. A mixture of normal renal cortex cells in kidney tissues from 11 patients was prepared as a universal control. Experiments were performed using 6 sets of slides (slide set 1-6 corresponding to ID_REF 1-27648).
Project description:Novel single cell technologies have paved the way for the characterization and improved biological understanding of clear cell renal cell carcinoma (ccRCC) where the focus has been mostly on the immunological compartments of the tumor microenvironment (TME). However, the identification of metastatic tumor cell clones, and the stromal compartments of TME of untreated ccRCC patients still remains to be elucidated. Here we perform single-cell RNA-sequencing on treatment naive ccRCC and adjacent normal kidney tissue.