Dataset Information

Genomic profiling of renal cell carcinoma in patients with end-stage renal disease

ABSTRACT: In this study, eighty tumor samples from 63 patients with renal cell carcinoma (RCC)-end-stage renal disease (ESRD) were analyzed by array comparative genomic hybridization (array CGH) using the Agilent Whole Human Genome 4×44K Oligo Micro Array.

ORGANISM(S): Homo sapiens

PROVIDER: GSE28601 | GEO | 2012/03/24

SECONDARY ACCESSION(S): PRJNA139103

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Accurate diagnostic discrimination of benign renal oncocytoma (OC) and malignant renal cell carcinomas (RCC) is not only useful for planning appropriate treatment strategies of patients with renal masses but also for estimating prognosis. Classification of renal neoplasms solely by histopathology can often be challenging for a variety of reasons. The aim of this study was to develop and validate a genomic algorithm for molecular classification of renal cortical neoplasms that could be implemented in a routine clinical diagnostic setting. Using TCGA (The Cancer Genome Atlas) copy number profiles of over 600 RCC specimens, prior FISH studies and published literature, a classification algorithm was developed consisting of 15 genomic markers: loss of VHL, 3p21, 8p, and chromosomes 1, 2, 6, 10 and 17, and gain of 5qter, 16p, 17q, 20q, and chromosomes 3, 7, and 12. Criteria for scoring specimens for the presence of each genomic marker were established. As validation, 191 surgically resected formalin-fixed paraffin-embedded renal neoplasms were blindly submitted to targeted array-CGH and were classified according to the algorithm. Upon histologic re-review leading to exclusion of three specimens and using histology as the gold standard, the algorithm correctly classified 58 of 62 (93%) clear cell renal cell carcinoma, 51 of 56 (91%) papillary RCC, and 33 of 34 (97%) chromophobe RCC. Of the 36 OC specimens, 17 were classified as OC, two as a malignant subtype, 14 as benign, and three exhibited alterations not associated with a specific subtype. In ten of the latter two groups, CCND1-rearrangement was detected by fluorescence in situ hybridization, affording a classification as OC. Together, 33 of 36 (92%) OC were classified as OC or benign. For the entire validation cohort, an overall diagnostic sensitivity of 93% and above 97% specificity was achieved, suggesting that the implementation of genome-based molecular classification in a clinical diagnostic setting could impact the overall management and outcome of patients with renal tumors. A total of 191 RCC FFPE samples are analyzed including 63 clear cell RCC (ccRCC), 57 papillary RCC (pRCC), 35 chromophobe RCC (chrRCC) and 36 oncocytoma (OC). Two-color array-comparative genomic hybdrization on custom designed using RCC DNA as test and normal sex-matched DNA as reference.

Project description:Cardiovascular disease is the major cause of morbidity and death in patients with chronic kidney disease (CKD) and end-stage renal disease (ESRD). Patients with CKD and ESRD are at high risk for myocardial dysfunction, ischemia and heart failure. The mechanisms linking impaired renal function and increased risk for cardiovascular diseases, however, remain elusive. In addition, conventional therapeutics proven effective in reducing cardiovascular events in general population fail to provide similar benefits in uremic patients. There is a clear need to identify novel mediators of cardiovascular complications in uremic patients to provide insights into the pathogenesis, to tailor clinical care based on cardiovascular risks, and to develop new therapeutic strategies. It has become increasingly clear that the transcription of the eukaryotic genome is far more pervasive and complex than previously appreciated. While the expression of messenger RNAs (mRNAs) and microRNAs (miRNAs) account for only ~1% of all transcribed species, up to 90% of the mammalian genome is transcribed as long non-coding RNAs (lncRNAs), a heterogeneous group of non-coding transcripts longer than 200 nucleotides. LncRNAs have been shown to be functional and involved in specific physiological and pathological processes through epigenetic, transcriptional and post-transcriptional mechanisms. While the roles of lncRNAs in human diseases including cancer and neurodegenerative disorders are beginning to emerge, it remains unclear how lncRNA regulation contributes to cardiovascular complications in patients with renal dysfunction. In this proposal, we seek to apply next-generation sequencing technology to investigate circulating (plasma) lncRNA expression in control subjects and in patients with CKD and ESRD. We will test the hypothesis that circulating lncRNA expression signature can reflect the underlying kidney disease states in patients with CKD and ESRD. In addition, we will determine if circulating lncRNA expression signature could be a sensitive and specific biomarker to predict adverse cardiovascular events in patients with ESRD.

Dataset Information

Genomic profiling of renal cell carcinoma in patients with end-stage renal disease

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure