Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene expression characterization of high and low grade clear cell renal cell carcinoma

ABSTRACT: Patients undergoing either partial or radical nephrectomy at William Beaumont Hospital (Royal Oak, MI) were consented prior to surgery with local IRB oversight. Samples were collected at time of surgery and stored at -80Â°C according to CAP (College of American Pathologist)-accredited standard operating procedures. Disease pathology of frozen samples was validated with hematoxylin and eosin stained tissue sections from adjacently collected formalin fixed paraffin embedded tissue. The objective of this study was to examine the gene expression patterns of clear cell carcinoma in relation to adjacent normal kidney as well as other benign kidney conditions. In particular, the goal was to identify gene expression that could differentiate high grade ccRCC from low grade ccRCC. Samples from patients with high grade ccRCC (Fuhrman grades 3 & 4, n=16) were compared to normal kidney samples (n=14) and also to samples from patients with benign kidney conditions (n=6). Samples from patients with low grade ccRCC (Fuhrman grades 1 & 2, n=13) were then also compared to normal kidney samples (n=14) and also to samples from patients with benign kidney conditions (n=6).

ORGANISM(S): Homo sapiens

SUBMITTER: Bryan Thibodeau

PROVIDER: E-GEOD-68417 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Characterization of clear cell renal cell carcinoma by gene expression profiling.

Thibodeau Bryan J BJ Fulton Matthew M Fortier Laura E LE Geddes Timothy J TJ Pruetz Barbara L BL Ahmed Samreen S Banes-Berceli Amy A Zhang Ping L PL Wilson George D GD Hafron Jason J

Urologic oncology 20151203 4

<h4>Objectives</h4>Use global gene expression to characterize differences between high-grade and low-grade clear cell renal cell carcinoma (ccRCC) compared with normal and benign renal tissue.<h4>Methods</h4>Tissue samples were collected from patients undergoing surgical resection for ccRCC. Affymetrix gene expression arrays were used to examine global gene expression patterns in high- (n = 16) and low-grade ccRCC (n = 13) as well as in samples from normal kidney (n =14) and benign kidney diseas ...[more]

PMID: 26670202

Similar Datasets

Project description:Tumorigenic processes are understood to be driven by epi-/genetic and genomic alterations from single point mutations to chromosomal alterations such as insertions and deletions of nucleotides up to gains and losses of large chromosomal fragments including products of chromosomal rearrangements e.g. fusion genes and proteins. Overall comparisons of copy number alterations (CNAs) present in 48 clear cell renal cell carcinoma (ccRCC) genomes result in ratios of gene losses versus gene gains between 26 ccRCC Fuhrman malignancy grades G1 (ratio 1.25) and 20 G3 (ratio 0.58). Gene losses and gains of 15762 CNA genes are mapped to 795 chromosomal cytoband loci including 280 KEGG pathways. CNAs are classified according to their contribution to Fuhrman tumour gradings G1 and G3. Gene gains and losses turn out to be highly structured processes in ccRCC genomes enabling the subclassification and stratification of ccRCC tumours in a genome-wide manner. CNAs of ccRCC seem to start with common tumour related gene losses flanked by CNAs specifying Fuhrman grade G1 losses and CNA gains favouring grade G3 tumours. The appearance of recurrent CNA signatures implies the presence of causal mechanisms most likely implicated in the pathogenesis and disease-outcome of ccRCC tumours distinguishing lower from higher malignant tumours. Finally, the diagnostic quality of initial 201 genes (108 genes supporting G1 and 93 genes G3 phenotypes) are successfully validated on published Swiss data (GSE19949) leading to a restricted CNA gene set of 171 CNA genes of which 85 genes favour Fuhrman grade G1 and 86 genes Fuhrman grade G3. Regarding these gene sets overall survival decreases with the number of G3 related gene losses plus the total number of gene gains. CNA gene sets presented define an entry to a gene-directed and pathway-related functional understanding of ongoing copy number alterations within and between individual ccRCC tumours leading to CNA genes of prognostic and predictive value.

Project description:BACKGROUND: Despite the moderate incidence of papillary renal cell carcinoma; (PRCC), there is a disproportionately limited understanding of its underlying genetic programs. There is no effective therapy for metastatic PRCC, and patients are often excluded from kidney cancer trials. A morphological classification of PRCC into Type 1 and Type 2 tumors has been recently proposed, but its biological relevance remains uncertain. PATIENTS AND METHODS. We studied the gene expression profiles of 34 cases of PRCC using Affymetrix HGU133 Plus 2.0 arrays (54,675 probe sets) using both unsupervised and supervised analysis. Comparative genomic microarray analysis (CGMA) was used to infer cytogenetic aberrations, and pathways were ranked with a curated database. Expression of selected genes was validated by immunohistochemistry in 34 samples, with 15 independent tumors. RESULTS. We identified 2 highly distinct molecular PRCC subclasses with morphologic correlation. The first class, with excellent survival, corresponded to 3 histological subtypes: Type 1, low-grade Type 2 and mixed Type 1/low-grade Type 2 tumors. The second class, with poor survival, corresponded to high-grade Type 2 tumors (n=11). Dysregulation of G1/S and G2/M checkpoint genes were found in Class 1 and Class 2 tumors respectively, alongside characteristic chromosomal aberrations. We identified a 7-transcript predictor that classified samples on cross-validation with 97% accuracy. Immunohistochemistry confirmed high expression of cytokeratin 7 in Class 1 tumors, and of topoisomerase IIa in Class 2 tumors. CONCLUSIONS. We report 2 molecular subclasses of PRCC, which are biologically and clinically distinct, which may be readily distinguished in a clinical setting. Experiment Overall Design: 34 individual samples analyzed, no technical replicates. Based on histologic features and Fuhrman grading system, we designated four categories of tumors: type 1 (n = 14) characterized by small tumor cells of low Fuhrman grade (2); type 2A (n = 4) characterized by large eosinophilic tumor cells of low Fuhrman grade (2); combined type 1 and 2A (n = 5); and type 2B (n = 11) characterized by large eosinophilic tumor cells with Fuhrman grade.

Dataset Information

Gene expression characterization of high and low grade clear cell renal cell carcinoma

Publications

Characterization of clear cell renal cell carcinoma by gene expression profiling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure