Dataset Information

CGH profiling of 26 Ewing Sarcoma tumour samples

ABSTRACT: Ewing’s Sarcoma (ES) is characterized by specific chromosomal translocations, the most common being t(11;22)(q24;q12). Additionally, other types of genetic abnormalities may occur and be relevant to explain the variable tumoural biology and clinical outcome. We have carried out a high-resolution array CGH and expression profiling on 25 ES tumour samples to characterize the DNA copy number aberrations (CNA) occurring in these tumours and to determine their association with gene expression profiles (GEO Series accession number: GSE8303) and their clinical outcome. CNA were observed in 84% of the cases. We observed a median number of 3 aberrations per case. Besides numerical chromosomal changes, smaller aberrations were found and defined at chromosomes 5p, 7q and 9p. All CNA were compiled to define the smallest overlapping regions of imbalance (SORI). Thirty five SORI were delimited. Bioinformatic analyses were conducted to identify subgroups according to the pattern of genomic instability obtained. Unsupervised and supervised clustering analyses (using SORI as variables) segregated the tumours into two distinct groups: one genomically stable (≤ 3 CNA) and another genomically unstable one (> 3 CNA). The genomic unstable group showed a statistically significant shorter overall survival and was more refractory to chemotherapy. This report elucidates data about genomic instability in ES, based on CNA and expression profiling for the first time, and shows that a genomically unstable group of Ewing tumours is correlated with a significant poor prognosis. Keywords: Comparative Genomic Hybridization - array; Genomic Instability

ORGANISM(S): Homo sapiens

PROVIDER: GSE8398 | GEO | 2007/11/09

SECONDARY ACCESSION(S): PRJNA101447

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

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.

Dataset Information

CGH profiling of 26 Ewing Sarcoma tumour samples

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets