Ontology highlight
ABSTRACT:
PROVIDER: PRJNA246223 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Frozen tumour samples of 131 gastric cancer patients [array CGH]
| PRJNA246222 | ENA
Project description:In this study, we investigated CNAs of 59 tumor samples from 27 patients with submucosal-invasive gastric cancers (SMGC) by 44k oligonucleotide-based array comparative genomic hybridization (array CGH).
2012-01-20 | GSE26800 | GEO
Project description:We sought to illustrate molecular subtypes associated with clinical prognosis and to identify genetic aberrations for potential targeted therapeutics through comprehensive whole-genome analysis of 131 Chinese gastric cancer tissue specimens using whole-genome array CGH.
2014-05-06 | GSE57302 | GEO
Project description:Genomic copy number aberrations of 11 gastric cancer cell lines were analyzed by 244k CGH array from Agilent Technologies. Based on this results, we separated the 11 cell lines into 2 groups, with and without copy number increase at chromosome 20q13
2016-04-01 | GSE67604 | GEO
Project description:We sought to illustrate molecular subtypes associated with clinical prognosis and to identify genetic aberrations for potential targeted therapeutics through comprehensive whole-genome analysis of 131 Chinese gastric cancer tissue specimens using whole-genome array CGH. We profiled 131 Chinese gastric cancer genomes using Agilent 244K array CGH technology. 70 samples Among them were further profiled by Affymetrix Hu133Plus2 arrays for mRNA expression.
2014-05-06 | E-GEOD-57302 | biostudies-arrayexpress
Project description:Array CGH analysis was done with 56 primary gastric cancers to elucidate prognostic biomarkers on the BAC basis.
2010-08-10 | GSE15436 | GEO
Project description:Gene expression profiling of 82 patients with cervical cancer was performed. The expression data were correlated with copy number alterations of the same patients, as assessed with array CGH in a separate study, in order to identify drivers of cervical cancer carcinogenesis.
2013-01-31 | GSE27469 | GEO
Project description:The series represents the analysis data of four TAR syndrome patients by submegabase resolution BAC array. Keywords: array CGH
2007-01-07 | GSE5781 | GEO
Project description:A series of studies have been published that evaluate the chromosomal copy number changes of different tumor classes using array Comparative Genomic Hybridization (array CGH), however the chromosomal aberrations that distinguish the different tumor classes have not been fully characterized. Therefore, we performed a meta-analysis of different array CGH data sets in an attempt to classify samples tested across different platforms. As opposed to RNA expression a common reference is used in dual channel CGH arrays: normal human DNA, theoretically facilitating cross-platform analysis. To this aim, cell line and primary cancer data sets from three different dual channel array CGH platforms obtained by four different institutes were integrated. The cell line data were used to develop preprocessing methods which performed noise reduction and transformed samples into a common format. The transformed array CGH profiles allowed perfect clustering by cell line, but importantly not by platform or institute. The same preprocessing procedures used for the cell line data were applied to data from 373 primary tumors profiled by array CGH, including controls. Results indicated that there is no apparent feature related to the institute or platform and that array CGH allows for unambiguous cross-platform meta-analysis. Major clusters with common tissue origin were identified. Interestingly, tumors of hematopoietic and mesenchymal origins cluster separately from tumors of epithelial origin. Therefore it can be concluded that chromosomal aberrations of tumors from hematopoietic and mesenchymal origin versus tumors of epithelial origin are distinct, and these differences can be picked up by metaanalysis of array CGH data. This suggests the possibility of prospectively using combined analysis of diverse copy number datasets for cancer subtype classification. Keywords: comparative genomic hybridization, meta-analysis, cancer
2006-08-29 | GSE5051 | GEO