Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1232616 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:OBJECTIVES: Amplification of the 11q13 locus is commonly observed in a number of human cancers including both breast and ovarian cancer. Cyclin D1 and EMS1 have been implicated as candidate oncogenes involved in the emergence of amplification at this locus. Detailed analysis of the 11q13 amplicon in breast cancer led to the discovery of four regions of amplification suggesting the involvement of other genes. Here, we investigate the role of EMSY, a recently described BRCA2 interacting protein, as a key element of the 11q13 amplicon in ovarian cancer. EMSY maps to 11q13.5 and is amplified in 13% of breast and 17% of ovarian carcinomas. METHODS: EMSY amplification was assessed by fluorescent in-situ hybridization (FISH) in 674 ovarian cancers in a tissue microarray and correlated with histopathological subtype and tumor grade. A detailed map of the 11q13 amplicon in 51 cases of ovarian cancer was obtained using cDNA-array-based comparative genomic hybridization (aCGH). To further characterize the role of EMSY within this amplicon, we evaluated both the amplification profiles and RNA expression levels of EMSY and two other genes from the 11q13 amplicon in an additional series of 22 ovarian carcinomas. : EMSY amplification was seen in 52/285 (18%) high grade papillary serous carcinomas, 4/27 (15%) high grade endometrioid carcinomas, 3/38 (8%) clear cell carcinomas, and 3/10 (30%) undifferentiated carcinomas. aCGH mapping of 11q13 in ovarian cancer showed that EMSY localized to the region with the highest frequency of copy number gain. Cyclin D1 and EMS1 showed a lower frequency of copy number gain. A highly significant correlation between EMSY gene amplification and RNA expression was also observed (P = 0.0001). This was a stronger correlation than for other genes at 11q13 including Cyclin D1 and PAK1. CONCLUSIONS: These findings support the role of EMSY as a key oncogene within the 11q13 amplicon in ovarian cancer. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set
2009-06-04 | GSE16408 | GEO
Project description:A subset of ovarian cancer are characterized by 19q12 amplification. To perform funtional studies of this amplicon the profile has been determined by SNP analysis.
2010-12-24 | GSE26301 | GEO
Project description:OBJECTIVES: Amplification of the 11q13 locus is commonly observed in a number of human cancers including both breast and ovarian cancer. Cyclin D1 and EMS1 have been implicated as candidate oncogenes involved in the emergence of amplification at this locus. Detailed analysis of the 11q13 amplicon in breast cancer led to the discovery of four regions of amplification suggesting the involvement of other genes. Here, we investigate the role of EMSY, a recently described BRCA2 interacting protein, as a key element of the 11q13 amplicon in ovarian cancer. EMSY maps to 11q13.5 and is amplified in 13% of breast and 17% of ovarian carcinomas. METHODS: EMSY amplification was assessed by fluorescent in-situ hybridization (FISH) in 674 ovarian cancers in a tissue microarray and correlated with histopathological subtype and tumor grade. A detailed map of the 11q13 amplicon in 51 cases of ovarian cancer was obtained using cDNA-array-based comparative genomic hybridization (aCGH). To further characterize the role of EMSY within this amplicon, we evaluated both the amplification profiles and RNA expression levels of EMSY and two other genes from the 11q13 amplicon in an additional series of 22 ovarian carcinomas. : EMSY amplification was seen in 52/285 (18%) high grade papillary serous carcinomas, 4/27 (15%) high grade endometrioid carcinomas, 3/38 (8%) clear cell carcinomas, and 3/10 (30%) undifferentiated carcinomas. aCGH mapping of 11q13 in ovarian cancer showed that EMSY localized to the region with the highest frequency of copy number gain. Cyclin D1 and EMS1 showed a lower frequency of copy number gain. A highly significant correlation between EMSY gene amplification and RNA expression was also observed (P = 0.0001). This was a stronger correlation than for other genes at 11q13 including Cyclin D1 and PAK1. CONCLUSIONS: These findings support the role of EMSY as a key oncogene within the 11q13 amplicon in ovarian cancer. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set Using regression correlation
2010-06-25 | E-GEOD-16408 | biostudies-arrayexpress
Project description:multiplexed amplicon strategy
2020-04-29 | OEX00003182 | NODE
Project description:Comparison of different tools for metagenome taxonomic classification
| PRJEB55832 | ENA
Project description:Accompanying benchmarking sample for "TaxIt: An iterative computational pipeline for untargeted strain-level identification using MS/MS spectra from pathogenic single-organism samples": Untargeted accurate strain-level classification of a priori unidentified organisms using tandem mass spectrometry is a challenging task. Reference databases often lack taxonomic depth, limiting peptide assignments to the species level. However, the extension with detailed strain information increases runtime and decreases statistical power. In addition, larger databases contain a higher number of similar proteomes. We present TaxIt, an iterative workflow to address the increasing search space required for MS/MS-based strain-level classification of samples with unknown taxonomic origin. TaxIt first applies reference sequence data for initial identification of species candidates, followed by automated acquisition of relevant strain sequences for low level classification. Furthermore, proteome similarities resulting in ambiguous taxonomic assignments are addressed with an abundance weighting strategy to increase the confidence in candidate taxa. For benchmarking the performance of our method, we apply our iterative workflow on several samples of bacterial and viral origin. In comparison to non-iterative approaches using unique peptides or advanced abundance correction, TaxIt identifies microbial strains correctly in all examples presented (with one tie), thereby demonstrating the potential for untargeted and deeper taxonomic classification. TaxIt makes extensive use of public, unrestricted and continuously growing sequence resources such as the NCBI databases and is available under open-source BSD license at https://gitlab.com/rki_bioinformatics/TaxIt.
2020-05-11 | PXD014913 | Pride