Ovarian Cancer CGH

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