Abstract

Genetic changes in sporadic ovarian cancer are relatively poorly characterized compared with other tumor types. We have evaluated the use of high-resolution whole genome arrays for the genetic profiling of epithelial ovarian cancer. We have evaluated 31 primary ovarian cancers and matched normal DNA for loss of heterozygosity and copy number alterations using 500 K single nucleotide polymorphism arrays. In addition to identifying the expected large-scale genomic copy number changes, >380 small regions of copy number gain or loss (<500 kb) were identified among the 31 tumors, including 33 regions of high-level gain (>5 copies) and 27 homozygous deletions. The existence of such a high frequency of small regions exhibiting copy number alterations had not been previously suspected because earlier genomic array platforms lacked comparable resolution. Interestingly, many of these regions harbor known cancer genes. For example, one tumor harbored a 350-kb high-level amplification centered on FGFR1 and three tumors showed regions of homozygous loss 109 to 216 kb in size involving the RB1 tumor suppressor gene only. These data suggest that novel cancer genes may be located within the other identified small regions of copy number alteration. Analysis of the number of copy number breakpoints and the distribution of the small regions of copy number change indicate high levels of structural chromosomal genetic instability in ovarian cancer.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.