Abstract:
:Analysis of ovarian carcinomas has shown that karyotypes are often highly abnormal and cannot be identified with certainty by conventional cytogenetic methods. In this study, 17 tumors derived from 13 patients were analyzed by a combination of spectral karyotyping (SKY), comparative genomic hybridization (CGH), and expression microarrays. Within the study group, a total of 396 chromosomal rearrangements could be identified by SKY and CGH analysis. When the distribution of aberrations was normalized with respect to relative genomic length, chromosomes 3, 8, 11, 17, and 21 had the highest frequencies. Parallel microarray expression studies of 1718 human cDNAs were used to analyze expression profiles and to determine whether correlating gene expression with chromosomal rearrangement would identify smaller subsets of differentially expressed genes. Within the entire set of samples, microarray expression analysis grouped together poorly differentiated tumors irrespective of histological subtype. For three patients, a comparison between genomic alterations and gene expression pattern was performed on samples of primary and metastatic tumors. Their common origin was demonstrated by the close relationship of both the SKY and CGH karyotypes and the observed profiles of gene expression. In agreement with the pattern of genomic imbalance observed for chromosome 3 in ovarian cancer, the relative expression profile with respect to a normal ovary exhibited a contiguous pattern of reduced expression of genes mapping to the 3p25.5-3p21.31 and increased expression of genes from 3q13.33-3q28. This study demonstrates that SKY, CGH, and microarray analysis can in combination identify significantly smaller subsets of differentially expressed genes for future studies.
journal_name
Cancer Resjournal_title
Cancer researchauthors
Bayani J,Brenton JD,Macgregor PF,Beheshti B,Albert M,Nallainathan D,Karaskova J,Rosen B,Murphy J,Laframboise S,Zanke B,Squire JAsubject
Has Abstractpub_date
2002-06-15 00:00:00pages
3466-76issue
12eissn
0008-5472issn
1538-7445journal_volume
62pub_type
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