Expression profiles of 290 ESTs mapped to chromosome 3 in human epithelial ovarian cancer cell lines using DNA expression oligonucleotide microarrays

利用DNA表达寡核苷酸微阵列技术,分析了定位于3号染色体上的290个EST在人卵巢上皮癌细胞系中的表达谱。

阅读:1

Abstract

We have investigated previously the utility of oligonucleotide expression microarray technology in an analysis of four spontaneously transformed epithelial ovarian cancer (EOC) cell lines, TOV-21G, TOV-81D, OV-90, and TOV-112D. Here, we examine the expression of 290 expressed sequence tags (ESTs) that map to human chromosome 3 in a primary culture derived from normal ovarian surface epithelium (NOSE), NOV-31, and the four spontaneously transformed EOC cell lines. One of these cell lines, OV-90, harbors a deletion of an entire chromosome 3p arm. Whereas the most aggressive cell lines (OV-90, TOV-112D, and TOV-21G) exhibited the highest levels of expression, assessed by the mean of expression values of all ESTs, OV-90 showed the lowest mean of expression of ESTs that map to the 3p arm in comparison with TOV-112D and TOV-21G. This difference in expression profile of 3p ESTs in OV-90 is also reflected in the ratio of expression of ESTs on 3p versus the 3q arm and in that the expression values of ESTs that map to 3p were more often lower than higher in OV-90 in two-way comparisons with NOV-31, TOV-21G, and TOV-112D. The loss of a 3p arm does not affect the pattern of differential expression in analyses based on the range of numeric expression values of each EST or fold differences in expression for each EST in comparison with NOV-31. However, 25 differentially expressed ESTs were identified on the basis of threefold differences in expression values between NOV-31 and any EOC cell line; and six of these ESTs were differentially expressed uniquely in OV-90. The investigation of these ESTs could facilitate the identification of novel chromosome 3 genes implicated in ovarian tumorigenesis.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。