five

Gene expression patterns associated with p53 status in breast cancer

收藏
NIAID Data Ecosystem2026-03-08 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE3178
下载链接
链接失效反馈
官方服务:
资源简介:
Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function). In this study, the p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. Each cell line displayed unique patterns of gene expression, but cell type specific trends were evident. A common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss in primary breast tumors and predicted relapse-free survival and overall survival in independent test data sets. Keywords: untreated x treated We analyzed 48 arrays performed using 48 polyA RNA samples. RNAs were collected from cell lines treated with an IC50 dose of doxorubicin hydrochloride or with a feeding control. Each cell line had its own reference which represented the second sample on the dual channel array. These untreated RNAs were prepared by pooling four harvests of that cell line at 60-80% confluence and 48h after feeding
创建时间:
2015-07-17
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作