Identification of a gene signature in cell cycle pathway for breast cancer prognosis using gene expression profiling data.

ABSTRACT:

Background

Numerous studies have used microarrays to identify gene signatures for predicting cancer patient clinical outcome and responses to chemotherapy. However, the potential impact of gene expression profiling in cancer diagnosis, prognosis and development of personalized treatment may not be fully exploited due to the lack of consensus gene signatures and poor understanding of the underlying molecular mechanisms.

Methods

We developed a novel approach to derive gene signatures for breast cancer prognosis in the context of known biological pathways. Using unsupervised methods, cancer patients were separated into distinct groups based on gene expression patterns in one of the following pathways: apoptosis, cell cycle, angiogenesis, metastasis, p53, DNA repair, and several

SUBMITTER: Liu J 

PROVIDER: S-EPMC2551605 | biostudies-literature | 2008 Sep

REPOSITORIES: biostudies-literature