Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets.

ABSTRACT:

Background

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively.

Methods and findings

Our results show that the

SUBMITTER: Martin KJ 

PROVIDER: S-EPMC2500166 | biostudies-literature | 2008 Aug

REPOSITORIES: biostudies-literature