Merging microarray data from separate breast cancer studies provides a robust prognostic test

Background: There is an urgent need for new prognostic markers of breast cancer metastases to ensure that newly diagnosed patients receive appropriate therapy. Recent studies have demonstrated the potential value of gene expression signatures in assessing the risk of developing distant metastases. However, due to the small sample sizes of individual studies, the overlap among signatures is almost zero and their predictive power is often limited. Integrating microarray data from multiple studies in order to increase sample size is therefore a promising approach to the development of more robust prognostic tests. Results: In this study, by using a highly stable data aggregation procedure based on expression comparisons, we have integrated three independent microarray gene expression data sets for breast cancer and identified a structured prognostic signature consisting of 112 genes organized into 80 pair-wise expression comparisons. A classical likelihood ratio test based on these compa...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Lei Xu, Aik Choon Tan, Raimond L. Winslow, Donald Geman
• Keywords: BMCBI 2008, Breast Cancer, Distant Metastases, Prognostic