Derivation of molecular signatures for breast cancer recurrence prediction using a two-way validation approach

Yijun Sun, Virginia Urquidi, Steve Goodison
2009 Breast Cancer Research and Treatment  
Previous studies have demonstrated the potential value of gene expression signatures in assessing the risk of post-surgical breast cancer recurrence, however, many of these predictive models have been derived using simple computational algorithms and validated internally or using one-way validation on a single dataset. We have recently developed a new feature selection algorithm that overcomes some limitations inherent to high-dimensional data analysis. In this study, we applied this algorithm
more » ... o two publicly available gene expression datasets obtained from over 400 patients with breast cancer to investigate whether we could derive more accurate prognostic signatures and reveal common predictive factors across independent datasets. We compared the performance of three advanced computational algorithms using a robust two-way validation method, where one dataset was used for training and to establish a prediction model that was then blindly tested on the other dataset. The experiment was then repeated in the reverse direction. Analyses identified prognostic signatures that while comprised of only 10-13 genes, significantly outperformed previously reported signatures for breast cancer evaluation. The cross-validation approach revealed CEGP1 and PRAME as major candidates for breast cancer biomarker development. Keywords Microarray; Breast cancer prognosis; Predictive model; PRAME Breast cancer is the second most common cause of death from cancer among women in the United States. In 2009, it is estimated that about 182, 480 new cases of breast cancer will be diagnosed, and 40, 930 women are expected to die from this disease. The major clinical problem of breast cancer is the recurrence of disseminated disease. Adjuvant therapy (chemotherapy and hormonal therapy) reduces the risk of distant metastases by one-third, however, it is Correspondence to: Goodison Steve, steve.goodison@jax.ufl.edu. Electronic supplementary material: The online version of this article (
doi:10.1007/s10549-009-0365-6 pmid:19291396 pmcid:PMC2844120 fatcat:tsjqjzewhndhlajoi4goi2msdu