Quantitative real-time RT-PCR analysis of eight novel estrogen-regulated genes in breast cancer.

BACKGROUND: Biological markers capable of predicting the risk of recurrence and the response to treatment in breast cancer are eagerly awaited. Estrogen and progesterone receptors (ER, PgR) in tumor cells mark cancers that are more likely to respond to endocrine treatment, but up to 40% of such patients do not respond. Here, the expression of a group of estrogen-regulated genes, previously identified by microarray analysis of in vitro models, was measured in breast tumors and possible associations with other clinicopathological variables were investigated. METHODS: The expression of CD24, CD44, HAT-1, BAK-1, G1P3, TIEG, NRP-1 and RXRalpha was measured by quantitative real-time RT-PCR on RNA from eighteen primary breast tumors. Statistical analyses were used to identify correlations among the eight genes and the available clinicopathological data. RESULTS: Variable expression levels of all the genes were observed in all the samples examined. Significant associations of CD24 with tumor size, CD44 with lymph node invasion, and HAT-1 and BAK-1 with ER positivity were found. The possible combinatorial value of these genes was assessed. Unsupervised hierarchical clustering analysis demonstrated that the expression profile of these genes was able to predict ER status with an acceptable approximation. CONCLUSIONS: Eight novel potential markers for breast cancer have been preliminarily characterized. As expected from in vitro data, their expression is able to discriminate ER- versus ER+ tumors.