Background: Neoadjuvant administration of chemotherapy provides a unique opportunity to monitor response to treatment in breast cancer and assesses response exactly. Global gene expression profiling by microarrays has been used as a valuable tool for the identification of prognostic and predictive marker genes. Even though this technology is now wide spread and relatively standardized, there are only few data available which compare established parameters with expression values to determine reliability of this method. Therefore we analyzed gene expression data of pretreatment biopsies of breast cancer patients and compared them with the results of the immunohistochemical receptor expression for ER/ PR and Her-2, as well as FISH testing for HER-2 amplification. We analyzed the change of expression of these markers before and after neoadjuvant chemotherapy. Furthermore we evaluated the predictive significance of prognostic gene signatures as described by Sorlie, van't Veer and Ahr for response to neoadjuvant chemotherapy.
Methods: Pretherapeutic core biopsies were obtained from 70 patients undergoing neoadjuvant TAC chemotherapy within the GEPARTRIO-trial. Samples were characterized according to standard pathology including ER, PR and HER2 IHC and amount of cancer cells. Only biopsies with more than 80 % tumor cells were considered for further examination. RNA was isolated and expression profiling performed using Affymetrix Hg U133 Arrays (22 500 genes). GeneData's Expressionist software was used for bioinformatic analyses.
Results: More than two thirds of the biopsies yielded sufficient amounts (> 5 microg) of RNA for expression profiling and high quality data were obtained for 50 samples. Unsupervised clustering broadly revealed a correlation with hormone receptor status. When ER-alpha, PR and HER2 as analyzed by immunohistochemistry were compared to the corresponding mRNA data from gene chips more than 90 % concordance was observed. We could observe a switch of receptor expression for ER, PR or HER-2 from positive to negative and vice versa in 16/35 cases (45.7 %) and 5/22 cases (22.7 %) respectively. The prognostic marker sets of Sorlie, van't Veer and Ahr could not discriminate responders from non-responders in our patient group.
Conclusions: Our results demonstrate that reliable expression profiles can be achieved by using limited amounts of tissue obtained during neoadjuvant chemotherapy. Microarray data capture conventional prognostic markers but might contain additional informative gene sets correlated with treatment outcome. Prognostic marker sets are not suitable to predict tumor response in the neoadjuvant setting, suggesting the necessity of class prediction methods to identify marker sets predictive for the type of therapy used.