Prediction of chemotherapy response in breast cancer by using a four-gene panel including osteopontin, activating leukocyte cell adhesion molecule (ALCAM), HER2 and estrogen receptor (ER)

• Published in: Cancer research (Chicago, Ill.) Vol. 69; no. 2_Supplement; p. 2033
• Main Authors: Ihnen, M, Müller, V, Wirtz, RM, Milde-Langosch, K, Witzel, I, Lisboa, BW, Jänicke, F
• Format: Journal Article
• Language: English
• Published: 15.01.2009
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/0008-5472.SABCS-2033

Abstract Abstract #2033 Background: Several prognostic factors such as TNM-stage, hormone receptor and HER2 status refer to therapeutical decisions towards adjuvant chemotherapy. Up to now it is still difficult to predict the response to chemotherapy for a single patient, which is a challenging problem in order to spare patients from cost-intensive ineffective treatment and adverse side effects. Therefore there is urgent need for additional predictive markers. Our previous findings implicated that tumor tissue expression of Activated Leucocyte Cell Adhesion Molecule (ALCAM/CD166) is associated with chemotherapy response. Osteopontin (OPN) has been described as prognostic marker in breast cancer and recently it was shown that high OPN levels in vitro mediate chemoresistance of breast cancer cells by inhibition of apoptosis. If these findings result in chemoresistance in vivo has not been investigated so far. Material and Methods: Primary breast cancer tissues from 100 patients treated with Taxane-free adjuvant standard chemotherapy regimen were collected at surgery prior to any additional therapy. The median follow-up time was 81 months. We analyzed ALCAM and OPN mRNA expression in the biological context of additional and predefined breast cancer markers, like estrogen receptor (ER), Her-2/neu (HER2), members of the urokinase plasminogen activator (uPA) system, vascular endothelial growth factor (VEGF) using oligonucleotide microarrays (Affymetrix HG-U133A). Hierarchical cluster analysis was performed to develop a gene algorithm predicting outcome after standard chemotherapy. Results: In contrast to ALCAM overexpression, which was associated with better outcome upon chemotherapy, OPN overexpression was associated with a significantly higher recurrence rate (p=0,027), but not with shorter overall survival. In addition, there were significant positive correlations of OPN with uPA, PAI-1, uPAR and VEGF-A mRNA expression. By cluster analysis based on the four markers ER, HER2, ALCAM and OPN, we identified a group of high-risk patients, which was characterized by low ER and HER2 expression, high OPN and low ALCAM levels, and with significantly shorter recurrence-free and overall survival (p<0,001). Discussion: In our cohort of patients the combination of ALCAM, OPN, ER and HER2 expression levels turned out as valuable predictive marker for response to adjuvant Taxane-free chemotherapy. The ratio of high OPN and low ALCAM levels was particularly associated with chemoresistance and a poor prognosis in tumors having low ER and HER2 expression levels. We hypothesize that this simple four-gene panel could help to reassign an optimized therapy to the single patients. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2033.