Purpose: Prognostic and predictive markers in breast cancer are currently determined by single analysis of protein amounts. If RNA-based multi-gene analyses enter clinical practice, simultaneous determination of currently established markers like human epidermal growth factor receptor 2 (HER2), urokinase plasminogen activator (uPA) and its inhibitor (PAI-1) would represent an elegant simplification. To investigate the correlation between RNA and protein levels, we assessed HER2, uPA and PAI-1 in patients with breast cancer. In addition, we evaluated the influence of these factors on patient outcome.
Methods: We collected tumour samples from 133 patients with primary breast cancer. Protein and mRNA levels were measured for HER2, uPA and PAI-1. Protein concentration was measured by ELISA, mRNA expression was analysed by Affymetrix A133U Gene Chip and validated by quantitative PCR.
Results: We were able to demonstrate a statistically significant correlation between mRNA and protein expression for HER2 (r = 0.67, P < 0.001) and uPA (r = 0.7, P < 0.001) but not for PAI-1 (r = 0.27). We observed a prognostic information for PAI-1 mRNA and protein values. Patients with high PAI-1 mRNA expression had a reduced 10-year disease-free survival (DFS) rate (60 vs. 70%, P = 0.071) and 10-year overall survival (OS) rate (68 vs. 79%, P = 0.034). Patients with PAI-1 protein levels above 14 ng/mg protein had a reduced disease-free (10-year DFS rate 54 vs. 71%, P = 0.006) and overall survival rate (10-year OS-rate 63 vs. 83%, P = 0.018). In the patient cohort with no chemotherapy, PAI-1 mRNA levels were the strongest prognostic factor for OS in univariate and multivariate analysis.
Conclusions: Results of RNA-based multi-gene analyses of the prognostic and predictive markers HER2 and uPA correlate with the corresponding protein levels. This is not the case for PAI-1. However, PAI-1 mRNA expression might reveal new clinically relevant information in addition to PAI protein levels.
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