HER-2/neu gene amplification by fluorescence in situ hybridization allows risk-group assessment in node-negative breast cancer.

: In a collective of 112 node-negative breast cancer patients, we compared the prognostic impact of HER-2/neu gene amplification (AMP) determined by fluorescence in situ hybridization (FISH) and HER-2/neu protein overexpression (EXP) measured by immunohistochemistry (IHC) with traditional prognostic factors (tumor size, grade, steroid hormone receptor status, menopausal status) and tumor invasion markers uPA (urokinase-type plasminogen activator) and its inhibitor PAI-1 determined by enzyme immunoassay (ELISA). Median follow-up in patients still alive at time of analysis was 7 years. Automated FISH and IHC were performed on parallel-cut formalin-fixed paraffin-embedded tissue sections. HER-2/neu AMP was detected by FISH in 31% and HER-2/neu EXP was measured by IHC in 41% of the cases. In 13% of the tumors, both AMP and EXP were found. FISH and IHC results were concordant in 56% of all analyzed cases. In univariate analysis, HER-2/neu AMP significantly predicted both disease-free (DFS) and overall survival (OS). HER-2/neu EXP was significant for OS, only. In multivariate analysis of all analyzed prognostic factors, HER-2/neu AMP was the only independent predictive factor for both DFS and OS. CART analysis revealed that HER-2/neu AMP together with the combination uPA/PAI-1 allowed optimal risk-group assessment after a 7-year median follow-up: patients with low levels of both uPA and PAI-1 and no HER-2/neu AMP had a significantly lower relapse rate (4.6%) than the remaining patients (32%). In conclusion, HER-2/neu gene AMP determined by FISH allowed a more accurate risk-group assessment than HER-2/neu protein EXP measured by IHC. Combining the HER-2/neu gene status measured by FISH with levels of tumor invasion markers uPA and PAI-1 improves clinically relevant risk-group assessment. In addition to its prognostic strength, the significant impact of HER-2/neu AMP on OS may reflect its ability to predict resistance to systemic therapy.