Abstract

22009 Background: Laboratory assessment of HER2 is of marked clinical importance. Accurate quantification remains problematic within and between laboratories. Here we report central laboratory HER2 results comparing IHC and quantitative RT-PCR using Oncotype DX in patients enrolled in a large adjuvant breast cancer trial. Methods: 755 patients with 0 to 3 positive lymph nodes from Intergroup study E2197 were studied. Central IHC for HER2 was performed using duplicate 1.0 mm microarrays (HercepTest; Dako). Percent positive cells and staining intensity (0–3+) was assessed, where IHC positive cases exhibited 3+ staining in >30% cells, IHC equivocal cases exhibited 3+ staining in <30% cells or 2+ staining, and IHC negative cases exhibited 0 or 1+ staining. Quantitative RT-PCR for HER2 used Oncotype DX and pre-defined cutoffs: positive ≥11.5 units, equivocal >10.7-<11.5 units, and negative ≤10.7 units (each unit represents a 2-fold change in expression). Concordance analysis excluded the equivocal range from both assays according to ASCO/CAP Guidelines (Wolff et al, 2006). Results: HER2 expression by IHC and by RT-PCR is shown in the Table below. 175 cases were equivocal by IHC (165 of these were HER2 negative by RT-PCR). 26 cases were equivocal by RT-PCR (3 of these were HER2 negative by IHC). The overall concordance for HER2 status by central IHC and central RT-PCR was 95% (95% CI, 92%, 96%). Conclusions: There is a high degree of overall concordance between central IHC and central RT-PCR positive and negative HER2 cases. Assessment of HER2 status by RT-PCR using Oncotype DX is an alternative to IHC. FISH is in progress and results will be reported. IHC - RT-PCR HER2 Concordance HER2 Central IHC Positive Central IHC Equivocal Central IHC Negative Total RT-PCR RT-PCR Positive 94 0 4 98 RT-PCR Equivocal 13 10 3 26 RT-PCR Negative 27 165 439 631 Total IHC 134 175 443 755 Author Disclosure Employment or Leadership Consultant or Advisory Role Stock Ownership Honoraria Research Expert Testimony Other Remuneration Genomic Health

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