Abstract S2-4: Final Results of a Prospectively Planned Biomarker Analysis: HER1-3 as Predictive Markers of Benefit from Early Treatment with Aromatase Inhibitors Versus Tamoxifen in the TEAM Pathology Sub-Study.

Abstract

Background: The Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial included prospectively planned biomarker studies to identify predictive biomarkers for patients receiving endocrine therapy. Quantitative IHC data for ER/PgR, HER1, HER2, HER3 and FISH analysis of HER2 in all cases was available for the current analysis relative to outcome of estrogen receptor-positive (ER+) early breast cancer patients treated with exemestane versus tamoxifen. Patients & Methods: Pathology blocks from 4598 TEAM patients were collected and tissue microarrays constructed. Quantitative analysis of receptors (HER1/2/3) by conventional IHC, and FISH (for HER2 only) were analysed relative to disease-free survival and treatment on an intent to treat basis using survival data for the first 2.75 years of the TEAM trial. Results: Of 4595 eligible cases samples received, 16 were excluded, and 4010 had complete biomarker data for all markers (HER1/HER2 & HER3) for the final biomarker analysis, 3.5% were HER1 positive, 13% HER2 positive & 21% HER3 positive. 1248 (31%) cases were HER1or2or3 positive (HER1-3+ve). HER1-3 positivity was associated with poor outcome (HR=1.6 95%CI=1.3-2.0). In HER1-3 negative patients the hazard ratio (for risk of relapse on exemestane versus tamoxifen in the first 2.75 years) was 0.68 (95% CI = 0.52-0.89), for the HER1-3 positive cases the hazard ratio was 1.14 (95% CI = 0.83-1.56) with a significant treatment by marker interaction (HR=1.68 95%CI=1.1-2.5; p=0.0014 in multivariate analysis). Trends for similar effects were seen for HER1 negative (-ve) vs HER1 positive (+ve) (HRs 0.80, 95%CI=0.65-0.99 vs 1.63 95%CI=0.74-3.59), HER2-ve vs HER2+ve (HRs 0.71, 95%CI=0.57- 0.9 vs 1.69 95%CI=108-2.63) and HER3-ve vs HER3+ve (HRs 0.78 95%CI=0.62-0.99 vs 1.04 95%CI=0.67-1.62) breast cancers. Conclusion: Preferential exemestane versus tamoxifen treatment benefit was seen in HER1/2/3 negative cases, whilst HER1/2/3 positive cases had a poor prognosis in this endocrine treated population (suggesting a degree of resistance to endocrine therapy), and no evidence of additional benefit from AIs versus tamoxifen. These three Type I receptor tyrosine kinases appear to identify breast cancers with relative resistance to all forms of endocrine therapy. This prospectively planned and powered treatment by marker analysis provides high level scientific evidence which may assist clinicians and patients in determining optimal AI schedules for women with early breast cancer. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr S2-4.

Do type 1 receptor tyrosine kinases inform treatment choice? A prospectively planned analysis of the TEAM trial

“…Patient demographics and tumour characteristics were similar between the analysed subset and all patients in the pathology substudy; patients in the pathology subset were at slightly higher risk than the entire TEAM population (Bartlett et al , 2010) (Supplementary Table 1: CONSORT table).…”

“…However, there was no apparent differential benefit among HER3-negative or HER3-positive patients (HR=0.80; 95% CI, 0.64–0.99 vs HR=1.00; 95% CI, 0.65–1.53; interaction test HR=0.80; 95% CI, 0.50–1.29; P =0.36; Figure 2A). In a second exploratory analysis, tumours expressing either HER1 or HER2 were assumed (by the formation of active homo- or heterodimers) to exhibit ‘active HER signalling', whereas tumours lacking HER1, HER2, and HER3 expression or expressing HER3 only were assumed to exhibit limited ‘HER signalling' (Bartlett et al , 2010). A significant (exemestane vs tamoxifen) treatment-by-marker (‘active HER signalling' vs cases without ‘active HER signalling') interaction (HR=0.42; 95% CI, 0.27–0.65; P <0.001; Figure 2B) suggests that patients with active HER signalling do not derive benefit from early exemestane treatment.…”

Exemestane in the Adjuvant Treatment of Breast Cancer in Postmenopausal Women

“…97 Translational studies may identify prognostic markers that can improve the classification of individual risk for relapse and thereby provide guidance in selection of the optimal AI therapy for an individual patient. [98][99][100][101][102][103][104][105][106][107][108] These studies may also identify predictive factors for benefit from each AI and possibly determine patient subsets that preferentially benefit from a particular AI.…”