Do type 1 receptor tyrosine kinases inform treatment choice|[quest]| A prospectively planned analysis of the TEAM trial

Aromatase inhibitors (AIs) confer a disease-free survival (DFS) benefit over and above that achieved with adjuvant tamoxifen in postmenopausal women with early oestrogen-or progestrone-receptor (ER/PgR)-positive breast cancer (Thurlimann et al, 2005; Forbes et al, 2008; van de Velde et al, 2011). Recent data from the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) and Breast International Group (BIG) 1–98 trials suggest that DFS is similar in patients treated with either an AI for 5 years or ‘switched’ to an AI following 2–3 years of tamoxifen (Thurlimann et al, 2005; van de Velde et al, 2011). This observation has generated debate regarding the optimal treatment strategy (upfront AIs vs switch) for postmenopausal ER/PgR-positive breast cancer. As, for all strategies, the benefit of AIs vs tamoxifen is modest when compared with tamoxifen vs no endocrine treatment (Abe et al, 2005; Viale et al, 2009), there is considerable impetus for translational studies aimed at identification of those patients most likely to benefit from upfront AIs. The differences in benefit between hormonal regimens may be explained, in part, by the diverse biology of breast cancer, particularly the differences between luminal A and luminal B cancers (Perou et al, 2000). Clearly, multiple factors may influence differential response to hormonal treatments. Including HER2, Ki-67, and RAS/RAF or PI3K/Akt signalling (Beeram et al, 2007; Viale et al, 2008). Future selection of optimal endocrine therapy for early breast cancer will need to be personalised based on studies identifying an increasing number of patient subsets with unique molecular profiles, for example (Curtis et al, 2012). Selecting optimal adjuvant endocrine therapy and/or chemotherapy is currently influenced by measures of residual risk (Van Belle et al, 2010). However, selection between endocrine agents (AIs vs tamoxifen) requires specific markers indicating differential benefit from these agents. We have previously shown, within TEAM, that quantitative analysis of ER and PgR expression combined with clinicopathologic factors (age, tumour size and grade, and nodal status) can identify patients at higher risk for early recurrence (Bartlett et al, 2011). We confirmed previous data indicating that PgR, although prognostic, is not a predictive marker of benefit from AI vs tamoxifen (Dowsett et al, 2008; Simon et al, 2009). Our study was, unlike previous studies, based on an adequately powered and prospectively planned treatment-by-marker analysis, satisfying criteria for high-level evidence (Simon et al, 2009). Type 1 receptor kinase expression (HER1, HER2, and HER3 (HER1–3)) is associated with a higher probability of early relapse in tamoxifen-treated patients (Tovey et al, 2004, 2005), consistent with both preclinical and clinical data suggesting overexpression of HER2, and HER1/EGFR confer resistance to tamoxifen (Benz et al, 1992; Carlomagno et al, 1996; Houston et al, 1999). Conversely, neoadjuvant studies suggest that AIs are effective regardless of HER1 or HER2 overexpression (Ellis et al, 2001; Dixon et al, 2004). On the basis of these observations, we hypothesised that overexpression of HER1, HER2, and/or HER3 is associated with a differential benefit of an AI compared with tamoxifen in the adjuvant setting, and that outcome in patients with HER1–3-positive tumours would be improved by initiating treatment with an AI rather than tamoxifen. The analysis presented here was prospectively planned and powered to test the hypothesis, within the TEAM study, that HER1–3 status acts as a predictive biomarker for benefit of exemestane vs tamoxifen during the 2.75 years prior to the switch point. In general, patients had histologically or cytologically confirmed T1-3 N0-2 M0 breast adenocarcinoma and were treated with surgical resection followed by radiotherapy and/or adjuvant chemotherapy. Among countries participating in the TEAM trial, five (United Kingdom/Ireland, The Netherlands, Belgium, Germany, and Greece) provided tumour samples for this substudy after appropriate ethical review. The predictive value of HER expression was assessed using Cox proportional hazards regression models. Interactions between treatment arms and HER expression levels were evaluated using the Wald chi-square (χ2) statistic. The predictive value of HER expression was further investigated in multivariate analyses, consistent with REMARK guidelines (McShane et al, 2006), adjusting for known prognostic factors: patient age (continuous variable); tumour size (continuous variable); number of positive nodes (continuous variable); treatment with chemotherapy (yes/no); treatment arm (tamoxifen/exemestane); and expression of HER1–3 (negative/positive), ER, PgR, and Ki67 (each a continuous variable). Continuous variables were evaluated for nonlinearity by applying simple log transformations followed by more complex fractional polynomials, and the best-fitting transformation was applied as assessed by the change in Akaike’s information criterion between univariate Cox proportional hazard models of transformed and untransformed data (Collett, 1994). Treatment allocation was included as a time-dependent covariate to investigate the impact of switching on the tamoxifen randomised arm. The proportional hazards assumption was investigated and time and covariate interactions were analysed to evaluate changing effects with time. All data were analysed using SAS/STAT statistical software (SAS Institute, Cary, NC, USA). As expected, given the time dependence of the HER1–3/treatment interaction term, assessment of the proportional hazard assumptions of the Cox model shows that the hazard of disease is not proportional between the two groups (Figure 5). Relapse risks clearly diverge between 0–3 years indicating that the hazard of disease during this time period for the two groups are not proportional. After 3 years, the proportionality assumptions are met. Therefore, the inclusion of the interaction with time of the treatment-by-marker interaction term is justified and explains the lack of evidence for treatment-by-marker interaction with extended follow-up without the use of a time-dependent model. The results of this prospectively planned translational study show that expression of HER1, HER2, or HER3 predicts a differential benefit from initial adjuvant therapy with an AI compared with tamoxifen, which is shown to be both real and time dependent. In a prospectively planned and powered analysis, a significant DFS benefit in favour of initiating treatment with exemestane was observed among patients with HER1–3-negative tumours, in both univariate and multivariate analyses including the treatment-by-marker interaction (Figure 1, Table 1). Strikingly, this study did not show any benefit associated with initial exemestane treatment vs tamoxifen in patients with HER1-, HER2-, or HER3-positive tumours suggesting these tumours are partially resistant to endocrine therapy (Shou et al, 2004; Folgiero et al, 2008; Massarweh et al, 2008; Osborne et al, 2011). However, lack of overexpression of HER1, HER2, or HER3 is confirmed as an independent predictive biomarker for early AI benefit in patients with ER/PgR-positive early breast cancer. Exploratory analyses suggested that this effect was largely driven by HER1/HER2 expression, consistent with predicted HER signalling activity (HER3 lacks significant signalling potential) (Yarden and Pines, 2012). Therefore, assessing HER1/HER2 could provide valuable information in clinical practice in ER-positive disease (Hudelist et al, 2003; Sassen et al, 2008). Finally, in an exploratory time-dependent analysis (Figure 5), we identified a difference in the risk of relapse, relative to other tumours, associated with HER1–3-negative tumours treated with exemestane as time progressed. This time-dependent effect ultimately negates the treatment benefit observed in the pre-planned analysis (performed at 2.75 years) such that by 6.5 years median follow-up, no significant interaction between initial endocrine treatment and outcome is observed. Strikingly, in an exploratory analysis of DFS from treatment switch time point (2.75 years), the interaction term was inverted owing to the time-dependent effect in the HER1–3-negative exemestane group (data not shown). Nonetheless the time-dependent analysis confirms the statistical robustness of the interaction during the initial treatment period prior to switching from tamoxifen to exemestane. The lack of DFS benefit associated with exemestane in the HER1–3-positive subset observed in the current study is entirely consistent with data from transATAC (an ATAC substudy) indicating no difference between benefit from tamoxifen and anastrozole in HER2-positive cancers (Dowsett et al, 2008). In HER2-positive ATAC patients, recurrence rates were 18.8% among tamoxifen-treated patients vs 19.8% among anastrozole-treated patients (Dowsett et al, 2008). Conversely, in HER2-negative patients, 5-year recurrence rates were 9.0% for tamoxifen-treated vs 5.9% for anastrozole-treated patients (Dowsett et al, 2008). These data are consistent with a HER2 treatment-by-marker interaction HR of ~0.6, similar to that observed in the present study when patients received either tamoxifen or exemestane (prior to 2.75 years). In BIG-1–98, the possibility of a similar interaction between treatment and HER2 status is suggested by the fact that 48 fewer events were observed in the AI treatment arm for HER2-negative patients vs 13 more events in the AI-treated vs tamoxifen-treated HER2-positive group (Viale et al, 2009). A future meta-analysis of this effect across multiple trials (in collaboration with the AI overview group) will be important in evaluating whether effects of HER2 signalling are consistent across multiple trials. Another striking observation in the TEAM study is the time dependency of the interaction between HER1–3 and treatment (Figures 1 and 4). The subgroup of patients with HER1–3-negative tumours treated with exemestane experience a time-dependent increase in risk of disease relapse when compared with all other patients (Figure 5). This increase progressively erodes the benefit of early treatment with exemestane relative to tamoxifen in the HER1–3-negative group. This apparently paradoxical effect does not appear to occur in either the ATAC or BIG-1–98 studies. How then, could it be explained? The key difference between ATAC/BIG-1–98 and TEAM is that the TEAM addresses specifically a switch from tamoxifen to AIs, whereas ATAC/BIG-1–98 predominantly address AIs vs 5 years of tamoxifen. Further analysis of the effect observed in the TEAM study could be performed in the relatively small switching arms within BIG-1–98. Exploration of a time-dependent effect of these different strategies is warranted; however, if such a time-dependent effect is not observed, the challenge of explaining our observations remains. We speculate that a proportion of HER1–3-negative early breast cancers are primed to develop endocrine resistance, as distinct from those with primary endocrine resistance, and that for a proportion of these cases AIs prevent or delay early recurrence. If our admittedly speculative hypothesis is correct, those cases where AIs delay recurrence may explain the increase in risk for HER1–3-negative patients observed in TEAM, while cases where switching from tamoxifen to AIs provides benefit may explain the convergence of the event rates for HER1–3-negative patients treated with tamoxifen followed by exemestane to those treated with AIs alone. Although we cannot speculate as to the molecular mechanisms relating to these trends, they reflect clinical experience with delayed recurrence following endocrine therapy. Biomarker analyses raise questions relating to which biomarkers should be included in a risk assessment panel to achieve an optimal result, and how should data be interpreted? Overexpression of HER2 is associated with poor prognosis (Slamon et al, 1989), and the current analysis suggests that patients with HER1–3-positive tumours are at increased risk of early relapse regardless of treatment with exemestane vs tamoxifen consistent with previous data that signalling through multiple members of the HER family is associated with endocrine resistance (Tovey et al, 2004, 2005; Naresh et al, 2006). In patients with HER1–3-negative tumours, the question becomes whether these patients benefit from upfront AI treatment rather than tamoxifen. Assessing signalling potential suggests that exemestane provides a significant differential DFS benefit vs tamoxifen in tumours with ‘inactive’ HER1–3 signalling (Figure 3). These results suggest that the receptor activation may better indicate tumour response to adjuvant therapy than simple expression. The TEAM trial was conducted before introduction of adjuvant HER2-directed therapies, and for women eligible for HER2-directed therapy, an additional dimension exists in understanding the impact of such therapy. In conclusion, upfront exemestane provided a superior DFS benefit compared with tamoxifen in tumours that were HER1–3-negative or had inactive HER signalling. The time dependency of this effect was explained by a progressive increase in relapse risk, over time, in HER1–3-negative patients treated with exemestane. These results warrant further confirmation in meta-analyses. Tumours that are HER1–3-positive appear to be relatively resistant to endocrine therapy. Pragmatically in clinical practice, HER2 results should provide adequate information for selection of early endocrine therapy although the addition of HER1/EGFR results will be of benefit to a small proportion of patients. Annette Hasenburg has received support for travel expenses to meetings for the study, payment for lectures (honoraria), and expert testimony from Pfizer. Dirk G Kieback has received speaker’s honoraria and research grant funding from Pfizer. Christos Markopoulos has received speaker’s honoraria and educational grants from AstraZeneca (UK), Novartis (Basel, Switzerland), Pfizer Inc. (New York, NY, USA) and Genomic Health Inc. (USA). Elizabeth A Mallon has received speaker’s honoraria from Roche Pharmaceuticals. Daniel W Rea has received consultancy fees from Pfizer, Novartis, and Astra Zeneca. All remaining authors have declared no conflict of interest. We gratefully acknowledge the support of all pathologists, treating physicians, and the participation of all patients who consented to provide paraffin blocks for the study. Cassandra L Brookes was the lead statistician conducting analyses for the TEAM pathology substudy. Tammy Robson, Nicola Lyttle, and Mary Anne Quintayo were the highly trained observers who manually scored tissue cores. This study was conducted with the support of the Ontario Institute for Cancer Research through funding provided by the Government of Ontario. The TEAM trial is a multinational study supported by an unrestricted research grant by Pfizer Inc., and funding from Cancer Research UK (grant number C7602/A7215). Editorial support was provided by Tamara Fink, PhD, of Accuverus, a division of ProEd Communications, Inc., Beachwood, Ohio, and was funded by Pfizer Inc. Clinical trials registration numbers: NCT00036270, NCT00032136, NCT00279448, NTR 267, Ethics Commission Trial 27/2001, and UMIN C000000057. Supplementary Information accompanies this paper on British Journal of Cancer website