Abstract

Abstract Approximately 75% of all breast cancer patients is treated with endocrine therapy, based on stratification using estrogen receptor (ER) and progesterone receptor. To date, these classical biomarkers are the only ones available to predict the response to (neo)adjuvant endocrine therapy. Response to endocrine therapy depends on the presence of an active tumor-driving ER signalling pathway and, in the case of treatment with aromatase inhibitors (AI), also on aromatase-induced estradiol as the pathway activating ligand. Conventional nuclear staining for ER is not necessarily indicative of an estradiol-activated ER signalling pathway. We evaluated a recently described diagnostic computational model (Verhaegh, Cancer Research 2014) which identifies ER pathway activity based on tissue-derived target gene mRNA levels, for its clinical utility to predict neoadjuvant AI response in ER positive breast cancer patients. Tumour tissue from pre-treatment biopsies and post-treatment resection material was collected from patients with early breast cancer (>2 cm and >50% ER expression) participating in the TEAM-IIA trial, which were treated with neoadjuvant exemestane for 3 to 6 months. Using Laser Capture Microdissection (LCM), tumour cells were isolated and the probability of ER pathway activity was assessed with RT-qPCR. In total, 77 FFPE samples were analysed (51 biopsies + 26 paired resection cases). In a preliminary analysis, results were correlated with clinical response based on palpation and mammography. ER pathway activity significantly decreased during therapy (0.45 vs 0.27, two sided t-test p=0.001). Based on mammography, baseline ER activity in biopsy predicted therapy outcome after 3 months, with a higher probability of ER activity in responders, n=7, compared to non-responders, n=12, (0.73 vs 0.44, one sided t-test p=0.003). When therapy was continued up to 6 months, no correlation was found suggesting that other factors influence overall outcome of neo-adjuvant therapy. Baseline ER-pathway activity significantly predicted progressive disease by palpation at the end of therapy (mean treatment duration of 174 days, range 86-288 days) with a mean ER-pathway activity at biopsy of 0.53 vs 0.16 (p=0.01). The significant difference in baseline activity with progressive disease indicates that low ER pathway activity could be used to predict low response rates. This is supported by the observation that all progressive disease cases at end of therapy had low baseline ER activity. Furthermore, baseline activity particularly predicted early radiological response based on mammography. These preliminary results indicate that our ER pathway activity model could be able to predict response to endocrine neoadjuvant therapy. Further evaluation will be performed in order to assess the influence of post-treatment activity and other markers for response (Ki-67). *First and second author contributed equally to this work. Citation Format: Blok EJ, Alves de Inda M, Charehbili A, den Biezen E, Fruytier S, van Brussel A, Seynaeve CM, Kroep JR, Verhaegh W, van de Velde CJH, van de Stolpe A, Kuppen PJK. ER pathway activity as a predictive biomarker for neoadjuvant endocrine therapy. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-65.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call