Abstract CT074: Pre-existing ESR1 mutations in early-stage primary breast cancer predict failure of endocrine therapy and poor survival

Abstract

Background
More than three-quarters of primary breast cancers are positive for estrogen receptor alpha (ER; encoded by the gene ESR1), the most important factor for directing anti-estrogenic endocrine therapy. Although mutation in ESR1 is known as an acquired mechanism of resistance to endocrine therapy (ET), found in 12-55% of metastatic breast cancers treated previously with ET, the impact of ESR1 mutation on therapy response in primary breast cancer is unclear.
Patients and Methods
In this study we analyzed 3217 real-world and population-based early-stage primary breast cancers (within the SCAN-B study, ClinicalTrials.gov NCT02306096). Tissues were sampled from initial diagnosis prior to any treatment and analyzed for the presence of ESR1 mutations using RNA sequencing. Mutations were verified by SAGAsafe droplet digital PCR.
Results
We identified ESR1 resistance mutations in 30 cases (0.9%), of which 29 were ER-positive (1.1%). In ER-positive disease, presence of ESR1 mutation was significantly associated to poor relapse-free survival (RFS) and overall survival (OS) (p=0.011 and p=0.019, respectively), and moreover predicted poor RFS and OS within the patient group that received ET (p=0.007 and p=0.010, respectively).
Conclusions
These results indicate that ESR1 mutations at diagnosis of untreated primary breast cancer are rare, however we confirm for the first time that such early mutations predict eventual resistance to standard hormone therapy in the adjuvant setting. If replicated, tumor ESR1 screening may be considered in ER-positive primary breast cancer and, in mutated cases, ER-degraders such as fulvestrant or other therapeutic options may be considered as more appropriate.

Publication
Cancer Research, 2020. 80:16_Supplement
Christian Brueffer
Christian Brueffer
Bioinformatician and Data Scientist

Freelance Bioinformatician and Data Scientist with interests including disease biology and diagnostics, particularly in cancer, and open source bioinformatics.