Tracking evolution of aromatase inhibitor resistance with circulating tumour DNA analysis in metastatic breast cancer

Abstract

Background

Selection of resistance mutations may play a major role in the development of endocrine resistance. ESR1 mutations are rare in primary breast cancer but have high prevalence in patients treated with aromatase inhibitors (AI) for advanced breast cancer. We investigated the evolution of genetic resistance to first line AI therapy using sequential ctDNA sampling in patients with advanced breast cancer.

Patients and Methods

83 patients on first line AI therapy for metastatic breast cancer were enrolled in a prospective study. Plasma samples were collected every 3 months to disease progression and ctDNA analysed by digital droplet PCR and enhanced tagged-amplicon sequencing (eTAm-Seq). Mutations identified in progression samples by sequencing were tracked back through samples prior to progression to study the evolution of mutations on therapy. The frequency of novel mutations were validated in an independent cohort of available baseline plasma samples in the SoFEA trial, which enrolled patients with prior sensitivity to AI.

Results

Of the 39 patients who progressed on first line AI, 56.4%(22/39) had ESR1 mutations detectable at progression, which were polyclonal in 40.9%(9/22) patients. In serial tracking, ESR1 mutations were detectable median 6.7 months (95%CI 3.7-NA) prior to clinical progression. Utilising eTAm-Seq ctDNA sequencing of progression plasma, ESR1 mutations were demonstrated to be sub-clonal in 72.2%(13/18) patients. Mutations in RAS genes were identified in 15.4%(6/39) of progressing patients (4 KRAS, 1 HRAS, 1 NRAS). In SoFEA, KRAS mutations were detected in 21.2%(24/113) patients, although there was no evidence that KRAS mutation status was prognostic for progression free or overall survival.

Conclusions

Cancers progressing on first line AI show high levels of genetic heterogeneity, with frequent sub-clonal mutations. Sub-clonal KRAS mutations are found at high frequency. The genetic diversity of AI resistant cancers may limit subsequent targeted therapy approaches.

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