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Updated: Jun 2, 2026

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
Published on: August 24, 2017
ESR1 mutations in ER-positive breast cancer: from endocrine resistance to ctDNA-guided therapeutic interception
Thais Martinez1, Samantha Wegner2, Hisham F Bahmad3
1Herbert Wertheim College of Medicine, Florida International University, Miami, FL 33199, USA.
Abstract:
Endocrine resistance in estrogen receptor-positive (ER+) breast cancer has undergone a fundamental reconceptualization over the past decade. The discovery that activating mutations in the ESR1 gene encoding ERα emerge under aromatase inhibitor (AI) selection pressure and drive ligand-independent receptor activation established a shift from empirical treatment sequencing to molecularly guided intervention. This review provides a synopsis of the structural biology underlying constitutive ER activation, the evolutionary dynamics of ESR1-mutant clones detectable through circulating tumor DNA (ctDNA), and the clinical evidence demonstrating that early molecular detection can trigger therapeutic switches that alter disease trajectory. The regulatory approval of elacestrant for ESR1-mutant disease and randomized trial data showing progression-free survival (PFS) benefit from ctDNA-guided endocrine switching (PADA-1, SERENA-6) position ESR1 genotyping as a dynamic biomarker with direct therapeutic implications. We examine the integration of oral selective ER degraders (SERDs) into treatment algorithms, the role of co-occurring alterations in the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathway, and emerging directions, including machine learning approaches to ctDNA kinetics and adaptive trial designs that treat clonal evolution as an actionable target. The convergence of structural mechanisms, liquid biopsy technology, and biomarker-driven drug development provides a framework for precision oncology in endocrine-resistant breast cancer. While these advances are substantial, important challenges remain, including the lack of mature overall survival (OS) data from interception trials, cost and accessibility barriers to serial ctDNA monitoring in diverse global healthcare settings, the unresolved question of optimal therapeutic sequencing in patients with concurrent ESR1 and PI3K pathway alterations, and the need to distinguish clinically actionable low-variant allele frequency (VAF) ESR1 calls from background noise in liquid biopsies.
Insights
Estrogen receptor 1 (ESR1) mutations drive endocrine resistance in breast cancer. Early detection via circulating tumor DNA (ctDNA) and targeted therapies like elacestrant offer improved outcomes, guiding precision oncology strategies.
Area of Science:
- Oncology
- Genetics
- Pharmacology
Background:
- Endocrine resistance in estrogen receptor-positive (ER+) breast cancer is a major clinical challenge.
- Activating mutations in the ESR1 gene drive ligand-independent ERα activation, leading to resistance against aromatase inhibitors (AIs).
Purpose of the Study:
- To review the structural biology of constitutive ER activation.
- To discuss the evolutionary dynamics of ESR1-mutant clones detected by ctDNA.
- To examine clinical evidence for molecularly guided interventions in ESR1-mutant breast cancer.
Main Methods:
- Synopsis of structural biology of constitutive ER activation.
- Analysis of ESR1 clone evolution using circulating tumor DNA (ctDNA).
- Review of clinical trial data (PADA-1, SERENA-6) for ctDNA-guided therapy and elacestrant.
Main Results:
- ESR1 mutations emerge under AI pressure, causing constitutive ER activation.
- Early ctDNA detection of ESR1 mutations can guide therapeutic switches, improving progression-free survival (PFS).
- Elacestrant is approved for ESR1-mutant disease; ctDNA-guided switching shows PFS benefit.
Conclusions:
- ESR1 genotyping is a dynamic biomarker for precision oncology in endocrine-resistant breast cancer.
- Integration of oral selective ER degraders (SERDs) and PI3K/AKT pathway analysis is crucial.
- Challenges include OS data, monitoring accessibility, optimal sequencing for co-alterations, and distinguishing low-VAF ESR1 calls.
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