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Adaptation to AI Therapy in Breast Cancer Can Induce Dynamic Alterations in ER Activity Resulting in
Damir Varešlija1, Jean McBryan1, Ailís Fagan1
1Endocrine Oncology Research Group, Department of Surgery, Royal College of Surgeons in Ireland, Dublin 2, Ireland.
Purpose:
Acquired resistance to aromatase inhibitor (AI) therapy is a major clinical problem in the treatment of breast cancer. The detailed mechanisms of how tumor cells develop this resistance remain unclear. Here, the adapted function of estrogen receptor (ER) to an estrogen-depleted environment following AI treatment is reported.
Experimental Design:
Global ER chromatin immuno-precipitation (ChIP)-seq analysis of AI-resistant cells identified steroid-independent ER target genes. Matched patient tumor samples, collected before and after AI treatment, were used to assess ER activity.
Results:
Maintained ER activity was observed in patient tumors following neoadjuvant AI therapy. Genome-wide ER-DNA-binding analysis in AI-resistant cell lines identified a subset of classic ligand-dependent ER target genes that develop steroid independence. The Kaplan-Meier analysis revealed a significant association between tumors, which fail to decrease this steroid-independent ER target gene set in response to neoadjuvant AI therapy, and poor disease-free survival and overall survival (n = 72 matched patient tumor samples, P = 0.00339 and 0.00155, respectively). The adaptive ER response to AI treatment was highlighted by the ER/AIB1 target gene, early growth response 3 (EGR3). Elevated levels of EGR3 were detected in endocrine-resistant local disease recurrent patient tumors in comparison with matched primary tissue. However, evidence from distant metastatic tumors demonstrates that the ER signaling network may undergo further adaptations with disease progression as estrogen-independent ER target gene expression is routinely lost in established metastatic tumors.
Conclusions:
Overall, these data provide evidence of a dynamic ER response to endocrine treatment that may provide vital clues for overcoming the clinical issue of therapy resistance. Clin Cancer Res; 22(11); 2765-77. ©2016 AACR.
Insights
Tumor cells adapt to aromatase inhibitor (AI) therapy by maintaining estrogen receptor (ER) activity, leading to steroid-independent gene expression. This adaptation predicts poor survival in breast cancer patients, offering insights into overcoming AI resistance.
Area of Science:
- Endocrinology
- Oncology
- Molecular Biology
Background:
- Acquired resistance to aromatase inhibitor (AI) therapy is a significant challenge in breast cancer treatment.
- The precise mechanisms by which tumor cells develop resistance to AI therapy are not fully understood.
- Estrogen receptor (ER) signaling plays a critical role in hormone-dependent breast cancers.
Purpose of the Study:
- To investigate the adaptive mechanisms of estrogen receptor (ER) function in response to AI treatment in breast cancer.
- To identify specific ER target genes that contribute to steroid-independent activity and AI resistance.
- To correlate ER activity and target gene expression with patient survival outcomes.
Main Methods:
- Global ER chromatin immunoprecipitation sequencing (ChIP-seq) was performed on AI-resistant breast cancer cell lines.
- Matched patient tumor samples before and after neoadjuvant AI therapy were analyzed to assess ER activity.
- Kaplan-Meier analysis was used to evaluate the association between gene expression patterns and patient survival.
Main Results:
- Maintained ER activity was observed in patient tumors following neoadjuvant AI therapy.
- A subset of ligand-dependent ER target genes acquired steroid independence in AI-resistant cells.
- Failure to decrease steroid-independent ER target gene expression correlated significantly with poor disease-free and overall survival.
- The ER/AIB1 target gene, early growth response 3 (EGR3), was identified as a key adaptive response marker.
Conclusions:
- Tumor cells exhibit dynamic adaptive responses to endocrine therapy, including ER adaptation to estrogen-depleted environments.
- Steroid-independent ER target gene expression is a potential biomarker for AI resistance and poor prognosis.
- Understanding these adaptive ER mechanisms may offer new strategies to overcome therapeutic resistance in breast cancer.
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