Adaptation to AI therapy in breast cancer can induce dynamic alterations in ER activity resulting in estrogen-independent metastatic tumors

10Citations
Citations of this article
18Readers
Mendeley users who have this article in their library.

Abstract

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 steroidindependent 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.

Cite

CITATION STYLE

APA

Varešlija, D., Mcbryan, J., Fagan, A., Redmond, A. M., Hao, Y., Sims, A. H., … Young, L. S. (2016). Adaptation to AI therapy in breast cancer can induce dynamic alterations in ER activity resulting in estrogen-independent metastatic tumors. Clinical Cancer Research, 22(11), 2765–2777. https://doi.org/10.1158/1078-0432.CCR-15-1583

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free