Estrogen receptor (ER, alpha isoform) was the first biomarker to be clinically validated as a predictor of cancer therapy response, and still stands as one of the few tumor biomarkers with sufficient medical evidence to justify its routine use in clinical decision making. While low or absent tumor ER expression (ER-) accurately predicts lack of responsiveness to endocrine therapy, tumor overexpression of ER (ER+) is a poor predictor of response with an accuracy averaging only 50%. Hence, improving the predictive accuracy of current ER assays that measure only tumor ER content is one of the most important unresolved issues in cancer research. Since the constellation of posttranslational modifications (PTMs) on any given protein is known to be a molecular code dictating conformation, localization, and intracellular function, we assembled an interdisciplinary team of translational investigators and protein chemists who developed mass spectrometry (MS) approaches, employing multiple reaction monitoring (MRM) capable of detecting and quantitating diverse PTMs, including Ser/Thr/Tyr phosphorylations, Lys modifications (acetylation/methylation/ubiquitination), and Cys oxidation across the six domains of endogenously expressed ER protein. Two study aims are proposed based on the premise that decoding ER PTMs is essential for improving ER biomarker specificity and the clinical subtyping of ER+ breast cancers.
Aim 1 studies will fully optimize MRM/MS procedures to quantitate ligand-dependent (estrogen) and ligand-independent (growth factor, oxidative stress) induction of ER PTMs across a panel of ER+ human breast cancer cell lines selected for their range of antiestrogen sensitivities. Special emphasis will be given to the ER hinge and DNA-binding domains where specific PTM patterns are known to alter ER functionality and determine antiestrogen sensitivity. The functional impact of novel ER PTMs will also be assessed by introducing mutated ER PTM constructs and evaluating their intracellular impact on endogenous ER dependent gene expression. Among other objectives, Aim 1 efforts will generate a candidate PTM profile predictive of cell line antiestrogen resistance for further evaluation in Aim 2 tumor samples.
Aim 2 studies will employ fully optimized MRM/MS protocols from Aim 1 to evaluate the prevalence and spectrum of tumor ER PTMs using two different clinically annotated cohorts of ER+ primary breast cancers. The two tumor cohorts available for MRM/MS analysis are powered to: i) validate our Aim 1 derived ER PTM profile associating with cell line tamoxifen responsiveness, and ii) independently derive and validate a tumor ER PTM profile associating with clinical resistance to adjuvant tamoxifen and other aggressive tumor features linked to early clinical relapse. On completion of these study aims, quantitative MRM/MS assays will have defined the spectrum and prevalence of all breast cancer PTMs, and a PTM pattern associated with more aggressive and antiestrogen resistant breast cancers will have been identified and validated.

Public Health Relevance

The estrogen receptor protein represents one of the most important tumor biomarkers in routine clinical use, and is employed to identify breast cancers that overexpress ER (designated ER+), signifying that they MAY respond favorably to endocrine therapy with tamoxifen or aromatase inhibitors. Although low ER expressing tumors (ER-) are almost invariably unresponsive to such therapies, the corollary that ER+ tumors will always respond is not true. Using a sensitive and sophisticated mass spectrometry-based approach that we have pioneered, we will test the hypothesis that decoding the chemical modifications known or suspected to occur on various ER amino acids (known as post-translational modifications or PTMs) will enable more accurate prediction of ER+ breast tumors responsive to endocrine therapy, and provide new insight into ER+ breast cancer mechanisms associated with endocrine resistance.

National Institute of Health (NIH)
National Cancer Institute (NCI)
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Cancer Biomarkers Study Section (CBSS)
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Sathyamoorthy, Neeraja
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Buck Institute for Age Research
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