Abstract 3558: Single cell-based image analysis of nuclear receptor levels and activity in breast cancer cells reveals heterogeneous subpopulations: Development of biological response fingerprints for ligands and endocrine disruptors.
Authors: Stossi Fabio , Renwick Alexander , Dandekar Radhika D. , Newberg Justin Y. , Rao Arvind , Mancini Michael A. 
Published: August 2014

Abstract
Modern microscopy- and flow cytometry-based analyses indicate tumor cell populations can be markedly heterogeneous. Yet, the vast majority of approaches used to investigate tumorigenic mechanisms and therapeutic responses are based upon average single-point analysis of bulk populations of cells, where subpopulation responses are undetectable and therefore unexplored. For example, breast cancers are generally classified by IHC as either estrogen receptor-alpha positive (ER+) or negative (ER-); however, in ER+ tumors, there is a broad range of ER levels in individual cells. Despite a growing awareness of the importance of tumor cell heterogeneity and outlier biology in cancer therapeutics, there is a paucity of data on the potential interplay between multiple nuclear receptors and coregulators, their heterogeneity of expression and functions, and their combinatorial role in determining therapeutic response, or in sensing environmental stressors (e.g., endocrine disruptors).
To specifically quantify biological responses on an individual cell basis rather than averaged responses from bulk populations, we performed single cell-based high content analysis (HCA) to examine MCF-7 breast cancer cells in terms of simultaneous expression of several type-1 nuclear receptors (e.g., Estrogen, Androgen and Glucocorticoid receptors - ER, AR and GR) and coregulators (e.g., SRC-2 and SRC-3). Quantitative immunofluorescence reveals a wide range of heterogeneity in the expression and ratios of ER, AR, and GR. Multi-parametric analyses describing NR expression and spatial distribution were used to evaluate ligand dose responses and time pattern of the three nuclear receptors, simultaneously. Next, we are expanding our analysis to endogenous target gene expression via mRNA fluorescence in situ hybridization (RNA FISH) and to cell cycle marker analysis to link heterogeneity of NRs/coregulators expression with transcriptional output and cell cycle phases. We are also implementing robust analysis pipelines to describe and quantify NRs and coregulators patterns of phenotypic heterogeneity to create “biological response fingerprints,” which we are using to classify the effects of individual or mixed ligand treatments with particular focus on chemotherapeutic drugs and endocrine disruptors. We are also starting to expand our HCA approach to other breast cancer cell lines moving towards primary tumors microarrays analysis to evaluate the prognostic/diagnostic significance of NR heterogeneity. Collectively, these high throughput-amenable approaches are poised to greatly aid in the understanding the role of heterogeneity in breast cancer, and serve as a robust model for next-generation drug screening and endocrine disruptor assays moving toward personalized medicine.
Citation Format: Fabio Stossi, Alexander Renwick, Radhika D. Dandekar, Justin Y. Newberg, Arvind Rao, Michael A. Mancini. Single cell-based image analysis of nuclear receptor levels and activity in breast cancer cells reveals heterogeneous subpopulations: Development of biological response fingerprints for ligands and endocrine disruptors. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3558. doi:10.1158/1538-7445.AM2013-3558