Dataset Information

Single-Cell Distribution Analysis of AR Levels by High-Throughput Microscopy in Cell Models: Application for Testing Endocrine-Disrupting Chemicals.

ABSTRACT: Cell-to-cell variation of protein expression in genetically homogeneous populations is a common biological trait often neglected during analysis of high-throughput (HT) screens and is rarely used as a metric to characterize chemicals. We have captured single-cell distributions of androgen receptor (AR) nuclear levels after perturbations as a means to evaluate assay reproducibility and characterize a small subset of chemicals. AR, a member of the nuclear receptor family of transcription factors, is the central regulator of male reproduction and is involved in many pathophysiological processes. AR protein levels and nuclear localization often increase following ligand binding, with dihydrotestosterone (DHT) being the natural agonist. HT AR immunofluorescence imaging was used in multiple cell lines to define single-cell nuclear values extracted from thousands of cells per condition treated with DHT or DMSO (control). Analysis of numerous biological replicates led to a quality control metric that takes into account the distribution of single-cell data, and how it changes upon treatments. Dose-response experiments across several cell lines showed a large range of sensitivity to DHT, prompting us to treat selected cell lines with 45 Environmental Protection Agency (EPA)-provided chemicals that include many endocrine-disrupting chemicals (EDCs); data from six of the compounds were then integrated with orthogonal assays. Our comprehensive results indicate that quantitative single-cell distribution analysis of AR protein levels is a valid method to detect the potential androgenic and antiandrogenic actions of environmentally relevant chemicals in a sensitive and reproducible manner.

SUBMITTER: Stossi F

PROVIDER: S-EPMC7430197 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Publications

Single-Cell Distribution Analysis of AR Levels by High-Throughput Microscopy in Cell Models: Application for Testing Endocrine-Disrupting Chemicals.

Stossi Fabio F Mistry Ragini M RM Singh Pankaj K PK Johnson Hannah L HL Mancini Maureen G MG Szafran Adam T AT Mancini Michael A MA

SLAS discovery : advancing life sciences R & D 20200618 7

Cell-to-cell variation of protein expression in genetically homogeneous populations is a common biological trait often neglected during analysis of high-throughput (HT) screens and is rarely used as a metric to characterize chemicals. We have captured single-cell distributions of androgen receptor (AR) nuclear levels after perturbations as a means to evaluate assay reproducibility and characterize a small subset of chemicals. AR, a member of the nuclear receptor family of transcription factors, ...[more]

PMID: 32552291

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Project description:BackgroundGlobally, the burden of breast cancer has increased significantly in recent decades. Emerging evidence suggested that endocrine-disrupting chemicals (EDCs), which have the potential to interfere with the function of normal hormones, may play a crucial role in this trend. However, the potential relationships were inconsistent in various studies.Objective and search methodsIn our study, we sought to fully evaluate the currently available epidemiological evidence to ascertain whether certain EDC congeners and their metabolites are related to breast cancer risk. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we conducted a comprehensive literature search of original peer-reviewed publications in three electronic databases: PubMed, Web of Science, and Embase. Publications that covered xenobiotic EDC exposures and breast cancer-confirmed histological results or antecedent medical records or reporting to health registers were taken into consideration.OutcomesThe final result of the literature search was 6,498 references, out which we found 67 publications that matched the requirements for meta-analysis and eight publications for qualitative trend synthesis. In this meta-analysis, statistically significant associations revealed that (i) 1-chloro-4-[2,2,2-trichloro-1-(4-chlorophenyl)ethyl]benzene (p,p'-DDT) and its major metabolite 2,2-bis(4-chlorophenyl)-1,1-dichloroethylene (p,p'-DDE) were somewhat related to a greater risk of breast cancer. However, this relationship only existed in blood serum but not in adipose tissue. (ii) Breast cancer risk was increased by exposure to chlordane and hexachlorocyclohexane. (iii) Five polychlorinated biphenyls (PCB 99, PCB 105, PCB 118, PCB 138, and PCB 183) can increase the risk of breast cancer. (iv) One phthalate congener (BBP) and one per- and polyfluoroalkyl substance congener (PFDoDA) were negatively associated with breast cancer risk. Unfortunately, heterogeneity was not well explained in our review, and a limited number of available prospective studies investigating the associations between EDC exposure and breast cancer were included in our meta-analysis. To elucidate the overall associations, future large, longitudinal epidemiological investigations are needed.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD 42023420927.

Dataset Information

Single-Cell Distribution Analysis of AR Levels by High-Throughput Microscopy in Cell Models: Application for Testing Endocrine-Disrupting Chemicals.

Publications

Single-Cell Distribution Analysis of AR Levels by High-Throughput Microscopy in Cell Models: Application for Testing Endocrine-Disrupting Chemicals.

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