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Folly Beach Library
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Edgar Allan Poe/Sullivan's Island Library
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Wando Mount Pleasant Library
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Village Library
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St. Paul's/Hollywood Library
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McClellanville Library
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Keith Summey North Charleston Library
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Hurd/St. Andrews Library
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![loading](/sites/all/modules/hf_eds/images/loading.gif)
High-Throughput Transcriptomics of Nontumorigenic Breast Cells Exposed to Environmentally Relevant Chemicals.
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![loading](/sites/all/modules/hf_eds/images/loading.gif)
- Author(s): Sala-Hamrick, Kimberley E.; Tapaswi, Anagha; Polemi, Katelyn M.; Nguyen, Vy K.; Colacino, Justin A.
- Source:
Environmental Health Perspectives. Apr2024, Vol. 132 Issue 4, p047002-1-047002-12. 12p. - Source:
- Additional Information
- Subject Terms: EPITHELIAL cells; PHENOMENOLOGICAL biology; RESEARCH funding; BREAST tumors; CELL physiology; QUESTIONNAIRES; POLYMERASE chain reaction; CELLULAR signal transduction; BIOCHEMISTRY; CELL lines; CELL culture; GENE expression; RNA; SURVEYS; GENE expression profiling; ENVIRONMENTAL exposure; ANALYSIS of variance; BIOMARKERS; SEQUENCE analysis
- Abstract: BACKGROUND: There is a suite of chemicals, including metals, pesticides, and personal care product compounds, which are commonly detected at high levels in US Center for Disease Control’s National Health and Nutrition Examination Survey (NHANES) chemical biomarker screens. Whether these chemicals influence development of breast cancer is not well understood. OBJECTIVES: The objectives were to perform an unbiased concentration-dependent assessment of these chemicals, to quantify differences in cancer-specific genes and pathways, to describe if these differences occur at human population–relevant concentrations, and to specifically test for differences in markers of stemness and cellular plasticity. METHODS: We treated nontumorigenic mammary epithelial cells, MCF10A, with 21 chemicals at four concentrations (25 nM, 250 nM, 2.5 μM, and 25 μM) for 48 h. We conducted RNA-sequencing for these 408 samples, adapting the plex Well plate-based RNA-sequencing method to analyze differences in gene expression. We calculated gene and biological pathway-specific benchmark concentrations (BMCs) using BMDExpress3, identifying differentially expressed genes and generating the best fit benchmark concentration models for each chemical across all genes. We identified enriched biological processes and pathways for each chemical and tested whether chemical exposures change predicted cell type distributions. We contextualized benchmark concentrations relative to human population biomarker concentrations in NHANES. RESULTS: We detected chemical concentration–dependent differences in gene expression for thousands of genes. Enrichment and cell type distribution analyses showed benchmark concentration responses correlated with differences in breast cancer–related pathways, including induction of basal-like characteristics for some chemicals, including arsenic, lead, copper, and methyl paraben. Comparison of benchmark data to NHANES chemical biomarker (urine or blood) concentrations indicated an overlap between exposure levels and levels sufficient to cause a gene expression response. DISCUSSION: These analyses revealed that many of these 21 chemicals resulted in differences in genes and pathways involved in breast cancer in vitro at human exposure–relevant concentrations. [ABSTRACT FROM AUTHOR]
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