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Gene expression profiling analysis of bisphenol A-induced perturbation in biological processes in ER-negative HEK293 cells.

ABSTRACT: Bisphenol A (BPA) is an environmental endocrine disruptor which has been detected in human bodies. Many studies have implied that BPA exposure is harmful to human health. Previous studies mainly focused on BPA effects on estrogen receptor (ER)-positive cells. Genome-wide impacts of BPA on gene expression in ER-negative cells is unclear. In this study, we performed RNA-seq to characterize BPA-induced cellular and molecular impacts on ER-negative HEK293 cells. The microscopic observation showed that low-dose BPA exposure did not affect cell viability and morphology. Gene expression profiling analysis identified a list of differentially expressed genes in response to BPA exposure in HEK293 cells. These genes were involved in variable important biological processes including ion transport, cysteine metabolic process, apoptosis, DNA damage repair, etc. Notably, BPA up-regulated the expression of ERCC5 encoding a DNA endonuclease for nucleotide-excision repair. Further electrochemical experiment showed that BPA induced significant DNA damage in ER-positive MCF-7 cells but not in ER-negative HEK293 cells. Collectively, our study revealed that ER-negative HEK293 cells employed mechanisms in response to BPA exposure different from ER-positive cells.

SUBMITTER: Yin R

PROVIDER: S-EPMC4047077 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Gene expression profiling analysis of bisphenol A-induced perturbation in biological processes in ER-negative HEK293 cells.

Yin Rong R Gu Liang L Li Min M Jiang Cizhong C Cao Tongcheng T Zhang Xiaobai X

PloS one 20140605 6

Bisphenol A (BPA) is an environmental endocrine disruptor which has been detected in human bodies. Many studies have implied that BPA exposure is harmful to human health. Previous studies mainly focused on BPA effects on estrogen receptor (ER)-positive cells. Genome-wide impacts of BPA on gene expression in ER-negative cells is unclear. In this study, we performed RNA-seq to characterize BPA-induced cellular and molecular impacts on ER-negative HEK293 cells. The microscopic observation showed th ...[more]

PMID: 24901218

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Project description:BACKGROUND: The characterization of copy number alteration patterns in breast cancer requires high-resolution genome-wide profiling of a large panel of tumor specimens. To date, most genome-wide array comparative genomic hybridization studies have used tumor panels of relatively large tumor size and high Nottingham Prognostic Index (NPI) that are not as representative of breast cancer demographics. RESULTS: We performed an oligo-array-based high-resolution analysis of copy number alterations in 171 primary breast tumors of relatively small size and low NPI, which was therefore more representative of breast cancer demographics. Hierarchical clustering over the common regions of alteration identified a novel subtype of high-grade estrogen receptor (ER)-negative breast cancer, characterized by a low genomic instability index. We were able to validate the existence of this genomic subtype in one external breast cancer cohort. Using matched array expression data we also identified the genomic regions showing the strongest coordinate expression changes ('hotspots'). We show that several of these hotspots are located in the phosphatome, kinome and chromatinome, and harbor members of the 122-breast cancer CAN-list. Furthermore, we identify frequently amplified hotspots on 8q22.3 (EDD1, WDSOF1), 8q24.11-13 (THRAP6, DCC1, SQLE, SPG8) and 11q14.1 (NDUFC2, ALG8, USP35) associated with significantly worse prognosis. Amplification of any of these regions identified 37 samples with significantly worse overall survival (hazard ratio (HR) = 2.3 (1.3-1.4) p = 0.003) and time to distant metastasis (HR = 2.6 (1.4-5.1) p = 0.004) independently of NPI. CONCLUSION: We present strong evidence for the existence of a novel subtype of high-grade ER-negative tumors that is characterized by a low genomic instability index. We also provide a genome-wide list of common copy number alteration regions in breast cancer that show strong coordinate aberrant expression, and further identify novel frequently amplified regions that correlate with poor prognosis. Many of the genes associated with these regions represent likely novel oncogenes or tumor suppressors.

Project description:The recombinant adeno-associated virus (rAAV) vector is among the most promising viral vectors in gene therapy. However, the limited manufacturing capacity in human embryonic kidney (HEK) cells is a barrier to rAAV commercialization. We investigated the impact of endoplasmic reticulum (ER) protein processing and apoptotic genes on transient rAAV production in HEK293 cells. We selected four candidate genes based on prior transcriptomic studies: XBP1, GADD34 / PPP1R15A, HSPA6, and BCL2. These genes were stably integrated into HEK293 host cells. Traditional triple-plasmid transient transfection was used to assess the vector production capability and the quality of both the overexpressed stable pools and the parental cells. We show that the overexpression of XBP1, HSPA6, and GADD34 increases rAAV productivity by up to 100% and increases specific rAAV productivity by up to 78% in HEK293T cells. Additionally, more prominent improvement associated with ER protein processing gene overexpression was observed when parental cell productivity was high, but no substantial variation was detected under low-producing conditions. We also confirmed genome titer improvement across different serotypes (AAV2 and AAV8) and different cell lines (HEK293T and HEK293); however, the extent of improvement may vary. This study unveiled the importance of ER protein processing pathways in viral particle synthesis, capsid assembly, and vector production. KEY POINTS: • Upregulation of endoplasmic reticulum (ER) protein processing (XBP1, HSPA6, and GADD34) leads to a maximum 100% increase in rAAV productivity and a maximum 78% boost in specific rAAV productivity in HEK293T cells • The enhancement in productivity can be validated across different HEK293 cell lines and can be used for the production of various AAV serotypes, although the extent of the enhancement might vary slightly • The more pronounced improvements linked to overexpressing ER protein processing genes were observed when parental cell productivity was high, with minimal variation noted under low-producing conditions.

Project description:BACKGROUND:Expression of the oestrogen receptor (ER) in breast cancer predicts benefit from endocrine therapy. Minimising the frequency of false negative ER status classification is essential to identify all patients with ER positive breast cancers who should be offered endocrine therapies in order to improve clinical outcome. In routine oncological practice ER status is determined by semi-quantitative methods such as immunohistochemistry (IHC) or other immunoassays in which the ER expression level is compared to an empirical threshold. The clinical relevance of gene expression-based ER subtypes as compared to IHC-based determination has not been systematically evaluated. Here we attempt to reduce the frequency of false negative ER status classification using two gene expression approaches and compare these methods to IHC based ER status in terms of predictive and prognostic concordance with clinical outcome. METHODOLOGY/PRINCIPAL FINDINGS:Firstly, ER status was discriminated by fitting the bimodal expression of ESR1 to a mixed Gaussian model. The discriminative power of ESR1 suggested bimodal expression as an efficient way to stratify breast cancer; therefore we identified a set of genes whose expression was both strongly bimodal, mimicking ESR expression status, and highly expressed in breast epithelial cell lines, to derive a 23-gene ER expression signature-based classifier. We assessed our classifiers in seven published breast cancer cohorts by comparing the gene expression-based ER status to IHC-based ER status as a predictor of clinical outcome in both untreated and tamoxifen treated cohorts. In untreated breast cancer cohorts, the 23 gene signature-based ER status provided significantly improved prognostic power compared to IHC-based ER status (P?=?0.006). In tamoxifen-treated cohorts, the 23 gene ER expression signature predicted clinical outcome (HR?=?2.20, P?=?0.00035). These complementary ER signature-based strategies estimated that between 15.1% and 21.8% patients of IHC-based negative ER status would be classified with ER positive breast cancer. CONCLUSION/SIGNIFICANCE:Expression-based ER status classification may complement IHC to minimise false negative ER status classification and optimise patient stratification for endocrine therapies.

Dataset Information

Gene expression profiling analysis of bisphenol A-induced perturbation in biological processes in ER-negative HEK293 cells.

Publications

Gene expression profiling analysis of bisphenol A-induced perturbation in biological processes in ER-negative HEK293 cells.

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