Estrogen down regulates COMT transcription via promoter DNA methylation in human breast cancer cells.

Catechol-O-methyltransferase (COMT) acts as a 'gate-keeper' to prevent DNA damage during estrogen metabolism. Both experimental and epidemiological studies suggest the role of COMT in pathogenesis of human breast cancer (BCa). It was previously reported that inhibition of COMT enzyme activity in estradiol-treated human breast epithelial carcinoma-derived MCF-7 cells caused increased oxidative DNA damage and formation of mutagenic depurinating adducts. To improve our understanding of factors influencing estrogen metabolism in BCa, it requires a mechanistic study illustrating the regulation of this 'gate-keeper'. We investigated the epigenetic mechanisms underlying decreased COMT transcription in MCF-7 cells exposed to 17ß-estradiol (E2) and the phytoestrogen, genistein (GEN). CpG site-specific methylation at promoters for both soluble (S) and membrane-bound (MB) COMT transcripts were assessed. Both E2 and GEN induced CpG site-specific methylation within the distal promoter of MB-COMT. In addition, ChIP analysis showed that there was increased binding of DNMT3B, MBD2 and HDAC1 within this promoter. These epigenetic changes were associated with decreased COMT transcript levels. Interestingly, sulforaphane, an antioxidant commonly found in cruciferous vegetables, was able to reverse the estrogen-induced epigenetic changes and gene silencing of COMT. Our data provide a new insight in epigenetically targeting COMT transcription. Since reactive estrogen metabolites may contribute to breast cancer, our findings may help in developing prevention and/or intervention strategies for human BCa.

Metabolomic network analysis of estrogen-stimulated MCF-7 cells: a comparison of overrepresentation analysis, quantitative enrichment analysis and pathway analysis versus metabolite network analysis.

In the context of the Human Toxome project, mass spectroscopy-based metabolomics characterization of estrogen-stimulated MCF-7 cells was studied in order to support the untargeted deduction of pathways of toxicity. A targeted and untargeted approach using overrepresentation analysis (ORA), quantitative enrichment analysis (QEA) and pathway analysis (PA) and a metabolite network approach were compared. Any untargeted approach necessarily has some noise in the data owing to artifacts, outliers and misidentified metabolites. Depending on the chemical analytical choices (sample extraction, chromatography, instrument and settings, etc.), only a partial representation of all metabolites will be achieved, biased by both the analytical methods and the database used to identify the metabolites. Here, we show on the one hand that using a data analysis approach based exclusively on pathway annotations has the potential to miss much that is of interest and, in the case of misidentified metabolites, can produce perturbed pathways that are statistically significant yet uninformative for the biological sample at hand. On the other hand, a targeted approach, by narrowing its focus and minimizing (but not eliminating) misidentifications, renders the likelihood of a spurious pathway much smaller, but the limited number of metabolites also makes statistical significance harder to achieve. To avoid an analysis dependent on pathways, we built a de novo network using all metabolites that were different at 24 h with and without estrogen with a p value <0.01 (53) in the STITCH database, which links metabolites based on known reactions in the main metabolic network pathways but also based on experimental evidence and text mining. The resulting network contained a "connected component" of 43 metabolites and helped identify non-endogenous metabolites as well as pathways not visible by annotation-based approaches. Moreover, the most highly connected metabolites (energy metabolites such as pyruvate and alpha-ketoglutarate, as well as amino acids) showed only a modest change between proliferation with and without estrogen. Here, we demonstrate that estrogen has subtle but potentially phenotypically important alterations in the acyl-carnitine fatty acids, acetyl-putrescine and succinoadenosine, in addition to likely subtle changes in key energy metabolites that, however, could not be verified consistently given the technical limitations of this approach. Finally, we show that a network-based approach combined with text mining identifies pathways that would otherwise neither be considered statistically significant on their own nor be identified via ORA, QEA, or PA.

Effects of cadmium on estrogen receptor mediated signaling and estrogen induced DNA synthesis in T47D human breast cancer cells.

Cadmium (Cd) has been shown to bind to the human estrogen receptor (ER), yet studies on Cd's estrogenic effects have yielded inconsistent results. In this study, we investigated the effects of Cd on DNA synthesis and its simultaneous effects on both genomic (mediated by nuclear ER (nER)) and non-genomic (mediated by membrane-bound ER (mER)) signaling in human breast cancer derived T47D cells. No effects on DNA synthesis were observed for non-cytotoxic concentrations of CdCl(2) (0.1-1000 nM), and Cd did not increase progesterone receptor (PgR) or pS2 mRNA levels. However, Cd stimulated phosphorylation of ERK1/2 MAPK, detectable following 10 min and 18 h of treatment. The sustained Cd-induced ERK1/2 phosphorylation was inhibited by the ER antagonist ICI 182,780, suggesting the involvement of ER. In addition, Cd enhanced DNA synthesis and pS2 mRNA levels in estrogen (10 pM estradiol) treated T47D cells. The MEK1/2 specific inhibitor U0126 blocked DNA synthesis stimulated by estradiol (E2) and the E2-Cd mixtures. These findings indicate that the ERK1/2 signaling is critical in E2-related DNA synthesis. The sustained ERK1/2 phosphorylation may contribute to the Cd-induced enhancement of DNA synthesis and pS2 mRNA in mixture with low-concentration E2.

Microglia Increase Inflammatory Responses in iPSC-Derived Human BrainSpheres.

Human induced pluripotent stem cells (iPSCs), together with 21st century cell culture methods, have the potential to better model human physiology with applications in toxicology, disease modeling, and the study of host-pathogen interactions. Several models of the human brain have been developed recently, demonstrating cell-cell interactions of multiple cell types with physiologically relevant 3D structures. Most current models, however, lack the ability to represent the inflammatory response in the brain because they do not include a microglial cell population. Microglia, the resident immunocompetent phagocytes in the central nervous system (CNS), are not only important in the inflammatory response and pathogenesis; they also function in normal brain development, strengthen neuronal connections through synaptic pruning, and are involved in oligodendrocyte and neuronal survival. Here, we have successfully introduced a population of human microglia into 3D human iPSC-derived brain spheres (BrainSpheres, BS) through co-culturing cells of the Immortalized Human Microglia - SV40 cell line with the BS model (µBS). We detected an inflammatory response to lipopolysaccharides (LPS) and flavivirus infection, which was only elicited in the model when microglial cells were present. A concentration of 20 ng/mL of LPS increased gene expression of the inflammatory cytokines interleukin-6 (IL-6), IL-10, and IL-1ß, with maximum expression at 6-12 h post-exposure. Increased expression of the IL-6, IL-1ß, tumor necrosis factor alpha (TNF-α), and chemokine (C-C motif) ligand 2 (CCL2) genes was observed in µBS following infection with Zika and Dengue Virus, suggesting a stronger inflammatory response in the model when microglia were present than when only astrocyte, oligodendrocyte, and neuronal populations were represented. Microglia innately develop within cerebral organoids (Nature communications), our findings suggest that the µBS model is more physiologically relevant and has potential applications in infectious disease and host-pathogen interactions research.

Genetic variability in a frozen batch of MCF-7 cells invisible in routine authentication affecting cell function.

Common recommendations for cell line authentication, annotation and quality control fall short addressing genetic heterogeneity. Within the Human Toxome Project, we demonstrate that there can be marked cellular and phenotypic heterogeneity in a single batch of the human breast adenocarcinoma cell line MCF-7 obtained directly from a cell bank that are invisible with the usual cell authentication by short tandem repeat (STR) markers. STR profiling just fulfills the purpose of authentication testing, which is to detect significant cross-contamination and cell line misidentification. Heterogeneity needs to be examined using additional methods. This heterogeneity can have serious consequences for reproducibility of experiments as shown by morphology, estrogenic growth dose-response, whole genome gene expression and untargeted mass-spectroscopy metabolomics for MCF-7 cells. Using Comparative Genomic Hybridization (CGH), differences were traced back to genetic heterogeneity already in the cells from the original frozen vials from the same ATCC lot, however, STR markers did not differ from ATCC reference for any sample. These findings underscore the need for additional quality assurance in Good Cell Culture Practice and cell characterization, especially using other methods such as CGH to reveal possible genomic heterogeneity and genetic drifts within cell lines.

Quality assurance of metabolomics.

Metabolomics promises a holistic phenotypic characterization of biological responses to toxicants. This technology is based on advanced chemical analytical tools with reasonable throughput, including mass-spectroscopy and NMR. Quality assurance, however - from experimental design, sample preparation, metabolite identification, to bioinformatics data-mining - is urgently needed to assure both quality of metabolomics data and reproducibility of biological models. In contrast to microarray-based transcriptomics, where consensus on quality assurance and reporting standards has been fostered over the last two decades, quality assurance of metabolomics is only now emerging. Regulatory use in safety sciences, and even proper scientific use of these technologies, demand quality assurance. In an effort to promote this discussion, an expert workshop discussed the quality assurance needs of metabolomics. The goals for this workshop were 1) to consider the challenges associated with metabolomics as an emerging science, with an emphasis on its application in toxicology and 2) to identify the key issues to be addressed in order to establish and implement quality assurance procedures in metabolomics-based toxicology. Consensus has still to be achieved regarding best practices to make sure sound, useful, and relevant information is derived from these new tools.