The carcinogenic activity of bisphenol A (BPA) is responsible for stimulating growth in estrogen-dependent breast cancer tissues, cell lines and rodent studies. However, it is not fully understood how this compound promotes mammary carcinogenesis. In our study, we examined the effect of BPA on cellular proliferation and senescence in human mammary epithelial cells (HMEC). Exposure to BPA for 1 week at the early stage at passage 8 increased the proliferation and sphere size of HMEC at the later stage up to passage 16, suggesting that BPA has the capability to modulate cell growth in breast epithelial cells. Interestingly, the number of human heterochromatin protein-1γ positive cells, which is a marker of senescence, was also increased among BPA-treated cells. Consistent with these findings, the protein levels of both p16 and cyclin E, which are known to induce cellular senescence and promote proliferation, respectively, were increased in BPA-exposed HMEC. Furthermore, DNA methylation levels of genes related to development of most or all tumor types, such as BRCA1, CCNA1, CDKN2A (p16), THBS1, TNFRSF10C and TNFRSF10D, were increased in BPA-exposed HMEC. Our findings in the HMEC model suggested that the genetic and epigenetic alterations by BPA might damage HMEC function and result in complex activities related to cell proliferation and senescence, playing a role in mammary carcinogenesis.

Predictive toxicology using stem cells or their derived tissues has gained increasing importance in biomedical and pharmaceutical research. Here, we show that toxicity category prediction by support vector machines (SVMs), which uses qRT-PCR data from 20 categorized chemicals based on a human embryonic stem cell (hESC) system, is improved by the adoption of gene networks, in which network edge weights are added as feature vectors when noisy qRT-PCR data fail to make accurate predictions. The accuracies of our system were 97.5–100% for three toxicity categories: neurotoxins (NTs), genotoxic carcinogens (GCs) and non-genotoxic carcinogens (NGCs). For two uncategorized chemicals, bisphenol-A and permethrin, our system yielded reasonable results: bisphenol-A was categorized as an NGC, and permethrin was categorized as an NT; both predictions were supported by recently published papers. Our study has two important features: (i) as the first study to employ gene networks without using conventional quantitative structure-activity relationships (QSARs) as input data for SVMs to analyze toxicogenomics data in an hESC validation system, it uses additional information of gene-to-gene interactions to significantly increase prediction accuracies for noisy gene expression data; and (ii) using only undifferentiated hESCs, our study has considerable potential to predict late-onset chemical toxicities, including abnormalities that occur during embryonic development.

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We have previously established a protocol for the neural differentiation of mouse embryonic stem cells (mESCs) as an efficient tool to evaluate the neurodevelopmental toxicity of environmental chemicals. Here, we described a multivariate bioinformatic approach to identify the stage-specific gene sets associated with neural differentiation of mESCs. We exposed mESCs (B6G-2 cells) to 10−8 or 10−7 M of retinoic acid (RA) for 4 days during embryoid body formation and then performed morphological analysis on day of differentiation (DoD) 8 and 36, or genomic microarray analysis on DoD 0, 2, 8, and 36. Three gene sets, namely a literature-based gene set (set 1), an analysis-based gene set (set 2) using self-organizing map and principal component analysis, and an enrichment gene set (set 3), were selected by the combined use of knowledge from literatures and gene information selected from the microarray data. A gene network analysis for each gene set was then performed using Bayesian statistics to identify stage-specific gene expression signatures in response to RA during mESC neural differentiation. Our results showed that RA significantly increased the size of neurosphere, neuronal cells, and glial cells on DoD 36. In addition, the gene network analysis showed that glial fibrillary acidic protein, a neural marker, remarkably up-regulates the other genes in gene set 1 and 3, and Gbx2, a neural development marker, significantly up-regulates the other genes in gene set 2 on DoD 36 in the presence of RA. These findings suggest that our protocol for identification of developmental stage-specific gene expression and interaction is a useful method for the screening of environmental chemical toxicity during neurodevelopmental periods.

Pyrethroids are one of the most widely used classes of insecticides and show neurotoxic effects that induce oxidative stress in the neonatal rat brain. However, little is still known about effects of prenatal exposure to permethrin on vascular development in fetal brain, central nervous system development, and adult offspring behaviors. In this study, the effects of prenatal exposure to permethrin on the development of cerebral arteries in fetal brains, neurotransmitter in neonatal brains, and locomotor activities in offspring mice were investigated. Permethrin (0, 2, 10, 50, and 75 mg/kg) was orally administered to pregnant females once on gestation day 10.5. The brains of permethrin-treated fetuses showed altered vascular formation involving shortened lengths of vessels, an increased number of small branches, and, in some cases, insufficient fusion of the anterior communicating arteries in the area of circle of Willis. The prenatal exposure to permethrin altered neocortical and hippocampus thickness in the mid brain and significantly increased norepinephrine and dopamine levels at postnatal day 7 mice. For spontaneous behavior, the standing ability test using a viewing jar and open-field tests showed significant decrease of the standing ability and locomotor activity in male mice at 8 or 12 weeks of age, respectively. The results suggest that prenatal exposure to permethrin may affect insufficient development of the brain through alterations of vascular development.