Identification of biomarkers of chemically induced hepatocarcinogenesis in rasH2 mice by toxicogenomic analysis

Short-term in vivo testing to discriminate genotoxic carcinogens from non-genotoxic carcinogens and non-carcinogens using next-generation RNA sequencing, DNA microarray, and qPCR

Next-generation RNA sequencing (RNA-Seq) has identified more differentially expressed protein-coding genes (DEGs) and provided a wider quantitative range of expression level changes than conventional DNA microarrays. JEMS·MMS·Toxicogenomics group studied DEGs with targeted RNA-Seq on freshly frozen rat liver tissues and on formalin-fixed paraffin-embedded (FFPE) rat liver tissues after 28 days of treatment with chemicals and quantitative real-time PCR (qPCR) on rat and mouse liver tissues after 4 to 48 h treatment with chemicals and analyzed by principal component analysis (PCA) as statics. Analysis of rat public DNA microarray data (Open TG-GATEs) was also performed. In total, 35 chemicals were analyzed [15 genotoxic hepatocarcinogens (GTHCs), 9 non-genotoxic hepatocarcinogens (NGTHCs), and 11 non-genotoxic non-hepatocarcinogens (NGTNHCs)]. As a result, 12 marker genes (Aen, Bax, Btg2, Ccnf, Ccng1, Cdkn1a, Gdf15, Lrp1, Mbd1, Phlda3, Plk2, and Tubb4b) were proposed to discriminate GTHCs from NGTHCs and NGTNHCs. U.S. Environmental Protection Agency studied DEGs induced by 4 known GTHCs in rat liver using DNA microarray and proposed 7 biomarker genes, Bax, Bcmp1, Btg2, Ccng1, Cdkn1a, Cgr19, and Mgmt for GTHCs. Studies involving the use of whole-transcriptome RNA-Seq upon exposure to chemical carcinogens in vivo have also been performed in rodent liver, kidney, lung, colon, and other organs, although discrimination of GTHCs from NGTHCs was not examined. Candidate genes published using RNA-Seq, qPCR, and DNA microarray will be useful for the future development of short-term in vivo studies of environmental carcinogens using RNA-Seq.

Small heat shock protein genes of the green algae Closterium ehrenbergii: Cloning and differential expression under heat and heavy metal stresses

The freshwater green algae Closterium ehrenbergii has been considered as a model for eco-toxicological assessment in aquatic systems. Heat shock proteins (HSPs) are a class of highly conserved proteins produced in all living organisms, which participate in environmental stress responses. In the present study, we determined the cDNA sequences of small heat shock protein 10 (sHSP10) and sHSP17.1 from C. ehrenbergii, and examined the physiological changes and transcriptional responses of the genes after exposure to thermal shock and toxicants treatments. The open reading frame (ORF) of CeHSP10 was 300 bp long, encoding 99 amino acid (aa) residues (10.53 kDa) with a GroES chaperonin conserved site of 22 aa. The CeHSP17.1 had a 468 bp ORF, encoding 155 aa with a conserved C-terminal α-crystallin domain. For heat stress, cells presented pigment loss and possible chloroplast damage, with an up-regulation in the expression of both sHSP10 and sHSP17.1 genes. As for the heavy metal stressors, an increase in the production of reactive oxygen species was registered in a dose dependent manner, with a significant up-regulation of both sHSP10 and sHSP17.1 genes. These results suggest that sHSP genes in C. ehrenbergii may play a role in responses to stress environments, and they could be used as an early detection parameter as biomarker genes in molecular toxicity assessments.

Comparison of toxicogenomics and traditional approaches to inform mode of action and points of departure in human health risk assessment of benzo[a]pyrene in drinking water

Toxicogenomics is proposed to be a useful tool in human health risk assessment. However, a systematic comparison of traditional risk assessment approaches with those applying toxicogenomics has never been done. We conducted a case study to evaluate the utility of toxicogenomics in the risk assessment of benzo[a]pyrene (BaP), a well-studied carcinogen, for drinking water exposures. Our study was intended to compare methodologies, not to evaluate drinking water safety. We compared traditional (RA1), genomics-informed (RA2) and genomics-only (RA3) approaches. RA2 and RA3 applied toxicogenomics data from human cell cultures and mice exposed to BaP to determine if these data could provide insight into BaP's mode of action (MOA) and derive tissue-specific points of departure (POD). Our global gene expression analysis supported that BaP is genotoxic in mice and allowed the development of a detailed MOA. Toxicogenomics analysis in human lymphoblastoid TK6 cells demonstrated a high degree of consistency in perturbed pathways with animal tissues. Quantitatively, the PODs for traditional and transcriptional approaches were similar (liver 1.2 vs. 1.0 mg/kg-bw/day; lungs 0.8 vs. 3.7 mg/kg-bw/day; forestomach 0.5 vs. 7.4 mg/kg-bw/day). RA3, which applied toxicogenomics in the absence of apical toxicology data, demonstrates that this approach provides useful information in data-poor situations. Overall, our study supports the use of toxicogenomics as a relatively fast and cost-effective tool for hazard identification, preliminary evaluation of potential carcinogens, and carcinogenic potency, in addition to identifying current limitations and practical questions for future work.

A toxicogenomic approach for the prediction of murine hepatocarcinogenesis using ensemble feature selection

The current strategy for identifying the carcinogenicity of drugs involves the 2-year bioassay in male and female rats and mice. As this assay is cost-intensive and time-consuming there is a high interest in developing approaches for the screening and prioritization of drug candidates in preclinical safety evaluations. Predictive models based on toxicogenomics investigations after short-term exposure have shown their potential for assessing the carcinogenic risk. In this study, we investigated a novel method for the evaluation of toxicogenomics data based on ensemble feature selection in conjunction with bootstrapping for the purpose to derive reproducible and characteristic multi-gene signatures. This method was evaluated on a microarray dataset containing global gene expression data from liver samples of both male and female mice. The dataset was generated by the IMI MARCAR consortium and included gene expression profiles of genotoxic and nongenotoxic hepatocarcinogens obtained after treatment of CD-1 mice for 3 or 14 days. We developed predictive models based on gene expression data of both sexes and the models were employed for predicting the carcinogenic class of diverse compounds. Comparing the predictivity of our multi-gene signatures against signatures from literature, we demonstrated that by incorporating our gene sets as features slightly higher accuracy is on average achieved by a representative set of state-of-the art supervised learning methods. The constructed models were also used for the classification of Cyproterone acetate (CPA), Wy-14643 (WY) and Thioacetamid (TAA), whose primary mechanism of carcinogenicity is controversially discussed. Based on the extracted mouse liver gene expression patterns, CPA would be predicted as a nongenotoxic compound. In contrast, both WY and TAA would be classified as genotoxic mouse hepatocarcinogens.

Benzo[a]pyrene-induced transcriptomic responses in primary hepatocytes and in vivo liver: toxicokinetics is essential for in vivo-in vitro comparisons

The traditional 2-year cancer bioassay needs replacement by more cost-effective and predictive tests. The use of toxicogenomics in an in vitro system may provide a more high-throughput method to investigate early alterations induced by carcinogens. Recently, the differential gene expression response in wild-type and cancer-prone Xpa (-/-) p53 (+/-) primary mouse hepatocytes after exposure to benzo[a]pyrene (B[a]P) revealed downregulation of cancer-related pathways in Xpa (-/-) p53 (+/-) hepatocytes only. Here, we investigated pathway regulation upon in vivo B[a]P exposure of wild-type and Xpa (-/-) p53 (+/-) mice. In vivo transcriptomics analysis revealed a limited gene expression response in mouse livers, but with a significant induction of DNA replication and apoptotic/anti-apoptotic cellular responses in Xpa (-/-) p53 (+/-) livers only. In order to be able to make a meaningful in vivo-in vitro comparison we estimated internal in vivo B[a]P concentrations using DNA adduct levels and physiologically based kinetic modeling. Based on these results, the in vitro concentration that corresponded best with the internal in vivo dose was chosen. Comparison of in vivo and in vitro data demonstrated similarities in transcriptomics response: xenobiotic metabolism, lipid metabolism and oxidative stress. However, we were unable to detect cancer-related pathways in either wild-type or Xpa (-/-) p53 (+/-) exposed livers, which were previously found to be induced by B[a]P in Xpa (-/-) p53 (+/-) primary hepatocytes. In conclusion, we showed parallels in gene expression responses between livers and primary hepatocytes upon exposure to equivalent concentrations of B[a]P. Furthermore, we recommend considering toxicokinetics when modeling a complex in vivo endpoint with in vitro models.