Generation of Human iPSC-Derived Intestinal Epithelial Cell Monolayers by CDX2 Transduction.

BACKGROUND & AIMS: To develop an effective and safe orally administered drug, it is important to predict its intestinal absorption rate, intestinal first-pass effect, and drug-drug interactions of orally administered drugs. However, there is no existing model to comprehensively predict the intestinal pharmacokinetics and drug-response of orally administered drugs. In this study, we attempted to generate homogenous and functional intestinal epithelial cells from human induced pluripotent stem (iPS) cells for pharmaceutical research. METHODS: We generated almost-homogenous Villin- and zonula occludens-1 (ZO1)-positive intestinal epithelial cells by caudal-related homeobox transcription factor 2 (CDX2) transduction into human iPS cell-derived intestinal progenitor cells. RESULTS: The drug absorption rates in human iPS cell-derived intestinal epithelial cell monolayers (iPS-IECM) were highly correlated with those in humans (R2=0.91). The expression levels of cytochrome P450 (CYP) 3A4, a dominant drug-metabolizing enzyme in the small intestine, in human iPS-IECM were similar to those in human small intestine in vivo. In addition, intestinal availability in human iPS-IECM (the fraction passing the gut wall: Fg=0.73) was more similar to that in the human small intestine in vivo (Fg=0.57) than to that in Caco-2 cells (Fg=0.99), a human colorectal adenocarcinoma cell line. Moreover, the drug-drug interaction and drug-food interaction could be observed by using our human iPS-IECM in the presence of an inducer and inhibitor of CYP3A4, i.e., rifampicin and grape fruit juice, respectively. CONCLUSION: Taking these results together, we succeeded in generating the human iPS-IECM that can be applied to various intestinal pharmacokinetics and drug-response tests of orally administered drugs.

Quantifying the relative immune cell activation from whole tissue/organ-derived differentially expressed gene data.

Evaluation of immune responses in individual immune cell types is important for the development of new medicines. Here, we propose a computational method designated ICEPOP (Immune CEll POPulation) to estimate individual immune cell type responses from bulk tissue and organ samples. The relative gene responses are scored for each cell type by using the data from differentially expressed genes derived from control- vs drug-treated sample pairs, and the data from public databases including ImmGen and IRIS, which contain gene expression profiles of a variety of immune cells. By ICEPOP, we analysed cell responses induced by vaccine-adjuvants in the mouse spleen, and extended the analyses to human peripheral blood mononuclear cells and gut biopsy samples focusing on human papilloma virus vaccination and inflammatory bowel disease treatment with Infliximab. In both mouse and human datasets, our method reliably quantified the responding immune cell types and provided insightful information, demonstrating that our method is useful to evaluate immune responses from bulk sample-derived gene expression data. ICEPOP is available as an interactive web site ( https://vdynamics.shinyapps.io/icepop/ ) and Python package ( https://github.com/ewijaya/icepop ).

Isoflurane is a suitable alternative to ether for anesthetizing rats prior to euthanasia for gene expression analysis.

Diethyl ether (ether) had been widely used in Japan for anesthesia, despite its explosive properties and toxicity to both humans and animals. We also had used ether as an anesthetic for euthanizing rats for research in the Toxicogenomics Project (TGP). Because the use of ether for these purposes will likely cease, it is required to select an alternative anesthetic which is validated for consistency with existing TGP data acquired under ether anesthesia. We therefore compared two alternative anesthetic candidates, isoflurane and pentobarbital, with ether in terms of hematological findings, serum biochemical parameters, and gene expressions. As a result, few differences among the three agents were observed. In hematological and serum biochemistry analysis, no significant changes were found. In gene expression analysis, four known genes were extracted as differentially expressed genes in the liver of rats anesthetized with ether, isoflurane, or pentobarbital. However, no significant relationships were detected using gene ontology, pathway, or gene enrichment analyses by DAVID and TargetMine. Surprisingly, although it was expected that the lung would be affected by administration via inhalation, only one differentially expressed gene was extracted in the lung. Taken together, our data indicate that there are no significant differences among ether, isoflurane, and pentobarbital with respect to effects on hematological parameters, serum biochemistry parameters, and gene expression. Based on its smallest affect to existing data and its safety profile for humans and animals, we suggest isoflurane as a suitable alternative anesthetic for use in rat euthanasia in toxicogenomics analysis.

Advax, a Delta Inulin Microparticle, Potentiates In-built Adjuvant Property of Co-administered Vaccines.

Advax, a delta inulin-derived microparticle, has been developed as an adjuvant for several vaccines. However, its immunological characteristics and potential mechanism of action are yet to be elucidated. Here, we show that Advax behaves as a type-2 adjuvant when combined with influenza split vaccine, a T helper (Th)2-type antigen, but behaves as a type-1 adjuvant when combined with influenza inactivated whole virion (WV), a Th1-type antigen. In addition, an adjuvant effect was not observed when Advax-adjuvanted WV vaccine was used to immunize toll-like receptor (TLR) 7 knockout mice which are unable to respond to RNA contained in WV antigen. Similarly, no adjuvant effect was seen when Advax was combined with endotoxin-free ovalbumin, a neutral Th0-type antigen. An adjuvant effect was also not seen in tumor necrosis factor (TNF)-α knockout mice, and the adjuvant effect required the presences of dendritic cells (DCs) and phagocytic macrophages. Therefore, unlike other adjuvants, Advax potentiates the intrinsic or in-built adjuvant property of co-administered antigens. Hence, Advax is a unique class of adjuvant which can potentiate the intrinsic adjuvant feature of the vaccine antigens through a yet to be determined mechanism.

Plasma lipid profiling of different types of hepatic fibrosis induced by carbon tetrachloride and lomustine in rats.

BACKGROUND: Plasma lipid profiling has emerged as a useful tool for understanding the pathophysiology of hepatic injury and disease. Hepatic fibrosis results from chronic, progressive damage to the liver and can lead, in turn, to more serious conditions such as hepatic cirrhosis and hepatocellular carcinoma. Thus, the present study aimed to investigate the plasma lipid profiles of two types of hepatic fibrosis in order to aid the understanding of the pathophysiology of hepatic fibrosis. METHODS: A liquid chromatography and mass spectrometry platform was used to reveal and compare the plasma lipid profiles of two types of chemical-induced hepatic fibrosis. Rat models of centrilobular fibrosis and bile duct fibrosis were established via chronic exposure to the known fibrogenic hepatotoxins, carbon tetrachloride (CCl4) or lomustine (LS), respectively, over a 28-day period. To delineate the specific alterations in the lipid profiles as a result of the hepatic fibrosis, we also employed non-fibrogenic hepatotoxicants (2-acetamidofluorene, N-nitrosodiethylamine, and ethambutol) as well as 3-day treatment of CCl4 and LS, which did not induce fibrosis. RESULTS: Our assay platform identified 228 lipids in the rat plasma, and the global lipid profile clearly distinguished these models from the control via principal component analysis. In addition, the alteration of the plasma lipid profile caused by CCl4 and LS were clearly different. Furthermore, a number of lipids were identified as specific alterations caused by fibrosis induced only by CCl4 and LS, respectively. Three lysophosphatidylcholines (LPC[18:3], LPC[20:4], and LPC[22:6]), and three phosphatidylcholines (PC[18:2/20:4], PC[40:8], and PC[20:4/22:6]) are specific circulating lipids, the levels of which were altered by both CCl4 and LS treatment; however, their levels were decreased by chronic exposure to CCl4 and increased by chronic exposure to LS. CONCLUSIONS: These results suggest that different types of chemical-induced hepatic fibrosis demonstrate clear differences in their plasma lipid profiles. Our study provides insights into the alteration of plasma lipidomic profiles as a result of the fibrosis of different parts of the hepatic lobule, and may help to understand the pathophysiology of different types of hepatic fibrosis.

Toxygates: interactive toxicity analysis on a hybrid microarray and linked data platform.

MOTIVATION: In early stage drug development, it is desirable to assess the toxicity of compounds as quickly as possible. Biomarker genes can help predict whether a candidate drug will adversely affect a given individual, but they are often difficult to discover. In addition, the mechanism of toxicity of many drugs and common compounds is not yet well understood. The Japanese Toxicogenomics Project provides a large database of systematically collected microarray samples from rats (liver, kidney and primary hepatocytes) and human cells (primary hepatocytes) after exposure to 170 different compounds in different dosages and at different time intervals. However, until now, no intuitive user interface has been publically available, making it time consuming and difficult for individual researchers to explore the data. RESULTS: We present Toxygates, a user-friendly integrated analysis platform for this database. Toxygates combines a large microarray dataset with the ability to fetch semantic linked data, such as pathways, compound-protein interactions and orthologs, on demand. It can also perform pattern-based compound ranking with respect to the expression values of a set of relevant candidate genes. By using Toxygates, users can freely interrogate the transcriptome's response to particular compounds and conditions, which enables deep exploration of toxicity mechanisms.

Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database.

The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificity in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing.

Mechanism-based biomarker gene sets for glutathione depletion-related hepatotoxicity in rats.

Chemical-induced glutathione depletion is thought to be caused by two types of toxicological mechanisms: PHO-type glutathione depletion [glutathione conjugated with chemicals such as phorone (PHO) or diethyl maleate (DEM)], and BSO-type glutathione depletion [i.e., glutathione synthesis inhibited by chemicals such as l-buthionine-sulfoximine (BSO)]. In order to identify mechanism-based biomarker gene sets for glutathione depletion in rat liver, male SD rats were treated with various chemicals including PHO (40, 120 and 400 mg/kg), DEM (80, 240 and 800 mg/kg), BSO (150, 450 and 1500 mg/kg), and bromobenzene (BBZ, 10, 100 and 300 mg/kg). Liver samples were taken 3, 6, 9 and 24 h after administration and examined for hepatic glutathione content, physiological and pathological changes, and gene expression changes using Affymetrix GeneChip Arrays. To identify differentially expressed probe sets in response to glutathione depletion, we focused on the following two courses of events for the two types of mechanisms of glutathione depletion: a) gene expression changes occurring simultaneously in response to glutathione depletion, and b) gene expression changes after glutathione was depleted. The gene expression profiles of the identified probe sets for the two types of glutathione depletion differed markedly at times during and after glutathione depletion, whereas Srxn1 was markedly increased for both types as glutathione was depleted, suggesting that Srxn1 is a key molecule in oxidative stress related to glutathione. The extracted probe sets were refined and verified using various compounds including 13 additional positive or negative compounds, and they established two useful marker sets. One contained three probe sets (Akr7a3, Trib3 and Gstp1) that could detect conjugation-type glutathione depletors any time within 24h after dosing, and the other contained 14 probe sets that could detect glutathione depletors by any mechanism. These two sets, with appropriate scoring systems, could be promising biomarkers for preclinical examination of hepatotoxicity.

Identification of candidate genes determining chemosensitivity to anti-cancer drugs of gastric cancer cell lines.

In order to efficiently develop improved cancer therapies it is important to predict the efficacy of anti-cancer drugs. In this regard, identification of genes that are related to drug sensitivity is vital. We previously established a panel of 39 human cancer cell lines (JFCR39) and a panel aiming for organ-specific analysis of 45 human cancer cell lines (JFCR45). Here, we focus on 20 human gastric cancer cell lines from JFCR45, a panel of human cancer cell lines to predict genes that determine chemosensitivity to anti-cancer drugs. We measured both chemosensitivity to a range of anti-cancer drugs as well as changes in gene expression profile. We then identified genes in which expression is related to chemosensitivity by using a Pearson correlation. As a result, anti-cancer drugs that have similar mechanisms of action showed similar fingerprints against a gastric subpanel of human cancer cell lines, as was the case with JFCR39 and JFCR45. Furthermore, we identified many candidate genes related to the sensitivity of gastric cancer cells to anti-cancer drugs.

Evaluation of action mechanisms of toxic chemicals using JFCR39, a panel of human cancer cell lines.

We previously established a panel of human cancer cell lines, JFCR39, coupled to an anticancer drug activity database; this panel is comparable with the NCI60 panel developed by the National Cancer Institute. The JFCR39 system can be used to predict the molecular targets or evaluate the action mechanisms of the test compounds by comparing their cell growth inhibition profiles (i.e., fingerprints) with those of the standard anticancer drugs using the COMPARE program. In this study, we used this drug activity database-coupled JFCR39 system to evaluate the action mechanisms of various chemical compounds, including toxic chemicals, agricultural chemicals, drugs, and synthetic intermediates. Fingerprints of 130 chemicals were determined and stored in the database. Sixty-nine of 130 chemicals ( approximately 60%) satisfied our criteria for the further analysis and were classified by cluster analysis of the fingerprints of these chemicals and several standard anticancer drugs into the following three clusters: 1) anticancer drugs, 2) chemicals that shared similar action mechanisms (for example, ouabain and digoxin), and 3) chemicals whose action mechanisms were unknown. These results suggested that chemicals belonging to a cluster (i.e., a cluster of toxic chemicals, a cluster of anticancer drugs, etc.) shared similar action mechanism. In summary, the JFCR39 system can classify chemicals based on their fingerprints, even when their action mechanisms are unknown, and it is highly probable that the chemicals within a cluster share common action mechanisms.

Chemosensitivity profile of cancer cell lines and identification of genes determining chemosensitivity by an integrated bioinformatical approach using cDNA arrays.

We have established a panel of 45 human cancer cell lines (JFCR-45) to explore genes that determine the chemosensitivity of these cell lines to anticancer drugs. JFCR-45 comprises cancer cell lines derived from tumors of three different organs: breast, liver, and stomach. The inclusion of cell lines derived from gastric and hepatic cancers is a major point of novelty of this study. We determined the concentration of 53 anticancer drugs that could induce 50% growth inhibition (GI50) in each cell line. Cluster analysis using the GI50s indicated that JFCR-45 could allow classification of the drugs based on their modes of action, which coincides with previous findings in NCI-60 and JFCR-39. We next investigated gene expression in JFCR-45 and developed an integrated database of chemosensitivity and gene expression in this panel of cell lines. We applied a correlation analysis between gene expression profiles and chemosensitivity profiles, which revealed many candidate genes related to the sensitivity of cancer cells to anticancer drugs. To identify genes that directly determine chemosensitivity, we further tested the ability of these candidate genes to alter sensitivity to anticancer drugs after individually overexpressing each gene in human fibrosarcoma HT1080. We observed that transfection of HT1080 cells with the HSPA1A and JUN genes actually enhanced the sensitivity to mitomycin C, suggesting the direct participation of these genes in mitomycin C sensitivity. These results suggest that an integrated bioinformatical approach using chemosensitivity and gene expression profiling is useful for the identification of genes determining chemosensitivity of cancer cells.