Hydroxypropyl-ß-cyclodextrin spikes local inflammation that induces Th2 cell and T follicular helper cell responses to the coadministered antigen.

Cyclodextrins are commonly used as a safe excipient to enhance the solubility and bioavailability of hydrophobic pharmaceutical agents. Their efficacies and mechanisms as drug-delivery systems have been investigated for decades, but their immunological properties have not been examined. In this study, we reprofiled hydroxypropyl-ß-cyclodextrin (HP-ß-CD) as a vaccine adjuvant and found that it acts as a potent and unique adjuvant. HP-ß-CD triggered the innate immune response at the injection site, was trapped by MARCO(+) macrophages, increased Ag uptake by dendritic cells, and facilitated the generation of T follicular helper cells in the draining lymph nodes. It significantly enhanced Ag-specific Th2 and IgG Ab responses as potently as did the conventional adjuvant, aluminum salt (alum), whereas its ability to induce Ag-specific IgE was less than that of alum. At the injection site, HP-ß-CD induced the temporary release of host dsDNA, a damage-associated molecular pattern. DNase-treated mice, MyD88-deficient mice, and TBK1-deficient mice showed significantly reduced Ab responses after immunization with this adjuvant. Finally, we demonstrated that HP-ß-CD-adjuvanted influenza hemagglutinin split vaccine protected against a lethal challenge with a clinically isolated pandemic H1N1 influenza virus, and the adjuvant effect of HP-ß-CD was demonstrated in cynomolgus macaques. Our results suggest that HP-ß-CD acts as a potent MyD88- and TBK1-dependent T follicular helper cell adjuvant and is readily applicable to various vaccines.

Open TG-GATEs: a large-scale toxicogenomics database.

Toxicogenomics focuses on assessing the safety of compounds using gene expression profiles. Gene expression signatures from large toxicogenomics databases are expected to perform better than small databases in identifying biomarkers for the prediction and evaluation of drug safety based on a compound's toxicological mechanisms in animal target organs. Over the past 10 years, the Japanese Toxicogenomics Project consortium (TGP) has been developing a large-scale toxicogenomics database consisting of data from 170 compounds (mostly drugs) with the aim of improving and enhancing drug safety assessment. Most of the data generated by the project (e.g. gene expression, pathology, lot number) are freely available to the public via Open TG-GATEs (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System). Here, we provide a comprehensive overview of the database, including both gene expression data and metadata, with a description of experimental conditions and procedures used to generate the database. Open TG-GATEs is available from http://toxico.nibio.go.jp/english/index.html.

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.

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.

"Per cell" normalization method for mRNA measurement by quantitative PCR and microarrays.

BACKGROUND: Transcriptome data from quantitative PCR (Q-PCR) and DNA microarrays are typically obtained from a fixed amount of RNA collected per sample. Therefore, variations in tissue cellularity and RNA yield across samples in an experimental series compromise accurate determination of the absolute level of each mRNA species per cell in any sample. Since mRNAs are copied from genomic DNA, the simplest way to express mRNA level would be as copy number per template DNA, or more practically, as copy number per cell. RESULTS: Here we report a method (designated the "Percellome" method) for normalizing the expression of mRNA values in biological samples. It provides a "per cell" readout in mRNA copy number and is applicable to both quantitative PCR (Q-PCR) and DNA microarray studies. The genomic DNA content of each sample homogenate was measured from a small aliquot to derive the number of cells in the sample. A cocktail of five external spike RNAs admixed in a dose-graded manner (dose-graded spike cocktail; GSC) was prepared and added to each homogenate in proportion to its DNA content. In this way, the spike mRNAs represented absolute copy numbers per cell in the sample. The signals from the five spike mRNAs were used as a dose-response standard curve for each sample, enabling us to convert all the signals measured to copy numbers per cell in an expression profile-independent manner. A series of samples was measured by Q-PCR and Affymetrix GeneChip microarrays using this Percellome method, and the results showed up to 90 % concordance. CONCLUSION: Percellome data can be compared directly among samples and among different studies, and between different platforms, without further normalization. Therefore, "percellome" normalization can serve as a standard method for exchanging and comparing data across different platforms and among different laboratories.

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.

Glucosylceramide and lysophosphatidylcholines as potential blood biomarkers for drug-induced hepatic phospholipidosis.

Drug-induced phospholipidosis is one of the major concerns in drug development and clinical treatment. The present study involved the use of a nontargeting lipidomic analysis with liquid chromatography-mass spectrometry to explore noninvasive blood biomarkers for hepatic phospholipidosis from rat plasma. We used three tricyclic antidepressants (clomipramine [CPM], imipramine [IMI], and amitriptyline [AMT]) for the model of phospholipidosis in hepatocytes and ketoconazole (KC) for the model of phospholipidosis in cholangiocytes and administered treatment for 3 and 28 days each. Total plasma lipids were extracted and measured. Lipid molecules contributing to the separation of control and drug-treated rat plasma in a multivariate orthogonal partial least squares discriminant analysis were identified. Four lysophosphatidylcholines (LPCs) (16:1, 18:1, 18:2, and 20:4) and 42:1 hexosylceramide (HexCer) were identified as molecules separating control and drug-treated rats in all models of phospholipidosis in hepatocytes. In addition, 16:1, 18:2, and 20:4 LPCs and 42:1 HexCer were identified in a model of hepatic phospholipidosis in cholangiocytes, although LPCs were identified only in the case of 3-day treatment with KC. The levels of LPCs were decreased by drug-induced phospholipidosis, whereas those of 42:1 HexCer were increased. The increase in 42:1 HexCer was much higher in the case of IMI and AMT than in the case of CPM; moreover, the increase induced by IMI was dose-dependent. Structural characterization determining long-chain base and hexose delineated that 42:1 HexCer was d18:1/24:0 glucosylceramide (GluCer). In summary, our study demonstrated that d18:1/24:0 GluCer and LPCs are potential novel biomarkers for drug-induced hepatic phospholipidosis.

Identification of novel liver-specific mRNAs in plasma for biomarkers of drug-induced liver injury and quantitative evaluation in rats treated with various hepatotoxic compounds.

Circulating liver-specific mRNAs such as albumin (Alb) and α-1-microglobulin/bikunin precursor (Ambp) have been reported to be potential biomarkers for drug-induced liver injury (DILI). We identified novel circulating liver-specific mRNAs and quantified them, together with the two previously reported mRNAs, in plasma from rats treated with various hepatotoxicants to validate circulating liver-specific mRNAs as biomarkers for DILI. Among six genes selected from the database, high liver specificity of apolipoprotein h (Apoh) and group-specific component (Gc) mRNAs were confirmed by reverse transcription (RT)-PCR and the copy numbers of these mRNAs elevated in plasma from rats treated with thioacetamide. Liver-specific mRNAs (Alb, Ambp, Apoh, and Gc) were quantified by real-time RT-PCR in plasma from rats with single dosing of seven hepatotoxicants. There were noticeable interindividual and intercompound variabilities in the severity of liver injury. The levels of four mRNAs increased almost in parallel and correlated with changes in the alanine aminotransferase (ALT) values and the hepatocellular necrosis scores at 24h after dosing. It was noteworthy that the magnitude of the increases in mRNA levels was greater than that in the ALT value. Time course analysis within 24h after dosing revealed that the timing of the increase was different among mRNA species, and the plasma levels of Alb and Gc mRNAs increased substantially earlier than the ALT values, suggesting that patterns of changes in circulating liver-specific mRNAs indicate the progression of liver injury. These results strongly support the reliability and usefulness of the four circulating liver-specific mRNAs as biomarkers for DILI.

Toxicogenomic biomarkers for renal papillary injury in rats.

Renal papillary injury is a common side effect observed during nonclinical and clinical investigations in drug development. The present study aimed to identify genomic biomarkers for early and sensitive detection of renal papillary injury in rats. We hypothesized that previously identified genomic biomarkers for tubular injury might be applicable for the sensitive detection of papillary injury in rats. We selected 18 genes as candidate biomarkers for papillary injury based on previously published studies and analyzed their expression profiles by RT-PCR in each kidney region, namely the cortex, cortico-medullary junction, and papilla in various nephrotoxicity models. Comparative analysis of gene expression profiles revealed that some genes were commonly upregulated or downregulated in the renal papilla, reflecting papillary injuries induced by 2-bromoethylamine hydrobromide, phenylbutazone, or n-phenylanthranilic acid. By applying receiver operator characteristics analysis, six candidate biomarkers were identified and their usefulness was confirmed by using an independent data set. The three top-ranked genes, Timp1, Igf1, and Lamc2, exhibited the best prediction performance in an external data set with area under the curve (AUC) values of greater than 0.91. An optimized support vector machine model consisting of three genes achieved the highest AUC value of 0.99. In conclusion, even though definitive validation studies are required for the establishment of their usefulness and reliability, these identified genes may prove to be the most promising candidate genomic biomarkers of renal papillary injury in rats.

Oral administration of pentachlorophenol induces interferon signaling mRNAs in C57BL/6 male mouse liver.

Pentachlorophenol (PCP) was monitored for transcriptome responses in adult mouse liver at 2, 4, 8 and 24 hr after a single oral administration at four dose levels, 0, 10, 30 and 100 mg/kg. The expression data obtained using Affymetrix GeneChip MOE430 2.0 were absolutized by the Percellome method and expressed as three dimensional (3D) surface graphs with axes of time, dose and copy numbers of mRNA per cell. We developed the programs RSort, for comprehensive screening of the 3D surface data and PercellomeExploror for cross-referencing and confirmed the significant responses by visual inspection. In the first 8 hr, approximately 100 probe sets (PSs) related to PXR/SXR and Cyp2a4 and other metabolic enzymes were induced whereas Fos and JunB were suppressed. At 24 hr, about 1,200 PSs were strongly induced. We cross-referenced the Percellome database consisting of 111 chemicals on the liver transcriptome and found that about half of the PSs belonged to the metabolic pathways including Nrf2-mediated oxidative stress response networks shared with some of the 111 chemicals. The other half of the induced genes were interferon signaling network genes (ISG) and their induction was unique to PCP. Toll like receptors and other pattern recognition receptors, interferon regulatory factors and interferon alpha itself were included but inflammatory cytokines were not induced. In summary, these data indicated that functional symptoms of PCP treatment, such as hyperthermia and profuse sweating might be mediated by the ISG rather than the previously documented mitochondrial uncoupling mechanism. PCP might become a hint for developing low molecular weight orally available interferon mimetic drugs following imiquimod and RO4948191 as agonists of toll-like receptor and interferon receptor.

Toxicogenomic multigene biomarker for predicting the future onset of proximal tubular injury in rats.

Drug-induced renal tubular injury is a major concern in the preclinical safety evaluation of drug candidates. Toxicogenomics is now a generally accepted tool for identifying chemicals with potential safety problems. The specific aim of the present study was to develop a model for use in predicting the future onset of drug-induced proximal tubular injury following repeated dosing with various nephrotoxicants. In total, 41 nephrotoxic and nonnephrotoxic compounds were used for the present analysis. Male Sprague-Dawley rats were dosed orally or intravenously once daily. Animals were exposed to three different doses (low, middle, and high) of each compound, and kidney tissue was collected at 3, 6, 9, and 24 h after single dosing, and on days 4, 8, 15, and 29 after repeated dosing. Gene expression profiles were generated from kidney total RNA using Affymetrix DNA microarrays. Filter-type gene selection and linear classification algorithms were employed to discriminate future onset of proximal tubular injury. We identified genomic biomarkers for use in future onset prediction using the gene expression profiles determined on day 1, when most of the nephrotoxicants had yet to produce detectable histopathological changes. The model was evaluated using a five-fold cross validation, and achieved a sensitivity of 93% and selectivity of 90% with 19 probes. We also found that the prediction accuracy of the optimized model was substantially higher than that produced by any of the single genomic biomarkers or histopathology. The genes included in our model were primarily involved in DNA replication, cell cycle control, apoptosis, and responses to oxidative stress and chemical stimuli. In summary, our toxicogenomic model is particularly useful for predicting the future onset of proximal tubular injury.

Identification of genomic biomarkers for concurrent diagnosis of drug-induced renal tubular injury using a large-scale toxicogenomics database.

Drug-induced renal tubular injury is one of the major concerns in preclinical safety evaluations. Toxicogenomics is becoming a generally accepted approach for identifying chemicals with potential safety problems. In the present study, we analyzed 33 nephrotoxicants and 8 non-nephrotoxic hepatotoxicants to elucidate time- and dose-dependent global gene expression changes associated with proximal tubular toxicity. The compounds were administered orally or intravenously once daily to male Sprague-Dawley rats. The animals were exposed to four different doses of the compounds, and kidney tissues were collected on days 4, 8, 15, and 29. Gene expression profiles were generated from kidney RNA by using Affymetrix GeneChips and analyzed in conjunction with the histopathological changes. We used the filter-type gene selection algorithm based on t-statistics conjugated with the SVM classifier, and achieved a sensitivity of 90% with a selectivity of 90%. Then, 92 genes were extracted as the genomic biomarker candidates that were used to construct the classifier. The gene list contains well-known biomarkers, such as Kidney injury molecule 1, Ceruloplasmin, Clusterin, Tissue inhibitor of metallopeptidase 1, and also novel biomarker candidates. Most of the genes involved in tissue remodeling, the immune/inflammatory response, cell adhesion/proliferation/migration, and metabolism were predominantly up-regulated. Down-regulated genes participated in cell adhesion/proliferation/migration, membrane transport, and signal transduction. Our classifier has better prediction accuracy than any of the well-known biomarkers. Therefore, the toxicogenomics approach would be useful for concurrent diagnosis of renal tubular injury.

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.