Translating whole exome sequencing (WES) for prospective clinical use may impact the care of cancer patients; however, multiple innovations are necessary for clinical implementation. These include: (1) rapid and robust WES from formalin-fixed paraffin embedded (FFPE) tumor tissue, (2) analytical output similar to data from frozen samples, and (3) clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival FFPE tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a “long tail” of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15/16 patients. In one patient, previously undetected findings guided clinical trial enrollment leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine.
The U.S. Tox21 program has screened a library of approximately 10,000 (10K) environmental chemicals and drugs in three independent runs for estrogen receptor alpha (ERα) agonist and antagonist activity using two types of ER reporter gene cell lines, one with an endogenous full length ERα (ER-luc; BG1 cell line) and the other with a transfected partial receptor consisting of the ligand binding domain (ER-bla; ERα β-lactamase cell line), in a quantitative high-throughput screening (qHTS) format. The ability of the two assays to correctly identify ERα agonists and antagonists was evaluated using a set of 39 reference compounds with known ERα activity. Although both assays demonstrated adequate (i.e. >80%) predictivity, the ER-luc assay was more sensitive and the ER-bla assay more specific. The qHTS assay results were compared with results from previously published ERα binding assay data and showed >80% consistency. Actives identified from both the ER-bla and ER-luc assays were analyzed for structure-activity relationships (SARs) revealing known and potentially novel ERα active structure classes. The results demonstrate the feasibility of qHTS to identify environmental chemicals with the potential to interact with the ERα signaling pathway and the two different assay formats improve the confidence in correctly identifying these chemicals.
Differentiation of human embryonic stem cells (hESCs) provides a unique opportunity to study the regulatory mechanisms that facilitate cellular transitions in a human context. To that end, we performed comprehensive transcriptional and epigenetic profiling of populations derived through directed differentiation of hESCs representing each of the three embryonic germ layers. Integration of whole genome bisulfite sequencing, chromatin immunoprecipitation-sequencing and RNA-sequencing reveals unique events associated with specification towards each lineage. Dynamic alterations in DNA methylation and H3K4me1 are evident at putative distal regulatory elements bound by pluripotency factors or activated in specific lineages. In addition, we identified germ layer-specific H3K27me3 enrichment at sites exhibiting high DNA methylation in the undifferentiated state. A better understanding of these initial specification events will facilitate identification of deficiencies in current approaches leading to more faithful differentiation strategies as well as provide insights into the rewiring of human regulatory programs during cellular transitions.
Aims: Nrf2 is an essential transcription factor for protection against oxidant disorders. However, its role in organ development and neonatal disease has received little attention. Therapeutically administered oxygen has been considered to contribute to bronchopulmonary dysplasia (BPD) in prematurity. The current study was performed to determine Nrf2-mediated molecular events during saccular-to-alveolar lung maturation, and the role of Nrf2 in the pathogenesis of hyperoxic lung injury using newborn Nrf2-deficient (Nrf2−/−) and wild-type (Nrf2+/+) mice. Results: Pulmonary basal expression of cell cycle, redox balance, and lipid/carbohydrate metabolism genes was lower while lymphocyte immunity genes were more highly expressed in Nrf2−/− neonates than in Nrf2+/+ neonates. Hyperoxia-induced phenotypes, including mortality, arrest of saccular-to-alveolar transition, and lung edema, and inflammation accompanying DNA damage and tissue oxidation were significantly more severe in Nrf2−/− neonates than in Nrf2+/+ neonates. During lung injury pathogenesis, Nrf2 orchestrated expression of lung genes involved in organ injury and morphology, cellular growth/proliferation, vasculature development, immune response, and cell–cell interaction. Bioinformatic identification of Nrf2 binding motifs and augmented hyperoxia-induced inflammation in genetically deficient neonates supported Gpx2 and Marco as Nrf2 effectors. Innovation: This investigation used lung transcriptomics and gene targeted mice to identify novel molecular events during saccular-to-alveolar stage transition and to elucidate Nrf2 downstream mechanisms in protection from hyperoxia-induced injury in neonate mouse lungs. Conclusion:
Nrf2 deficiency augmented lung injury and arrest of alveolarization caused by hyperoxia during the newborn period. Results suggest a therapeutic potential of specific Nrf2 activators for oxidative stress-associated neonatal disorders including BPD. Antioxid. Redox Signal. 00, 000–000.
The use of gene expression profiling in both clinical and laboratory settings would be enhanced by better characterization of variation due to individual, environmental, and technical factors. Analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in liver gene expression in the rodent. Here, studies which highlight contributions of different factors to gene expression variability in the rodent liver are discussed including a large meta-analysis of rat liver, which identified genes that vary in control animals in the absence of chemical treatment. Genes and their pathways that are the most and least variable were identified in a number of these studies. Life stage, fasting, sex, diet, circadian rhythm and liver lobe source can profoundly influence gene expression in the liver. Recognition of biological and technical factors that contribute to variability of background gene expression can help the investigator in the design of an experiment that maximizes sensitivity and reduces the influence of confounders that may lead to misinterpretation of genomic changes. The factors that contribute to variability in liver gene expression in rodents are likely analogous to those contributing to human interindividual variability in drug response and chemical toxicity. Identification of batteries of genes that are altered in a variety of background conditions could be used to predict responses to drugs and chemicals in appropriate models of the human liver.
toxicogenomics; baseline expression; microarray; fasting; sex; circadian rhythm; microbiota; life stage; diet
As researchers begin probing deep coverage sequencing data for increasingly rare mutations and subclonal events, the fidelity of next generation sequencing (NGS) laboratory methods will become increasingly critical. Although error rates for sequencing and polymerase chain reaction (PCR) are well documented, the effects that DNA extraction and other library preparation steps could have on downstream sequence integrity have not been thoroughly evaluated. Here, we describe the discovery of novel C > A/G > T transversion artifacts found at low allelic fractions in targeted capture data. Characteristics such as sequencer read orientation and presence in both tumor and normal samples strongly indicated a non-biological mechanism. We identified the source as oxidation of DNA during acoustic shearing in samples containing reactive contaminants from the extraction process. We show generation of 8-oxoguanine (8-oxoG) lesions during DNA shearing, present analysis tools to detect oxidation in sequencing data and suggest methods to reduce DNA oxidation through the introduction of antioxidants. Further, informatics methods are presented to confidently filter these artifacts from sequencing data sets. Though only seen in a low percentage of reads in affected samples, such artifacts could have profoundly deleterious effects on the ability to confidently call rare mutations, and eliminating other possible sources of artifacts should become a priority for the research community.
Sequencing-based approaches have led to new insights about DNA methylation. While many different techniques for genome-scale mapping of DNA methylation have been employed, throughput has been a key limitation for most. To further facilitate the mapping of DNA methylation, we describe a protocol for gel-free multiplexed reduced representation bisulfite sequencing (mRRBS) that reduces the workload dramatically and enables processing of 96 or more samples per week. mRRBS achieves similar CpG coverage to the original RRBS protocol, while the higher throughput and lower cost make it better suited for large-scale DNA methylation mapping studies, including cohorts of cancer samples.
The use of gene signatures can potentially be of considerable value in the field of clinical diagnosis. However, gene signatures defined with different methods can be quite various even when applied the same disease and the same endpoint. Previous studies have shown that the correct selection of subsets of genes from microarray data is key for the accurate classification of disease phenotypes, and a number of methods have been proposed for the purpose. However, these methods refine the subsets by only considering each single feature, and they do not confirm the association between the genes identified in each gene signature and the phenotype of the disease. We proposed an innovative new method termed Minimize Feature's Size (MFS) based on multiple level similarity analyses and association between the genes and disease for breast cancer endpoints by comparing classifier models generated from the second phase of MicroArray Quality Control (MAQC-II), trying to develop effective meta-analysis strategies to transform the MAQC-II signatures into a robust and reliable set of biomarker for clinical applications.
We analyzed the similarity of the multiple gene signatures in an endpoint and between the two endpoints of breast cancer at probe and gene levels, the results indicate that disease-related genes can be preferably selected as the components of gene signature, and that the gene signatures for the two endpoints could be interchangeable. The minimized signatures were built at probe level by using MFS for each endpoint. By applying the approach, we generated a much smaller set of gene signature with the similar predictive power compared with those gene signatures from MAQC-II.
Our results indicate that gene signatures of both large and small sizes could perform equally well in clinical applications. Besides, consistency and biological significances can be detected among different gene signatures, reflecting the studying endpoints. New classifiers built with MFS exhibit improved performance with both internal and external validation, suggesting that MFS method generally reduces redundancies for features within gene signatures and improves the performance of the model. Consequently, our strategy will be beneficial for the microarray-based clinical applications.
Cancer stem cells are presumed to have virtually unlimited proliferative and self-renewal abilities and to be highly resistant to chemotherapy, a feature that is associated with overexpression of ATP-binding cassette transporters. We investigated whether prolonged continuous selection of cells for drug resistance enriches cultures for cancer stem–like cells.
Cancer stem cells were defined as CD44+/CD24− cells that could self-renew (ie, generate cells with the tumorigenic CD44+/CD24− phenotype), differentiate, invade, and form tumors in vivo. We used doxorubicin-selected MCF-7/ADR cells, weakly tumorigenic parental MCF-7 cells, and MCF-7/MDR, an MCF-7 subline with forced expression of ABCB1 protein. Cells were examined for cell surface markers and side-population fractions by microarray and flow cytometry, with in vitro invasion assays, and for ability to form mammospheres. Xenograft tumors were generated in mice to examine tumorigenicity (n = 52). The mRNA expression of multidrug resistance genes was examined in putative cancer stem cells and pathway analysis of statistically significantly differentially expressed genes was performed. All statistical tests were two-sided.
Pathway analysis showed that MCF-7/ADR cells express mRNAs from ABCB1 and other genes also found in breast cancer stem cells (eg, CD44, TGFB1, and SNAI1). MCF-7/ADR cells were highly invasive, formed mammospheres, and were tumorigenic in mice. In contrast to parental MCF-7 cells, more than 30% of MCF-7/ADR cells had a CD44+/CD24− phenotype, could self-renew, and differentiate (ie, produce CD44+/CD24− and CD44+/CD24+ cells) and overexpressed various multidrug resistance–linked genes (including ABCB1, CCNE1, and MMP9). MCF-7/ADR cells were statistically significantly more invasive in Matrigel than parental MCF-7 cells (MCF-7 cells = 0.82 cell per field and MCF-7/ADR = 7.51 cells per field, difference = 6.69 cells per field, 95% confidence interval = 4.82 to 8.55 cells per field, P < .001). No enrichment in the CD44+/CD24− or CD133+ population was detected in MCF-7/MDR.
The cell population with cancer stem cell characteristics increased after prolonged continuous selection for doxorubicin resistance.
Nrf2 is a key transcription factor that regulates cellular redox and defense responses. However, permanent Nrf2 activation in human lung carcinomas promotes pulmonary malignancy and chemoresistance. We tested the hypothesis that Nrf2 has cell survival properties and lack of Nrf2 suppresses chemically-induced pulmonary neoplasia by treating Nrf2+/+ and Nrf2-/- mice with urethane. Airway inflammation and injury were assessed by bronchoalveolar lavage analyses and histopathology, and lung tumors were analyzed by gross and histologic analysis. We used transcriptomics to assess Nrf2-dependent changes in pulmonary gene transcripts at multiple stages of neoplasia. Lung hyperpermeability, cell death and apoptosis, and inflammatory cell infiltration were significantly higher in Nrf2-/- mice compared to Nrf2+/+ mice 9 and 11 wk after urethane. Significantly fewer lung adenomas were found in Nrf2-/- mice than in Nrf2+/+ mice at 12 and 22 wk. Nrf2 modulated expression of genes involved cell-cell signaling, glutathione metabolism and oxidative stress response, and immune responses during early stage neoplasia. In lung tumors, Nrf2-altered genes had roles in transcriptional regulation of cell cycle and proliferation, carcinogenesis, organismal injury and abnormalities, xenobiotic metabolism, and cell-cell signaling genes. Collectively, Nrf2 deficiency decreased susceptibility to urethane-induced lung tumorigenesis in mice. Cell survival properties of Nrf2 were supported, at least in part, by reduced early death of initiated cells and heightened advantage for tumor cell expansion in Nrf2+/+ mice relative to Nrf2-/- mice. Our results were consistent with the concept that Nrf2 over-activation is an adaptive response of cancer conferring resistance to anti-cancer drugs and promoting malignancy.
This report summarizes the proceedings of the second workshop of the ‘Minimum Information for Biological and Biomedical Investigations’ (MIBBI) consortium held on Dec 1-2, 2010 in Rüdesheim, Germany through the sponsorship of the Beilstein-Institute. MIBBI is an umbrella organization uniting communities developing Minimum Information (MI) checklists to standardize the description of data sets, the workflows by which they were generated and the scientific context for the work. This workshop brought together representatives of more than twenty communities to present the status of their MI checklists and plans for future development. Shared challenges and solutions were identified and the role of MIBBI in MI checklist development was discussed. The meeting featured some thirty presentations, wide-ranging discussions and breakout groups. The top outcomes of the two-day workshop as defined by the participants were: 1) the chance to share best practices and to identify areas of synergy; 2) defining a series of tasks for updating the MIBBI Portal; 3) reemphasizing the need to maintain independent MI checklists for various communities while leveraging common terms and workflow elements contained in multiple checklists; and 4) revision of the concept of the MIBBI Foundry to focus on the creation of a core set of MIBBI modules intended for reuse by individual MI checklist projects while maintaining the integrity of each MI project. Further information about MIBBI and its range of activities can be found at http://mibbi.org/.
The mechanisms underlying ozone (O3)-induced pulmonary inflammation remain unclear. Interleukin-10 (IL-10) is an anti-inflammatory cytokine that is known to inhibit inflammatory mediators.
We investigated the molecular mechanisms underlying interleuken-10 (IL-10)–mediated attenuation of O3-induced pulmonary inflammation in mice.
Il10-deficient (Il10−/−) and wild-type (Il10+/+) mice were exposed to 0.3 ppm O3 or filtered air for 24, 48, or 72 hr. Immediately after exposure, differential cell counts and total protein (a marker of lung permeability) were assessed from bronchoalveolar lavage fluid (BALF). mRNA and protein levels of cellular mediators were determined from lung homogenates. We also used global mRNA expression analyses of lung tissue with Ingenuity Pathway Analysis to identify patterns of gene expression through which IL-10 modifies O3-induced inflammation.
Mean numbers of BALF polymorphonuclear leukocytes (PMNs) were significantly greater in Il10−/− mice than in Il10+/+ mice after exposure to O3 at all time points tested. O3-enhanced nuclear NF-κB translocation was elevated in the lungs of Il10−/− compared with Il10+/+ mice. Gene expression analyses revealed several IL-10–dependent and O3-dependent mediators, including macrophage inflammatory protein 2, cathepsin E, and serum amyloid A3.
Results indicate that IL-10 protects against O3-induced pulmonary neutrophilic inflammation and cell proliferation. Moreover, gene expression analyses identified three response pathways and several genetic targets through which IL-10 may modulate the innate and adaptive immune response. These novel mechanisms of protection against the pathogenesis of O3-induced pulmonary inflammation may also provide potential therapeutic targets to protect susceptible individuals.
air pollution; gene array; IL-10; inflammation; lung; ozone; pulmonary
The genotoxicity testing battery is highly sensitive for detection of chemical carcinogens. However, it features a low specificity and provides only limited mechanistic information required for risk assessment of positive findings. This is especially important in case of positive findings in the in vitro chromosome damage assays, because chromosome damage may be also induced secondarily to cell death. An increasing body of evidence indicates that toxicogenomic analysis of cellular stress responses provides an insight into mechanisms of action of genotoxicants. To evaluate the utility of such a toxicogenomic analysis we evaluated gene expression profiles of TK6 cells treated with four model genotoxic agents using a targeted high density real-time PCR approach in a multilaboratory project coordinated by the Health and Environmental Sciences Institute Committee on the Application of Genomics in Mechanism-based Risk Assessment. We show that this gene profiling technology produced reproducible data across laboratories allowing us to conclude that expression analysis of a relevant gene set is capable of distinguishing compounds that cause DNA adducts or double strand breaks from those that interfere with mitotic spindle function or that cause chromosome damage as a consequence of cytotoxicity. Furthermore, our data suggest that the gene expression profiles at early time points are most likely to provide information relevant to mechanisms of genotoxic damage and that larger gene expression arrays will likely provide richer information for differentiating molecular mechanisms of action of genotoxicants. Although more compounds need to be tested to identify a robust molecular signature, this study confirms the potential of toxicogenomic analysis for investigation of genotoxic mechanisms.
gene expression; genetic toxicology; risk assessment
In spite of the application of toxicogenomic (TGx) data to the field of toxicology for the past 10 years, the broad implementation and full impact of TGx for chemical and drug evaluation to improve decision making within organizations and by policy makers has not been achieved.
The goal of the Health and Environmental Sciences Institute (HESI) Committee on the Application of Genomics to Mechanism-based Risk Assessment was to construct and summarize a multisector survey, addressing key issues and perspectives on the current and future practical uses and challenges of implementing TGx data to facilitate discussions for decision making within organizations and by policy makers.
An online survey to probe the current status and future challenges facing the field of TGx for drug and chemical evaluation in experimental and nonclinical models was taken by scientists and scientific decision/policy makers actively engaged in the field of TGx within industrial, academic, and regulatory sectors of the United States, Europe, and Japan. For this survey, TGx refers specifically to the analysis of gene expression responses to evaluate xenobiotic exposure in experimental and preclinical models.
The survey results are summarized from questions covering broad areas including technology used, organizational capacity and resource allocation, experimental approaches, data storage and exchange, perceptions of benefits and hurdles, and future expectations.
The survey findings provide valuable information on the current state of the science of TGx applications and identify key areas in which TGx will have an impact as well as the key hurdles in applying TGx data to address issues. The findings serve as a public resource to facilitate discussions on the focus of future TGx efforts to ensure that a maximal benefit can be obtained from toxicogenomic studies.
applications; HESI survey; impact and hurdles; toxicogenomics
Experimental descriptions are typically stored as free text without using standardized terminology, creating challenges in comparison, reproduction and analysis. These difficulties impose limitations on data exchange and information retrieval.
The Ontology for Biomedical Investigations (OBI), developed as a global, cross-community effort, provides a resource that represents biomedical investigations in an explicit and integrative framework. Here we detail three real-world applications of OBI, provide detailed modeling information and explain how to use OBI.
We demonstrate how OBI can be applied to different biomedical investigations to both facilitate interpretation of the experimental process and increase the computational processing and integration within the Semantic Web. The logical definitions of the entities involved allow computers to unambiguously understand and integrate different biological experimental processes and their relevant components.
OBI is available at http://purl.obolibrary.org/obo/obi/2009-11-02/obi.owl
Ontologies describe reality in specific domains in ways that can bridge various disciplines and languages. They allow easier access and integration of information that is collected by different groups. Ontologies are currently used in the biomedical sciences, geography, and law. A Biomedical Ethics Ontology (BMEO) would benefit members of ethics committees who deal with protocols and consent forms spanning numerous fields of inquiry. There already exists the Ontology for Biomedical Investigations (OBI); the proposed BMEO would interoperate with OBI, creating a powerful information tool. We define a domain ontology and begin to construct a BMEO, focused on the process of evaluating human research protocols. Finally, we show how our BMEO can have practical applications for ethics committees. This paper describes ongoing research and a strategy for its broader continuation and cooperation.
ontology; taxonomy; ethics committee review; automation; semantics
The development of the Functional Genomics Investigation Ontology (FuGO) is a collaborative, international effort that will provide a resource for annotating functional genomics investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. FuGO will contain both terms that are universal to all functional genomics investigations and those that are domain specific. In this way, the ontology will serve as the “semantic glue” to provide a common understanding of data from across these disparate data sources. In addition, FuGO will reference out to existing mature ontologies to avoid the need to duplicate these resources, and will do so in such a way as to enable their ease of use in annotation. This project is in the early stages of development; the paper will describe efforts to initiate the project, the scope and organization of the project, the work accomplished to date, and the challenges encountered, as well as future plans.
Therapeutic strategies exist for human pulmonary neoplasia, however due to the heterogeneity of the disease, most are not very effective. The innate immunity gene, toll-like receptor 4 (TLR4), protects against chronic pulmonary inflammation and tumorigenesis in mice, but the mechanism is unclear. This study was designed to identify TLR4-mediated gene expression pathways that may be used as prognostic indicators of susceptibility to lung tumorigenesis in mice and provide insight into the mechanism.
Whole lung mRNA was isolated from C.C3H-Tlr4Lps-d (BALBLps-d; Tlr4 mutant) and BALB/c (Tlr4 normal) mice following butylated hydroxytoluene (BHT)-treatment (four weekly ip. injections; 150-200 mg/kg/each; "promotion"). mRNA from micro-dissected tumors (adenomas) and adjacent uninvolved tissue from both strains were also compared 27 wks after a single carcinogen injection (3-methylcholanthrene (MCA), 10 μg/g; "control") or followed by BHT (6 weekly ip. injections; 125-200 mg/kg/each; "progression"). Bronchoalveolar lavage fluid was analyzed for inflammatory cell content and total protein determination, a marker of lung hyperpermeability; inflammation was also assessed using immunohistochemical staining for macrophages (F4/80) and lymphocytes (CD3) in mice bearing tumors (progression).
During promotion, the majority of genes identified in the BALBLps-d compared to BALB/c mice (P < 0.05) were involved in epithelial growth factor receptor (EGFR) signaling (e.g. epiregulin (Ereg)), secreted phosphoprotein 1(Spp1)), which can lead to cell growth and eventual tumor development. Inflammation was significantly higher in BALBLps-d compared to BALB/c mice during progression, similar to the observed response during tumor promotion in these strains. Increases in genes involved in signaling through the EGFR pathway (e.g. Ereg, Spp1) were also observed during progression in addition to continued inflammation, chemotactic, and immune response gene expression in the BALBLps-d versus BALB/c mice (P < 0.05), which appears to provide more favorable conditions for cell growth and tumor development. In support of these findings, the BALB/c mice also had significantly reduced expression of many immune response and inflammatory genes in both the tumors and uninvolved tissue.
This transcriptomic study determined the protective effect of TLR4 in lung carcinogenesis inhibition of multiple pathways including EGFR (e.g. Ereg), inflammatory response genes (e.g. Cxcl5), chemotaxis (e.g. Ccr1) and other cell proliferation genes (e.g. Arg1, Pthlh). Future studies will determine the utility of these pathways as indicators of immune system deficiencies and tumorigenesis.
The Minimum Information for Biological and Biomedical Investigations (MIBBI) project provides a resource for those exploring the range of extant minimum information checklists and fosters coordinated development of such checklists.
Histopathology, clinical chemistry, hematology and gene expression data were collected from the rat liver and blood after treatment with eight known hepatotoxins.
This report details the standardized experimental design and the different data streams that were collected (histopathology, clinical chemistry, hematology and gene expression from the target tissue (liver) and a bio-available tissue (blood)) after treatment with eight known hepatotoxicants (at multiple time points and doses with multiple biological replicates). The results of the study demonstrate the classification of histopathological differences, likely reflecting differences in mechanisms of cell-specific toxicity, using either liver tissue or blood transcriptomic data.
The use of gene expression profiling in both clinical and laboratory settings would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies could yield useful information on baseline fluctuations in gene expression, although control animal data has not been available on a scale and in a form best served for data-mining.
A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques.
The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selective, or altered by fasting were also identified and functionally categorized. Better characterization of gene expression variability in control animals will aid in the design of toxicogenomics studies and in the interpretation of their results.
Understanding the mechanisms of multidrug resistance (MDR) could improve clinical drug efficacy. MDR is associated with ABC transporters, but the factors that regulate their expression at clinically relevant drug concentrations are poorly understood. We report that a single-step selection with low doses of anti-cancer agents, similar to concentrations reported in vivo induces MDR that is mediated exclusively by ABCG2. We selected breast, ovarian and colon cancer cells (MCF-7, IGROV-1, and S-1) after exposure to 14 or 21 nM doxorubicin for only 10 days. We found that these cells overexpress ABCG2 at the mRNA and protein levels. RNAi analysis confirmed that ABCG2 confers drug resistance. Furthermore, ABCG2 up-regulation was facilitated by histone hyperacetylation due to weaker HDAC1-promoter association indicating that these epigenetic changes elicit changes in ABCG2 gene expression. These studies indicate that the MDR phenotype arises following low dose, single-step exposure to doxorubicin, and further suggest that ABCG2 may mediate early stages of MDR development. This is the first report of single-step, low dose selection leading to overexpression of ABCG2 by epigenetic changes in multiple cancer cell lines.
Multidrug Resistance (MDR); Doxorubicin; ABCG2; Epigenetics; Single-step selection
The propensity of compounds to produce adverse health effects in humans is generally evaluated using animal-based test methods. Such methods can be relatively expensive, low-throughput, and associated with pain suffered by the treated animals. In addition, differences in species biology may confound extrapolation to human health effects.
The National Toxicology Program and the National Institutes of Health Chemical Genomics Center are collaborating to identify a battery of cell-based screens to prioritize compounds for further toxicologic evaluation.
A collection of 1,408 compounds previously tested in one or more traditional toxicologic assays were profiled for cytotoxicity using quantitative high-throughput screening (qHTS) in 13 human and rodent cell types derived from six common targets of xenobiotic toxicity (liver, blood, kidney, nerve, lung, skin). Selected cytotoxicants were further tested to define response kinetics.
qHTS of these compounds produced robust and reproducible results, which allowed cross-compound, cross-cell type, and cross-species comparisons. Some compounds were cytotoxic to all cell types at similar concentrations, whereas others exhibited species- or cell type–specific cytotoxicity. Closely related cell types and analogous cell types in human and rodent frequently showed different patterns of cytotoxicity. Some compounds inducing similar levels of cytotoxicity showed distinct time dependence in kinetic studies, consistent with known mechanisms of toxicity.
The generation of high-quality cytotoxicity data on this large library of known compounds using qHTS demonstrates the potential of this methodology to profile a much broader array of assays and compounds, which, in aggregate, may be valuable for prioritizing compounds for further toxicologic evaluation, identifying compounds with particular mechanisms of action, and potentially predicting in vivo biological response.
1,536-well; cell viability; NTP 1,408 compound library; PubChem; qHTS; RT-CES
CEBS (Chemical Effects in Biological Systems) is an integrated public repository for toxicogenomics data, including the study design and timeline, clinical chemistry and histopathology findings and microarray and proteomics data. CEBS contains data derived from studies of chemicals and of genetic alterations, and is compatible with clinical and environmental studies. CEBS is designed to permit the user to query the data using the study conditions, the subject responses and then, having identified an appropriate set of subjects, to move to the microarray module of CEBS to carry out gene signature and pathway analysis. Scope of CEBS: CEBS currently holds 22 studies of rats, four studies of mice and one study of Caenorhabditis elegans. CEBS can also accommodate data from studies of human subjects. Toxicogenomics studies currently in CEBS comprise over 4000 microarray hybridizations, and 75 2D gel images annotated with protein identification performed by MALDI and MS/MS. CEBS contains raw microarray data collected in accordance with MIAME guidelines and provides tools for data selection, pre-processing and analysis resulting in annotated lists of genes of interest. Additionally, clinical chemistry and histopathology findings from over 1500 animals are included in CEBS. CEBS/BID: The BID (Biomedical Investigation Database) is another component of the CEBS system. BID is a relational database used to load and curate study data prior to export to CEBS, in addition to capturing and displaying novel data types such as PCR data, or additional fields of interest, including those defined by the HESI Toxicogenomics Committee (in preparation). BID has been shared with Health Canada and the US Environmental Protection Agency. CEBS is available at http://cebs.niehs.nih.gov. BID can be accessed via the user interface from https://dir-apps.niehs.nih.gov/arc/. Requests for a copy of BID and for depositing data into CEBS or BID are available at http://www.niehs.nih.gov/cebs-df/.
With the increasing use of metabolomics as a means to study a large number of different biological research questions, there is a need for a minimal set of reporting standards that allow the scientific community to evaluate, understand, repeat, compare and re-investigate metabolomics studies. Here we propose, a first draft of minimal requirements to effectively describe the biological context of metabolomics studies that involve microbial or in vitro biological subjects. This recommendation has been produced by the microbiology and in vitro biology working subgroup of the Metabolomics Standards Initiative in collaboration with the yeast systems biology network as part of a wider standardization initiative led by the Metabolomics Society. Microbial and in vitro biology metabolomics is defined by this sub-working group as studies with any cell or organism that require a defined external medium to facilitate growth and propagation. Both a minimal set and a best practice set of reporting standards for metabolomics experiments have been defined. The minimal set of reporting standards for microbial or in vitro biology metabolomics experiments includes those factors that are specific for metabolomics experiments and that critically determine the outcome of the experiments. The best practice set of reporting standards contains both the factors that are specific for metabolomics experiments and general aspects that critically determine the outcome of any microbial or in vitro biological experiment.
Microbiology; In vitro biology, Metabolomics; Minimal reporting standards; Sample context