Proteasome inhibition creates a chromatin landscape favorable to RNA Pol II processivity.

Proteasome activity is required for diverse cellular processes, including transcriptional and epigenetic regulation. However, inhibiting proteasome activity can lead to an increase in transcriptional output that is correlated with enriched levels of trimethyl H3K4 and phosphorylated forms of RNA polymerase (Pol) II at the promoter and gene body. Here, we perform gene expression analysis and ChIP followed by sequencing (ChIP-seq) in MCF-7 breast cancer cells treated with the proteasome inhibitor MG132, and we further explore genome-wide effects of proteasome inhibition on the chromatin state and RNA Pol II transcription. Analysis of gene expression programs and chromatin architecture reveals that chemically inhibiting proteasome activity creates a distinct chromatin state, defined by spreading of the H3K4me3 mark into the gene bodies of differentially-expressed genes. The distinct H3K4me3 chromatin profile and hyperacetylated nucleosomes at transcription start sites establish a chromatin landscape that facilitates recruitment of Ser-5- and Ser-2-phosphorylated RNA Pol II. Subsequent transcriptional events result in diverse gene expression changes. Alterations of H3K36me3 levels in the gene body reflect productive RNA Pol II elongation of transcripts of genes that are induced, underscoring the requirement for proteasome activity at multiple phases of the transcriptional cycle. Finally, by integrating genomics data and pathway analysis, we find that the differential effects of proteasome inhibition on the chromatin state modulate genes that are fundamental for cancer cell survival. Together, our results uncover underappreciated downstream effects of proteasome inhibitors that may underlie targeting of distinct chromatin states and key steps of RNA Pol II-mediated transcription in cancer cells.

RATEmiRs: the rat atlas of tissue-specific and enriched miRNAs for discerning baseline expression exclusivity of candidate biomarkers.

MicroRNAs (miRNAs) are small RNAs that regulate mRNA expression and have been targeted as biomarkers of organ damage and disease. To explore the utility of miRNAs to assess injury to specific tissues, a tissue atlas of miRNA abundance was constructed. The Rat Atlas of Tissue-specific and Enriched miRNAs (RATEmiRs) catalogues miRNA sequencing data from 21 and 23 tissues in male and female Sprague-Dawley rats, respectively. RATEmiRs identifies tissue-enriched (TE), tissue-specific (TS), or organ-specific (OS) miRNAs via comparisons of one or more tissue or organ vs others. We provide a brief overview of RATEmiRs and present how to use it to detect miRNA expression abundance of candidate biomarkers as well as to compare the expression of miRNAs between rat and human. The database is available at https://www.niehs.nih.gov/ratemirs/.

Revealing a human p53 universe.

p53 transcriptional networks are well-characterized in many organisms. However, a global understanding of requirements for in vivo p53 interactions with DNA and relationships with transcription across human biological systems in response to various p53 activating situations remains limited. Using a common analysis pipeline, we analyzed 41 data sets from genome-wide ChIP-seq studies of which 16 have associated gene expression data, including our recent primary data with normal human lymphocytes. The resulting extensive analysis, accessible at p53 BAER hub via the UCSC browser, provides a robust platform to characterize p53 binding throughout the human genome including direct influence on gene expression and underlying mechanisms. We establish the impact of spacers and mismatches from consensus on p53 binding in vivo and propose that once bound, neither significantly influences the likelihood of expression. Our rigorous approach revealed a large p53 genome-wide cistrome composed of >900 genes directly targeted by p53. Importantly, we identify a core cistrome signature composed of genes appearing in over half the data sets, and we identify signatures that are treatment- or cell-specific, demonstrating new functions for p53 in cell biology. Our analysis reveals a broad homeostatic role for human p53 that is relevant to both basic and translational studies.

RATEmiRs: the rat atlas of tissue-specific and enriched miRNAs database.

BACKGROUND: MicroRNAs (miRNAs) regulate gene expression and have been targeted as indicators of environmental/toxicologic stressors. Using the data from our deep sequencing of miRNAs in an extensive sampling of rat tissues, we developed a database called RATEmiRs for the Rat Atlas of Tissue-specific and Enriched miRNAs to allow users to dynamically determine mature-, iso- and pre-miR expression abundance, enrichment and specificity in rat tissues and organs. RESULTS: Illumina sequencing count data from mapped reads and meta data from the miRNA body atlas consisting of 21 and 23 tissues (14 organs) of toxicologic interest from 12 to 13 week old male and female Sprague Dawley rats respectively, were managed in a relational database with a user-friendly query interface. Data-driven pipelines are available to tailor the identification of tissue-enriched (TE) and tissue-specific (TS) miRNAs. Data-driven organ-specific (OS) pipelines reveal miRNAs that are expressed predominately in a given organ. A user-driven approach is also available to assess the tissue expression of user-specified miRNAs. Using one tissue vs other tissues and tissue(s) of an organ vs other organs, we illustrate the utility of RATEmiRs to facilitate the identification of candidate miRNAs. As a use case example, RATEmiRs revealed two TS miRNAs in the liver: rno-miR-122-3p and rno-miR-122-5p. When liver is compared to just the brain tissues for example, rno-miR-192-5p, rno-miR-193-3p, rno-miR-203b-3p, rno-miR-3559-5p, rno-miR-802-3p and rno-miR-802-5p are also detected as abundantly expressed in liver. As another example, 55 miRNAs from the RATEmiRs query of ileum vs brain tissues overlapped with miRNAs identified from the same comparison of tissues in an independent, publicly available dataset of 10 week old male rat microarray data suggesting that these miRNAs are likely not age-specific, platform-specific nor pipeline-dependent. Lastly, we identified 10 miRNAs that have conserved tissue/organ-specific expression between the rat and human species. CONCLUSIONS: RATEmiRs provides a new platform for identification of TE, TS and OS miRNAs in a broad array of rat tissues. RATEmiRs is available at: https://www.niehs.nih.gov/ratemirs.

Tunable regulation of CREB DNA binding activity couples genotoxic stress response and metabolism.

cAMP response element binding protein (CREB) is a key regulator of glucose metabolism and synaptic plasticity that is canonically regulated through recruitment of transcriptional coactivators. Here we show that phosphorylation of CREB on a conserved cluster of Ser residues (the ATM/CK cluster) by the DNA damage-activated protein kinase ataxia-telangiectasia-mutated (ATM) and casein kinase1 (CK1) and casein kinase2 (CK2) positively and negatively regulates CREB-mediated transcription in a signal dependent manner. In response to genotoxic stress, phosphorylation of the ATM/CK cluster inhibited CREB-mediated gene expression, DNA binding activity and chromatin occupancy proportional to the number of modified Ser residues. Paradoxically, substoichiometric, ATM-independent, phosphorylation of the ATM/CK cluster potentiated bursts in CREB-mediated transcription by promoting recruitment of the CREB coactivator, cAMP-regulated transcriptional coactivators (CRTC2). Livers from mice expressing a non-phosphorylatable CREB allele failed to attenuate gluconeogenic genes in response to DNA damage or fully activate the same genes in response to glucagon. We propose that phosphorylation-dependent regulation of DNA binding activity evolved as a tunable mechanism to control CREB transcriptional output and promote metabolic homeostasis in response to rapidly changing environmental conditions.

Informatics and Data Analytics to Support Exposome-Based Discovery for Public Health.

The complexity of the human exposome-the totality of environmental exposures encountered from birth to death-motivates systematic, high-throughput approaches to discover new environmental determinants of disease. In this review, we describe the state of science in analyzing the human exposome and provide recommendations for the public health community to consider in dealing with analytic challenges of exposome-based biomedical research. We describe extant and novel analytic methods needed to associate the exposome with critical health outcomes and contextualize the data-centered challenges by drawing parallels to other research endeavors such as human genomics research. We discuss efforts for training scientists who can bridge public health, genomics, and biomedicine in informatics and statistics. If an exposome data ecosystem is brought to fruition, it will likely play a role as central as genomic science has had in molding the current and new generations of biomedical researchers, computational scientists, and public health research programs.

EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data.

BACKGROUND: RNA sequencing (RNA-Seq) measures genome-wide gene expression. RNA-Seq data is count-based rendering normal distribution models for analysis inappropriate. Normalization of RNA-Seq data to transform the data has limitations which can adversely impact the analysis. Furthermore, there are a few count-based methods for analysis of RNA-Seq data but they are essentially for pairwise analysis of treatment groups or multiclasses but not pattern-based to identify co-expressed genes. RESULTS: We adapted our extracting patterns and identifying genes methodology for RNA-Seq (EPIG-Seq) count data. The software uses count-based correlation to measure similarity between genes, quasi-Poisson modelling to estimate dispersion in the data and a location parameter to indicate magnitude of differential expression. EPIG-Seq is different than any other software currently available for pattern analysis of RNA-Seq data in that EPIG-Seq 1) uses count level data and supports cases of inflated zeros, 2) identifies statistically significant clusters of genes that are co-expressed across experimental conditions, 3) takes into account dispersion in the replicate data and 4) provides reliable results even with small sample sizes. EPIG-Seq operates in two steps: 1) extract the pattern profiles from data as seeds for clustering co-expressed genes and 2) cluster the genes to the pattern seeds and compute statistical significance of the pattern of co-expressed genes. EPIG-Seq provides a table of the genes with bootstrapped p-values and profile plots of the patterns of co-expressed genes. In addition, EPIG-Seq provides a heat map and principal component dimension reduction plot of the clustered genes as visual aids. We demonstrate the utility of EPIG-Seq through the analysis of toxicogenomics and cancer data sets to identify biologically relevant co-expressed genes. EPIG-Seq is available at: sourceforge.net/projects/epig-seq. CONCLUSIONS: EPIG-Seq is unlike any other software currently available for pattern analysis of RNA-Seq count level data across experimental groups. Using the EPIG-Seq software to analyze RNA-Seq count data across biological conditions permits the ability to extract biologically meaningful co-expressed genes associated with coordinated regulation.

The Rat microRNA body atlas; Evaluation of the microRNA content of rat organs through deep sequencing and characterization of pancreas enriched miRNAs as biomarkers of pancreatic toxicity in the rat and dog.

BACKGROUND: MicroRNAs (miRNA) are ~19-25 nucleotide long RNA molecules that fine tune gene expression through the inhibition of translation or degradation of the mRNA through incorporation into the RNA induced silencing complex (RISC). MicroRNAs are stable in the serum and plasma, are detectable in a wide variety of body fluids, are conserved across veterinary species and humans and are expressed in a tissue specific manner. They can be detected at low concentrations in circulation in animals and humans, generating interest in the utilization of miRNAs as serum and/or plasma based biomarkers of tissue injury. MicroRNA tissue profiling in rodents has been published, but sample an insufficient number of organs of toxicologic interest using microarray or qPCR technologies for miRNA detection. Here we impart an improved rat microRNA body atlas consisting of 21 and 23 tissues of toxicologic interest from male and female Sprague Dawley rats respectively, using Illumina miRNA sequencing. Several of the authors created a dog miRNA body atlas and we collaborated to test miRNAs conserved in rat and dog pancreas in caerulein toxicity studies utilizing both species. RESULTS: A rich data set is presented that more robustly defines the tissue specificity and enrichment profiles of previously published and undiscovered rat miRNAs. We generated 1,927 sequences that mapped to mature miRNAs in rat, mouse and human from miRBase and discovered an additional 1,162 rat miRNAs as compared to the current number of rat miRNAs in miRBase version 21. Tissue specific and enriched miRNAs were identified and a subset of these miRNAs were validated by qPCR for tissue specificity or enrichment. As an example of the power of this approach, we have conducted rat and dog pancreas toxicity studies and examined the levels of some tissue specific and enriched miRNAs conserved between rat and dog in the serum of each species. The studies demonstrate that conserved tissue specific/enriched miRs-216a-5p, 375-3p, 148a-3p, 216b-5p and 141-3p are candidate biomarkers of pancreatic injury in the rat and dog. CONCLUSIONS: A microRNA body atlas for rat and dog was useful in identifying new candidate miRNA biomarkers of organ toxicity in 2 toxicologically relevant species.

Effects of mannose-binding lectin on pulmonary gene expression and innate immune inflammatory response to ozone.

Ozone is a common, potent oxidant pollutant in industrialized nations. Ozone exposure causes airway hyperreactivity, lung hyperpermeability, inflammation, and cell damage in humans and laboratory animals, and exposure to ozone has been associated with exacerbation of asthma, altered lung function, and mortality. The mechanisms of ozone-induced lung injury and differential susceptibility are not fully understood. Ozone-induced lung inflammation is mediated, in part, by the innate immune system. We hypothesized that mannose-binding lectin (MBL), an innate immunity serum protein, contributes to the proinflammatory events caused by ozone-mediated activation of the innate immune system. Wild-type (Mbl(+/+)) and MBL-deficient (Mbl(-/-)) mice were exposed to ozone (0.3 ppm) for up to 72 h, and bronchoalveolar lavage fluid was examined for inflammatory markers. Mean numbers of eosinophils and neutrophils and levels of the neutrophil attractants C-X-C motif chemokines 2 [Cxcl2 (major intrinsic protein 2)] and 5 [Cxcl5 (limb expression, LIX)] in the bronchoalveolar lavage fluid were significantly lower in Mbl(-/-) than Mbl(+/+) mice exposed to ozone. Using genome-wide mRNA microarray analyses, we identified significant differences in transcript response profiles and networks at baseline [e.g., nuclear factor erythroid-related factor 2 (NRF2)-mediated oxidative stress response] and after exposure (e.g., humoral immune response) between Mbl(+/+) and Mbl(-/-) mice. The microarray data were further analyzed to discover several informative differential response patterns and subsequent gene sets, including the antimicrobial response and the inflammatory response. We also used the lists of gene transcripts to search the LINCS L1000CDS(2) data sets to identify agents that are predicted to perturb ozone-induced changes in gene transcripts and inflammation. These novel findings demonstrate that targeted deletion of Mbl caused differential levels of inflammation-related gene sets at baseline and after exposure to ozone and significantly reduced pulmonary inflammation, thus indicating an important innate immunomodulatory role of the gene in this model.

Technical guide for applications of gene expression profiling in human health risk assessment of environmental chemicals.

Toxicogenomics promises to be an important part of future human health risk assessment of environmental chemicals. The application of gene expression profiles (e.g., for hazard identification, chemical prioritization, chemical grouping, mode of action discovery, and quantitative analysis of response) is growing in the literature, but their use in formal risk assessment by regulatory agencies is relatively infrequent. Although additional validations for specific applications are required, gene expression data can be of immediate use for increasing confidence in chemical evaluations. We believe that a primary reason for the current lack of integration is the limited practical guidance available for risk assessment specialists with limited experience in genomics. The present manuscript provides basic information on gene expression profiling, along with guidance on evaluating the quality of genomic experiments and data, and interpretation of results presented in the form of heat maps, pathway analyses and other common approaches. Moreover, potential ways to integrate information from gene expression experiments into current risk assessment are presented using published studies as examples. The primary objective of this work is to facilitate integration of gene expression data into human health risk assessments of environmental chemicals.

Persistent gene expression and DNA methylation alterations linked to carcinogenic effects of dichloroacetic acid.

Background: Mechanistic understanding of transient exposures that lead to adverse health outcomes will enhance our ability to recognize biological signatures of disease. Here, we measured the transcriptomic and epigenomic alterations due to exposure to the metabolic reprogramming agent, dichloroacetic acid (DCA). Previously, we showed that exposure to DCA increased liver tumor incidence in B6C3F1 mice after continuous or early life exposures significantly over background level. Methods: Using archived formalin-fixed liver samples, we utilized modern methodologies to measure gene expression and DNA methylation levels to link to previously generated phenotypic measures. Gene expression was measured by targeted RNA sequencing (TempO-seq 1500+ toxicity panel: 2754 total genes) in liver samples collected from 10-, 32-, 57-, and 78-week old mice exposed to deionized water (controls), 3.5 g/L DCA continuously in drinking water ("Direct" group), or DCA for 10-, 32-, or 57-weeks followed by deionized water until sample collection ("Stop" groups). Genome-scaled alterations in DNA methylation were measured by Reduced Representation Bisulfite Sequencing (RRBS) in 78-week liver samples for control, Direct, 10-week Stop DCA exposed mice. Results: Transcriptomic changes were most robust with concurrent or adjacent timepoints after exposure was withdrawn. We observed a similar pattern with DNA methylation alterations where we noted attenuated differentially methylated regions (DMRs) in the 10-week Stop DCA exposure groups compared to the Direct group at 78-weeks. Gene pathway analysis indicated cellular effects linked to increased oxidative metabolism, a primary mechanism of action for DCA, closer to exposure windows especially early in life. Conversely, many gene signatures and pathways reversed patterns later in life and reflected more pro-tumorigenic patterns for both current and prior DCA exposures. DNA methylation patterns correlated to early gene pathway perturbations, such as cellular signaling, regulation and metabolism, suggesting persistence in the epigenome and possible regulatory effects. Conclusion: Liver metabolic reprogramming effects of DCA interacted with normal age mechanisms, increasing tumor burden with both continuous and prior DCA exposure in the male B6C3F1 rodent model.

Gene expression signatures but not cell cycle checkpoint functions distinguish AT carriers from normal individuals.

Ataxia telangiectasia (AT) is a rare autosomal recessive disease caused by mutations in the ataxia telangiectasia-mutated gene (ATM). AT carriers with one mutant ATM allele are usually not severely affected although they carry an increased risk of developing cancer. There has not been an easy and reliable diagnostic method to identify AT carriers. Cell cycle checkpoint functions upon ionizing radiation (IR)-induced DNA damage and gene expression signatures were analyzed in the current study to test for differential responses in human lymphoblastoid cell lines with different ATM genotypes. While both dose- and time-dependent G1 and G2 checkpoint functions were highly attenuated in ATM-/- cell lines, these functions were preserved in ATM+/- cell lines equivalent to ATM+/+ cell lines. However, gene expression signatures at both baseline (consisting of 203 probes) and post-IR treatment (consisting of 126 probes) were able to distinguish ATM+/- cell lines from ATM+/+ and ATM-/- cell lines. Gene ontology (GO) and pathway analysis of the genes in the baseline signature indicate that ATM function-related categories, DNA metabolism, cell cycle, cell death control, and the p53 signaling pathway, were overrepresented. The same analyses of the genes in the IR-responsive signature revealed that biological categories including response to DNA damage stimulus, p53 signaling, and cell cycle pathways were overrepresented, which again confirmed involvement of ATM functions. The results indicate that AT carriers who have unaffected G1 and G2 checkpoint functions can be distinguished from normal individuals and AT patients by expression signatures of genes related to ATM functions.

Principal component analysis-based filtering improves detection for Affymetrix gene expression arrays.

Gene expression array technology has reached the stage of being routinely used to study clinical samples in search of diagnostic and prognostic biomarkers. Due to the nature of array experiments, which examine the expression of tens of thousands of genes simultaneously, the number of null hypotheses is large. Hence, multiple testing correction is often necessary to control the number of false positives. However, multiple testing correction can lead to low statistical power in detecting genes that are truly differentially expressed. Filtering out non-informative genes allows for reduction in the number of null hypotheses. While several filtering methods have been suggested, the appropriate way to perform filtering is still debatable. We propose a new filtering strategy for Affymetrix GeneChips®, based on principal component analysis of probe-level gene expression data. Using a wholly defined spike-in data set and one from a diabetes study, we show that filtering by the proportion of variation accounted for by the first principal component (PVAC) provides increased sensitivity in detecting truly differentially expressed genes while controlling false discoveries. We demonstrate that PVAC exhibits equal or better performance than several widely used filtering methods. Furthermore, a data-driven approach that guides the selection of the filtering threshold value is also proposed.

Differential transcriptomic analysis of spontaneous lung tumors in B6C3F1 mice: comparison to human non-small cell lung cancer.

Lung cancer is the leading cause of cancer-related death in people and is mainly due to environmental factors such as smoking and radon. The National Toxicology Program (NTP) tests various chemicals and mixtures for their carcinogenic hazard potential. In the NTP chronic bioassay using B6C3F1 mice, the incidence of lung tumors in treated and control animals is second only to the liver tumors. In order to study the molecular mechanisms of chemically induced lung tumors, an understanding of the genetic changes that occur in spontaneous lung (SL) tumors from untreated control animals is needed. The authors have evaluated the differential transcriptomic changes within SL tumors compared to normal lungs from untreated age-matched animals. Within SL tumors, several canonical pathways associated with cancer (eukaryotic initiation factor 2 signaling, RhoA signaling, PTEN signaling, and mammalian target of rapamycin signaling), metabolism (Inositol phosphate metabolism, mitochondrial dysfunction, and purine and pyramidine metabolism), and immune responses (FcγR-mediated phagocytosis, clathrin-mediated endocytosis, interleukin 8 signaling, and CXCR4 signaling) were altered. Meta-analysis of murine SL tumors and human non-small cell lung cancer transcriptomic data sets revealed a high concordance. These data provide important information on the differential transcriptomic changes in murine SL tumors that will be critical to our understanding of chemically induced lung tumors and will aid in hazard analysis in the NTP 2-year carcinogenicity bioassays.

Sources of variance in baseline gene expression in the rodent liver.

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.

Mitochondrial-nuclear epistasis underlying phenotypic variation in breast cancer pathology.

The interplay between genes harboring single nucleotide polymorphisms (SNPs) is vital to better understand underlying contributions to the etiology of breast cancer. Much attention has been paid to epistasis between nuclear genes or mutations in the mitochondrial genome. However, there is limited understanding about the epistatic effects of genetic variants in the nuclear and mitochondrial genomes jointly on breast cancer. We tested the interaction of germline SNPs in the mitochondrial (mtSNPs) and nuclear (nuSNPs) genomes of female breast cancer patients in The Cancer Genome Atlas (TCGA) for association with morphological features extracted from hematoxylin and eosin (H&E)-stained pathology images. We identified 115 significant (q-value < 0.05) mito-nuclear interactions that increased nuclei size by as much as 12%. One interaction between nuSNP rs17320521 in an intron of the WSC Domain Containing 2 (WSCD2) gene and mtSNP rs869096886, a synonymous variant mapped to the mitochondrially-encoded NADH dehydrogenase 4 (MT-ND4) gene, was confirmed in an independent breast cancer data set from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). None of the 10 mito-nuclear interactions identified from non-diseased female breast tissues from the Genotype-Expression (GTEx) project resulted in an increase in nuclei size. Comparisons of gene expression data from the TCGA breast cancer patients with the genotype homozygous for the minor alleles of the SNPs in WSCD2 and MT-ND4 versus the other genotypes revealed core transcriptional regulator interactions and an association with insulin. Finally, a Cox proportional hazards ratio = 1.7 (C.I. 0.98-2.9, p-value = 0.042) and Kaplan-Meier plot suggest that the TCGA female breast cancer patients with low gene expression of WSCD2 coupled with large nuclei have an increased risk of mortality. The intergenomic dependency between the two variants may constitute an inherent susceptibility of a more severe form of breast cancer and points to genetic targets for further investigation of additional determinants of the disease.

Gene Expression Profiling Elucidates Cellular Responses to NCX4040 in Human Ovarian Tumor Cells: Implications in the Mechanisms of Action of NCX4040.

The nitric oxide donor, NCX4040 is a non-steroidal anti-inflammatory-NO donor and has been shown to be extremely cytotoxic to a number of human tumors, including ovarian tumors cells. We have found that NCX4040 is cytotoxic against both OVCAR-8 and its adriamycin-selected OVCAR-8 variant (NCI/ADR-RES) tumor cell lines. While the mechanism of action of NCX4040 is not entirely clear, we as well as others have shown that NCX4040 generates reactive oxygen species (ROS) and induces DNA damage in tumor cells. Recently, we have reported that NCX4040 treatment resulted in a significant depletion of cellular glutathione, and formation of both reactive oxygen and nitrogen species (ROS/RNS), resulting in oxidative stress in these tumor cells. Furthermore, our results indicated that more ROS/RNS were generated in OVCAR-8 cells than in NCI/ADR-RES cells due to increased activities of superoxide dismutase (SOD), glutathione peroxidase and transferases expressed in NCI/ADR-RES cells. Further studies suggested that NCX4040-induced cell death may be mediated by peroxynitrite formed from NCX4040 in cells. In this study we used microarray analysis following NCX4040 treatment of both OVCAR-8 and its ADR-resistant variant to identify various molecular pathways involved in NCX4040-induced cell death. Here, we report that NCX4040 treatment resulted in the differential induction of oxidative stress genes, inflammatory response genes (TNF, IL-1, IL-6 and COX2), DNA damage response and MAP kinase response genes. A mechanism of tumor cell death is proposed based on our findings where oxidative stress is induced by NCX4040 from simultaneous induction of NOX4, TNF-α and CHAC1 in tumor cell death.

Maximizing biomarker discovery by minimizing gene signatures.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

Global gene profiling of spontaneous hepatocellular carcinoma in B6C3F1 mice: similarities in the molecular landscape with human liver cancer.

Hepatocellular carcinoma (HCC) is an important cause of morbidity and mortality worldwide. Although the risk factors of human HCC are well known, the molecular pathogenesis of this disease is complex, and in general, treatment options remain poor. The use of rodent models to study human cancer has been extensively pursued, both through genetically engineered rodents and rodent models used in carcinogenicity and toxicology studies. In particular, the B6C3F1 mouse used in the National Toxicology Program (NTP) two-year bioassay has been used to evaluate the carcinogenic effects of environmental and occupational chemicals, and other compounds. The high incidence of spontaneous HCC in the B6C3F1 mouse has challenged its use as a model for chemically induced HCC in terms of relevance to the human disease. Using global gene expression profiling, we identify the dysregulation of several mediators similarly altered in human HCC, including re-expression of fetal oncogenes, upregulation of protooncogenes, downregulation of tumor suppressor genes, and abnormal expression of cell cycle mediators, growth factors, apoptosis regulators, and angiogenesis and extracellular matrix remodeling factors. Although major differences in etiology and pathogenesis remain between human and mouse HCC, there are important similarities in global gene expression and molecular pathways dysregulated in mouse and human HCC. These data provide further support for the use of this model in hazard identification of compounds with potential human carcinogenicity risk, and may help in better understanding the mechanisms of tumorigenesis resulting from chemical exposure in the NTP two-year carcinogenicity bioassay.

Global transcriptome and deletome profiles of yeast exposed to transition metals.

A variety of pathologies are associated with exposure to supraphysiological concentrations of essential metals and to non-essential metals and metalloids. The molecular mechanisms linking metal exposure to human pathologies have not been clearly defined. To address these gaps in our understanding of the molecular biology of transition metals, the genomic effects of exposure to Group IB (copper, silver), IIB (zinc, cadmium, mercury), VIA (chromium), and VB (arsenic) elements on the yeast Saccharomyces cerevisiae were examined. Two comprehensive sets of metal-responsive genomic profiles were generated following exposure to equi-toxic concentrations of metal: one that provides information on the transcriptional changes associated with metal exposure (transcriptome), and a second that provides information on the relationship between the expression of approximately 4,700 non-essential genes and sensitivity to metal exposure (deletome). Approximately 22% of the genome was affected by exposure to at least one metal. Principal component and cluster analyses suggest that the chemical properties of the metal are major determinants in defining the expression profile. Furthermore, cells may have developed common or convergent regulatory mechanisms to accommodate metal exposure. The transcriptome and deletome had 22 genes in common, however, comparison between Gene Ontology biological processes for the two gene sets revealed that metal stress adaptation and detoxification categories were commonly enriched. Analysis of the transcriptome and deletome identified several evolutionarily conserved, signal transduction pathways that may be involved in regulating the responses to metal exposure. In this study, we identified genes and cognate signaling pathways that respond to exposure to essential and non-essential metals. In addition, genes that are essential for survival in the presence of these metals were identified. This information will contribute to our understanding of the molecular mechanism by which organisms respond to metal stress, and could lead to an understanding of the connection between environmental stress and signal transduction pathways.