Biomedical subjects

Pierre R Bushel

Publications and source records attributed to Pierre R Bushel.

18 recordsLinked to original sources

PubMed2021

Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology.

Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments and proficiency testing on standardized, cell-line-derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas, below this limit, detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false negatives) were more common than erroneous candidates (false positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best practice guidelines and provides a resource for precision oncology.

Circulating Tumor DNA↗

PubMed2006

ATM requirement in gene expression responses to ionizing radiation in human lymphoblasts and fibroblasts.

The heritable disorder ataxia telangiectasia (AT) is caused by mutations in the AT-mutated (ATM) gene with manifestations that include predisposition to lymphoproliferative cancers and hypersensitivity to ionizing radiation (IR). We investigated gene expression changes in response to IR in human lymphoblasts and fibroblasts from seven normal and seven AT-affected individuals. Both cell types displayed ATM-dependent gene expression changes after IR, with some responses shared and some responses varying with cell type and dose. Interestingly, after 5 Gy IR, lymphoblasts displayed ATM-independent responses not seen in the fibroblasts at this dose, which likely reflect signaling through ATM-related kinases, e.g., ATR, in the absence of ATM function.

Ataxia Telangiectasia↗

PubMed2006

Profiles of global gene expression in ionizing-radiation-damaged human diploid fibroblasts reveal synchronization behind the G1 checkpoint in a G0-like state of quiescence.

Cell cycle arrest and stereotypic transcriptional responses to DNA damage induced by ionizing radiation (IR) were quantified in telomerase-expressing human diploid fibroblasts. Analysis of cytotoxicity demonstrated that 1.5 Gy IR inactivated colony formation by 40-45% in three fibroblast lines; this dose was used in all subsequent analyses. Fibroblasts exhibited > 90% arrest of progression from G2 to M at 2 hr post-IR and a similarly severe arrest of progression from G1 to S at 6 and 12 hr post-IR. Normal rates of DNA synthesis and mitosis 6 and 12 hr post-IR caused the S and M compartments to empty by > 70% at 24 hr. Global gene expression was analyzed in IR-treated cells. A microarray analysis algorithm, EPIG, identified nine IR-responsive patterns of gene expression that were common to the three fibroblast lines, including a dominant p53-dependent G1 checkpoint response. Many p53 target genes, such as CDKN1A, GADD45, BTG2, and PLK3, were significantly up-regulated at 2 hr post-IR. Many genes whose expression is regulated by E2F family transcription factors, including CDK2, CCNE1, CDC6, CDC2, MCM2, were significantly down-regulated at 24 hr post-IR. Numerous genes that participate in DNA metabolism were also markedly repressed in arrested fibroblasts apparently as a result of cell synchronization behind the G1 checkpoint. However, cluster and principal component analyses of gene expression revealed a profile 24 hr post-IR with similarity to that of G0 growth quiescence. The results reveal a highly stereotypic pattern of response to IR in human diploid fibroblasts that reflects primarily synchronization behind the G1 checkpoint but with prominent induction of additional markers of G0 quiescence such as GAS1.

Cell Line↗

PubMed2005

PAGE: phase-shifted analysis of gene expression.

Grouping of gene expression patterns across biological experiments, treatments and time-series data is performed in q-intervals of measurements using phase-shifted analysis of gene expression (PAGE); a Java-based tool to find clusters of genes that share trends of expression profiles within the dataset. The patterns and genes within q-Clusters are visualized in trend plots and compared to determine biological relevance from the gene annotations.

Algorithms↗

PubMed2005

Chemical effects in biological systems--data dictionary (CEBS-DD): a compendium of terms for the capture and integration of biological study design description, conventional phenotypes, and 'omics data.

A critical component in the design of the Chemical Effects in Biological Systems (CEBS) Knowledgebase is a strategy to capture toxicogenomics study protocols and the toxicity endpoint data (clinical pathology and histopathology). A Study is generally an experiment carried out during a period of time for the purpose of obtaining data, and the Study Design Description captures the methods, timing, and organization of the Study. The CEBS Data Dictionary (CEBS-DD) has been designed to define and organize terms in an attempt to standardize nomenclature needed to describe a toxicogenomics Study in a structured yet intuitive format and provide a flexible means to describe a Study as conceptualized by the investigator. The CEBS-DD will organize and annotate information from a variety of sources, thereby facilitating the capture and display of toxicogenomics data in biological context in CEBS, i.e., associating molecular events detected in highly-parallel data with the toxicology/pathology phenotype as observed in the individual Study Subjects and linked to the experimental treatments. The CEBS-DD has been developed with a focus on acute toxicity studies, but with a design that will permit it to be extended to other areas of toxicology and biology with the addition of domain-specific terms. To illustrate the utility of the CEBS-DD, we present an example of integrating data from two proteomics and transcriptomics studies of the response to acute acetaminophen toxicity (A. N. Heinloth et al., 2004, Toxicol. Sci. 80, 193-202).

Acetaminophen↗

PubMed2005

Standardizing global gene expression analysis between laboratories and across platforms.

To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.

Gene Expression Profiling↗

PubMed2005

Systematic variation normalization in microarray data to get gene expression comparison unbiased.

Normalization removes or minimizes the biases of systematic variation that exists in experimental data sets. This study presents a systematic variation normalization (SVN) procedure for removing systematic variation in two channel microarray gene expression data. Based on an analysis of how systematic variation contributes to variability in microarray data sets, our normalization procedure includes background subtraction determined from the distribution of pixel intensity values from each data acquisition channel and log conversion, linear or non-linear regression, restoration or transformation, and multiarray normalization. In the case when a non-linear regression is required, an empirical polynomial approximation approach is used. Either the high terminated points or their averaged values in the distributions of the pixel intensity values observed in control channels may be used for rescaling multiarray datasets. These pre-processing steps remove systematic variation in the data attributable to variability in microarray slides, assay-batches, the array process, or experimenters. Biologically meaningful comparisons of gene expression patterns between control and test channels or among multiple arrays are therefore unbiased using normalized but not unnormalized datasets.

Algorithms↗

PubMed2004

Database development in toxicogenomics: issues and efforts.

The marriage of toxicology and genomics has created not only opportunities but also novel informatics challenges. As with the larger field of gene expression analysis, toxicogenomics faces the problems of probe annotation and data comparison across different array platforms. Toxicogenomics studies are generally built on standard toxicology studies generating biological end point data, and as such, one goal of toxicogenomics is to detect relationships between changes in gene expression and in those biological parameters. These challenges are best addressed through data collection into a well-designed toxicogenomics database. A successful publicly accessible toxicogenomics database will serve as a repository for data sharing and as a resource for analysis, data mining, and discussion. It will offer a vehicle for harmonizing nomenclature and analytical approaches and serve as a reference for regulatory organizations to evaluate toxicogenomics data submitted as part of registrations. Such a database would capture the experimental context of in vivo studies with great fidelity such that the dynamics of the dose response could be probed statistically with confidence. This review presents the collaborative efforts between the European Molecular Biology Laboratory-European Bioinformatics Institute ArrayExpress, the International Life Sciences Institute Health and Environmental Science Institute, and the National Institute of Environmental Health Sciences National Center for Toxigenomics Chemical Effects in Biological Systems knowledge base. The goal of this collaboration is to establish public infrastructure on an international scale and examine other developments aimed at establishing toxicogenomics databases. In this review we discuss several issues common to such databases: the requirement for identifying minimal descriptors to represent the experiment, the demand for standardizing data storage and exchange formats, the challenge of creating standardized nomenclature and ontologies to describe biological data, the technical problems involved in data upload, the necessity of defining parameters that assess and record data quality, and the development of standardized analytical approaches.

Animals↗

PubMed2003

Identification of distinct and common gene expression changes after oxidative stress and gamma and ultraviolet radiation.

The human genome is exposed to many different kinds of DNA-damaging agents. While most damage is detected and repaired through complex damage recognition and repair machineries, some damage has the potential to escape these mechanisms. Unrepaired DNA damage can give rise to alterations and mutations in the genome in an individual cell, which can result in malignant transformation, especially when critical genes are deregulated. In this study, we investigated gene expression changes in response to oxidative stress, gamma (gamma) radiation, and ultraviolet (UV) radiation and their potential implications in cancer development. Doses were selected for each of the three treatments, based on their ability to cause a similar G(1) checkpoint induction and slow down in early S-phase progression, as reflected by a comparable reduction in cyclin E-associated kinase activity of at least 75% in logarithmically growing human dermal diploid fibroblasts. To investigate gene expression changes, logarithmically growing dermal diploid fibroblasts were exposed to either gamma radiation (5 Gy), oxidative stress (75 microM of tert-butyl hydroperoxide (t-butyl-OOH)), or UV radiation (UVC) (7.5 J/m(2)) and RNA was harvested 6 h after treatment. Gene expression was analyzed using the NIEHS Human ToxChip 2.0 with approximately 1901 cDNA clones representing known genes and expressed sequence tags (ESTs). We were able to identify common and distinct responses in dermal diploid fibroblasts to the three different stimuli used. Within our analysis, gene expression profiles in response to gamma radiation and oxidative stress appeared to be more similar than profiles expressed after UV radiation. Interestingly, equivalent cyclin E-associated kinase activity reduction with all the three treatments was associated with greater transcriptional changes after UV radiation than after gamma radiation and oxidative stress. While samples treated with UV radiation displayed modulations of their mitogen activated protein kinase (MAPK) pathway, gamma radiation had its major influence on cell-cycle progression in S-phase and mitosis. In addition, cell cultures from different individuals displayed significant differences in their gene expression responses to DNA damage.

Adult↗

PubMed2003

ATM-dependent and -independent gene expression changes in response to oxidative stress, gamma irradiation, and UV irradiation.

Ataxia telangiectasia (AT) is an autosomal recessive disorder characterized by progressive cerebellar degeneration, immunodeficiencies, telangiectasias, sensitivity to ionizing radiation, and high predisposition for malignancies. The ataxia telangiectasia mutated (ATM) gene encodes a protein (ATM) with serine/threonine kinase activity. DNA-double strand breaks are known to increase its kinase activity. While cells from individuals with AT are attenuated in their G(1)-, S- and G(2)-phase cell cycle checkpoint functions in response to gamma irradiation and oxidative stress, their response to UV irradiation appears to be equivalent to that of wild-type cells. In this study, we investigated changes in gene expression in response to gamma irradiation, oxidative stress, and UV irradiation, focusing on the dependence on ATM. Doses for all three treatments were selected that resulted in roughly an equivalent induction of a G(1) checkpoint response and inhibition of progression through S phase. To investigate gene expression changes, logarithmically growing wild-type and AT dermal diploid fibroblasts were exposed to either gamma radiation (5 Gy), oxidative stress (75 micro M t-butyl-hydroperoxide), or UV radiation (7.5 J/m(2)), and RNA was harvested 6 h after treatment. Gene expression analysis was performed using the NIEHS Human ToxChip 2.0 with approximately 1900 cDNA clones representing known genes and ESTs. All three treatments resulted in distinct patterns of gene expression changes, as shown previously. ATM-dependent and ATM-independent components were detected within these patterns, as were novel indications of involvement of ATM in regulation of transcription factors such as SP1, AP1 and MTF1.

Algorithms↗

PubMed2003

Tamoxifen functions as a molecular agonist inducing cell cycle-associated genes in breast cancer cells.

Tamoxifen is a widely used breast cancer therapeutic and preventative agent. Although functioning as an estrogen antagonist at the cellular level, transcriptional profiling revealed that at the molecular level, tamoxifen functions largely as an agonist, virtually recapitulating the gene expression profile induced in breast cancer cells by estrogen. Remarkably, tamoxifen induces transcription factors and genes involved in promoting cell cycle progression including fos, myc, myb, cdc25a, cyclins E and A2, and stk15 with kinetics that paralleled that of cells cycling in response to estrogen, even though tamoxifen-treated cells are not transiting through the cell cycle. Induction of cell cycle-associated genes was specific for tamoxifen, and did not occur with raloxifene. However, cyclin D1 was a key estrogen-induced gene not expressed in response to tamoxifen or raloxifene but constitutively expressed in tamoxifen-resistant cells.

Antineoplastic Agents↗

PubMed2002

Genomic interrogation of mechanism(s) underlying cellular responses to toxicants.

Assessment of the impact of xenobiotic exposure on human health and disease progression is complex. Knowledge of mode(s) of action, including mechanism(s) contributing to toxicity and disease progression, is valuable for evaluating compounds. Toxicogenomics, the subdiscipline which merges genomics with toxicology, holds the promise to contributing significantly toward the goal of elucidating mechanism(s) by studying genome-wide effects of xenobiotics. Global gene expression profiling, revolutionized by microarray technology and a crucial aspect of a toxicogenomic study, allows measuring transcriptional modulation of thousands of genes following exposure to a xenobiotic. We use our results from previous studies on compounds representing two different classes of xenobiotics (barbiturate and peroxisome proliferator) to discuss the application of computational approaches for analyzing microarray data to elucidate mechanism(s) underlying cellular responses to toxicants. In particular, our laboratory demonstrated that chemical-specific patterns of gene expression can be revealed using cDNA microarrays. Transcript profiling provides discrimination between classes of toxicants, as well as, genome-wide insight into mechanism(s) of toxicity and disease progression. Ultimately, the expectation is that novel approaches for predicting xenobiotic toxicity in humans will emerge from such information.

Computational Biology↗

PubMed2002

Computational selection of distinct class- and subclass-specific gene expression signatures.

In this investigation we used statistical methods to select genes with expression profiles that partition classes and subclasses of biological samples. Gene expression data corresponding to liver samples from rats treated for 24 h with an enzyme inducer (phenobarbital) or a peroxisome proliferator (clofibrate, gemfibrozil or Wyeth 14,643) were subjected to a modified Z-score test to identify gene outliers and a binomial distribution to reduce the probability of detecting genes as differentially expressed by chance. Hierarchical clustering of 238 statistically valid differentially expressed genes partitioned class-specific gene expression signatures into groups that clustered samples exposed to the enzyme inducer or to peroxisome proliferators. Using analysis of variance (ANOVA) and linear discriminant analysis methods we identified single genes as well as coupled gene expression profiles that separated the phenobarbital from the peroxisome proliferator treated samples and discerned the fibrate (gemfibrozil and clofibrate) subclass of peroxisome proliferators. A comparison of genes ranked by ANOVA with genes assessed as significant by mixedlinear models analysis [J. Comput. Biol. 8 (2001) 625] or ranked by information gain revealed good congruence with the top 10 genes from each statistical method in the contrast between phenobarbital and peroxisome proliferators expression profiles. We propose building upon a classification regimen comprised of analysis of replicate data, outlier diagnostics and gene selection procedures to utilize cDNA microarray data to categorize subclasses of samples exposed to pharmacologic agents.

Algorithms↗

PubMed2002

Gene expression analysis reveals chemical-specific profiles.

The application of gene expression profiling technology to examine multiple genes and signaling pathways simultaneously promises a significant advance in understanding toxic mechanisms to ultimately aid in protection of public health. Public and private efforts in the new field of toxicogenomics are focused on populating databases with gene expression profiles of compounds where toxicological and pathological endpoints are well characterized. The validity and utility of a toxicogenomics is dependent on whether gene expression profiles that correspond to different chemicals can be distinguished. The principal hypothesis underlying a toxicogenomic or pharmacogenomic strategy is that chemical-specific patterns of altered gene expression will be revealed using high-density microarray analysis of tissues from exposed organisms. Analyses of these patterns should allow classification of toxicants and provide important mechanistic insights. This report provides a verification of this hypothesis. Patterns of gene expression corresponding to liver tissue derived from chemically exposed rats revealed similarity in gene expression profiles between animals treated with different agents from a common class of compounds, peroxisome proliferators [clofibrate (ethyl-p-chlorophenoxyisobutyrate), Wyeth 14,643 ([4-chloro-6(2,3-xylidino)-2-pyrimidinylthio]acetic acid), and gemfibrozil (5-2[2,5-dimethylphenoxy]2-2-dimethylpentanoic acid)], but a very distinct gene expression profile was produced using a compound from another class, enzyme inducers (phenobarbital).

Animals↗

PubMed2002

Prediction of compound signature using high density gene expression profiling.

DNA microarrays, used to measure the gene expression of thousands of genes simultaneously, hold promise for future application in efficient screening of therapeutic drugs. This will be aided by the development and population of a database with gene expression profiles corresponding to biological responses to exposures to known compounds whose toxicological and pathological endpoints are well characterized. Such databases could then be interrogated, using profiles corresponding to biological responses to drugs after developmental or environmental exposures. A positive correlation with an archived profile could lead to some knowledge regarding the potential effects of the tested compound or exposure. We have previously shown that cDNA microarrays can be used to generate chemical-specific gene expression profiles that can be distinguished across and within compound classes, using clustering, simple correlation, or principal component analyses. In this report, we test the hypothesis that knowledge can be gained regarding the nature of blinded samples, using an initial training set comprised of gene expression profiles derived from rat liver exposed to clofibrate, Wyeth 14,643, gemfibrozil, or phenobarbital for 24 h or 2 weeks of exposure. Highly discriminant genes were derived from our database training set using approaches including linear discriminant analysis (LDA) and genetic algorithm/K-nearest neighbors (GA/KNN). Using these genes in the analysis of coded liver RNA samples derived from 24-h, 3-day, or 2-week exposures to phenytoin, diethylhexylpthalate, or hexobarbital led to successful prediction of whether these samples were derived from livers of rats exposed to enzyme inducers or to peroxisome proliferators. This validates our initial hypothesis and lends credibility to the concept that the further development of a gene expression database for chemical effects will greatly enhance the hazard identification processes.

Algorithms↗

PubMed2002

Differential toxicogenomic responses to 2,3,7,8-tetrachlorodibenzo-p-dioxin in malignant and nonmalignant human airway epithelial cells.

In humans, exposure to high levels of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is associated with chronic obstructive pulmonary disease and lung cancer. While several studies have shown that the lung is a target organ for TCDD toxicity, little is known on the specific biological pathways altered by TCDD. Studies have shown that the transcriptional response of TCDD (in vivo and in vitro) is complex, and exhibits cell type and tissue specificity. Thus, the purpose of this study was to look at global and concentration-dependent effects of TCDD on gene expression in human lung cells. Gene expression profiling of both a nontumorigenic (HPL1A) and a malignant, tumorigenic lung cell line (A549) was performed by microarray dual fluorescence hybridizations in cells treated with increasing concentrations of TCDD (0, 0.1, 1, 10 nM) for 24 h. Real time RT-PCR was used to verify alterations in specific genes. Results showed that 68 out of 2091 genes were changed in each cell line, and 15 of those genes were found altered in both cell lines. Common gene responses altered by TCDD were identified and included known xenobiotic metabolizing genes, genes known to alter cell cycle, as well as genes that are involved with cell signaling and that mediate cell motility or communication. Cell line specific differences in gene expression were found that indicate the nonmalignant HPL1A cells are retinoic acid responsive. In addition, TCDD altered specific immunomodulatory genes in the HPL1A cells. These data show that TCDD alters multiple integrated networks of signaling pathways associated with pulmonary disease, particularly that of lung cancer.

Algorithms↗

PubMed2002

Regulation of DNA replication fork genes by 17beta-estradiol.

The steroid hormone estrogen can stimulate mitogenesis in hormone-responsive breast cancer epithelial cells. This action is attributed to the transcriptional activity of the ER, a ligand-dependent transcription factor. However, the exact molecular mechanism underlying estrogen-induced proliferation has yet to be completely elucidated. Using custom cDNA microarrays containing many genes implicated in cell cycle progression and DNA replication, we examined the gene expression of a hormone-responsive breast cancer cell line (MCF-7) treated with a mitogenic dose of estrogen in the absence of confounding growth factors found in serum. Gene expression changes were monitored 1, 4, 12, 24, 36, and 48 h after estrogen stimulation so that RNA levels at critical times throughout cell cycle progression could be monitored. Significant changes include the altered transcript levels of genes implicated in transcription, cellular signaling, and cell cycle checkpoints. At time points during which increased numbers of cells were progressing through S phase, a majority of the genes associated with the DNA replication fork were also found to be induced. The coexpression of DNA replication fork genes by estrogen without the support of serum growth factors indicates an important estrogen regulatory component of the molecular mechanism driving estrogen-induced mitogenesis.

Cell Division↗

PubMedDate not supplied

Methapyrilene toxicity: anchorage of pathologic observations to gene expression alterations.

Methapyrilene (MP) exposure of animals can result in an array of adverse pathological responses including hepatotoxicity. This study investigates gene expression and histopathological alterations in response to MP treatment in order to 1) utilize computational approaches to classify samples derived from livers of MP treated rats based on severity of toxicity incurred in the corresponding tissue, 2) to phenotypically anchor gene expression pattems, and 3) to gain insight into mechanism(s) of methapyrilene hepatotoxicity. Large-scale differential gene expression levels associated with the exposure of male Sprague-Dawley rats to the rodent hepatic carcinogen MP for 1, 3, or 7 days after daily dosage with 10 or 100 mg/kg/day were monitored. Hierarchical clustering and principal component analysis were successful in classifying samples in agreement with microscopic observations and revealed low-dose effects that were not observed histopathologically. Data from cDNA microarray analysis corroborated observed histopathological alterations such as hepatocellular necrosis, bile duct hyperplasia, microvesicular vacuolization, and portal inflammation observed in the livers of MP exposed rats and provided insight into the role of specific genes in the studied toxicological processes.

Animals↗