Gene expression response in target organ and whole blood varies as a function of target organ injury phenotype

Genome Biology Gene expression response in target organ and whole blood varies as a function of target organ injury phenotype Edward K Lobenhofer*, J Todd Auman, Pamela E Blackshear, Gary A Boorman 5 Pierre R Bushel 4 Michael L Cunningham 5 Jennifer M Fostel 1 Kevin Gerrish 0 Alexandra N Heinloth 0 Richard D Irwin 5 David E Malarkey 3 B Alex Merrick 1 Stella O Sieber 0 Charles J Tucker 0 Sandra M Ward 3 Ralph E Wilson 3 Patrick Hurban 3 Raymond W Tennant 0 Richard S Paules 2 0 NIEHS Microarray Group, National Institute of Environmental Health Sciences, National Institutes of Health , Research Triangle Park, NC 27709 , USA 1 Laboratory of Respiratory Biology, National Institute of Environmental Health Sciences, National Institutes of Health , Research Triangle Park, NC 27709 , USA 2 Integrated Laboratory Systems, Inc. , Research Triangle Park, NC 27709 , USA 3 Cogenics, a Division of Clinical Data, Inc. , Morrisville, NC 27560 , USA 4 Biostatistics Branch, National Institute of Environmental Health Sciences, National Institutes of Health , Research Triangle Park, NC 27709 , USA 5 National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health , Research Triangle Park, NC 27709 , USA 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. - Background The use of genomic approaches to better understand the adverse effects of environmental and xenobiotic exposures on human injury and disease processes engendered a great deal of early enthusiasm and excitement. This research initially focused on using gene expression alterations as measured by microarray analyses and is often referred to as 'toxicogenomics' [1]. Quite early on, investigators were able to demonstrate that exposure to different toxicants could be discriminated or classified in rodent model systems by microarray profiling of gene expression alterations in the target tissues, that is, tissues that display visible adverse effects in response to toxicant exposure [2-5]. Gene expression microarrays have developed over the past decade into a powerful tool for investigating biological, mechanistic, and disease processes in addition to developing genomic classifiers. Recent standardization efforts by the Microarray Quality Control Consortium, the Toxicogenomics Resource Consortium as well as other groups have clearly demonstrated the reproducibility of transcript level data generated using these approaches [6-9]. However, in most instances these studies have understandably been based on reference samples with little or no biological significance. The Microarray Quality Control Consortium did substantiate their findings by performing a cross-platform study using samples from a multi-agent rat toxicogenomics study at a single dose and time point and the Toxicogenomics Resource Consortium did perform a cross-laboratory, time course assessment using samples from a single toxic agent [10,11]. However, there are still open questions regarding the utility and applicability of the microarray technology in biological research and in particular with respect to understanding and classifying injury processes that arise as a consequence of exposures to various agents. For example, can gene expression data distinguish similar biological responses that occur in different physiological regions within an organ (for example, necrosis within different zones of the liver lobule) or similar lesions that are the result of exposure to different compounds? Linking gene expression changes with more traditional toxicological measurements of adverse biological responses to toxicants (for example, histopathology and clinical chemistry), referred to as 'phenotypic anchoring', allowed investigators to gain new insight into the processes involved in the adverse effects on target tissues [12-15]. In addition to analysis of target tissues, the use of whole blood as a tissue source for gene expression profiling is extremely appealing and already has been demonstrated for a variety of diseases and exposures [16-22]. This has tremendous potential in a therapeutic setting - the use of blood as a surrogate for the primary tissue of interest greatly facilitates sample collection and analysis. The benefits would be realized in basic research studies as well. If transcript data in whole blood can function as a surrogate for the target organ, a researcher would be able to collect serial time points from an animal as opposed to harvesting tissue at a single time point after sacrifice. This would not only decrease the number of animals being used in a study, but would increase the amount and value of the data generated from a single animal as early transcriptional events could be phenotypically anchored to histopathological observations or clinical chemistry data that were not observed until later time points within the same animal. The amount of total RNA required to perform microarray-based gene expression profiling from whole blood continues to decrease, thereby increasing the potential for practical applications. Thus, one question of interest is whether expression data from whole blood can serve as a surrogate for a target organ through either an ability to detect the same transcript changes or an ability to identify different transcript biomarkers with similar or enhanced classification utility. While much progress has been made in the application of toxicogenomics to the classification of toxicants and the investigation of mechanisms of toxicity, a full realization of its potential in a systems biology context, sometimes referred to as 'systems toxicology' [23], has yet to be accomplished. A primary obstacle has been the lack of truly robust data sets that capture not only genome-wide gene expression measurements but also traditional biological and toxicological information associated with exposures that vary over dose and time. This need was recently highlighted in the National Research Council's report on toxicogenomics [24]. Here we present a comprehensive, public dataset of gene expression and accompanying data (histopathology, clinical chemistry, hematology) from a standardized study to serve as a resource to further advance the development of systems toxicology. The present report details the experimental design and the different data that were collected, and provides examples of how these data can be used to address important biological questions. This investigation of eight (...truncated)