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May 15, 2007 (Vol. 27, No. 10)

Toxicogenomics for Compound Selection

IPA-Tox™ Adds Toxicity Pathways and Functional Analysis to Software

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    Figure 1

    Today, only one in nine compounds makes it successfully through the pharmaceutical development process and gets approved by the European and/or the U.S. regulatory authorities. The vast majority of compounds fail because of toxicity and safety issues in full clinical development. To identify potential biological risks associated with candidates earlier in the drug development process, pharmaceutical companies are incorporating genomics approaches such as molecular toxicology (toxicogenomics) to improve decision-making and increase confidence in progressing compounds from one stage to the next.

    Molecular toxicology links genome-wide expression changes to clinical pathology endpoints, an approach that offers distinct advantages over traditional toxicology technologies. Molecular toxicology is more sensitive in predicting or diagnosing clinical pathology endpoints associated with the compound or chemical series under investigation and provides mechanistic understanding of the induced toxicological response that eventually leads to the observed clinical pathology.

    Advances in microarray technologies for genome-wide gene-expression analysis, such as improved reproducibility and reduction in array costs, have clearly impacted the field. With the surge of large-scale genomic and proteomic data generation, a need for rapid and reliable methods for data analysis and interpretation to realize the full value of molecular toxicology approaches for compound prioritization and selection has emerged.

    To directly address this need, Ingenuity Systems (www.ingenuity.com) developed a new analysis capability within the Ingenuity Pathways Analysis (IPA) software application: IPA-Tox. IPA was designed to help researchers identify the functions and pathways most relevant to experimental datasets or gene lists of interest and to visualize and understand the molecular mechanisms and biological processes that underlie diseases and cellular processes. It supports drug discovery and development workflows by enabling the user to search and synthesize biological and chemical knowledge spread across the scientific literature.

    IPA-Tox delivers a focused and summarized understanding of a candidate compound’s potential to induce toxicity, enables hypothesis generation of mechanism of action (MOA) and toxicity (MOT), and helps identify potential candidate markers of drug toxicity. In developing IPA-Tox, new content relevant to investigational toxicology was manually curated from toxicology-focused scientific literature and added to IPA’s knowledge base of findings.

    IPA-Tox brings molecular toxicology expertise to nonexpert users and helps overcome the data-interpretation bottleneck currently prevalent in the genomics and proteomics field. To demonstrate the potential of IPA-Tox for rapid assessment of risks associated with candidate compounds, a case study using three anticancer drugs—carmustine, methotrexate, and thioguanine—will be presented. The gene expression profiles of livers from rats treated at two doses (low and high dose) and three time points (one, three, and five days) in short-term, repeat-dose studies were analyzed and compared using IPA-Tox. The toxicity of these compounds has been well characterized using traditional toxicology methodologies. All three drugs are toxic to the hematopoietic progenitor cells of the bone marrow and cause leukocyte depletion, whereas liver toxicity, marked by AST and ALT increase and observed bile duct hyperplasia, was observed primarily for carmustine treatments only.

  • Linking Gene Expression Profiles to Clinical Pathology Endpoints

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    Figure 2a

    One of the major components of IPA-Tox is the Toxicity Functions, which cover a wide spectrum of well-known drug-related injuries and pathologies usually exhibited as a clinical manifestation. Toxicity Functions are known associations between genes and clinical pathology endpoints and are based on findings published in the toxicology literature. They include specific functions for liver, such as cholestasis, fibrosis, necrosis, proliferation, and steatosis; kidney, such as atrophy, fibrosis, hydronephrosis, and tubular nephrosis; and heart, like dilation, enlargement, hypertrophy, hypoplasia, and inflammation.

    These functions are of particular value when analyzing compound-induced gene-expression changes, as they are indicative of the potential for the drug to induce a clinical pathology. Carmustine high-dose (16 mg/kg) and later-time-point (day three and five) treatments are clearly associated with liver toxicities such as hepatomegaly and steatosis (Figure 1). These associations were not observed for any of the other compound treatments analyzed in this study, with the exception of one high-dose thioguanine treatment.

    Clinical pathology as measured using traditional histopathology is usually an observed manifestation of the drug treatment. To better understand immediate and/or early response to the drug treatment at the mechanistic level, IPA-Tox utilizes a library of Toxicity Lists manually curated from the scientific literature. The Toxicity Lists consist of sets of genes that are known to be perturbed upon compound treatment and include functional gene groupings based on critical biological processes such as adaptive, defensive, or reparative responses to xenobiotic insult.

    Figure 2 shows the results from analyzing drug-induced gene-expression changes in the context of the Toxicity Lists library and provides insight into the mechanism of carmustine-induced hepatotoxicity. This analysis returned several impacted Toxicity Lists, the most significant being the “CAR/RXR Activation”, “Hepatic Cholestasis,” and “LPS & IL-1 Mediated Inhibition of RXR Function” gene lists. These results agree with the previously identified hepatomegaly and steatosis Toxicity Functions results and suggest marked induction of all phases of xenobiotic metabolism.

    Hepatomegaly is associated and can be explained with centrilobular hypertrophy, a result of Cyp P450 gene induction. In addition, the significant association of carmustine treatments with the “Hepatic Cholestasis” gene list is in agreement with the bile duct hyperplasia observed at the histopathology level. Cholestasis often occurs either as a result of altered hepatocyte bile formation or disruption of bile flow out of the hepatocyte through intrahepatic bile ductules.

    IPA-Tox is fully integrated with IPA’s repository of biological and chemical knowledge, and, as a result, researchers have the ability to explore the biological effects of their compound beyond the context of toxicity, understand the MOA and MOT, and identify potential biomarkers. IPA’s molecular networks, computationally generated from the set of genes perturbed by carmustine_HI_5day treatment, help elucidate carmustine’s mechanism of action by highlighting drug-induced changes in expression of genes involved in xenobiotic metabolism, cell growth, and proliferation (data not shown). This effect was seen across all three high-dose carmustine treatments.

    IPA-Tox can identify the number and type of genes associated with carmustine-induced toxicity. In addition, it helps in discriminating carmustine’s induced hepatotoxocity from other anticancer drugs and can be used to build a hypothesis model for how toxicity evolves at the molecular level.

    As the field of drug discovery and development continues to adopt molecular toxicology and as new biomarkers of pharmacological effects are discovered and validated, it will be crucial for genomics analysis tools to keep pace with these new discoveries. IPA’s knowledge base of biological and chemical information provides a system for the incorporation of new assay data and information and can adjust to new technology implementations. Its structure enables continuous modeling and incorporation of scientific discoveries as they are published.

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    Figure 2b


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