Pharmacogenomic responses of rat liver to methylprednisolone: an approach to mining a rich microarray time series

Transitioning from Basic toward Systems Pharmacodynamic Models: Lessons from Corticosteroids

Technology in bioanalysis, -omics, and computation have evolved over the past half century to allow for comprehensive assessments of the molecular to whole body pharmacology of diverse corticosteroids. Such studies have advanced pharmacokinetic and pharmacodynamic (PK/PD) concepts and models that often generalize across various classes of drugs. These models encompass the "pillars" of pharmacology, namely PK and target drug exposure, the mass-law interactions of drugs with receptors/targets, and the consequent turnover and homeostatic control of genes, biomarkers, physiologic responses, and disease symptoms. Pharmacokinetic methodology utilizes noncompartmental, compartmental, reversible, physiologic [full physiologically based pharmacokinetic (PBPK) and minimal PBPK], and target-mediated drug disposition models using a growing array of pharmacometric considerations and software. Basic PK/PD models have emerged (simple direct, biophase, slow receptor binding, indirect response, irreversible, turnover with inactivation, and transduction models) that place emphasis on parsimony, are mechanistic in nature, and serve as highly useful "top-down" methods of quantitating the actions of diverse drugs. These are often components of more complex quantitative systems pharmacology (QSP) models that explain the array of responses to various drugs, including corticosteroids. Progressively deeper mechanistic appreciation of PBPK, drug-target interactions, and systems physiology from the molecular (genomic, proteomic, metabolomic) to cellular to whole body levels provides the foundation for enhanced PK/PD to comprehensive QSP models. Our research based on cell, animal, clinical, and theoretical studies with corticosteroids have provided ideas and quantitative methods that have broadly advanced the fields of PK/PD and QSP modeling and illustrates the transition toward a global, systems understanding of actions of diverse drugs. SIGNIFICANCE STATEMENT: Over the past half century, pharmacokinetics (PK) and pharmacokinetics/pharmacodynamics (PK/PD) have evolved to provide an array of mechanism-based models that help quantitate the disposition and actions of most drugs. We describe how many basic PK and PK/PD model components were identified and often applied to the diverse properties of corticosteroids (CS). The CS have complications in disposition and a wide array of simple receptor-to complex gene-mediated actions in multiple organs. Continued assessments of such complexities have offered opportunities to develop models ranging from simple PK to enhanced PK/PD to quantitative systems pharmacology (QSP) that help explain therapeutic and adverse CS effects. Concurrent development of state-of-the-art PK, PK/PD, and QSP models are described alongside experimental studies that revealed diverse CS actions.

Pathway-Based Analysis of the Liver Response to Intravenous Methylprednisolone Administration in Rats: Acute Versus Chronic Dosing

Pharmacological time-series data, from comparative dosing studies, are critical to characterizing drug effects. Reconciling the data from multiple studies is inevitably difficult; multiple in vivo high-throughput -omics studies are necessary to capture the global and temporal effects of the drug, but these experiments, though analogous, differ in (microarray or other) platforms, time-scales, and dosing regimens and thus cannot be directly combined or compared. This investigation addresses this reconciliation issue with a meta-analysis technique aimed at assessing the intrinsic activity at the pathway level. The purpose of this is to characterize the dosing effects of methylprednisolone (MPL), a widely used anti-inflammatory and immunosuppressive corticosteroid (CS), within the liver. A multivariate decomposition approach is applied to analyze acute and chronic MPL dosing in male adrenalectomized rats and characterize the dosing-dependent differences in the dynamic response of MPL-responsive signaling and metabolic pathways. We demonstrate how to deconstruct signaling and metabolic pathways into their constituent pathway activities, activities which are scored for intrinsic pathway activity. Dosing-induced changes in the dynamics of pathway activities are compared using a model-based assessment of pathway dynamics, extending the principles of pharmacokinetics/pharmacodynamics (PKPD) to describe pathway activities. The model-based approach enabled us to hypothesize on the likely emergence (or disappearance) of indirect dosing-dependent regulatory interactions, pointing to likely mechanistic implications of dosing of MPL transcriptional regulation. Both acute and chronic MPL administration induced a strong core of activity within pathway families including the following: lipid metabolism, amino acid metabolism, carbohydrate metabolism, metabolism of cofactors and vitamins, regulation of essential organelles, and xenobiotic metabolism pathway families. Pathway activities alter between acute and chronic dosing, indicating that MPL response is dosing dependent. Furthermore, because multiple pathway activities are dominant within a single pathway, we observe that pathways cannot be defined by a single response. Instead, pathways are defined by multiple, complex, and temporally related activities corresponding to different subgroups of genes within each pathway.

Mechanistic Multi-Tissue Modeling of Glucocorticoid-Induced Leucine Zipper Regulation: Integrating Circadian Gene Expression with Receptor-Mediated Corticosteroid Pharmacodynamics

The glucocorticoid-induced leucine zipper (GILZ) is an important mediator of anti-inflammatory corticosteroid action. The pharmacokinetic/pharmacodynamic/pharmacogenomic effects of acute and chronic methylprednisolone (MPL) dosing on the tissue-specific dynamics of GILZ expression were examined in rats. A mechanism-based model was developed to investigate and integrate the role of MPL and circadian rhythms on the transcriptional enhancement of GILZ in multiple tissues. Animals received a single 50-mg/kg intramuscular bolus or a 7-day 0.3-mg/kg/h subcutaneous infusion of MPL and were euthanized at several time points. An additional group of rats were euthanized at several times and served as 24-hour light/dark (circadian) controls. Plasma MPL and corticosterone concentrations were measured by high-performance liquid chromatography. The expression of GILZ and glucocorticoid receptor (GR) mRNA was quantified in tissues using quantitative real-time reverse-transcription polymerase chain reaction. The pharmacokinetics of MPL were described using a two-compartment model. Mild-to-robust circadian oscillations in GR and GILZ mRNA expression were characterized in muscle, lung, and adipose tissues and modeled using Fourier harmonic functions. Acute MPL dosing caused significant down-regulation (40%-80%) in GR mRNA and enhancement of GILZ mRNA expression (500%-1080%) in the tissues examined. While GILZ returned to its rhythmic baseline following acute dosing, a new steady-state was observed upon enhancement by chronic dosing. The model captured the complex dynamics in all tissues for both dosing regimens. The model quantitatively integrates physiologic mechanisms, such as circadian processes and GR tolerance phenomena, which control the tissue-specific regulation of GILZ by corticosteroids. These studies characterize GILZ as a pharmacodynamic marker of corticosteroid actions in several tissues.

Functional proteomic analysis of corticosteroid pharmacodynamics in rat liver: Relationship to hepatic stress, signaling, energy regulation, and drug metabolism

Corticosteroids (CS) are anti-inflammatory agents that cause extensive pharmacogenomic and proteomic changes in multiple tissues. An understanding of the proteome-wide effects of CS in liver and its relationships to altered hepatic and systemic physiology remains incomplete. Here, we report the application of a functional pharmacoproteomic approach to gain integrated insight into the complex nature of CS responses in liver in vivo. An in-depth functional analysis was performed using rich pharmacodynamic (temporal-based) proteomic data measured over 66h in rat liver following a single dose of methylprednisolone (MPL). Data mining identified 451 differentially regulated proteins. These proteins were analyzed on the basis of temporal regulation, cellular localization, and literature-mined functional information. Of the 451 proteins, 378 were clustered into six functional groups based on major clinically-relevant effects of CS in liver. MPL-responsive proteins were highly localized in the mitochondria (20%) and cytosol (24%). Interestingly, several proteins were related to hepatic stress and signaling processes, which appear to be involved in secondary signaling cascades and in protecting the liver from CS-induced oxidative damage. Consistent with known adverse metabolic effects of CS, several rate-controlling enzymes involved in amino acid metabolism, gluconeogenesis, and fatty-acid metabolism were altered by MPL. In addition, proteins involved in the metabolism of endogenous compounds, xenobiotics, and therapeutic drugs including cytochrome P450 and Phase-II enzymes were differentially regulated. Proteins related to the inflammatory acute-phase response were up-regulated in response to MPL. Functionally-similar proteins showed large diversity in their temporal profiles, indicating complex mechanisms of regulation by CS.

SIGNIFICANCE

Clinical use of corticosteroid (CS) therapy is frequent and chronic. However, current knowledge on the proteome-level effects of CS in liver and other tissues is sparse. While transcriptomic regulation following methylprednisolone (MPL) dosing has been temporally examined in rat liver, proteomic assessments are needed to better characterize the tissue-specific functional aspects of MPL actions. This study describes a functional pharmacoproteomic analysis of dynamic changes in MPL-regulated proteins in liver and provides biological insight into how steroid-induced perturbations on a molecular level may relate to both adverse and therapeutic responses presented clinically.

Role of Glucocorticoid Receptor and Pregnane X Receptor in Dexamethasone Induction of Rat Hepatic Aryl Hydrocarbon Receptor Nuclear Translocator and NADPH-Cytochrome P450 Oxidoreductase

The aryl hydrocarbon receptor (AHR) nuclear translocator (ARNT), as the AHR's heterodimerization partner, and NADPH-cytochrome P450 oxidoreductase (POR), as the key electron donor for all microsomal P450s, are independent and indispensable components in the adaptive and toxic responses to polycyclic aromatic hydrocarbons. Expression of both ARNT and POR in rat liver is induced by dexamethasone (DEX), a synthetic glucocorticoid known to activate both the glucocorticoid receptor (GR) and the pregnane X receptor (PXR). To better understand the role of GR and PXR in the in vivo DEX induction of rat hepatic ARNT and POR at the mRNA and protein levels, we studied the following: 1) the effects of DEX doses that activate GR (≥0.1 mg/kg) or PXR (≥10 mg/kg); 2) responses produced by GR- and PXR-selective agonists; 3) the impact of GR antagonism on DEX's inducing effects; and 4) whether biologic responses to DEX are altered in PXR-knockout rats. Our findings are consistent with a role for GR as a key mediator of the induction of rat hepatic ARNT expression by glucocorticoids; a role for PXR in the modulation of ARNT protein levels could not be excluded. Although GR activation may contribute to POR mRNA induction, regulation of POR expression and function by DEX is primarily PXR-mediated. This work suggests that the hepatic expression and function of ARNT and POR may be modulated by exposure to exogenous PXR activators and/or conditions that alter glucocorticoid levels such as stress, steroidal therapies, and diseases of excess or deficiency.

Quantitative tissue-specific dynamics of in vivo GILZ mRNA expression and regulation by endogenous and exogenous glucocorticoids

Glucocorticoids (GC) are steroid hormones, which regulate metabolism and immune function. Synthetic GCs, or corticosteroids (CS), have appreciable clinical utility via their ability to suppress inflammation in immune-mediated diseases like asthma and rheumatoid arthritis. Recent work has provided insight to novel GC-induced genes that mediate their anti-inflammatory effects, including glucocorticoid-induced leucine zipper (GILZ). Since GILZ comprises an important part of GC action, its regulation by both drug and hormone will influence CS therapy. In addition, GILZ expression is often employed as a biomarker of GC action, which requires judicious selection of sampling time. Understanding the in vivo regulation of GILZ mRNA expression over time will provide insight into both the physiological regulation of GILZ by endogenous GC and the dynamics of its enhancement by CS. A highly quantitative qRT-PCR assay was developed for measuring GILZ mRNA expression in tissues obtained from normal and CS-treated rats. This assay was applied to measure GILZ mRNA expression in eight tissues; to determine its endogenous regulation over time; and to characterize its dynamics in adipose tissue, muscle, and liver following treatment with CS. We demonstrate that GILZ mRNA is expressed in several tissues. GILZ mRNA expression in adipose tissue displayed a robust circadian rhythm that was entrained with the circadian oscillation of endogenous corticosterone; and is strongly enhanced by acute and chronic dosing. Single dosing also enhanced GILZ mRNA in muscle and liver, but the dynamics varied. In conclusion, GILZ is widely expressed in the rat and highly regulated by endogenous and exogenous GCs.

Tissue-specific gene expression and regulation in liver and muscle following chronic corticosteroid administration

Although corticosteroids (CSs) affect gene expression in multiple tissues, the array of genes that are regulated by these catabolic steroids is diverse, highly tissue specific, and depends on their functions in the tissue. Liver has many important functions in performing and regulating diverse metabolic processes. Muscle, in addition to its mechanical role, is critical in maintaining systemic energy homeostasis and accounts for about 80% of insulin-directed glucose disposal. Consequently, a better understanding of CS pharmacogenomic effects in these tissues would provide valuable information regarding the tissue-specificity of transcriptional dynamics, and would provide insights into the underlying molecular mechanisms of action for both beneficial and detrimental effects. We performed an integrated analysis of transcriptional data from liver and muscle in response to methylprednisolone (MPL) infusion, which included clustering and functional annotation of clustered gene groups, promoter extraction and putative transcription factor (TF) identification, and finally, regulatory closeness (RC) identification. This analysis allowed the identification of critical transcriptional responses and CS-responsive functions in liver and muscle during chronic MPL administration, the prediction of putative transcriptional regulators relevant to transcriptional responses of CS-affected genes which are also potential secondary bio-signals altering expression levels of target-genes, and the exploration of the tissue-specificity and biological significance of gene expression patterns, CS-responsive functions, and transcriptional regulation. The analysis provided an integrated description of the genomic and functional effects of chronic MPL infusion in liver and muscle.

Modeling autonomic regulation of cardiac function and heart rate variability in human endotoxemia

Heart rate variability (HRV), the quantification of beat-to-beat variability, has been studied as a potential prognostic marker in inflammatory diseases such as sepsis. HRV normally reflects significant levels of variability in homeostasis, which can be lost under stress. Much effort has been placed in interpreting HRV from the perspective of quantitatively understanding how stressors alter HRV dynamics, but the molecular and cellular mechanisms that give rise to both homeostatic HRV and changes in HRV have received less focus. Here, we develop a mathematical model of human endotoxemia that incorporates the oscillatory signals giving rise to HRV and their signal transduction to the heart. Connections between processes at the cellular, molecular, and neural levels are quantitatively linked to HRV. Rhythmic signals representing autonomic oscillations and circadian rhythms converge to modulate the pattern of heartbeats, and the effects of these oscillators are diminished in the acute endotoxemia response. Based on the semimechanistic model developed herein, homeostatic and acute stress responses of HRV are studied in terms of these oscillatory signals. Understanding the loss of HRV in endotoxemia serves as a step toward understanding changes in HRV observed clinically through translational applications of systems biology based on the relationship between biological processes and clinical outcomes.

Comparative analysis of acute and chronic corticosteroid pharmacogenomic effects in rat liver: transcriptional dynamics and regulatory structures

Background

Comprehensively understanding corticosteroid pharmacogenomic effects is an essential step towards an insight into the underlying molecular mechanisms for both beneficial and detrimental clinical effects. Nevertheless, even in a single tissue different methods of corticosteroid administration can induce different patterns of expression and regulatory control structures. Therefore, rich in vivo datasets of pharmacological time-series with two dosing regimens sampled from rat liver are examined for temporal patterns of changes in gene expression and their regulatory commonalities.

Results

The study addresses two issues, including (1) identifying significant transcriptional modules coupled with dynamic expression patterns and (2) predicting relevant common transcriptional controls to better understand the underlying mechanisms of corticosteroid adverse effects. Following the orientation of meta-analysis, an extended computational approach that explores the concept of agreement matrix from consensus clustering has been proposed with the aims of identifying gene clusters that share common expression patterns across multiple dosing regimens as well as handling challenges in the analysis of microarray data from heterogeneous sources, e.g. different platforms and time-grids in this study. Six significant transcriptional modules coupled with typical patterns of expression have been identified. Functional analysis reveals that virtually all enriched functions (gene ontologies, pathways) in these modules are shown to be related to metabolic processes, implying the importance of these modules in adverse effects under the administration of corticosteroids. Relevant putative transcriptional regulators (e.g. RXRF, FKHD, SP1F) are also predicted to provide another source of information towards better understanding the complexities of expression patterns and the underlying regulatory mechanisms of those modules.

Conclusions

We have proposed a framework to identify significant coexpressed clusters of genes across multiple conditions experimented from different microarray platforms, time-grids, and also tissues if applicable. Analysis on rich in vivo datasets of corticosteroid time-series yielded significant insights into the pharmacogenomic effects of corticosteroids, especially the relevance to metabolic side-effects. This has been illustrated through enriched metabolic functions in those transcriptional modules and the presence of GRE binding motifs in those enriched pathways, providing significant modules for further analysis on pharmacogenomic corticosteroid effects.

Sexually dimorphic actions of glucocorticoids provide a link to inflammatory diseases with gender differences in prevalence

Males and females show differences in the prevalence of many major diseases that have important inflammatory components to their etiology. These gender-specific diseases, which include autoimmune diseases, hepatocellular carcinoma, diabetes, and osteoporosis, are largely considered to reflect the actions of sex hormones on the susceptibility to inflammatory stimuli. However, inflammation reflects a balance between pro- and anti-inflammatory signals, and investigation of gender-specific responses to the latter has been neglected. Glucocorticoids are the primary physiological anti-inflammatory hormones in mammals, and synthetic derivatives of these hormones are prescribed as anti-inflammatory agents, irrespective of patient gender. We explored the possibility that sexually dimorphic actions of glucocorticoid regulation of gene expression may contribute to the dimorphic basis of inflammatory disease by evaluating the rat liver, a classic glucocorticoid-responsive organ. Surprisingly, glucocorticoid administration expanded the set of hepatic sexually dimorphic genes. Eight distinct patterns of glucocorticoid-regulated gene expression were identified, which included sex-specific genes. Our experiments also defined specific genes with altered expression in response to glucocorticoid treatment in both sexes, but in opposite directions. Pathway analysis identified sex-specific glucocorticoid-regulated gene expression in several canonical pathways involved in susceptibility to and progression of diseases with gender differences in prevalence. Moreover, a comparison of the number of genes involved in inflammatory disorders between sexes revealed 84 additional glucocorticoid-responsive genes in the male, suggesting that the anti-inflammatory actions of glucocorticoids are more effective in males. These gender-specific actions of glucocorticoids in liver were substantiated in vivo with a sepsis model of systemic inflammation.

The aryl hydrocarbon receptor pathway and the response to 3-methylcholanthrene are altered in the liver of adrenalectomized rats

The aryl hydrocarbon receptor (AHR) is activated by 3-methylcholanthrene (MC), a polycyclic aromatic hydrocarbon, and environmental contaminants, such as 2,3,7,8-tetrachlorodibenzo-p-dioxin. Adrenalectomized (ADX) rats have decreased hepatic AHR protein and lower levels of MC-induced CYP1B1 mRNA. To further characterize the effects of decreased AHR protein and the response to MC in ADX rats, we measured AHR-mediated responses in the liver of sham-operated (SHAM) and ADX rats, 6 and 54 h after MC treatment. CYP1A2 mRNA was suppressed by 46 to 60% 4 days after ADX in vehicle-treated animals. AHR mRNA was induced 4-fold 6 h after MC in SHAM rats, but no induction was observed in ADX rats. The MC-induced 7-ethoxyresorufin O-deethylation (EROD) activity in ADX rats was 35% of the activity in the MC-treated SHAM group at 6 h. At 54 h after treatment, the induction of EROD activity by MC was more pronounced in ADX rats than at 6 h. To assess the overall capacity for hepatic P450-mediated metabolism, we measured NADPH-cytochrome P450 oxidoreductase (POR) activity. POR activity was decreased by 50% after ADX. We have shown that the response to MC in ADX rats is suppressed for some, but not all, AHR-mediated responses and that reduced POR activity after ADX could contribute to a decreased capacity for P450-dependent metabolism. The current study contributes to our understanding of how adrenal-dependent factors modulate the AHR pathway and the response to MC in vivo.

NETWORKS, BIOLOGY AND SYSTEMS ENGINEERING: A CASE STUDY IN INFLAMMATION

Biological systems can be modeled as networks of interacting components across multiple scales. A central problem in computational systems biology is to identify those critical components and the rules that define their interactions and give rise to the emergent behavior of a host response. In this paper we will discuss two fundamental problems related to the construction of transcription factor networks and the identification of networks of functional modules describing disease progression. We focus on inflammation as a key physiological response of clinical and translational importance.

Glucocorticoid and adrenalectomy effects on the rat aryl hydrocarbon receptor pathway depend on the dosing regimen and post-surgical time

The aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor that mediates the effects of aromatic hydrocarbons, such as 2,3,7,8-tetrachlorodibenzo-p-dioxin and 3-methylcholanthrene (MC); the prototypical response is induction of drug-metabolizing enzymes. Factors that regulate AHR levels in vivo are poorly understood and it is also not clear how AHR levels affect aromatic hydrocarbon responsiveness. Our interest in pituitary-dependent regulation of AHR levels was prompted by two findings from our laboratory: (1) hypophysectomized rats have reduced hepatic levels of AHR protein; and (2) glucocorticoids increase AHR expression and aromatic hydrocarbon responsiveness in rodent hepatoma cells. To study whether adrenalectomy and glucocorticoids contribute to hormone-dependent regulation of the hepatic AHR pathway, male adrenalectomized (ADX) or SHAM-ADX rats were treated with dexamethasone (DEX) or vehicle. AHR protein was depleted by 50-60% at 4 days after ADX, but was not altered by DEX treatment. To assess whether the observed AHR depletion affected aromatic hydrocarbon responsiveness, the induction of hepatic cytochrome P450 1B1 (CYP1B1) mRNA by MC was measured as an AHR-mediated adaptive response. MC-induced hepatic CYP1B1 mRNA was reduced by 50% in ADX rats relative to SHAM-ADX. Exogenous glucocorticoid treatment (DEX - 1.5mg/kg) induced hepatic AHR nuclear translocator (ARNT) mRNA by up to 9-fold at 3 and 6h after dosing, with no corresponding change in ARNT protein levels. These data demonstrate that: (1) adrenal-dependent factors contribute to the physiological maintenance of hepatic AHR protein levels; (2) the depletion of hepatic AHR protein in ADX rats coincided with a diminished adaptive response to MC; and (3) exogenous glucocorticoid treatment increases hepatic ARNT mRNA levels regardless of adrenal status. This model is useful for studying the mechanisms of AHR and ARNT regulation and for further characterization of the impact of AHR protein depletion on the response to aromatic hydrocarbons in vivo.

In silico simulation of corticosteroids effect on an NFkB- dependent physicochemical model of systemic inflammation

BACKGROUND

During the onset of an inflammatory response signaling pathways are activated for "translating" extracellular signals into intracellular responses converging to the activation of nuclear factor (NF)-kB, a central transcription factor in driving the inflammatory response. An inadequate control of its transcriptional activity is associated with the culmination of a hyper-inflammatory response making it a desired therapeutic target. Predicated upon the nature of the response, a systems level analysis might provide rational leads for the development of strategies that promote the resolution of the response.

METHODOLOGY AND FINDINGS

A physicochemical host response model is proposed to integrate biological information in the form of kinetic rules and signaling cascades with pharmacokinetic models of drug action for the modulation of the response. The unifying hypothesis is that the response is triggered by the activation of the NFkB signaling module and corticosteroids serve as a template for assessing anti-inflammatory strategies. The proposed in silico model is evaluated through its ability to predict and modulate uncontrolled responses. The pre-exposure of the system to hypercortisolemia, i.e. 6 hr before or simultaneously with the infectious challenge "reprograms" the dynamics of the host towards a balanced inflammatory response. However, if such an intervention occurs long before the inflammatory insult a symptomatic effect is observed instead of a protective relief while a steroid infusion after inducing inflammation requires much higher drug doses.

CONCLUSIONS AND SIGNIFICANCE

We propose a reversed engineered inflammation model that seeks to describe how the system responds to a multitude of external signals. Timing of intervention and dosage regimes appears to be key determinants for the protective or symptomatic effect of exogenous corticosteroids. Such results lie in qualitative agreement with in vivo human studies exposed both to LPS and corticosteroids under various time intervals thus improving our understanding of how interacting modules generate a behavior.

Circadian variations in rat liver gene expression: relationships to drug actions

Chronopharmacology is an important but under-explored aspect of therapeutics. Rhythmic variations in biological processes can influence drug action, including pharmacodynamic responses, due to circadian variations in the availability or functioning of drug targets. We hypothesized that global gene expression analysis can be useful in the identification of circadian-regulated genes involved in drug action. Circadian variations in gene expression in rat liver were explored using Affymetrix gene arrays. A rich time series involving animals analyzed at 18 time points within the 24-h cycle was generated. Of the more than 15,000 probe sets on these arrays, 265 exhibited oscillations with a 24-h frequency. Cluster analysis yielded five distinct circadian clusters, with approximately two thirds of the transcripts reaching maximal expression during the dark/active period of the animal. Of the 265 probe sets, 107 were identified as having potential therapeutic importance. The expression levels of clock genes were also investigated in this study. Five clock genes exhibited circadian variation in the liver, and data suggest that these genes may also be regulated by corticosteroids.

Pharmacodynamic/pharmacogenomic modeling of insulin resistance genes in rat muscle after methylprednisolone treatment: exploring regulatory signaling cascades

Corticosteroids (CS) effects on insulin resistance related genes in rat skeletal muscle were studied. In our acute study, adrenalectomized (ADX) rats were given single doses of 50 mg/kg methylprednisolone (MPL) intravenously. In our chronic study, ADX rats were implanted with Alzet mini-pumps giving zero-order release rates of 0.3 mg/kg/h MPL and sacrificed at various times up to 7 days. Total RNA was extracted from gastrocnemius muscles and hybridized to Affymetrix GeneChips. Data mining and literature searches identified 6 insulin resistance related genes which exhibited complex regulatory pathways. Insulin receptor substrate-1 (IRS-1), uncoupling protein 3 (UCP3), pyruvate dehydrogenase kinase isoenzyme 4 (PDK4), fatty acid translocase (FAT) and glycerol-3-phosphate acyltransferase (GPAT) dynamic profiles were modeled with mutual effects by calculated nuclear drug-receptor complex (DR(N)) and transcription factors. The oscillatory feature of endothelin-1 (ET-1) expression was depicted by a negative feedback loop. These integrated models provide testable quantitative hypotheses for these regulatory cascades.

Mathematical modeling of corticosteroid pharmacogenomics in rat muscle following acute and chronic methylprednisolone dosing

The pharmacogenomic effects of a corticosteroid (CS) were assessed in rat skeletal muscle using microarrays. Adrenalectomized (ADX) rats were treated with methylprednisolone (MPL) by either 50 mg/kg intravenous injection or 7-day 0.3 mg/kg/h infusion through subcutaneously implanted pumps. RNAs extracted from individual rat muscles were hybridized to Affymetrix Rat Genome Genechips. Data mining yielded 653 and 2316 CS-responsive probe sets following MPL bolus and infusion treatments. Of these, 196 genes were controlled by MPL under both dosing conditions. Cluster analysis revealed that 124 probe sets exhibited three typical expression dynamic profiles following acute dosing. Cluster A consisted of up-regulated probe sets which were grouped into five subclusters each exhibiting unique temporal patterns during the infusion. Cluster B comprised down-regulated probe sets which were divided into two subclusters with distinct dynamics during the infusion. Cluster C probe sets exhibited delayed down-regulation under both bolus and infusion conditions. Among those, 104 probe sets were further grouped into subclusters based on their profiles following chronic MPL dosing. Several mathematical models were proposed and adequately captured the temporal patterns for each subcluster. Multiple types of dosing regimens are needed to resolve common determinants of gene regulation as chronic exposure results in unexpected differences in gene expression compared to acute dosing. Pharmacokinetic/pharmacodynamic (PK/PD) modeling provides a quantitative tool for elucidating the complexities of CS pharmacogenomics in skeletal muscle.

Pharmacodynamic modeling of acute and chronic effects of methylprednisolone on hepatic urea cycle genes in rats

Corticosteroids (CS) regulate many enzymes at both mRNA and protein levels. This study used microarrays to broadly assess regulation of various genes related to the greater urea cycle and employs pharmacokinetic/pharmacodynamic (PK/PD) modeling to quantitatively analyze and compare the temporal profiles of these genes during acute and chronic exposure to methylprednisolone (MPL). One group of adrenalectomized male Wistar rats received an intravenous bolus dose (50 mg/kg) of MPL, whereas a second group received MPL by a subcutaneous infusion (Alzet osmotic pumps) at a rate of 0.3 mg/kg/hr for seven days. The rats were sacrificed at various time points over 72 hours (acute) or 168 hours (chronic) and livers were harvested. Total RNA was extracted and Affymetrix gene chips (RG_U34A for acute and RAE 230A for chronic) were used to identify genes regulated by CS. Besides five primary urea cycle enzymes, many other genes related to the urea cycle showed substantial changes in mRNA expression. Some genes that were simply up- or down-regulated after acute MPL showed complex biphasic patterns upon chronic infusion indicating involvement of secondary regulation. For the simplest patterns, indirect response models were used to describe the nuclear steroid-bound receptor mediated increase or decrease in gene transcription (e.g. tyrosine aminotransferase, glucocorticoid receptor). For the biphasic profiles, involvement of a secondary biosignal was assumed (e.g. ornithine decarboxylase, CCAAT/enhancer binding protein) and more complex models were derived. Microarrays were used successfully to explore CS effects on various urea cycle enzyme genes. PD models presented in this report describe testable hypotheses regarding molecular mechanisms and quantitatively characterize the direct or indirect regulation of various genes by CS.

Pharmacodynamic Modeling of Acute and Chronic Effects of Methylprednisolone on Hepatic Urea Cycle Genes in Rats

Corticosteroids (CS) regulate many enzymes at both mRNA and protein levels. This study used microarrays to broadly assess regulation of various genes related to the greater urea cycle and employs pharmacokinetic/pharmacodynamic (PK/PD) modeling to quantitatively analyze and compare the temporal profiles of these genes during acute and chronic exposure to methylprednisolone (MPL). One group of adrenalectomized male Wistar rats received an intravenous bolus dose (50 mg/kg) of MPL, whereas a second group received MPL by a subcutaneous infusion (Alzet osmotic pumps) at a rate of 0.3 mg/kg/hr for seven days. The rats were sacrificed at various time points over 72 hours (acute) or 168 hours (chronic) and livers were harvested. Total RNA was extracted and Affymetrix® gene chips (RGU34A for acute and RAE 230A for chronic) were used to identify genes regulated by CS. Besides five primary urea cycle enzymes, many other genes related to the urea cycle showed substantial changes in mRNA expression. Some genes that were simply up- or down-regulated after acute MPL showed complex biphasic patterns upon chronic infusion indicating involvement of secondary regulation. For the simplest patterns, indirect response models were used to describe the nuclear steroid-bound receptor mediated increase or decrease in gene transcription (e.g. tyrosine aminotransferase, glucocorticoid receptor). For the biphasic profiles, involvement of a secondary biosignal was assumed (e.g. ornithine decarboxylase, CCAAT/enhancer binding protein) and more complex models were derived. Microarrays were used successfully to explore CS effects on various urea cycle enzyme genes. PD models presented in this report describe testable hypotheses regarding molecular mechanisms and quantitatively characterize the direct or indirect regulation of various genes by CS.

Pharmacokinetics of methylprednisolone after intravenous and intramuscular administration in rats

Methylprednisolone (MPL) pharmacokinetics was examined in adrenalectomized (ADX) and normal rats to assess the feasibility of intramuscular (i.m.) dosing for use in pharmacodynamic studies. Several study phases were pursued. Parallel group studies were performed in normal and ADX rats given 50 mg/kg MPL (i.v. or i.m.) and blood samples were collected up to 6 h. Data from studies where normal rats were dosed with 50 mg/kg MPL i.m. and killed over either 6 or 96 h were combined to determine muscle site and plasma MPL concentrations. Lastly, ADX rats were dosed with 50 mg/kg MPL i.m. and killed over 18 h to assess hepatic tyrosine aminotransferase (TAT) dynamics. MPL exhibited bi-exponential kinetics after i.v. dosing with a terminal slope of 2.1 h(-1). The i.m. drug was absorbed slowly with two first-order absorption rate constants, 1.26 and 0.219 h(-1) indicating flip-flop kinetics with overall 50% bioavailability. The kinetics of MPL at the injection site exhibited slow, dual absorption rates. Although i.m. MPL showed lower bioavailability compared with other corticosteroids in rats, TAT dynamics revealed similar i.m. and i.v. response profiles. The more convenient intramuscular dosing can replace the i.v. route without causing marked differences in pharmacodynamics.

Anti-inflammatory functions of glucocorticoid-induced genes

There is a broad consensus that glucocorticoids (GCs) exert anti-inflammatory effects largely by inhibiting the function of nuclear factor kappaB (NFkappaB) and consequently the transcription of pro-inflammatory genes. In contrast, side effects are thought to be largely dependent on GC-induced gene expression. Biochemical and genetic evidence suggests that the positive and negative effects of GCs on transcription can be uncoupled from one another. Hence, novel GC-related drugs that mediate inhibition of NFkappaB but do not activate gene expression are predicted to retain therapeutic effects but cause fewer or less severe side effects. Here, we critically re-examine the evidence in favor of the consensus, binary model of GC action and discuss conflicting evidence, which suggests that anti-inflammatory actions of GCs depend on the induction of anti-inflammatory mediators. We propose an alternative model, in which GCs exert anti-inflammatory effects at both transcriptional and post-transcriptional levels, both by activating and inhibiting expression of target genes. The implications of such a model in the search for safer anti-inflammatory drugs are discussed.

Microarray analysis of the temporal response of skeletal muscle to methylprednisolone: comparative analysis of two dosing regimens

The transcriptional response of skeletal muscle to chronic corticosteroid exposure was examined over 168 h and compared with the response profiles observed following a single dose of corticosteroid. Male adrenalectomized Wistar rats were given a constant-rate infusion of 0.3 mg x kg(-1) x h(-1) methylprednisolone for up to 7 days via subcutaneously implanted minipumps. Four control and forty drug-treated animals were killed at ten different time points during infusion. Liver total RNAs were hybridized to 44 individual Affymetrix REA230A gene chips. Previously, we described a filtration approach for identifying genes of interest in microarray data sets developed from tissues of rats treated with methylprednisolone (MPL) following acute dosing. Here, a similar approach involving a series of three filters was applied sequentially to identify genes of interest. These filters were designed to eliminate probe sets that were not expressed in the tissue, not regulated by the drug, or did not meet defined quality control standards. Filtering eliminated 86% of probe sets, leaving a remainder of 2,316 for further consideration. In a previous study, 653 probe sets were identified as MPL regulated following administration of a single (acute) dose of the drug. Comparison of the two data sets yielded 196 genes identified as regulated by MPL in both dosing regimens. Because of receptor downregulation, it was predicted that genes regulated by receptor-glucocorticoid response element interactions would exhibit tolerance in chronic profiles. However, many genes did not exhibit steroid tolerance, indicating that present perspectives on the mechanism of glucocorticoid action cannot entirely explain all temporal profiles.

A microarray analysis of the temporal response of liver to methylprednisolone: a comparative analysis of two dosing regimens

Microarray analyses were performed on livers from adrenalectomized male Wistar rats chronically infused with methylprednisolone (MPL) (0.3 mg/kg.h) using Alzet mini-osmotic pumps for periods ranging from 6 h to 7 d. Four control and 40 drug-treated animals were killed at 10 different times during drug infusion. Total RNA preparations from the livers of these animals were hybridized to 44 individual Affymetrix REA230A gene chips, generating data for 15,967 different probe sets for each chip. A series of three filters were applied sequentially. These filters were designed to eliminate probe sets that were not expressed in the tissue, were not regulated by the drug, or did not meet defined quality control standards. These filters eliminated 13,978 probe sets (87.5%) leaving a remainder of 1989 probe sets for further consideration. We previously described a similar dataset obtained from animals after administration of a single dose of MPL (50 mg/kg given iv). That study involved 16 time points over a 72-h period. A similar filtering schema applied to the single-bolus-dose dataset identified 1519 probe sets as being regulated by MPL. A comparison of datasets from the two different dosing regimens identified 358 genes that were regulated by MPL in response to both dosing regimens. Regulated genes were grouped into 13 categories, mainly on gene product function. The temporal profiles of these common genes were subjected to detailed scrutiny. Examination of temporal profiles demonstrates that current perspectives on the mechanism of glucocorticoid action cannot entirely explain the temporal profiles of these regulated genes.

Applications of quantitative pharmacodynamic effect markers in drug target identification and therapy development

Genome-wide transcriptional profiling is now feasible, and profiling of the proteome, although technically challenging, is advancing rapidly. Expression profiling provides a tool to accelerate discovery in a broad range of sciences, but its greatest impact on human health may be on the process of drug discovery and therapy development, and investigation of the functional networks underlying drug responses of diseased and normal tissue. For anticancer agents in particular, antitumor effects and toxicities to critical normal tissues may rest in a delicate balance that is governed by complex pharmacokinetic (PK) and pharmacodynamic (PD) inter-relationships. Recent advances in the development of mechanistic computational PD models promise to promote an understanding of these interrelationships, provided suitable quantitative PD effect markers will be identified. Here we describe both advances toward the unsupervised application of PD models to complex expression profiling datasets, as well as approaches to address the technical requirement of these models for quantitative assessment of protein expression levels. Together, these models and analytical approaches may contribute to the rational design of more effective pharmacotherapies.

Application of scaling factors in simultaneous modeling of microarray data from diverse chips

PURPOSE

Microarrays have been utilized in many biological, physiological and pharmacological studies as a high-throughput genomic technique. Several generations of Affymetrix GeneChip microarrays are widely used in gene expression studies. However, differences in intensities of signals for different probe sets that represent the same gene on various types of Affymetrix chips make comparison of datasets complicated.

MATERIALS AND METHODS

A power coefficient scaling factor was applied in the pharmacokinetic/pharmacodynamic (PK/PD) modeling to account for differences in probe set sensitivities (i.e., signal intensities). Microarray data from muscle and liver following methylprednisolone 50 mg/kg i.v. bolus and 0.3 mg/kg/h infusion regimens were taken as an exemplar.

RESULTS

The scaling factor applied to the pharmacodynamic output function was used to solve the problem of intensity differences between probe sets. This approach yielded consistent pharmacodynamic parameters for the applied models.

CONCLUSIONS

Modeling of pharmacodynamic/pharmacogenomic (PD/PG) data from diverse chips should be performed with caution due to differential probe set intensities. In such circumstances, a power scaling factor can be applied in the modeling.

Platinum drug effects on the expression of genes in the polyamine pathway: time-course and concentration-effect analysis based on Affymetrix gene expression profiling of A2780 ovarian carcinoma cells

PURPOSE

As a follow-up to our previous findings that platinum drugs induce a key enzyme in polyamine catabolism, gene expression profiling and mathematical modeling were used to define the effects of cisplatin and oxaliplatin on the expression of polyamine metabolic pathway genes in A2780 human ovarian carcinoma cells.

METHODS

Time-course and concentration-effect experiments were each carried out with cisplatin or oxaliplatin in two separate experiments and cells subjected to gene expression profiling using Affymetrix array technology. Time-course data were modeled using exponential increase and decrease models. Concentration-effect data were modeled using a four parameter Hill model.

RESULTS

Gene expression profiling of human ovarian carcinoma A2780 cells after exposure to either cisplatin or oxaliplatin indicates that the expression of several genes involved in polyamine pathway is affected by the platinum drugs. Mathematical/Statistical modeling of the data from time-course and concentration-effect experiments of gene expression from nine polyamine pathway genes represented on the HGU95Av2 chip, indicates that three biosynthetic pathway genes (SAMDC, ODC1 and SRM) are down-regulated and one catabolic pathway gene (SSAT) is up-regulated. Expression changes were similar for different probesets for a given gene on the array. Studies on the induction of SSAT by platinum drugs suggested by the Affymetrix data have been previously validated from this laboratory (Hector et al. in Mol Cancer Ther 3:813-822, 2004). Here, the effects of oxaliplatin exposure on SAMDC and ODC observed by Affymetix are validated with real time QRT-PCR.

CONCLUSION

The data indicate a concerted effect of platinum drugs on the polyamine metabolic pathway with down-regulation in the expression of several enzyme genes involved in biosynthesis and many-fold up-regulation in expression of SSAT, an acetylating enzyme gene that is critically involved in polyamine catabolism and export.

Corticosteroid-regulated genes in rat kidney: mining time series array data

Kidney is a major target for adverse effects associated with corticosteroids. A microarray dataset was generated to examine changes in gene expression in rat kidney in response to methylprednisolone. Four control and 48 drug-treated animals were killed at 16 times after drug administration. Kidney RNA was used to query 52 individual Affymetrix chips, generating data for 15,967 different probe sets for each chip. Mining techniques applicable to time series data that identify drug-regulated changes in gene expression were applied. Four sequential filters eliminated probe sets that were not expressed in the tissue, not regulated by drug, or did not meet defined quality control standards. These filters eliminated 14,890 probe sets (94%) from further consideration. Application of judiciously chosen filters is an effective tool for data mining of time series datasets. The remaining data can then be further analyzed by clustering and mathematical modeling. Initial analysis of this filtered dataset identified a group of genes whose pattern of regulation was highly correlated with prototype corticosteroid enhanced genes. Twenty genes in this group, as well as selected genes exhibiting either downregulation or no regulation, were analyzed for 5' GRE half-sites conserved across species. In general, the results support the hypothesis that the existence of conserved DNA binding sites can serve as an important adjunct to purely analytic approaches to clustering genes into groups with common mechanisms of regulation. This dataset, as well as similar datasets on liver and muscle, are available online in a format amenable to further analysis by others.