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Effects of ritonavir on adipocyte gene expression: evidence for a stress-related response.

ABSTRACT: To understand the molecular mechanisms underlying the development of dyslipidemia and lipodystrophy that occurs after administration of aspartic acid protease inhibitors, we examined transcriptional profiles using cDNA microarrays in 3T3-L1 adipocytes exposed to 10 micromol/l ritonavir for 2-21 days. The expression levels of approximately 12,000 transcripts were assessed using the MgU74Av2 mouse microarray chip. Ritonavir altered gene expression of inflammatory cytokines, stress response genes localized to endoplasmic reticulum, oxidative stress genes, apoptosis-related genes, and expression of genes involved in cell adhesion and extracellular matrix remodeling. Microarray analysis also identified a novel gene downregulated by ritonavir, Cidea, whose expression levels may affect free-fatty acid metabolism. These changes suggest a unique, stress-related pattern in adipocytes induced by chronic exposure to the protease inhibitor, ritonavir.

SUBMITTER: Adler-Wailes DC

PROVIDER: S-EPMC2614385 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature

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Effects of ritonavir on adipocyte gene expression: evidence for a stress-related response.

Adler-Wailes Diane C DC Guiney Evan L EL Koo Jashin J Yanovski Jack A JA

Obesity (Silver Spring, Md.) 20080717 10

To understand the molecular mechanisms underlying the development of dyslipidemia and lipodystrophy that occurs after administration of aspartic acid protease inhibitors, we examined transcriptional profiles using cDNA microarrays in 3T3-L1 adipocytes exposed to 10 micromol/l ritonavir for 2-21 days. The expression levels of approximately 12,000 transcripts were assessed using the MgU74Av2 mouse microarray chip. Ritonavir altered gene expression of inflammatory cytokines, stress response genes l ...[more]

PMID: 18719645

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Project description:BackgroundEstrogen receptors alpha (ER) are implicated in many types of female cancers, and are the common target for anti-cancer therapy using selective estrogen receptor modulators (SERMs, such as tamoxifen). However, cell-type specific and patient-to-patient variability in response to SERMs (from suppression to stimulation of cancer growth), as well as frequent emergence of drug resistance, represents a serious problem. The molecular processes behind mixed effects of SERMs remain poorly understood, and this strongly motivates application of systems approaches. In this work, we aimed to establish a mathematical model of ER-dependent gene expression to explore potential mechanisms underlying the variable actions of SERMs.ResultsWe developed an equilibrium model of ER binding with 17β-estradiol, tamoxifen and DNA, and linked it to a simple ODE model of ER-induced gene expression. The model was parameterised on the broad range of literature available experimental data, and provided a plausible mechanistic explanation for the dual agonism/antagonism action of tamoxifen in the reference cell line used for model calibration. To extend our conclusions to other cell types we ran global sensitivity analysis and explored model behaviour in the wide range of biologically plausible parameter values, including those found in cancer cells. Our findings suggest that transcriptional response to tamoxifen is controlled in a complex non-linear way by several key parameters, including ER expression level, hormone concentration, amount of ER-responsive genes and the capacity of ER-tamoxifen complexes to stimulate transcription (e.g. by recruiting co-regulators of transcription). The model revealed non-monotonic dependence of ER-induced transcriptional response on the expression level of ER, that was confirmed experimentally in four variants of the MCF-7 breast cancer cell line.ConclusionsWe established a minimal mechanistic model of ER-dependent gene expression, that predicts complex non-linear effects in transcriptional response to tamoxifen in the broad range of biologically plausible parameter values. Our findings suggest that the outcome of a SERM's action is defined by several key components of cellular micro-environment, that may contribute to cell-type-specific effects of SERMs and justify the need for the development of combinatorial biomarkers for more accurate prediction of the efficacy of SERMs in specific cell types.

Project description:Chromatin accessibility and gene expression in relevant cell contexts can guide identification of regulatory elements and mechanisms at genome-wide association study (GWAS) loci. To identify regulatory elements that display differential activity across adipocyte differentiation, we performed ATAC-seq and RNA-seq in a human cell model of preadipocytes and adipocytes at days 4 and 14 of differentiation. For comparison, we created a consensus map of ATAC-seq peaks in 11 human subcutaneous adipose tissue samples. We identified 58,387 context-dependent chromatin accessibility peaks and 3,090 context-dependent genes between all timepoint comparisons (log2 fold change>1, FDR<5%) with 15,919 adipocyte- and 18,244 preadipocyte-dependent peaks. Adipocyte-dependent peaks showed increased overlap (60.1%) with Roadmap Epigenomics adipocyte nuclei enhancers compared to preadipocyte-dependent peaks (11.5%). We linked context-dependent peaks to genes based on adipocyte promoter capture Hi-C data, overlap with adipose eQTL variants, and context-dependent gene expression. Of 16,167 context-dependent peaks linked to a gene, 5,145 were linked by two or more strategies to 1,670 genes. Among GWAS loci for cardiometabolic traits, adipocyte-dependent peaks, but not preadipocyte-dependent peaks, showed significant enrichment (LD score regression P<0.005) for waist-to-hip ratio and modest enrichment (P < 0.05) for HDL-cholesterol. We identified 659 peaks linked to 503 genes by two or more approaches and overlapping a GWAS signal, suggesting a regulatory mechanism at these loci. To identify variants that may alter chromatin accessibility between timepoints, we identified 582 variants in 454 context-dependent peaks that demonstrated allelic imbalance in accessibility (FDR<5%), of which 55 peaks also overlapped GWAS variants. At one GWAS locus for palmitoleic acid, rs603424 was located in an adipocyte-dependent peak linked to SCD and exhibited allelic differences in transcriptional activity in adipocytes (P = 0.003) but not preadipocytes (P = 0.09). These results demonstrate that context-dependent peaks and genes can guide discovery of regulatory variants at GWAS loci and aid identification of regulatory mechanisms.

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Effects of ritonavir on adipocyte gene expression: evidence for a stress-related response.

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Effects of ritonavir on adipocyte gene expression: evidence for a stress-related response.

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