Examination of Mechanisms of Hepatotoxicity of Anti-diabetic PPARγ Agonists Using Applied Biosystems Rat Whole Genome Microarrays
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1 Examination of Mechanisms of Hepatotoxicity of Anti-diabetic PPARγ Agonists Using Applied Biosystems Rat Whole Genome Microarrays Lu Zhang b, Lei Guo a, Leming Shi a, Weida Tong a, Yongming Sun b, Gary P. Schroth b, Eugene Herman a and Yvonne Dragan a Collaboration study between FDA/NCTR a and Applied Biosystems b
2 Type 2 Diabetes and PPARγ Type 2 Diabetes: Major health problem in the US and worldwide Insulin resistance PPARγ: (Peroxisome Proliferation Activated Receptor γ) Ligand-activated transcription factor Major target for diabetic drugs Three approved by FDA: Troglitazone (Rezulin) Rosiglitazone (Avandia) Pioglitazone (Actos) Insulin sensitizing
3 Cellular Mechanism of Action of PPARγ Agonists PPARγ agonists Glucose Uptake and Utilization PPARγ RXR Transcription of downstream genes Lipid Synthesis Adipogenesis
4 PPARγ agonist: Thiazolidinedione (TZDs) Troglitazone (Rezulin): Marketed by Pfizer in 1997, withdrawn in 2000 because of severe liver toxicity with unknown mechanism Rosiglitazone (Avandia) Marketed by GSK in 1999 Pioglitazone (Actos) Marketed by Takeda and Eli Lilly in 1999 Ciglitazone Drug candidate, Failed in Phase III trials
5 Rat Whole Genome Survey Array genes represented More than 10,000 novel genes
6 Rat array target source 27,088 genes 26,857 total probes 26,847 current probes Celera and public 10,887 (40.2%) Celera only 15,990 (59.0%) Public only 211 (0.8%) RR1B1
7 Experimental design I Samples from FDA: 36 total RNA samples from Rat hepatocyte primary cultures Treatment group: Four glitazones: Troglitazone (Tro) Rosiglitazone (Rosi) Pioglitazone (Pio) Ciglitazone (Cig) Two controls: JTT-501: Dual agonist for both PPARγ and PPARα DMSO Two time points: 6 and 10 hours One dosage: 30 um Three biological replicates
8 DMSO Experimental design II Tro Cig Rosi Pio JTT Primary Hepatocyte Animal A, B, C total RNA total RNA total RNA total RNA total RNA total RNA RT-IVT RT-IVT crna1 crna2 crna1 crna2 RT-IVT RT-IVT RT-IVT RT-IVT -crna pooled -crna pooled -crna -crna -crna -crna Within each animal and time group
9 Data Analysis for Differential Gene Expression 2-way ANOVA Analysis Treatment vs. Time Testing mixed effect of treatment and time* Fold change and Welch t test Each compound vs DMSO gene signatures Biological Interpretation of Results
10 2 Way ANOVA Analysis Data preparation Quantile-Quantile Normalization across arrays Per gene normalized to median P value < 0.05 with Benjamini-Hochberg FDR 2 way ANOVA (treatment vs. time) 46 Arrays: DMSO 5, Tro 6, Cig 3, Pio 3, Rosi 3, JTT 3 for both time points
11 Number of Differentially Expressed Genes by 2 way ANOVA ANOVA Gene Numbers Treatment 300 Time* 3258 Cutoff: P value < 0.05 with BH FDR * Time series have huge numbers of gene changed, apoptotic effects of cultured time for primary hepatocytes ** Gene Numbers for mixed effect of time vs. treatment is zero because of the big change by time alone
12 Hierarchical Clustering based on 2 Way ANOVA 300 Gene list Cig Tro Cig DMSO JTT Pio/Rosi
13 Compound Specific Clusters: Tro and Cig upregulated for both time points Cig Tro Cig DMSO JTT Pio/Rosi
14 Compound Specific Clusters: Tro and Cig up-regulated for 6 hour Cig Tro Cig DMSOJTT Pio/Rosi
15 Compound Specific clusters: Tro and Cig down-regulated Cig TroCig DMSO JTT Pio/Rosi
16 Compound Specific clusters: Pio/Rosi, JTT Cig TroCig DMSO JTT Pio/Rosi
17 Biological Interpretation Pathway Analysis Jubilant Pathway Genes in the pathway Overlapping genes Overlapping p-value Insulin Signaling Pathway NGF Signaling Pathway CDK5 Mediated Pathway PPAR Mediated Pathway TNF Signaling Pathway LDL Signaling Pathway PPARγ Mediated Pathway Jubilant Physiology or Disease Genes in the group Overlapping genes Overlapping p-value Diabetes Type II Obesity Use 2 way ANOVA 300 gene list, p value cutoff <0.05
18 Insulin signaling pathway 5/300
19 LDL and TNF signaling pathway 3/300
20 PPAR signaling pathway 2/300
21 KEGG MAPK signaling pathway 9/300
22 KEGG MAPK signaling pathway 9/300 Tro and Cig up regulated, while the other three remains unchanged
23 KEGG Fatty Acid Metabolism 4/300 JTT and/or Pio, Rosi up regulated, while Tro and Cig Remain the same
24 Fold Change and Welch t test Data preparation Cross arrays: QQ Normalization for 51 arrays DMSO 5, Tro 6, Cig 4, Pio 4, Rosi 4, JTT 4 for 6 hr, DMSO 6, Tro 6, Cig 3, Pio 3, Rosi 3, JTT 3 for 10hr Cross genes: Normalized to median P value cutoff: Fold change calculated using raw data, cutoff
25 Number of Differentially Expressed Genes by t test and fold changes Compound vs. P value cutoff Fold Changes P < 0.002& DMSO (6 hr) FC > or < 1.7 Troglitazone Ciglitazone Pioglitazone Rosiglitazone JTT Total list 135 Total number of genes used in clustering: 135 P < and Fold change ><1.7
26 Hierarchical Clustering based on t test and Fold change 135 Gene list 6 hour only Cig Tro JTT DMSO Pio Rosi
27 Potential Compound Signatures Cig Signature Tro Signature Rosi Signature
28 Summary Microarray results indicate that troglitazone and ciglitazone can be distinguished from pioglitazone and rosiglitazone based upon the expression profiles. Genes involved in the PPARγ and Insulin metabolism pathways are identified in these profiles. These profiles can be used to better understand the mechanism of liver toxicity in these compounds. Compound specific signatures have been identified for all the treatments. These signatures may be useful for predicting the efficacy of other TZD compounds.
29 Induction of Cytotoxicity in Primary Rat Hepatocytes and Human HepG2 Cells by Selected PPARγ Agonists SOT Poster session: #1912 Liver II, March 9, 2005 from 1:30 pm to 4:30 pm Presenter: Dr. Lei Guo, FDA/NCTR
30 Acknowledgement FDA/NCTR group: Dr. Lei Guo a Dr. Leming Shi b Dr. Weida Tong b Dr. Eugene Herman c Dr. Yvonne Dragan a a Center for Hepatotoxicity b Center for Toxicoinformatics, Division of Systems Toxicology, National Center for Toxicological Research (NCTR) US Food and Drug Administration Jefferson, AR c Center for Drug Evaluation and Review Division Applied Pharmacology Research US Food and Drug Administration Silver Springs, MD Applied Biosystems: Dr. Lu Zhang Dr. Gary Schroth & Arrays Product Development Group Dr. Yongming Sun & Data Analysis Group Dr. Jack Zhai & Marketing Group Applied Biosystems Foster City, CA 94404
31 Licensing & Trademarks For Research Use Only. Not for use in diagnostic procedures. The PCR process and 5' nuclease process are covered by patents owned by Roche Molecular Systems, Inc. and F. Hoffmann-La Roche Ltd. Applied Biosystems, Celera, and ABI PRISM are registered trademarks and AB (Design), Applera, iscience (design), Celera Discovery System, and PANTHER are trademarks of Applera Corporation or its subsidiaries in the US and/or certain other countries. TaqMan is a registered trademark of Roche Molecular Systems, Inc. All other trademarks are the sole property of their respective owners Applied Biosystems. All rights reserved.
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