SABIDA - New biomarker identification tool

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1 SABIDA - New biomarker identification tool Case study: Identification of safety biomarkers by integrating toxicogenomics datasets with biological networks (Merck Serono) Phil Hewith, PhD, Merck Serono Dragana Mitic, PhD, CCNet

2 Agenda: I. Relevance and advantages of safety biomarkers in tox assessment II. SABIDA- new safety biomarkers database III. Benchmarking the biomarker discovery tool IV.Experimental validation of the biomarker discovery tool using model nephrotoxic compounds

3 Agenda: I. Relevance and advantages of safety biomarkers in tox assessment II. SABIDA- new safety biomarkers database III. Benchmarking the biomarker discovery tool IV.Experimental validation of the biomarker discovery tool using model nephrotoxic compounds

4 Traditional animal models not always predictive of toxicity in humans 1. Therefore need new / better non clinical safety assays (Biomarkers)? 2. Potential to speed up non-clinical safety 3. Increased understanding of toxicity mechanisms Better our ability to predict toxicity Better our ability to exclude it Best hope for improved productivity 4. Early translational information for early clinical safety 5. Earlier decision making, investment risk reduction and promise of less late phase failures

5 Translational safety biomarkers Biomarker: a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention Translational Biomarker: a biomarker that can be applied in both a preclinical and clinical setting Safety Biomarker: a biomarker that reports a toxicological effect of a drug on an in vitro or in vivo system

6 Aim of the study To benchmark the new tool and identify candidate safety biomarkers for multiple organs by interrogating several hundred toxicogenomics datasets both in-house generated by Merck and all publically available datasets Additionally, raw transcriptomics datasets from the EU PredTox and Japanese TG-GATEs projects were assessed Novel Database 2000 unique toxicity gene signatures With direct links to their original studies 400 studies with links to original papers 300 compounds Gene signatures for 12 endpoints: 50 man years of expert interpretation and collection of signatures of disregulated genes identified as significant by the original study authors Cardiotoxicity Embryotoxicity Genotoxicity Hemotoxicity Hepatotoxicity Immunotoxicity Nephrotoxicity Neurotoxicity Reproductive toxicity Skin toxicity Teratotoxcicity

7 PubMed TG-GATES PredTox

8 PubMed TG-GATES PredTox Biomarker Identification

9 Defining biomarkers from gene expression datasets: A novel method for prioritization of biomarker candidates which uses a combination of scores Biomarkers ranked by a combination of scores: 1. presence of the datasets where biomarkers were sought (e.g. nephrotoxicity) 2. absence in control datasets (e.g. other toxicities) 3. network centrality within the dataset 4. previously observed presence of the protein coded by the gene in urine or blood samples.

10 Access the established and predicted biomarkers Selection criteria: 12 toxic endpoints 4 species In Vivo/In Vitro studies Up-regulated or downregulated in dataset Single/Repeated dose

11 Identify biomarkers by analyzing your genes

12 Identify biomarkers by analyzing your genes

13 Identify biomarkers by analyzing your genes

14 2000 signatures 400 publications 300 chemical compounds expression values Key features of Sabida Data from in vitro and in vivo experiments, single or repeated dose Organ, pathology or gene search Comparison of your signatures from gene expression, RNAseq or Proteomics data with more than 2000 annotated signatures Fast access to literature information related to any results you obtain

15 Aim of the study To benchmark the new tool and identify candidate safety biomarkers for multiple organs by interrogating several hundred toxicogenomics datasets both in-house generated by Merck and all publically available datasets Additionally, raw transcriptomics datasets from the EU PredTox and Japanese TG-GATEs projects were assessed Novel Database 2000 unique toxicity gene signatures With direct links to their original studies 400 studies with links to original papers 300 compounds Gene signatures for 12 endpoints: 50 man years of expert interpretation and collection of signatures of disregulated genes identified as significant by the original study authors Cardiotoxicity Embryotoxicity Genotoxicity Hemotoxicity Hepatotoxicity Immunotoxicity Nephrotoxicity Neurotoxicity Reproductive toxicity Skin toxicity Teratotoxcicity

16 I Benchmarking the new biomarker discovery tool We looked for genes that appear in multiple studies specific to a particular pathology of interest and which rarely appear in studies related to other pathologies. To date 9 urinary rat renal biomarkers have been qualified by the relevant safety and nephrotoxicity working groups Research focused on gene expression profiling both in vivo (rat) and in vitro (rat and human cells) in treatment with several model nephrotoxic compounds under different conditions Benchmark results: 5 out of 9 known biomarkers within the top 20 ranked (CD14, CD44, CYR61, HAVCR1 and LCN2) remaining 4 known biomarkers were identified among the top 50 Majority of 40 genes identified at Merck also listed

17 II Experimental validation of the biomarker discovery tool using model nephrotoxic compounds 2000

18 The Kidney a major target organ The kidney is uniquely susceptible to toxicant injury due to: High rate of blood flow Concentrating mechanisms Transport systems allowing accumulation of toxicants Bioactivation to toxic metabolites The Predictive Safety Testing Consortium selected 23 exploratory markers to determine their effectiveness to better predict drug-induced kidney injury in rats as compared to markers of renal function

19 Progress in the field of kidney biomarkers Novel urinary biomarkers qualified by FDA and EMA (2008) for acute rodent nephrotoxicity Markers associated with specific parts of the nephron 23 Proposed Exploratory Kidney Markers AGP Albumin β-2-microglobulin Calbindin Clusterin Cystatin C EGF GSTa GSTm Kim-1 Lipocalin-2 (NGAL) b-nag Osteoactivin (8 qualified by FDA / EMA / PMDA) Osteopontin Podocin RPA1 TFF3 Timp1 Total Urinary Protein Uromodulin (Tamm-Horsfall) VEGF Macrophage Migration Inhibitory Factor Monokine Induced by Interferon Gamma Interferon Gamma induced 10kDa Protein (IP-10) included in MILLIPLEX MAP kidney toxicity panels (EMD Millipore) Little data publicly available yet for response to sub-acute exposure! Fuchs et al. (2011 and 2012) Goodsaid et al. (2009) Clinical Pharmacology & Therapeutics 86 5,

20 Summary: Nephrotoxicity markers In vivo: 28 day repeat dose with Vancomycin, Cisplatin and Puromycin Qualified vs. exploratory biomarkers Sub-acute toxicity studies Diagnostic properties Effect of recovery periods Luminex xmap technology Reliable results for qualified and exploratory biomarkers were observed! Most promising / predictive biomarkers in this study NGAL, Kim-1, Osteopontin, Clusterin For some biomarkers differences in gender and performance were identified! Diagnostic value of most markers positive for their ability to detect sub-acute renal changes up to 28 days, as they are related to renal health status! Some intra-renal BMs of tubular degeneration showed good diagnostic properties! Extra-renal BMs need further specification about related pathology! In case of regeneration, the biomarker excretion can be altered! Enable monitoring, good reflection of intra-renal status Suitability for implementation into routine regulatory toxicity testing

21 Transcriptional biomarker evaluation Mechanistic Analysis (Vancomycin based) Biomarker analysis (Discovery project based) Published data SABIDA Db Final postulated transcriptional biomarker list. 40 Individual transcripts were grouped into 10 functional categories. Excellent overlap to the genes discovered by SABIDA Db

22 In Vitro Gene Expression - acute toxicity compound NOEC TC20 NRK-52E Puromycin h 72h Doxorubicin AmphotericinB Metformin D-Mannitol Total RNA AAAA AAAA AAAA Reverse Transcription Biomarkers discovery Prediction models Mechanistic analysis 1500 SPP1_male cdna In vitro Transcription Biotin-labeled crna B B B GeneChip Expression Array Hybridization B B B B Washing and staining B B B B Scanning and Quantification Bioinformatics analysis 0 4d C 8d C 15d C 29d C 4d LD 8d LD 15d LD 29d LD 4d HD 8d HD 15d HD 29d HD

23 NRK-52E altered genes A total number of 192 genes are shown. 128 genes were downregulated, 64 genes were up-regulated. Man [HD] Man [LD] Pur [LD] Met [HD] Met [LD] APAP [HD] AB [HD] Dox [HD] Dox [LD] APAP [LD] Pur [HD] AB [LD] Toxic Non-Toxic Pur: Puromycin Dox: Doxorubicin AB: Amphotericin B APAP: Paracetamol Met: Metformin Man: D-Mannitol In-Vitro

24 Relevance of altered genes in nephrotoxicity in-vivo 45 genes described in context of renal insult 12 genes are already commercialized biomarkers for detection of nephrotoxicity in-vivo fold-change of vehicle control 12 Puromycin LD Doxorubicin LD Amphotericin LD Puromycin HD Doxorubicin HD Amphotericin HD Threshold (+1.5) Threshold (-1.5) -4 Bhmt Ccng1 Cd44 Cdkn1a Cxcl1 Cyr61 Fn1 Gamt Idh1 Mgp Odc1 Tnfrsf12a

25 Outcome and conclusions For sub-acute rat studies performed at Merck Serono (28 day repeat dose with Vancomycin, Cisplatin and Puromycin) Identification of new, novel gene expression biomarkers (Vancomycin specific) Validation of nephrotoxicity biomarkers by SABIDA Db In vitro model with human cell line shows promising results with test compounds Gene expression markers found in vivo also present in vitro Extracted and curated gene expression datasets related to chemical-induced toxicities in human, rat, mouse and several non-mammalian species for 300 compounds º generated vast database containing more than 5000 unique genes, and nearly 50,000 individual expression values gathered into over 2000 toxicity gene signatures New database (SABIDA) is accessible via a web interface, allows comparisons with any new gene expression (

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