Development of a Pharmaceutical Hepatotoxicity Biomarker Panel Using a Discovery to Targeted Proteomics Approach
2012; Elsevier BV; Volume: 11; Issue: 8 Linguagem: Inglês
10.1074/mcp.m111.016493
ISSN1535-9484
AutoresBen C. Collins, Christine Miller, Alexandra Sposny, Phillip Hewitt, Martin T. Wells, William M. Gallagher, Stephen R. Pennington,
Tópico(s)Advanced Proteomics Techniques and Applications
ResumoThere is a pressing and continued need for improved predictive power in preclinical pharmaceutical toxicology assessment as substantial numbers of drugs are still removed from the market, or from late-stage development, because of unanticipated issues of toxicity. In recent years a number of consortia have been formed with a view to integrating -omics molecular profiling strategies to increase the sensitivity and predictive power of preclinical toxicology evaluation. In this study we report on the LC-MS based proteomic analysis of the effects of the hepatotoxic compound EMD 335823 on liver from rats using an integrated discovery to targeted proteomics approach. This compound was one of a larger panel studied by a variety of molecular profiling techniques as part of the InnoMed PredTox Consortium. Label-free LC-MS analysis of hepatotoxicant EMD 335823 treated animals revealed only moderate correlation of individual protein expression with changes in mRNA expression observed by transcriptomic analysis of the same liver samples. Significantly however, analysis of the protein and transcript changes at the pathway level revealed they were in good agreement. This higher level analysis was also consistent with the previously suspected PPARα activity of the compound. Subsequently, a panel of potential biomarkers of liver toxicity was assembled from the label-free LC-MS proteomics discovery data, the previously acquired transcriptomics data and selected candidates identified from the literature. We developed and then deployed optimized selected reaction monitoring assays to undertake multiplexed measurement of 48 putative toxicity biomarkers in liver tissue. The development of the selected reaction monitoring assays was facilitated by the construction of a peptide MS/MS spectral library from pooled control and treated rat liver lysate using peptide fractionation by strong cation exchange and off-gel electrophoresis coupled to LC-MS/MS. After iterative optimization and quality control of the selected reaction monitoring assay panel, quantitative measurements of 48 putative biomarkers in the liver of EMD 335823 treated rats were carried out and this revealed that the panel is highly enriched for proteins modulated significantly on drug treatment/hepatotoxic insult. This proof-of-principle study provides a roadmap for future large scale pre-clinical toxicology biomarker verification studies whereby putative toxicity biomarkers assembled from multiple disparate sources can be evaluated at medium-high throughput by targeted MS. There is a pressing and continued need for improved predictive power in preclinical pharmaceutical toxicology assessment as substantial numbers of drugs are still removed from the market, or from late-stage development, because of unanticipated issues of toxicity. In recent years a number of consortia have been formed with a view to integrating -omics molecular profiling strategies to increase the sensitivity and predictive power of preclinical toxicology evaluation. In this study we report on the LC-MS based proteomic analysis of the effects of the hepatotoxic compound EMD 335823 on liver from rats using an integrated discovery to targeted proteomics approach. This compound was one of a larger panel studied by a variety of molecular profiling techniques as part of the InnoMed PredTox Consortium. Label-free LC-MS analysis of hepatotoxicant EMD 335823 treated animals revealed only moderate correlation of individual protein expression with changes in mRNA expression observed by transcriptomic analysis of the same liver samples. Significantly however, analysis of the protein and transcript changes at the pathway level revealed they were in good agreement. This higher level analysis was also consistent with the previously suspected PPARα activity of the compound. Subsequently, a panel of potential biomarkers of liver toxicity was assembled from the label-free LC-MS proteomics discovery data, the previously acquired transcriptomics data and selected candidates identified from the literature. We developed and then deployed optimized selected reaction monitoring assays to undertake multiplexed measurement of 48 putative toxicity biomarkers in liver tissue. The development of the selected reaction monitoring assays was facilitated by the construction of a peptide MS/MS spectral library from pooled control and treated rat liver lysate using peptide fractionation by strong cation exchange and off-gel electrophoresis coupled to LC-MS/MS. After iterative optimization and quality control of the selected reaction monitoring assay panel, quantitative measurements of 48 putative biomarkers in the liver of EMD 335823 treated rats were carried out and this revealed that the panel is highly enriched for proteins modulated significantly on drug treatment/hepatotoxic insult. This proof-of-principle study provides a roadmap for future large scale pre-clinical toxicology biomarker verification studies whereby putative toxicity biomarkers assembled from multiple disparate sources can be evaluated at medium-high throughput by targeted MS. The inability of current preclinical toxicology evaluation methods to predict early, and with good accuracy, that a drug candidate will have to be removed from development (or from the market) because of toxicicity/safety issues is a serious bottleneck in the drug development pipeline (1Kola I. Landis J. Can the pharmaceutical industry reduce attrition rates?.Nat. Rev. Drug Discov. 2004; 3: 711-715Crossref PubMed Scopus (3207) Google Scholar). Novel omics profiling technologies have the potential to provide more effective preclinical predictive models for toxicity (2Waters M.D. Fostel J.M. Toxicogenomics and systems toxicology: aims and prospects.Nat. Rev. Genet. 2004; 5: 936-948Crossref PubMed Scopus (340) Google Scholar). By performing detailed and comprehensive molecular profiling of animal or cell-based models that have been exposed to known toxic insults, it should be possible to catalog the spectrum of molecular changes that cause or accompany a particular mechanism of toxicity. It is reasonable to assume that molecular changes underlying, or induced by, toxicologic mechanisms will be manifested at earlier time points and at lower dose levels than are required for classical toxicology evaluation endpoints. Hence, the basic premise of preclinical predictive systems toxicology is to perform molecular profiling experiments for a range of compounds, potentially hundreds, displaying various toxicities and deriving biomarker signatures related to given toxicological mechanisms or endpoints. This approach has recently begun to enjoy some success with a panel of seven urinary protein biomarkers for nephrotoxicity having been deemed acceptable in the context of nonclinical drug development for the detection of acute drug-induced kidney toxicity in a joint evaluation by the Food and Drug Administration (FDA) and European Medicines Agency (EMEA) (3Dieterle F. Sistare F. Goodsaid F. Papaluca M. Ozer J.S. Webb C.P. Baer W. Senagore A. Schipper M.J. Vonderscher J. Sultana S. Gerhold D.L. Phillips J.A. Maurer G. Carl K. Laurie D. Harpur E. Sonee M. Ennulat D. Holder D. Andrews-Cleavenger D. Gu Y.Z. Thompson K.L. Goering P.L. Vidal J.M. Abadie E. Maciulaitis R. Jacobson-Kram D. Defelice A.F. Hausner E.A. Blank M. Thompson A. Harlow P. Throckmorton D. Xiao S. Xu N. Taylor W. Vamvakas S. Flamion B. Lima B.S. Kasper P. Pasanen M. Prasad K. Troth S. Bounous D. Robinson-Gravatt D. Betton G. Davis M.A. Akunda J. McDuffie J.E. Suter L. Obert L. Guffroy M. Pinches M. Jayadev S. Blomme E.A. Beushausen S.A. Barlow V.G. Collins N. Waring J. Honor D. Snook S. Lee J. Rossi P. Walker E. Mattes W. Renal biomarker qualification submission: a dialog between the FDA-EMEA and Predictive Safety Testing Consortium.Nat. Biotechnol. 2010; 28: 455-462Crossref PubMed Scopus (350) Google Scholar). Consortia-based efforts have been established to systematically investigate drug-induced liver, and other toxicities, however, progress has been less apparent (4Mattes W.B. Public consortium efforts in toxicogenomics.Methods Mol. Biol. 2008; 460: 221-238Crossref PubMed Google Scholar, 5Gallagher W.M. Tweats D. Koenig J. Omic profiling for drug safety assessment: current trends and public-private partnerships.Drug Discov. Today. 2009; 14: 337-342Crossref PubMed Scopus (24) Google Scholar). The integrated EU Framework 6 Project InnoMed PredTox (6Suter L. Schroeder S. Meyer K. Gautier J.C. Amberg A. Wendt M. Gmuender H. Mally A. Boitier E. Ellinger-Ziegelbauer H. Matheis K. Pfannkuch F. EU Framework 6 Project: Predictive Toxicology (PredTox)-overview and outcome.Toxicol. Appl. Pharmacol. 2011; 252: 73-84Crossref PubMed Scopus (62) Google Scholar) was such a consortium, consisting of 14 pharmaceutical companies, three universities, and two technology providers, focused on assessing the potential of combining the molecular profiling techniques of transcriptomics, proteomics, and metabolomics with conventional toxicology measurements, to provide improved decision making in preclinical safety evaluation. The general conclusion from the PredTox consortium was that to some extent the “omics” technologies can help toxicologists to make better informed decisions during exploratory toxicological studies, however, integrating data sets from different molecular profiling technologies proved problematic (6Suter L. Schroeder S. Meyer K. Gautier J.C. Amberg A. Wendt M. Gmuender H. Mally A. Boitier E. Ellinger-Ziegelbauer H. Matheis K. Pfannkuch F. EU Framework 6 Project: Predictive Toxicology (PredTox)-overview and outcome.Toxicol. Appl. Pharmacol. 2011; 252: 73-84Crossref PubMed Scopus (62) Google Scholar). In particular, the proteomics studies performed in the context of the PredTox project were restricted to the use of SELDI (7Collins B.C. Sposny A. McCarthy D. Brandenburg A. Woodbury R. Pennington S.R. Gautier J.C. Hewitt P. Gallagher W.M. Use of SELDI MS to discover and identify potential biomarkers of toxicity in InnoMed PredTox: a multi-site, multi-compound study.Proteomics. 2010; 10: 1592-1608Crossref PubMed Scopus (12) Google Scholar) and two-dimensional electrophoresis (8Com E. Gruhler A. Courcol M. Gautier J.C. Protocols of two-dimensional difference gel electrophoresis to investigate mechanisms of toxicity.Methods Mol. Biol. 2011; 691: 187-203Crossref PubMed Scopus (8) Google Scholar) approaches which, although undertaken rigorously, displayed limited proteome coverage and identified relatively small numbers of modulated proteins. This limitation significantly hampered efforts aimed at integrated analysis of protein expression changes with the transcriptomics or metabolomics data sets. In order to address this issue with a view to increasing proteome coverage and then subsequently providing methods for robust and sensitive protein quantification in future studies of this type, we undertook a reanalysis of livers from rats treated with one of the PredTox compounds, EMD 335823, using LC-MS-based proteomics methods. For more specific information on the outcome of previous detailed studies, in particular with regard to gene expression profiling and mechanistic analyses, we refer the reader to a summary of the InnoMed PredTox Consortium activities surround EMD 335823 (9Sposny A. Schmitt C.S. Hewitt P. Mechanistic investigation of EMD 335 823s hepatotoxicity using multiple omics profiling technologies.in: Casciano D.A. Saura S.C. Handbook of Systems Toxicology. John Wiley & Sons Ltd., 2011: 346-389Google Scholar). The study described herein is a re-analysis of archived liver samples from the same in vivo dosing experiments. First, a discovery proteomics screen of liver from hepatotoxicant treated rats by MS1 intensity-based label-free liquid chromatography (LC)-MS (10America A.H. Cordewener J.H. Comparative LC-MS: a landscape of peaks and valleys.Proteomics. 2008; 8: 731-749Crossref PubMed Scopus (165) Google Scholar) was performed. Second, a panel of putative biomarkers assembled from the label-free LC-MS study, a previous transcriptomics study (9Sposny A. Schmitt C.S. Hewitt P. Mechanistic investigation of EMD 335 823s hepatotoxicity using multiple omics profiling technologies.in: Casciano D.A. Saura S.C. Handbook of Systems Toxicology. John Wiley & Sons Ltd., 2011: 346-389Google Scholar), and literature sources (11Amacher D.E. The discovery and development of proteomic safety biomarkers for the detection of drug-induced liver toxicity.Toxicol. Appl. Pharmacol. 2010; 245: 134-142Crossref PubMed Scopus (76) Google Scholar), were measured simultaneously in a larger cohort of hepatotoxicant treated rat livers by targeted MS using selected reaction monitoring (12Lange V. Picotti P. Domon B. Aebersold R. Selected reaction monitoring for quantitative proteomics: a tutorial.Mol. Syst. Biol. 2008; 4: 222Crossref PubMed Scopus (1121) Google Scholar). The goals of this study were to determine the feasibility of using LC-MS-based proteomics to augment and facilitate large-scale efforts in the direction of preclinical toxicology evaluation and systems toxicology. There are essentially two ways which advanced proteomics methodologies could contribute to this field. The first concerns the elucidation of biochemical and mechanistic aspects of toxicological phenotypes. The second is in the determination of biomarkers associated with the prediction of a given toxicological event. Although tissue-based analysis of the target organ of toxicity (as was carried out in this study) is directly appropriate for the first goal, the second goal remains a more complex prospect. In the ideal case a biomarker would be directly measureable in an accessible body fluid to facilitate longitudinal measurements, in addition to the possibility of transferring such a biomarker from preclinical to clinical utility, however, the difficulties associated with plasma/urine biomarker discovery and validation are well described (13Anderson N.L. Anderson N.G. The human plasma proteome: history, character, and diagnostic prospects.Mol. Cell. Proteomics. 2002; 1: 845-867Abstract Full Text Full Text PDF PubMed Scopus (3551) Google Scholar). The utility of tissue-based biomarkers is less clear as histological evaluation is routinely applied and, as such, a clear sensitivity benefit for novel tissue-based biomarkers over histopathology would have to be demonstrated. A more likely route may be the transfer of promising biomarkers candidates from tissue to plasma-based assays in the medium-long term. MS1 intensity-based label-free LC-MS (10America A.H. Cordewener J.H. Comparative LC-MS: a landscape of peaks and valleys.Proteomics. 2008; 8: 731-749Crossref PubMed Scopus (165) Google Scholar) (as opposed to spectral counting-based label-free LC-MS (14Lundgren D.H. Hwang S.I. Wu L. Han D.K. Role of spectral counting in quantitative proteomics.Expert Rev. Proteomics. 2010; 7: 39-53Crossref PubMed Scopus (313) Google Scholar)) has emerged as an attractive alternative to isotope labeling-based strategies for preclinical or clinical studies where relatively large numbers of samples need to be analyzed and integrating metabolic or chemical labeling into the sample preparation may be problematic. Although the achievable proteome coverage is not as high with label-free approaches as can be realized with isotope labeling which routinely incorporate extensive fractionation, substantial numbers of proteins can be quantified and identified by additionally employing a directed MS/MS approach incorporating re-injection of samples with inclusion lists to supplement the peptide identifications acquired in data dependent analyses (15Schmidt A. Claassen M. Aebersold R. Directed mass spectrometry: towards hypothesis-driven proteomics.Curr. Opin. Chem. Biol. 2009; 13: 510-517Crossref PubMed Scopus (80) Google Scholar, 16Domon B. Aebersold R. Options and considerations when selecting a quantitative proteomics strategy.Nat. Biotechnol. 2010; 28: 710-721Crossref PubMed Scopus (482) Google Scholar). The data analysis associated with the MS1 label-free approach, in particular the alignment of MS1 feature maps, remains a challenge. In addition, the success of this approach rests on maintaining stability and reproducibility in the chromatography, as well as mass accuracy and intensity measurements. Although recent advances in software and instrument robustness have made the label-free LC-MS approach feasible for small-medium scale discovery proteomics study with preclinical or clinical samples, the use of this approach in very large-scale studies is likely to be complex and currently difficult to achieve. Verification of biomarker panels for preclinical toxicology evaluation will most likely require the analysis of large numbers of compounds with well characterized toxicological properties and, as such, a technology platform that can reproducibly and sensitively measure proteins in a targeted fashion is required. The use of selected reaction monitoring (SRM) 1The abbreviations used are:SRMselected reaction monitoringACNacetonitrileESTexpressed sequence tagFDRfalse discovery rateIAAiodoacetamidenLC-MS/MSnanoflow liquid chromatography – tandem mass spectrometryPTMpost translational modificationQqTOFquadrupole time-of-flight mass spectrometerQqQtriple quadrupole mass spectrometerTCEPtris(2-carboxyethyl)phosphine. 1The abbreviations used are:SRMselected reaction monitoringACNacetonitrileESTexpressed sequence tagFDRfalse discovery rateIAAiodoacetamidenLC-MS/MSnanoflow liquid chromatography – tandem mass spectrometryPTMpost translational modificationQqTOFquadrupole time-of-flight mass spectrometerQqQtriple quadrupole mass spectrometerTCEPtris(2-carboxyethyl)phosphine. for proteomics studies has emerged in recent years as a powerful method for sensitive, robust, and increasingly routine targeted quantification of proteins in complex biological samples (12Lange V. Picotti P. Domon B. Aebersold R. 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This means that SRM assays targeting tens to hundreds of proteins can be developed in a matter of weeks and deployed indefinitely in large-scale targeted proteomics studies. The SRM method is also inherently flexible and can be easily refined to integrate additional new proteins into an assay panel that arise, for example, from ongoing discovery studies, or to remove proteins with low discriminatory power that are no longer required. selected reaction monitoring acetonitrile expressed sequence tag false discovery rate iodoacetamide nanoflow liquid chromatography – tandem mass spectrometry post translational modification quadrupole time-of-flight mass spectrometer triple quadrupole mass spectrometer tris(2-carboxyethyl)phosphine. selected reaction monitoring acetonitrile expressed sequence tag false discovery rate iodoacetamide nanoflow liquid chromatography – tandem mass spectrometry post translational modification quadrupole time-of-flight mass spectrometer triple quadrupole mass spectrometer tris(2-carboxyethyl)phosphine. In this study SRM was utilized as a means to undertake the measurement of a panel of putative biomarker candidates assembled from disparate sources, namely a discovery proteomics screen by label-free LC-MS, a previous transcriptomics study where the same liver samples were analyzed (9Sposny A. Schmitt C.S. Hewitt P. Mechanistic investigation of EMD 335 823s hepatotoxicity using multiple omics profiling technologies.in: Casciano D.A. Saura S.C. Handbook of Systems Toxicology. John Wiley & Sons Ltd., 2011: 346-389Google Scholar), and hepatotoxicity biomarker candidates taken from literature (11Amacher D.E. The discovery and development of proteomic safety biomarkers for the detection of drug-induced liver toxicity.Toxicol. Appl. Pharmacol. 2010; 245: 134-142Crossref PubMed Scopus (76) Google Scholar), into a single assay panel of 48 rat liver proteins. The primary set of proteins included in the SRM panel was derived from an MS1 intensity-based label-free LC-MS discovery proteomics study of a subset of the hepatotoxicant treated rat livers also conducted in the context of this study. These studies provide a significant proof-of-principle demonstration for future preclinical toxicology studies whereby (1) label-free LC-MS can provide putative biomarkers and mechanistic information on the toxicological insult, and, (2) putative biomarkers from multiple sources can be integrated into an SRM assay panel that can be deployed at medium-high throughput for large scale verification studies involving substantial numbers of well-characterized toxicants, and later for more sensitive toxicology evaluation for drugs under early development. Details of the compounds, animal studies, and classical toxicology evaluation procedures as well as further details of the InnoMed PredTox Consortium methods have been published previously (7Collins B.C. Sposny A. McCarthy D. Brandenburg A. Woodbury R. Pennington S.R. Gautier J.C. Hewitt P. Gallagher W.M. Use of SELDI MS to discover and identify potential biomarkers of toxicity in InnoMed PredTox: a multi-site, multi-compound study.Proteomics. 2010; 10: 1592-1608Crossref PubMed Scopus (12) Google Scholar, 29Mulrane L. Rexhepaj E. Smart V. Callanan J.J. Orhan D. Eldem T. Mally A. Schroeder S. Meyer K. Wendt M. O'Shea D. Gallagher W.M. Creation of a digital slide and tissue microarray resource from a multi-institutional predictive toxicology study in the rat: an initial report from the PredTox group.Exp. Toxicol. Pathol. 2008; 60: 235-245Crossref PubMed Scopus (36) Google Scholar, 30Adler M. Hoffmann D. Ellinger-Ziegelbauer H. Hewitt P. Matheis K. Mulrane L. Gallagher W.M. Callanan J.J. Suter L. Fountoulakis M.M. Dekant W. Mally A. Assessment of candidate biomarkers of drug-induced hepatobiliary injury in preclinical toxicity studies.Toxicol. Lett. 2010; 196: 1-11Crossref PubMed Scopus (29) Google Scholar, 31Hoffmann D. Adler M. Vaidya V.S. Rached E. Mulrane L. Gallagher W.M. Callanan J.J. Gautier J.C. Matheis K. Staedtler F. Dieterle F. Brandenburg A. Sposny A. Hewitt P. Ellinger-Ziegelbauer H. Bonventre J.V. Dekant W. Mally A. Performance of novel kidney biomarkers in preclinical toxicity studies.Toxicol. Sci. 2010; 116: 8-22Crossref PubMed Scopus (95) Google Scholar). The experiments described here focused on a single compound study in the InnoMed PredTox Consortium designated FP005ME. In this study Wistar rats were treated daily for 3 or 14 days with vehicle, a nontoxic dose (15 mg/kg), or a high dose (350 mg/kg) of the known hepatotoxic compound (EMD 335823, see supplemental Fig. S1 for chemical structure) the latter dose chosen to induce significant hepatotoxicity (liver necrosis, fibrosis, and bile duct necrosis/hyperplasia). Each drug treatment group contained five rats with a total of 30 rats across the six treatment groups analyzed. Animal experimentation plans underwent an ethical review within the project and were carried out according to the local regulations and permissions of each participant company and in accordance with the guidelines of the European Council on Experimental Animal Care. Additional details on the in vivo study design are given the supplementary information and supplemental Tables S1, S2, S3, and S4. Protein extraction from liver samples was as previously described (7Collins B.C. Sposny A. McCarthy D. Brandenburg A. Woodbury R. Pennington S.R. Gautier J.C. Hewitt P. Gallagher W.M. Use of SELDI MS to discover and identify potential biomarkers of toxicity in InnoMed PredTox: a multi-site, multi-compound study.Proteomics. 2010; 10: 1592-1608Crossref PubMed Scopus (12) Google Scholar). Briefly, the frozen left lateral lobe of the liver (100 ± 50 mg) was ground with a mortar and pestle under liquid nitrogen. Powdered tissue was transferred into a tube containing 125 μl lysis buffer I (10 mm Tris/pH 7.0.5, 1 mm EDTA, 0.2 m sucrose, Benzonase 25 U/μl (Calbiochem, San Diego, CA), protease inhibitor mixture (Set III - 100 mm AEBSF hydrochloride, 80 μm aprotinin (bovine lung), 5 mm bestatin, 1.5 mm E-64, 2 mm leupeptin hemisulfate, 1 mm pepstatin A, Calbiochem) and completely suspended. Afterward, 875 μl lysis buffer II (7 m urea, 2 m thiourea, 4% (w/v) 3-[(3-cholamidopropyl)dimethylammonio]propanesulfonate, 40 mm dithiothreitol, 20 mm spermine) was added and pipeted 30 times to aid suspension. The protein extracts were mixed at room temperature on a rotary shaker at 500 rpm for 1 h to ensure complete cell lysis and solubilization of protein. To separate membranous components and other insoluble debris, samples were ultracentrifuged for 30 min at 10 °C and 74,000 × g. The supernatant was aliquoted and stored at −80 °C. Two hundred micrograms of the liver protein extracts were reduced (5 mm TCEP, 20 min, room temperature) and alkylated (10 mm iodoacetamide, 30 min room temperature in the dark) before precipitation with six volumes of acetone for 2 h at −20 °C. The samples were centrifuged for 10 min at 5000 × g and 4 °C, and the pellets were resolubilized in Rapigest 1.3% (w/v), 50 mm NH3HCO3 or 5% (w/v) trifluoroethanol, 50 mm NH3HCO3 and incubated with 2 μg sequencing grade modified porcine trypsin, (overnight, 37 °C). Rapigest containing samples were acidified with 2% (v/v) formic acid (4 h, RT) and centrifuged (13,000 × g, 10 min) to remove the Rapigest hydrolysis products. The samples were transferred to clean tubes, evaporated to dryness
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