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Session: Influence of Epigenetics, Genetics, and Immunology Part A Toxicologic Pathology 2017, Vol. 45(1) 119-126 ª The Author(s) 2016 Reprints and permission: DOI: 10.1177/0192623316675064

Translational Safety Genetics: Leveraging Genetic Variation for Enhanced Safety Assessment Priyasma Bhoumik1, Alberto Del Rio-Espinola1, Florian Hahne1, Jonathan Moggs1, and Olivier Grenet1

Abstract The emerging field of translational safety genetics is providing new opportunities to enhance drug discovery and development. Genetic variation in therapeutic drug targets, off-target interactors and relevant drug metabolism/disposition pathways can contribute to diverse drug pharmacologic and toxicologic responses between different animal species, strains and geographic origins. Recent advances in the sequencing of rodent, canine, nonhuman primate, and minipig genomes have dramatically improved the ability to select the most appropriate animal species for preclinical drug toxicity studies based on genotypic characterization of drug targets/pathways and drug metabolism and/or disposition, thus avoiding inconclusive or misleading animal studies, consistent with the principles of the 3Rs (replacement, reduction and refinement). The genetic background of individual animals should also be taken into consideration when interpreting phenotypic outcomes from toxicity studies and susceptibilities to spontaneous safety-relevant background findings. Keywords safety genetics, sequencing, cynomolgus monkey, toxicology, animal species, genome, genetic variation Safety genetics addresses the impact of genetic variations in drug target biology, metabolism, and disposition of druginduced phenotypes. With the latest advances in the field of genomics and newest sequencing technologies, genomes of different toxicology animal species have been sequenced or their quality dramatically improved. Genetic variations in therapeutic targets, off-target interactors, and drug metabolism and disposition pathways may cause differences in both pharmacologic and toxicologic responses across species, strains, and/or animals from diverse geographic origins. New molecular entities and biological products are required to be tested in a rodent or nonrodent species prior to human clinical studies, following the fundamental principles of the 3Rs: replacement, reduction, and refinement (To¨rnqvist et al. 2014). Improved preclinical study design, coordination, and proper methodology can lead to a reduction in the number of animals needed in a study. Important sources of guidance for selecting an appropriate species for preclinical toxicity studies and safety assessment include the International Conference on Harmonization (ICH), U.S. Food and Drug Administration, and European Medicines Agency (EMA; ICH guideline 2012; ICH 1997; EMA 2008; Table 1). This review discusses the importance of characterizing genetic variation within preclinical animal species and opportunities for enhancing drug safety through translational safety genetics.

Species Selection for Toxicology Several animal species are currently used in toxicology including mice, rats, dogs, minipigs, and monkeys. These species are subject to well-characterized spontaneous pathology findings that can vary across species, strains, and geographic origins (Bradley, Mukaratirwa, and Petersen-Jones 2012; Chamanza et al. 2010; Jeppesen and Skydsgaard 2014; Mahler et al. 2016; Sato et al. 2012). We outline below the most commonly used toxicology species and how their genetic characterization can enhance the design and interpretation of toxicology studies.

Nonrodents Nonhuman primates (NHPs) have an important role in basic and translational research, and especially in toxicology studies of biologics or advanced therapeutics due to their similarity with humans in evolutionary ancestry. Frequently, NHPs are 1

Preclinical Safety, Translational Medicine, Novartis Institutes for Biomedical Research, Basel, Switzerland

Corresponding Author: Priyasma Bhoumik, Preclinical Safety, Translational Medicine, Novartis Institutes for Biomedical Research, CH-4057 Basel, Switzerland. Email: [email protected]


Toxicologic Pathology 45(1)

Table 1. Recommendations for Drug Target Characterization within Regulatory Guidelines for Preclinical Safety Testing. Guidelines



ICH S6(R1)

EMA/FDA/Japan ‘‘Comparisons of target sequence homology between species can be an appropriate starting point, followed by in vitro assays to make qualitative and quantitative cross species comparisons of relative target binding affinities and receptor/ ligand occupancy and kinetics’’ EMA (CHMP) ‘‘The sponsor should compare the available animal species to EMA FIH (guideline on strategies to identify and mitigate humans taking into account the target, its structural risks. For first-in-human clinical trials with investigational homology, distribution, signal transduction pathways and the medicinal products) nature of pharmacological effects’’ Note. ICH ¼ International Conference on Harmonization; EMA ¼ European Medicines Agency; FDA ¼ Food and Drug Administration; CHMP ¼ Committee for Medicinal Products for Human Use; FIH ¼ first-in-human.

the only nonhuman species capable of pharmacological responses to novel biotherapeutics (Capitanio and Emborg 2008). Some of the most conclusive human-relevant data for safety assessment has been obtained from monkey toxicology studies (Capitanio and Emborg 2008). Cynomolgus monkeys are the most commonly used nonrodent species for biologics (Brennan et al. 2010), while marmosets (Marmoset Genome Sequencing and Analysis Consortium 2014), African green monkeys (Warren et al. 2015), and Rhesus monkeys are only rarely used for preclinical toxicology and safety testing. Dogs are frequently used in the pharmaceutical industry when selecting nonrodent species for toxicological studies, mostly for low molecular weight compounds (Smith et al. 2002; Robertson, Breider, and Milad 2001). However, dogs are sensitive to sympathomimetic and hypotensive drugs and are susceptible to cardiotoxicity (Dogterom, Zbinden, and Reznik 1992; Lehmann 1998), making them a less relevant species for certain compound classes that are likely to affect those specific pathways. Minipigs are another nonrodent species used for comparative biology at molecular, biochemical, cellular, and tissue levels (Vamathevan et al. 2013) as well as toxicity assessment. Since their skin structure is similar to humans, the minipig is important for characterizing dermal compounds as well as investigation of immunopathological mechanisms and skin-related safety signals (Eaglstein and Mertz 1978; Swindle et al. 2012; Vana and Meingassner 2000). Given the similarity in anatomy, physiology, and biochemistry of minipigs to humans, it is also a particularly attractive species in reproductive toxicology testing, where early onset of sexual maturity and large size of litter is an advantage (Mitchell and Creasy 2007). Other less common nonrodent species used in specific toxicology studies include rabbits for reproductive toxicology because of their high rate of reproduction and ferrets for safety pharmacology (Foote and Carney 2000; Gad 2000).

Rodents Both mouse and rat are used for rodent toxicity and efficacy studies (Pritchard et al. 2003; Tirmenstein et al. 2015). Even

though they are phenotypically similar to each other, significant evolutionary differences need to be considered for optimal animal species selection (Iannaccone and Jacob 2009). For example, while the mouse has been one of the most commonly used animal species in fundamental research, its value as a model for the majority of human diseases is limited (Seok et al. 2013). Mouse models often serve to replicate specific processes within a disease but not the whole spectrum of physiological changes that occur in humans in the disease setting (Fingleton 2007; Mak, Evaniew, and Ghert 2014). Additional rodent models that are less frequently used for toxicity studies include hamsters (Brinkrolf et al. 2013; Dipaolo, Nelson, and Donovan 1972; Erexson, Periago, and Spicer 2001) and Guinea pigs (Rocca and Wehner 2009).

Paradigm Shift in Genetic Characterization of Toxicological Species Given the challenges associated with identifying reliable animal species for toxicity studies of a diverse range of innovative therapeutic modalities, it is important to optimize species selection using genetic data to ensure the use of a pharmacologically relevant species. Despite access to comprehensive human and mouse genome sequences for more than a decade, progress in preclinical safety genetics has been constrained by a lack of comprehensive genome data in animals commonly used for preclinical toxicology testing such as NHPs, dogs, minipigs, rats, and mice. Furthermore, breed or strain variations in these animal species add to the complexity of establishing genotype–phenotype relationships. Nevertheless, recently there has been tremendous progress in the whole genome sequencing of additional mammalian species that can be leveraged for toxicity studies and safety assessment (Table 2). The understanding of the baseline genetic variation in monkey is particularly important, as NHP studies are usually composed of a small number of animals due to the ethical and animal welfare concerns inherent to NHP work. Furthermore, only relatively limited access to monkeys from specific geographic origins is feasible. This is exemplified by a shift toward the usage of Chinese-origin rhesus monkeys for HIV research

Bhoumik et al.


Table 2. Mammalian Genetic Resources Supporting Translational Safety Genetics (‘‘Draft’’ Indicates a Partially Completed Genome). Species

Scientific names

Version type



Homo sapiens

Completed (hg38)

International Human Genome Sequencing Consortium (2013) International Human Genome Sequencing Consortium (2003) Venter et al. (2001) Lander et al. (2001) (Hoeppner et al. (2014) Lindblad-Toh et al. (2005) Vamathevan et al. (2013) Fang et al. (2012) Groenen et al. (2012) Heckel et al. (2015) Vamathevan et al. (2013) Carneiro et al. (2014) Marmoset Genome Sequencing and Analysis Consortium (2014) Warren et al. (2015) Zimin et al. (2014), Zhang et al. (2011), and Rhesus Macaque Genome Sequencing and Analysis Consortium et al. (2007) Yan et al. (2011) Ebeling et al. (2011) Higashino et al. (2012) Hermsen et al. (2015) and Gibbs et al. (2004)

Completed (hg17)


Canis lupus familiaris (Boxer) Canis lupus familiaris (Beagle)

Wuzhishan Minipig Duroc pig Go¨ttingen Minipig

Sus scrofa Sus scrofa Sus scrofa

Rabbit Marmoset monkey

Oryctolagus cuniculus Callithrix jacchus

Vervet monkey Rhesus monkey

Chlorocebus aethiops sabaeus Macaca mulatta

Cynomolgus monkey


Macaca fascicularis (Vietnamese) Macaca fascicularis (Mauritius) Macaca fascicularis (Malaysia) Rattus norvegicus


Mus musculus

Chinese hamster Ferret

Cricetulus griseus Mustela putorius furo

Draft Draft (hg3, hg4, hg5) Update (canFam3.1) Draft (canFam2) Genome reference Genome reference Genome reference Duroc reference based Genome reference Genome reference Genome reference Genome reference Latest version (rheMac8) Update Update Draft (rheMac2) Genome reference Genome reference Genome reference Latest version (RGSC6.0) Update (RGSC5.0) Draft (RGSC3.4) Latest version (MGSCv10) Update Draft (MGSCv3) Genome reference Draft (musFur1)

due to export limitations even though Indian-origin rhesus monkeys are a natural model for HIV (Marthas et al. 2001). Little attention was previously given to the geographic origins of the monkeys enrolled in toxicology programs. Differences in spontaneous pathological findings have been observed in cynomolgus monkeys from diverse geographic origins (DrevonGaillot et al. 2006; Vidal et al. 2010), as well as diverse major histocompatibility complex genetics (Campbell et al. 2009; Kita et al. 2009), and even geographic origin-dependent genetic variation within captive cynomolgus monkey stocks (Stevison and Kohn 2009). The first genome draft of the rhesus monkey, Macaca mulatta, was a major advance in biomedical sciences (Rhesus Macaque Genome Sequencing and Analysis Consortium et al. 2007). This genome draft enabled the identification of macaque-specific genes and also the assessment of population diversity at single nucleotide resolution. The first draft genome of the cynomolgus monkey (long-tailed macaque), Macaca fascicularis, was assembled using a whole-genome shotgun sequencing approach employing two independent deep sequencing technologies (Yan et al. 2011; Ebeling et al. 2011). These studies have been reinforced by numerous

Keane et al. (2012) Church et al. (2009) Waterston et al. (2002) Brinkrolf et al. (2013) Peng et al. (2014)

additional NHP genome sequencing efforts that are enabling the detailed characterization of both coding and noncoding parts of the macaque genome. We have been able to detect evidence at the exome level that geographic origin strongly influences the genetic background of cynomolgus monkeys. Whole genome sequencing initiatives provide an opportunity for enhanced early target characterization and toxicology species selection spanning all relevant rodent and nonrodent species. The identified genetic variants can help define the molecular basis for interindividual, intrastrain, and interspecies variation at the molecular, cellular, and physiologic levels. In particular, the systematic genotyping of therapeutic antibody targets/pathways within nonhuman primates combined with an assessment of human target genetic variation in the intended patient population can support optimal toxicology species selection and ensure optimal design of pharmacokinetics/pharmacodynamics assays (Kronenberg et al. 2013). Beyond genetic variation in the intended therapeutic target, additional confounding factors include the potential for species and strain differences in Fc receptor (FcR) binding and distinct Immunoglobulin G (IgG)-FcR interactions observed between


Toxicologic Pathology 45(1) provides the potential to improve the drug’s safety profile by identifying individuals at elevated risk for liver injury and excluding them from treatment (Singer et al. 2010). Carbamazepine, a drug prescribed for seizures, was observed to cause skin blisters (Steven–Johnson syndrome) in some patients carrying the HLA-B*1502 marker, a strong indicator of a genetic factor influencing drug response (Chung et al. 2004). It was subsequently found that the T-cell receptor (TCR) clonotype plays a key role in the pathogenic mechanism of Steven–Johnson syndrome (Ko et al. 2011). Thus, it appears that specific combinations of TCR and HLA genotypes with therapeutic drug exposure underlay this drug-induced hypersensitivity reaction. These findings are not restricted to immune-driven responses. Ischemic stroke patients treated with Alteplase and Tenecteplase and carrying polymorphisms in alpha-2-macroglobulin and coagulation factor 12 were more prone to suffer hemorrhagic transformations and inhospital death (Del Rı´o-Espı´nola et al. 2012).

Genetic Differences within Preclinical Models Figure 1. Integrating genetic variation in drug targets, metabolism, and disposition into translational safety genetics.

cynomolgus monkeys and humans (Warncke et al. 2012). Species differences have also been observed for IgG-neonatal Fc receptor (FcRn) interactions (Abdiche et al. 2015). For example, human IgG1 binds to cynomolgus monkey FcRn with a 2-fold higher affinity than human FcRn, whereas it binds rat FcRn with a 10-fold higher affinity than human FcRn. An overarching strategy for incorporating knowledge on genetic variation in drug targets, metabolism, and disposition into translational safety genetics is outlined in Figure 1.

Clinical Relevance of Genetic Variations The use of animal species for advancing medical science is widely accepted and recognized (Matthews 2008). However, the safety and efficacy profiles of therapeutics in animal species do not always correlate with human clinical trial outcomes (Mak, Evaniew, and Ghert 2014). This was exemplified by the TGN1412 clinical trial (Attarwala 2010) in which an anticluster of differentiation 28 (anti-CD28) therapeutic antibody led to organ failure in humans despite being deemed safe based on animal studies due to species differences in CD28 expression on CD4þ effector memory T-cells (Eastwood et al. 2010). Hence, it is critical to identify an appropriate animal species for human-relevant toxicity studies and safety assessment. It is also common to observe differences in drug responses between individual patients, which in some cases may be attributed to genetic variations. There is an increasing repertoire of examples where genetic factors play a role in the drug metabolism and/or toxicity phenotypes (Table 3). In the case of Lumiracoxib, the elucidation of a specific human leucocyte antigen (HLA) genotype association with drug-induced liver injury

Similar to humans, genetic variations underlie differences in drug response within animals from the same species as well as between different species. Celecoxib is a cyclooxygenase-2 inhibitor that readily metabolizes in dogs. A study on Beagle dogs identified 3 new variants in cytochrome P450 2D (CYP2D15; homologue to human CYP2D6) and a novel variant of CYP3A12, which were associated with different rates of metabolism of celecoxib in poor metabolizer (PM) and extensive metabolizer dog populations (Paulson et al. 1999). This was one of the earliest studies in dog that described a genetic polymorphism in a drug metabolizing enzyme. Another example in a rat study showed linkage of quantitative trait loci to a gut microbial metabolite (benzoate), which can be explained by deletion of the UDP glucuronosyltransferase 2b (Ugt2b) gene in several rat strains including Goto-Kakizaki (Rat), Brown Norway (Rat), and Wistar-Kyoto (Rat) (Dumas et al. 2007). Furthermore, Pol2RA mutations are associated with resistance to a-amanitin in mice (Bartolomei and Corden 1995), a natural toxin whose use in chemotherapy has been recently reinvigorated (Liu et al. 2015). Finally, the genetic variations can have an overt phenotypic impact such as the altered skin color caused by tyrosinase in rats (Bartolomei and Corden 1995; Blaszczyk et al. 2005).

Translatability of Preclinical Findings The preclinical evaluation of a novel p38 kinase inhibitor across inbred mice strains, dog, rats, and monkeys exemplifies the potential for species differences in pharmacokinetic profiles compared to humans, where rapid clearance of the drug was observed (Zhang et al. 2011). Differences in animal versus human metabolism were attributed to differences in enzyme activity of aldehyde oxidase-1 (AOX1) and the pattern of genetic variation in AOX1 from inbred mouse strains correlated with the rate of drug biotransformation (Zhang et al. 2011).

Bhoumik et al.


Table 3. Examples of Studies Where Genetic Factors Play a Role in the Drug Metabolism and/or Toxicity. Species



HLA haplotype association A2M/F12


Human Rhesus monkey Dog Rat (GK, BN, WKY strains)

Rat (Wistar) Mouse (BALB/c) Mouse (MRL/MpJ, LG/J, NZW/LaC, 129S1/SvImJ, SM/J, NZB/B1nJ, LP/J, DBA/2, C57BL/6, A/J, C3H/HeJ, BALB/c, B10.D2-H2dH2-T18c Hc0/oSnJ, BALB/cByJ, AKR/J, A/HeJ),)

Related phenotype

Lumiracoxib leads to increased risk for drug induced liver injury Polymorphisms increase susceptibility to hemorrhagic transformation and death after Alteplase or Tenecteplase treatment HLA-B1502 and TCR Carbamazepine induces Steven–Johnson syndrome (skin blisters) C3 Lack of binding of antibody due to H897F substitution CYP2D15 Polymorphism causes Celecoxib to readily metabolize Ugt2b Gut microbial metabolite (benzoate) is linked to deletion of a uridine diphosphate glucuronosyltransferase TYR Missense substitution causes albinism RNA PolR2A Mutation leading to a-amanitin resistance AOX1 Between mouse and humans, p38 MAP kinase inhibitor triggers rapid clearance in humans

Reference Singer et al. (2010) Del Rı´o-Espı´nola et al. (2012)

Chung et al. (2004) Ko et al. (2011) Katschke et al. (2009) Paulson et al. (1999) Dumas et al. (2007)

Blaszczyk et al. (2005) Bartolomei and Corden (1995) Zhang et al. (2011)

Note. AOX1 ¼ aldehyde oxidase-1; A2M ¼ alpha-2-macroglobulin; BN ¼ Brown Norway (Rat); CYP2D15 ¼ cytochrome P450 2D; F12 ¼ coagulation factor XII; GK ¼ Goto-Kakizaki (Rat); HLA ¼ human leucocyte antigen; MAP kinase ¼ mitogen-activated protein kinase; PolR2A ¼ polymerase (RNA) II subunit A; TCR ¼ T-cell receptor; TYR ¼ tyrosinase; Ugt2b ¼ UDP glucuronosyltransferase 2b; WKY ¼ Wistar-Kyoto (Rat).

The recommendation to assess the safety of therapeutic monoclonal antibodies in a preclinical species that is pharmacologically responsive to the treatment (Brennan et al. 2010) can be challenging. This is exemplified by a fully humanized C3b therapeutic antibody candidate (S77) that did not bind rhesus C3b due to a H897F substitution (Katschke et al. 2009). Such observations emphasize the need to assess functional equivalence of biotherapeutic drug epitopes in the animal species versus humans in order to optimize toxicology species selection. An important future aim for preclinical findings would be to predict the differences between animal phenotypes and clinical responses for various adverse events. This might be achieved in part through the characterization of genetic variants associated with drug metabolism and targeted pathways, combined with in vitro and in vivo assessments of functional consequences (Roden and George 2002).

Leveraging Animal Species Genome Sequencing Initiatives for Enhanced Safety Assessment In order to better understand the genetic variation between cynomolgus monkey populations, we have recently generated an exome sequencing-derived genome resource for rapid in silico assessment of genetic variation in targets and pathways. 10 individual cynomolgus monkeys from each of the 3 distinct geographic origins (Vietnam, Mauritius, and Philippines) were selected and exome sequencing was performed (Del Rio-Espinola, manuscript in preparation). The resultant database

containing genetic data is being used to support early target characterization and toxicology species selection; define interindividual, intrastrain, and interspecies genetic variants; and assess potential functional impact on gene/protein expression/function and translation to human genetic variation in intended patient populations. Similar applications are envisaged for rodent, canine, and minipig genome variation sequencing initiatives.

Conclusion Characterizing genetic variation in commonly used animal species can enhance toxicology species selection for translational safety assessment. Species-specific genotypes, strain-specific genotypes, intrastrain genetic variation, influence of geographic and breeder origins, and their impact on drug absorption, distribution, metabolism, excretion, pharmacology, and toxicology are some of the factors that need to be considered for enhanced safety genetics. While identifying genetic variation is relatively straightforward, assessing potential functional consequences is much more challenging and requires extensive in vitro– and in vivo–based characterization of candidate genetic variants. Some key future directions in translational safety genetics are (1) advanced genome resources for cross-species assessment of target/pathway genetic variation (enabling in silico assessment, hypothesis generation, and assessment of human relevance), (2) defining the importance of genetic variants by functionalization, (3) systematic sampling in toxicology studies for retrospective assessment of preclinical genotype–phenotype relationships, (4) proactive rather than reactive

124 preclinical genotyping for specific drug targets where functional variants have been identified, and (5) selection of appropriate preclinical species for new drug modalities (e.g., bispecific monoclocal antibodies; cell and gene therapies). Acknowledgments We would like to thank Leslie Pond and the Education Office in Novartis for their encouragement and support. We would also like to thank Dominique Brees and Page Bouchard (PreClinical Safety, Novartis) for reviewing the manuscript.

Authors’ Contribution Authors contributed to conception or design (PB, AD, FH, JM, OG); data acquisition, analysis, or interpretation (PB); drafting the manuscript (PB); and critically revising the manuscript (AD, FH, JM, OG). All authors gave final approval and agreed to be accountable for all aspects of work in ensuring that questions relating to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.

References Abdiche, Y. N., Yeung, Y. A., Chaparro-riggers, J., Barman, I., Strop, P., Chin, S. M., Pham, A., et al. (2015). The neonatal Fc receptor (FcRn) binds independently to both sites of the IgG homodimer with identical affinity. mAbs 7, 331–43. Attarwala, H. (2010). TGN1412: From discovery to disaster. Journal of Young Pharmacists: JYP 2, 332–36. doi: Bartolomei, M. S., and Corden, J. L. (1995). Clustered alpha-amanitin resistance mutations in mouse. Mol Gen Genet 246, 778–82. Blaszczyk, W. M., Arning, L., Hoffmann, K. P., and Epplen, J. T. (2005). A tyrosinase missense mutation causes albinism in the Wistar rat. Pigment Cell Res 18, 144–45. doi: Bradley, A., Mukaratirwa, S., and Petersen-Jones, M. (2012). Incidences and range of spontaneous findings in the lymphoid and haemopoietic system of control Charles River CD-1 Mice (Crl: CD-1(ICR) BR) used in chronic toxicity studies. Toxicol Pathol 40, 375–81. doi: 0192623311428479. Brennan, F. R., Morton, L. D., Spindeldreher, S., Kiessling, A., Allenspach, R., Hey, A., Muller, P. Y., Frings, W., and Sims, J. (2010). Safety and immunotoxicity assessment of immunomodulatory monoclonal antibodies. mAbs 2, 233–55. doi: Brinkrolf, K., Rupp, O., Laux, H., Kollin, F., Ernst, W., Linke, B., Kofler, R., et al. (2013). Chinese hamster genome sequenced from sorted chromosomes. Nat Biotechnol 31, 694–95. doi: Campbell, K. J., Detmer, A. M., Karl, J. A., Wiseman, R. W., Blasky, A. J., Hughes, A. L., Bimber, B. N., O’Connor, S. L., and O’Connor, D. H. (2009). Characterization of 47 MHC class i sequences in Filipino cynomolgus macaques. Immunogenetics 61, 177–87. doi: s00251-008-0351-x. Capitanio, J., and Emborg, M. (2008). Contributions of non-human primates to neuroscience research. Lancet 371, 1126–35. Carneiro, M., Rubin, C. J., Di Palma, F., Albert, F. W., Alfo¨ldi, J., Barrio, A. M., Pielberg, G., et al. (2014). Rabbit genome analysis reveals a polygenic basis for phenotypic change during domestication. Science 345, 1074–79.

Toxicologic Pathology 45(1) Chamanza, R., Marxfeld, H. A., Blanco, A. I., Naylor, S. W., and Bradley, A. E. (2010). Incidences and range of spontaneous findings in control cynomolgus monkeys (Macaca fascicularis) used in toxicity studies. Toxicol Pathol 38, 642–57. doi: Chung, W.-H., Hung, S.-I., Hong, H.-S., Hsih, M.-S., Yang, L.-C., Ho, H.-C., Wu, J. Y., and Chen, Y.-T. (2004). Medical genetics: A marker for Stevens–Johnson syndrome. Nature 428, 486. doi: 428486a. Church, D. M., Goodstadt, L., Hillier, L. W., Zody, M. C., Goldstein, S., She, X., Bult, C. J., et al. (2009). Lineage-specific biology revealed by a finished genome assembly of the mouse. PLoS Biology 7, e1000112. Del Rı´o-Espı´nola, A., Ferna´ndez-Cadenas, I., Giralt, D., Quiroga, A., Gutie´r´ lvarez, P., et al. (2012). A prerez-Agullo˜, M., Quintana, M., Ferna´ndez-A dictive clinical-genetic model of tissue plasminogen activator response in acute ischemic stroke. Ann Neurol 72, 716–29. doi: ana.23664. Dipaolo, J. A., Nelson, R. L., and Donovan, P. J. (1972). In vitro transformation of Syrian hamster embryo cells by diverse chemical carcinogens. Nature 235, 278–80. doi: Dogterom, P., Zbinden, G., and Reznik, G. K. (1992). Cardiotoxicity of vasodilators and positive inotropic/vasodilating drugs in dogs: An overview. Crit Rev Toxicol 22, 203–41. doi: Drevon-Gaillot, E., Perron-Lepage, M.-F., Cle´ment, C., and Burnett, R. (2006). A review of background findings in cynomolgus monkeys (Macaca fascicularis) from three different geographical origins. Exp Toxicol Pathol 58, 77–88. doi: Dumas, M.-E., Wilder, S. P., Bihoreau, M.-T., Barton, R. H., Fearnside, J. F., Argoud, K., D’Amato, L., et al. (2007). Direct quantitative trait locus mapping of mammalian metabolic phenotypes in diabetic and normoglycemic rat models. Nat Genet 39, 666–72. doi: ng2026. Eaglstein, W. H., and Mertz, P. M. (1978). New methods for assessing epidermal wound healing: The effects of triamcinolone acetonide and polyethylene film occlusion. J Investig Dermatol 71, 382–84. Eastwood, D., Findlay, L., Poole, S., Bird, C., Wadhwa, M., Moore, M., Burns, C., Thorpe, R., and Stebbings, R. (2010). Monoclonal antibody TGN1412 trial failure explained by species differences in CD28 expression on CD4 þ effector memory T-cells. Br J Pharmacol 161, 512–26. doi: 10.1111/j.1476-5381.2010.00922.x. Ebeling, M., Kung, E., See, A., Broger, C., Steiner, G., Berrera, M., Heckel, T., et al. (2011). Genome-based analysis of the nonhuman primate Macaca fascicularis as a model for drug safety assessment. Genome Res 21, 1746–56. doi:[pii]\r10.1101/gr.123117.111. EMA (European Medicines Agency). (2008). Guideline on immunogenicity assessment of biotechnology-derived therapeutic proteins. Accessed October 14, 2016. Scientific_guideline/2009/09/WC500003946.pdf. Erexson, G. L., Periago, M. V., and Spicer, C. S. (2001). Differential sensitivity of Chinese hamster V79 and Chinese hamster ovary (CHO) cells in the in vitro micronucleus screening assay. Mut Res 495, 75–80. doi: 10.1016/S1383-5718(01)00199-1. Fang, X., Mou, Y., Huang, Z., Li, Y., Han, L., Zhang, Y., Feng, Y., et al. (2012). The sequence and analysis of a Chinese pig genome. GigaScience 1, 16. Fingleton, B. (2007). Matrix metalloproteinases as valid clinical targets. Curr Pharm Des 13, 333–46. Foote, R. H., and Carney, E. W. (2000). The rabbit as a model for reproductive and developmental toxicity studies. Reprod Toxicol 14, 477–93. Gad, S. C. (2000). Pigs and ferrets as models in toxicology and biological safety assessment. Int J Toxicol 19, 149–68. doi: 10915810050074928. Gibbs, R. A., Weinstock, G. M., Metzker, M. L., Muzny, D. M., Sodergren, E. J., Scherer, S., Scott, G., et al. (2004). Genome sequence of the Brown Norway rat yields insights into mammalian evolution. Nature 428, 493–521 Groenen, M. A., Archibald, A. L., Uenishi, H., Tuggle, C. K., Takeuchi, Y., Rothschild, M. F., Rogel-Gaillard, C., et al. (2012). Analyses of pig genomes provide insight into porcine demography and evolution. Nature 491, 393–98.

Bhoumik et al. Heckel, T., Schmucki, R., Berrera, M., Ringshandl, S., Badi, L., Steiner, G., Ravon, M., et al. (2015). Functional analysis and transcriptional output of the Go¨ttingen minipig genome. BMC Genomics 16, 932. Hermsen, R., de Ligt, J., Spee, W., Blokzijl, F., Scha¨fer, S., Adami, E., Boymans, S., et al. (2015). Genomic landscape of rat strain and substrain variation. BMC Genomics 16, 357. Higashino, A., Sakate, R., Kameoka, Y., Takahashi, I., Hirata, M., Tanuma, R., Masui, T., Yasutomi, Y., and Osada, N. (2012). Whole-genome sequencing and analysis of the Malaysian cynomolgus macaque (Macaca fascicularis) genome. Genome Biol 13, R58. Hoeppner, M. P., Lundquist, A., Pirun, M., Meadows, J. R., Zamani, N., Johnson, J., Sundstro¨m, G., et al. (2014). An improved canine genome and a comprehensive catalogue of coding genes and non-coding transcripts. PLoS ONE 9, e91172. Iannaccone, P. M., and Jacob, H. J. (2009). Rats! Disease Models & Mechanisms 2, 206–10. doi: ICH (International Conference on Harmonization). (1997). ICH S6 (R1)— Preclinical safety evaluation of biotechnology-derived pharmaceuticals. Gl, Step 5, 22. doi: ICH guideline. (2012). Guidance for industry S6—Addendum to preclinical safety evaluation of biotechnology-derived pharmaceuticals. Accessed October 14, 2016. . . . /Guidances/ UCM194490.pdf. International Human Genome Sequencing Consortium. (2003). Accessed October 14, 2016. national-consortium-completes-hgp/. International Human Genome Sequencing Consortium. (2013). Accessed October 14, 2016. 8-released/. Jeppesen, G., and Skydsgaard, M. (2014). Spontaneous background pathology in Go¨ttingen Minipigs. Toxicol Pathol 43, 257–66. Katschke, K. J., Stawicki, S., Yin, J., Steffek, M., Xi, H., Sturgeon, L., Hass, P. E., et al. (2009). Structural and functional analysis of a C3bspecific antibody that selectively inhibits the alternative pathway of complement. J Biol Chem 284, 10473–79. doi: jbc.M809106200. Keane, T. M., Goodstadt, L., Danecek, P., White, M. A., Wong, K., Yalcin, B., Heger, A., et al. (2012). Mouse genomic variation and its effect on phenotypes and gene regulation. Nature 477, 289–94. Kita, Y. F., Hosomichi, K., Kohara, S., Itoh, Y., Ogasawara, K., Tsuchiya, H., Torii, R., et al. (2009). MHC class I A loci polymorphism and diversity in three Southeast Asian populations of cynomolgus macaque. Immunogenetics 61, 635–48. doi: Ko, T. M., Chung, W. H., Wei, C. Y., Shih, H. Y., Chen, J. K., Lin, C. H., Chen, Y. T., and Hung, S. I. (2011). Shared and restricted T-cell receptor use is crucial for carbamazepine-induced Stevens–Johnson syndrome. J Allergy Clin Immunol 128, 1266–76.e11. doi: Kronenberg, S., Com, S. K., Baumann, A., De Haan, L., Hinton, H. J., Moggs, J., Theil, F. P., Wakefield, I., and Singer, T. (2013). Current challenges and opportunities in nonclinical safety testing of biologics. Drug Discov Today 18, 1138–43. doi: Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C., Zody, M. C., Baldwin, J., Devon, K., et al. (2001). Initial sequencing and analysis of the human genome. Nature 409, 860–921. Lehmann, H. (1998). The minipig in general toxicology. Scand J Lab Anim Sci 25, 59–62. Lindblad-Toh, K., Wade, C. M., Mikkelsen, T. S., Karlsson, E. K., Jaffe, D. B., Kamal, M., Clamp, M., et al. (2005). Genome sequence, comparative analysis and haplotype structure of the domestic dog. Nature 438, 803–19. Liu, Y., Zhang, X., Han, C., Wan, G., Huang, X., Ivan, C., Jiang, D., et al. (2015). TP53 loss creates therapeutic vulnerability in colorectal cancer. Nature 520, 697–701. doi: Mahler, J. F., Stokes, W., Mann, P. C., Takaoka, M., Maronpot, R. R., Mice, F. V. B. N., and Carolina, N. (2016). Spontaneous lesions in aging FVB/N mice. Toxicol Pathol 24, 710–16. doi: Mak, I. W., Evaniew, N., and Ghert, M. (2014). Lost in translation: Animal models and clinical trials in cancer treatment. Am J Trans Res 6, 114–18.

125 Marmoset Genome Sequencing and Analysis Consortium. (2014). The common marmoset genome provides insight into primate biology and evolution. Nat Genet 46, 850–57. doi: Marthas, M. L., Lu, D., Penedo, M. C., Hendrickx, A. G., and Miller, C. J. (2001). Titration of an SIVmac251 stock by vaginal inoculation of Indian and Chinese origin rhesus macaques: Transmission efficiency, viral loads, and antibody responses. AIDS Res Hum Retroviruses 17, 1455–66. doi: Matthews, R. A. J. (2008). Medical progress depends on animal models— doesn’t it? J R Soc Med 101, 95–98. doi: 070164. Mitchell, D. J., and Creasy, D. M. (2007). Sexual maturity and age of animals in preclinical studies to support ‘‘first in man’’ studies. Poster at 46th Annual Meeting of the Society of Toxicology, Charlotte, North Carolina, March 25–29, 2007. Paulson, S. K., Engel, L., Reitz, B., Bolten, S., Burton, E. G., Maziasz, T. J., Yan, B., and Schoenhard, G. L. (1999). Evidence for polymorphism in the canine metabolism of the cyclooxygenase 2 inhibitor, celecoxib. Drug Metab Dispos 27, 1133–42. Peng, X., Alfo¨ldi, J., Gori, K., Eisfeld, A. J., Tyler, S. R., Tisoncik-Go, J., Brawand, D., et al. (2014). The draft genome sequence of the ferret (Mustela putorius furo) facilitates study of human respiratory disease. Nat Biotechnol 32, 1250–55. Pritchard, J. B., French, J. E., Davis, B. J., and Haseman, J. K. (2003). The role of transgenic mouse models in carcinogen identification. Environ Health Perspect 111, 444–54. doi: Rhesus Macaque Genome Sequencing and Analysis Consortium, Gibbs, R. A., Rogers, J., Katze, M. G., Bumgarner, R., Weinstock, G. M., Mardis, E. R., et al. (2007). Evolutionary and biomedical insights from the rhesus macaque genome. Science 316, 222–34. Robertson, D. G., Breider, M. A., and Milad, M. A. (2001). Preclinical safety evaluation of avasimibe in beagle dogs: An ACAT inhibitor with minimal adrenal effects. Toxicol Sci 59, 324–34. doi: 59.2.324. Rocca, M. S., and Wehner, N. G. (2009). The guinea pig as an animal model for developmental and reproductive toxicology studies. Birth Defects Res Part B Dev Reprod Toxicol 86, 92–97. doi: Roden, D. M., and George, A. L. (2002). The genetic basis of variability in drug responses. Nat Rev Drug Discov 1, 37–44. doi: Sato, J., Doi, T., Wako, Y., Hamamura, M., Kanno, T., Tsuchitani, M., and Narama, I. (2012). Histopathology of incidental findings in beagles used in toxicity studies. J Toxicol Pathol 25, 103–34. doi: tox.25.103. Seok, J., Warren, H. S., Cuenca, A. G., Mindrinos, M. N., Baker, H. V., Xu, W., Richards, D. R., et al. (2013). Genomic responses in mouse models poorly mimic human inflammatory diseases. Proc Natl Acad Sci U S A 110, 3507–12. Singer, J. B., Lewitzky, S., Leroy, E., Yang, F., Zhao, X., Klickstein, L., Wright, T. M., Meyer, J., and Paulding, C. A. (2010). A genome-wide study identifies HLA alleles associated with lumiracoxib-related liver injury. Nat Genet 42, 711–14. doi: Smith, D., Broadhead, C., Descotes, G., Fosse, R., Hack, R., Krauser, K., Pfister, R., et al. (2002). Preclinical safety evaluation using nonrodent species: An industry/welfare project to minimize dog use. ILAR J 43, S39–42. Stevison, L. S., and Kohn, M. H. (2009). Divergence population genetic analysis of hybridization between rhesus and cynomolgus macaques. Mol Ecol 18, 2457–75. doi: Swindle, M. M., Makin, A., Herron, A. J., Clubb, F. J., and Frazier, K. S. (2012). Swine as models in biomedical research and toxicology testing. Vet Pathol 49, 344–56. doi: Tirmenstein, M., Horvath, J., Graziano, M., Mangipudy, R., Dorr, T., Colman, K., Zinker, B., et al. (2015). Utilization of the Zucker Diabetic Fatty (ZDF) rat model for investigating hypoglycemia-related toxicities. Toxicol Pathol 43, 825–37. doi: ¨ berg, To¨rnqvist, E., Annas, A., Granath, B., Jalkesten, E., Cotgreave, I., and O M. (2014). Strategic focus on 3R principles reveals major reductions in the

126 use of animals in pharmaceutical toxicity testing. PloS One 9, e101638. doi: Vamathevan, J. J., Hall, M. D., Hasan, S., Woollard, P. M., Xu, M., Yang, Y., Li, X., et al. (2013). Minipig and beagle animal model genomes aid species selection in pharmaceutical discovery and development. Toxicol Appl Pharmacol 270, 149–57. doi: Vana, G., and Meingassner, J. G. (2000). Morphologic and immunohistochemical features of experimentally induced allergic contact dermatitis in Go¨ttingen minipigs. Vet Pathol 37, 565–80. Venter, J. C., Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., Smith, H. O., et al (2001). The sequence of the human genome. Science 291, 1304–51. Vidal, J. D., Drobatz, L. S., Holliday, D. F., Geiger, L. E., and Thomas, H. C. (2010). Spontaneous findings in the heart of Mauritian-origin cynomolgus macaques (Macaca fascicularis). Toxicol Pathol 38, 297–302. doi:http:// Warncke, M., Calzascia, T., Coulot, M., Balke, N., Touil, R., Kolbinger, F., and Heusser, C. (2012). Different adaptations of IgG effector function in human and nonhuman primates and implications for therapeutic antibody

Toxicologic Pathology 45(1) treatment. J Immunol 188, 4405–11. doi: 1200090. Warren, W. C., Jasinska, A. J., Garcı´a-Pe´rez, R., Svardal, H., Tomlinson, C., Rocchi, M., Archidiacono, N., et al. (2015). The genome of the vervet (Chlorocebus aethiops sabaeus), Genome Res 25, 1921–33. Yan, G., Zhang, G., Fang, X., Zhang, Y., Li, C., Ling, F., Cooper, D. N., et al. (2011). Genome sequencing and comparison of two nonhuman primate animal models, the cynomolgus and Chinese rhesus macaques. Nat Biotechnol 29, 1019–23. Waterston, R. H., Lindblad-Toh, K., Birney, E., Rogers, J., Abril, J. F., Agarwal, P., Agarwala, R., et al. (2002). Initial sequencing and comparative analysis of the mouse genome. Nature 420, 520–62. Zhang, X., Liu, H.-H., Weller, P., Zheng, M., Tao, W., Wang, J., Liao, G., Monshouwer, M., and Peltz, G. (2011). In silico and in vitro pharmacogenetics: Aldehyde oxidase rapidly metabolizes a p38 kinase inhibitor. Pharmacogenomics J 11, 15–24. doi: Zimin, A. V., Cornish, A. S., Maudhoo, M. D., Gibbs, R. M., Zhang, X., Pandey, S., Meehan, D. T., et al. (2014). A new rhesus macaque assembly and annotation for next-generation sequencing analyses. Biology Direct 9, 20.