BJP British Journal of Pharmacology DOI:10.1111/bph.12979 www.brjpharmacol.org REVIEW Correspondence Physiological, pharmacological and toxicological considerations of drug-induced structural cardiac injury Michael J Cross, MRC Centre for Drug Safety Science, Department of Molecular and Clinical Pharmacology, Sherrington Building, Ashton Street, The University of Liverpool, Liverpool L69 3GE, UK E-mail: m.j.cross@liv.ac.uk *Current address: Vanderbilt University School of Medicine, Cardiology Division, Nashville, TN, USA Received 17 June 2014 Revised M J Cross1, B R Berridge2, P J M Clements3, L Cove-Smith4, T L Force5*, P Hoffmann6, M Holbrook7, A R Lyon8, H R Mellor9, A A Norris1, M Pirmohamed10, J D Tugwood4, J E Sidaway11 and B K Park1 30 September 2014 Accepted October 2014 MRC Centre for Drug Safety Science, Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK, 2Safety Assessment, GlaxoSmithKline, Research Triangle Park, NC, USA, 3David Jack Centre for Research & Development, GlaxoSmithKline, Ware, Herts, UK, 4Clinical & Experimental Pharmacology, Cancer Research UK Manchester Institute, University of Manchester, Manchester, UK, 5Center for Translational Medicine and Cardiology Division, Temple University School of Medicine, Philadelphia, PA, USA, 6Preclinical Safety, Novartis Pharm Corp, East Hanover, NJ, USA, 7Safety Pharmacology, Covance Laboratories, Ltd., Harrogate, North Yorkshire, UK, 8NIHR Cardiovascular Biomedical Research Unit, Royal Brompton Hospital and Imperial College, London, UK, 9Drug Safety Evaluation, Vertex Pharmaceuticals (Europe), Ltd., Abingdon, Oxfordshire, UK, 10The Wolfson Centre for Personalised Medicine, Institute of Translational Medicine, University of Liverpool, Liverpool, UK, 11 Innovative Medicines, AstraZeneca R&D, Macclesfield, UK and The incidence of drug-induced structural cardiotoxicity, which may lead to heart failure, has been recognized in association with the use of anthracycline anti-cancer drugs for many years, but has also been shown to occur following treatment with the new generation of targeted anti-cancer agents that inhibit one or more receptor or non-receptor tyrosine kinases, serine/threonine kinases as well as several classes of non-oncology agents A workshop organized by the Medical Research Council Centre for Drug Safety Science (University of Liverpool) on September 2013 and attended by industry, academia and regulatory representatives, was designed to gain a better understanding of the gaps in the field of structural cardiotoxicity that can be addressed through collaborative efforts Specific recommendations from the workshop for future collaborative activities included: greater efforts to identify predictive (i) preclinical; and (ii) clinical biomarkers of early cardiovascular injury; (iii) improved understanding of comparative physiology/pathophysiology and the clinical predictivity of current preclinical in vivo models; (iv) the identification and use of a set of cardiotoxic reference compounds for comparative profiling in improved animal and human cellular models; (v) more sharing of data (through publication/consortia arrangements) on target-related toxicities; (vi) strategies to develop cardio-protective agents; and (vii) closer interactions between preclinical scientists and clinicians to help ensure best translational efforts Abbreviations ABPI, Association for British Pharmaceutical Industry; hESC-CM, human embryonic stem cell-derived cardiomyocyte; HF, heart failure; LVD, left ventricular dysfunction; LVEF, left ventricular ejection fraction; SCD, sudden cardiac death; TKI, tyrosine kinase inhibitor © 2014 The British Pharmacological Society British Journal of Pharmacology (2015) 172 957–974 957 M J Cross et al BJP Tables of Links TARGETS LIGANDS Other protein targetsa Catalytic receptorsd Enzymese 5-fluorouracil Imatinib FABP c-Met (Met) ACE Axitinib Lapatinib TNF Axl AMPK Bevacizumab Neuregulin-1 Pazopanib b GPCRs EphA2 Brk BNP 5-HT receptors ErbB1 (EGFR) ERK5 Cabozantinib Pertuzumab Angiotensin receptors ErbB2 (HER2) ILK Carvedilol Ponatinib β-adrenoceptors ErbB4 (HER4) MEK1 Casopitant Regorafenib Sorafenib NK1 receptor FGFR MEK2 Crizotinib Ion channelsc FLT3 MMPs Cyclophosphamide Sunitinib hERG (KV11.1) Kit p38α Dabrafenib Trametinib Trastuzumab (Herceptin) PDGFRα PDE3 Dasatinib PDGFRβ PDK1 Dexrazoxane Vandetanib Ret PTEN Doxorubicin Vemurafenib TGFBR1 (ALK5) a-Raf Enalapril Vincristine TIE2 b-Raf Erlotinib TrkB c-Raf VEGFR-1 Src family VEGFR-2 VEGFR-3 These Tables list key protein targets and ligands/inhibitors in this article which are hyperlinked to corresponding entries in http:// www.guidetopharmacology.org, the common portal for data from the IUPHAR/BPS Guide to PHARMACOLOGY (Pawson et al., 2014) and are permanently archived in the Concise Guide to PHARMACOLOGY 2013/14 (a,b,c,d,eAlexander et al., 2013a,b,c,d,e) Introduction Cardiovascular toxicities are observed with therapeutic agents used in the treatment of both cardiovascular and noncardiovascular diseases and affect all components of the CVS Cardiovascular adverse reactions can occur after acute or chronic treatment and can affect function (e.g alteration of the mechanical function of the myocardium) and/or structure (e.g morphological damage or loss of cellular/subcellular components of the heart) or vasculature They remain a major cause of drug attrition during preclinical and clinical development, and drug withdrawals from the marketplace This was highlighted in a scientific workshop on cardiovascular toxicity, which covered a wide range of potential liabilities, held at the Medical Research Council (MRC) Centre for Drug Safety Sciences (CDSS) in January 2010 (Laverty et al., 2011) A recommendation from the workshop was to reconvene to discuss in greater detail a small number of selected cardiovascular liabilities On September 2013, a workshop was hosted by the MRC CDSS (http://www.liv.ac.uk/drug-safety), University of Liverpool, in conjunction with the Association of the British Pharmaceutical Industry (ABPI) and the Medicines and Healthcare Products Regulatory Agency It discussed current challenges in determining and understanding ‘Structural Cardiotoxicity of Medicines’ as a major and emerging issue in the development of new therapies – particularly oncology agents The key aims of the workshop were to identify those areas of 958 British Journal of Pharmacology (2015) 172 957–974 cardiovascular safety testing where our knowledge and understanding should be further strengthened and to recommend areas where collaborative efforts should be focused The workshop was attended by representatives from pharmaceutical and biotechnology companies, contract research organizations, regulatory agencies and academia Drug-induced structural cardiac damage is associated with changes in multiple cardiac cell types leading to cardiac fibrosis and cardiomyopathy (deterioration of the function of the myocardium due to injury) and subsequently, heart failure (HF) Structural cardiotoxicity is a concern with several classes of anti-cancer agents as any gain in life expectancy from therapeutic intervention might be countered by increased morbidity and mortality due to a variety of cardiovascular problems, including: heart muscle injury with cardiomyopathy and HF, complications of coronary artery disease leading to myocardial ischaemia, arrhythmias, hypertension and thromboembolism (Stortecky and Suter, 2010; Berardi et al., 2013) Patnaik et al (2011) showed that after 8–9 years following initiation of drug treatment, mortality in breast cancer patients as a result of cardiovascular toxicity overtakes risk of death from breast cancer recurrence The incidence of structural cardiotoxicity depends on a number of different factors related to therapy (e.g type of drug, dose administered during each cycle, cumulative dose, schedule of administration, route of administration, combination of other cardiotoxic drugs or association with radiotherapy covering the heart in the therapeutic field) and also to the patient phenotype based Drug-induced cardiac injury on pre-existing cardiovascular risk (e.g age, presence of ‘traditional’ cardiovascular risk factors, underlying cardiac dysfunction and any prior exposure to cardiotoxic chemotherapy or radiotherapy) Cardiotoxic effects can occur immediately following drug administration, or they may not manifest themselves until months or, in some examples, many years after the patient has been treated There are a number of clinical challenges in managing cancer drug-treated patients and it is crucial that appropriate risk stratification based on previous drug exposure and patient phenotype is addressed Significant challenges to preclinical assessment are also apparent as attempts to model the clinical factors, highlighted earlier, may have dubious translatable value Although the use of traditional cancer therapies such as anthracyclines (Von Hoff et al., 1979) and radiation (Boivin et al., 1992) have long been associated with cardiac complications (up to a 20% risk of HF after 20 years following a period of treatment with chemotherapy and radiotherapy) (Hooning et al., 2007) other agents such as cyclophosphamide, 5-fluorouracil and paclitaxel are known to cause cardiac injury as well, albeit at lower rates than anthracyclines Dosing regimens and newer agents, plus pre-screening to exclude patients with reduced cardiac function at baseline, have helped to reduce risk in current patients receiving anthracyclines, but in contemporary studies the rate of left ventricular dysfunction (LVD) is still between 5–20% (Shakir and Rasul, 2009) depending upon the definition applied and follow-up duration The more recently introduced ‘targeted therapies’, which inhibit various PKs have also been associated with cardiotoxicity, through both on-target and off-target effects The toxicity of these agents is through different molecular and cellular mechanisms of cardiotoxicity to those caused by anthracyclines (Force and Kolaja, 2011; Mellor et al., 2011) However, in many cases, the adverse clinical cardiac events observed were not anticipated based on preclinical evaluation of these compounds It is therefore important to identify new models/techniques, which can better predict adverse clinical outcomes with these agents We set out to address the following points at the workshop: • What pathologies come under the banner of ‘cardiovascular toxicity’ and how well we understand these as individual pathologies and components of a syndrome? • What is the prevalence of the recognized individual pathologies, and how well we understand their pathogenesis? • How good is our mechanistic understanding of cancer therapeutics-induced structural cardiotoxicity? • How well we understand patient susceptibilities to cardiotoxicity and we need animal models of ‘disease’ and/or ‘physiological challenge’? • How translatable are animal pathologies to the relevant human pathology? • How can we share data on target-driven toxicities more efficiently to avoid a repetition of unnecessary animal research and preclinical toxicology studies? • Can functional changes predict specific pathologies (and vice versa)? • Can we identify/improve in vitro assays to model and predict specific animal/human pathologies? BJP This publication incorporates the key issues highlighted during the workshop along with the gap analysis and identifies key areas where a concerted effort could make a real difference by reducing cardiovascular liabilities of new medicines Clinical definitions of cardiovascular toxicity related to oncology therapies Drug-induced cardiovascular toxicity may develop acutely or subacutely during or after a treatment period and effects may include disorders such as myocardial dysfunction, ischaemia, hypotension, hypertension, QT-interval prolongation, arrhythmias and thromboembolism Chronic consequences of cardiomyocyte insult may manifest as an ‘early’ cardiomyopathy within the first year after treatment cessation or as a ‘later’ cardiomyopathy, occurring more than year afterwards; these probably represent a continuous spectrum of the same pathophysiology, with dose and coexisting risk factors determining the rate of progression of cardiac dysfunction Clinical presentation late in the course of the HF progression represents the most problematic type of injury The most common initial feature of chronic cardiotoxicity is asymptomatic systolic LVD; left untreated, this may progress to congestive HF This initial dysfunction may not be clinically apparent (i.e asymptomatic) for many years because of attempted normalization of function by compensatory mechanisms, as seen following other forms of cardiac injury such as acute myocardial infarction The incidence of chronic cardiotoxicity is influenced by a number of factors such as cumulative dose of chemotherapy administered, age of patient, cardiovascular disease history and prior radiation therapy, and can range from to 65% of patients treated with anthracyclines (Dolci et al., 2008) Anthracyclines produce a dose-related cardiac dysfunction, defined as type I cardiotoxicity (Ewer and Lippman, 2005), characterized by cardiomyocyte ultrastructural abnormalities, (vacuoles, myofibrillar disarray and dropout, necrosis), contractile abnormalities (dilated cardiomyopathy) and subsequent clinically evident dysfunction (Billingham et al., 1978) Some elements are initially reversible, but over time the burden of fibrosis and myocyte loss to apoptosis renders the dysfunction currently irreversible and more refractory to current HF therapy In contrast, cardiac dysfunction not associated with ultrastructural change, described as type II, typically manifests as an asymptomatic decrease in left ventricular ejection fraction (LVEF) (expressed as a percentage of the total amount of blood in the left ventricle that is ejected in each heartbeat, with a range of 55–70% in healthy individuals) and less often by clinical HF (Ewer and Lippman, 2005) Agents such as trastuzumab (Herceptin®, Genentech/ Roche, San Francisco, CA, USA) and the low molecular weight tyrosine kinase inhibitors (TKIs) for example sunitinib (Sutent®, Pfizer, New York, NY, USA), imatinib (Gleevec®, Novartis, Basel, Switzerland), lapatinib (Tykerb®, GlaxoSmithKline, London, UK) and sorafenib (Nexavar®, Bayer, Leverkusen, Germany) (see Table 1) are believed to cause type II cardiac dysfunction (Ewer and Ewer, 2010), although the cellular mechanism may be very drug-specific rather than a British Journal of Pharmacology (2015) 172 957–974 959 BJP M J Cross et al Table Adverse preclinical and clinical cardiac effects – approved kinase inhibitors used in oncology (adapted from Mellor et al., 2011) Drug/ Biological Target(s) Oncology indications Preclinical cardiac findings Clinical cardiac findings Axitinib (Inlyta®) VEGFR1/2/3 RCC Modest dose-dependent elevation in systolic BP in rats Hypertension Inlyta® FDA Pharm Review Inlyta® Prescribing Information Bevacizumab (Avastin®) VEGF CRC, NSCLC; breast cancer; None reported HF, hypertension, ischaemia Choueiri et al (2011) Chen et al (2013) Avastin® Prescribing Information Metastatic Cardiac inflammation noted in medullary a single female dog when thyroid cancer administered for a month period Hypertension Cometriq® Prescribing Information Cabozantinib Ret, Met, VEGFR1/2/3, (Cometriq®) Kit, trkB, FLT3, Axl, TIE2 References Crizotinib (Xalkori®) ALK, c-Met (HGFR), and ROS ALK-positive NSCLC Dose-dependent inhibition of the hERG current, decrease in HR and increase in left ventricular end-diastolic pressure in dogs, myonecrosis in rats QT-interval prolongation, bradycardia Xalkori® FDA Pharm Review Xalkori® Prescribing Information Dabrafenib (Tafinlar®) B-Raf MM Adverse cardiovascular effects in dogs consisting of coronary arterial degeneration/necrosis and haemorrhage, as well as cardiac atrio-ventricular valve hypertrophy/haemorrhage QT-interval prolongation, decreased LVEF Taflinar® Prescribing Information Dasatinib (Sprycel®) Bcr-Abl, Src family, Kit, PDGFRβ, EphA2 CML, ALL QT prolongation, increased BP QT-interval prolongation, Brave et al (2008) Vascular and cardiac fibrosis, HF, pericardial and Montani et al (2012) cardiac hypertrophy, pleural effusion, Sprycel® Prescribing Information myocardial necrosis, pulmonary hypertension haemorrhage of the valves, ventricle and atrium and cardiac inflammation Erlotinib (Tarceva®) ErbB1 (EGFR) RCC None reported Myocardial infarction/ischaemia Tarceva® Prescribing Information Imatinib mesylate (Gleevec®) Bcr-Abl, PDGFRα CML, ALL, GIST, and β, Kit MDS/MPD, ASM, HES, CEL, DFSP Reversible hypertrophy in rats Decrease in arterial BP after single i.v dose in rats No effect on the rate of beating or force of contraction in the isolated atria of guinea pigs Decreased LVEF, LVD, rare frequency of HF Kerkelä et al (2006) Gleevec® FDA Pharm Review Gleevec® Prescribing Information Lapatinib (Tykerb®) EGFR (ErbB1), HER-2 (ErbB2) Dose-responsive increase in BP in dog Focal fibrosis and myocyte degeneration in rat and dog No QT changes in rat and dog Decreased LVEF, HF, asymptomatic cardiac events, QT-interval prolongation Perez et al (2008) Tykerb® FDA Pharm Review Tykerb® Prescribing Information Nilotinib (Tasigna®) Bcr-Abl, PDGFRα CML and β, Kit QT-interval prolongation QT-interval prolongation, sudden death (possibly ventricular repolarization related) Ischaemia, peripheral ischemia Kantarjian et al (2007) Tefferi (2013) Weisberg et al (2005) Tasigna® Prescribing Information 960 HER-2+ ve breast cancer British Journal of Pharmacology (2015) 172 957–974 Drug-induced cardiac injury BJP Table Continued Drug/ Biological Target(s) Oncology indications Preclinical cardiac findings Clinical cardiac findings References Pazopanib (Votrient®) VEGFR1, VEGFR2, VEGFR3, PDGFRa/βKit RCC Acute increase in BP after dosing and decreased heart rate from 75 to 24.5 h post-dose in monkeys Cardiac dysfunction (congestive HF and decreased LVEF), QT prolongation, cases of Torsades de Pointes in clinical programme, hypertension Motzer et al (2013) Votrient® FDA Pharm Review Votrient® Prescribing Information Pertuzumab (Perjeta®) HER-2 (ErbB2) Breast cancer None reported Decreased LVEF, HF Perjeta® Prescribing Information Ponatinib (Iclusig®) Bcr-Abl, Bcr-Abl T315I, VEGFR, PDGFR, FGFR, Eph, Src family kinases, Kit, Ret, TIE2 and FLT3 CML, Ph chromosomepositive ALL Inhibition of hERG current in dose-dependent manner, systolic heart murmurs and myocardial necrosis in monkeys HF, myocardial ischaemia, peripheral ischaemia (stroke, peripheral vascular disease) Iclusig® FDA Pharm Review Iclusig® Prescribing Information Regorafenib (Stivarga®) VEGFR1/2/3, BCR-Abl, B-Raf, B-Raf (V600E), Kit, PDGFRα/β, Ret, FGFR1/2, TIE2 and EphA2 CRC Dose-dependent increase in the finding of thickening of the atrio-ventricular valve in rats at months Hypertension, myocardial ischaemia and infarction Stivarga® Prescribing Information Sorafenib (Nexavar®) Raf-1 (c-Raf), b-Raf , VEGFR1, & 3, PDGFR family, Kit HCC, RCC hERG K-current and Ca-inward current inhibition No ECG, BP or heart rate changes observed in 12 month dog study Autolysis, degeneration and inflammation in month rat study An increase in CK levels with haemorrhage and congestion of the heart in one animal in 12 month dog study QT-interval prolongation, sudden death (possibly ventricular repolarization related), HF (cardiomyopathy), coronary vasospasm, arterial thrombosis Choueiri et al (2010) Escudier et al (2009) Naib et al (2011) Schmidinger et al (2008) Uraizee et al (2011) Veronese et al (2006) Nexavar® FDA Pharm Review Nexavar® Prescribing Information Sunitinib malate (Sutent®) VEGFR1-3, PDGFRα and β, CSFR1, Ret kinase, Kit, FLT3 kinase RCC, GIST Potent hERG channel block and QT-interval prolongation and HR reduction at doses equivalent to human clinical exposures Multiple ECHO parameter changes in primate including reductions in the ratio of right atrial to aortic diameter, LVEF time and LV area Histopathological findings included capillary proliferation, myocardial vacuolization and pericardial inflammation QT-interval prolongation, decreased LVEF, LVD, HF, increased BP, CHF linked to cardiovascular co-morbidities, arterial thrombosis Bello et al (2009) Choueiri et al (2010) Chu et al (2007) Faivre et al (2006) Telli et al (2008) Sutent® FDA Pharm Review Sutent® Prescribing Information Trametinib (Mekinist®) MEK1, MEK2, MEK1 kinase, MEK2 kinase MM Inhibition of hERG channel, cardiomyopathy (decreased LVEF, increased heart weight) in mice Cardiomyopathy (cardiac failure, LVD, or decreased LVEF) Mekinist® FDA Pharm Review Mekinist® Prescribing Information British Journal of Pharmacology (2015) 172 957–974 961 BJP M J Cross et al Table Continued Drug/ Biological Target(s) Oncology indications Preclinical cardiac findings Clinical cardiac findings References Trastuzumab (Herceptin®) HER-2 (ErbB2) HER-2+ ve breast cancer None reported No evidence of toxicity in primate studies up to months Decreased LVEF, HF, increased risk if prior or concurrent anthracycline treatment Seidman et al (2002) Herceptin® FDA Pharm Review Herceptin®Prescribing Information Vandetanib (Caprelsa®) EGFRs, VEGFRs, Ret, Brk, TIE2, Eph receptors and Src Medullary thyroid cancer Inhibition of hERG channel, increase in BP in rats,increased QTc and BP in dogs QT-interval prolongation, Torsades de Pointes, acute cardiac failure, hypertension, Scheffel et al (2013) Caprelsa® Prescribing Information Vemurafenib (Zelboraf®) a/b/c-Raf and b-Raf MM Inhibition of hERG channel, increase in incidence of AV block in dogs, increased heart weight in rats QT-interval prolongation Zelboraf® FDA Pharm Review Zelboraf® Prescribing Information Ziv-aflibercept (Zaltrap®) VEGF CRC None reported Hypertension Zaltrap® Prescribing Information ALL, acute lymphocytic leukaemia; AP, action potential; ASM, aggressive systemic mastocytosis; AV, atrioventricular; CEL, chronic eosinophilic leukaemia; CK, creatinine kinase; CRC, colorectal cancer; DFSP, dermatofibrosarcoma protuberans; GIST, gastrointestinal stromal tumour; HCC, hepatocellular carcinoma; HES, hypereosinophilic syndrome; HR, heart rate; MDS, myelodysplastic syndrome; MM, metastatic melanoma; MPD, myeloproliferative disorder; NSCLC, non-small cell lung cancer; RCC, renal cell carcinoma class effect, reflecting both on target and off-target toxicity Typical features in this setting include lack of an obvious dose–relationship, increase in toxicity when given concurrently with anthracyclines, some reversibility after stopping treatment and restoration of normal cardiac function with appropriate medical management (Perik et al., 2007; Slamon et al., 2011) Many of these observations derived from cardiac safety analyses in oncology trials where patients were typically younger and pre-screened to exclude those with preexisting cardiovascular disease, thereby preselected as more resistant to cardiotoxicity from that class of drugs Cardiotoxicity rates tend to be higher in clinical practice compared with those reported in oncology trials (Farolfi et al., 2013), reversibility is less common, and duration of treatment, and therefore dose, may contribute to a cumulative risk Early detection of subclinical cardiac dysfunction could lead to the identification, drug-intervention (e.g ACE inhibitor and β-blocker) and prevention of late adverse cardiac events and this is ultimately the goal for both cardiologists and oncologists Collection of endomyocardial biopsies to identify histopathological evidence of myofibrillar loss is an inaccurate and impractical form of monitoring heart damage The use of LVEF as the only parameter of cardiac function is increasingly viewed, by the cardiology community, as an inadequate measure to predict and monitor cardiac damage Nevertheless, LVEF is measured routinely as 2-D echocardiography (Echo) is the methodology of choice for frequent monitoring and is cost-effective and has fairly widespread availability, despite its known higher method variability Other screening modalities, such as cardiac MRI, are gaining in popularity, because of low inter-scan variability and ability to offer virtual histology, which is capable of detecting signs 962 British Journal of Pharmacology (2015) 172 957–974 of fibrosis when combined with the contrast agent gadolinium (Tandri et al., 2005) Although there is no clear definition of cardiotoxicity, a practical and easily applicable definition was created by a panel of investigators involved in the clinical development of trastuzumab (Seidman et al., 2002), which considered chemotherapy-induced cardiotoxicity as either a 5% decline from baseline LVEF to less than 55% overall with accompanying signs or symptoms of HF, or asymptomatic decrease in LVEF in the range of equal to or greater than 10% to less than 55% Other trials have used 50% as the threshold to define cardiotoxicity, but given the potential variability of Echobased LVEF measurements as discussed earlier, in reality, this depends upon the low limit of normal (LLN) for a healthy population for individual centres, and therefore current guidance is to determine LLN and interpret the guidance using local cut-off values The extent to which this is practised in the real world has yet to be clarified Medical management of anthracycline-induced HF is based largely on the use of agents used to treat HF, including ACE inhibitors, β-blockers and aldosterone antagonists, with loop diuretics for decreasing fluid retention In a recent study of patients with an anthracycline-induced decrease in LVEF ≤ 45%, treatment with enalapril and carvedilol resulted in normalization of LVEF in 42% of patients (Cardinale et al., 2010) These responders had a higher LVEF after HF treatment compared with partial responders (whose LVEF increased >10%, but did not normalize) and nonresponders who were most resistant to HF treatment and failed to improve ventricular function A striking observation was that the patients in the responder group all had their ‘rescue’ HF therapy initiated within months of the chemotherapy, whereas if it was Drug-induced cardiac injury initiated beyond months then response was considerably less This is particularly important in light of recent data that indicates that only 31% of patients receiving chemotherapy with an asymptomatic decrease in LVEF receive an ACE inhibitor or angiotensin receptor blocker, 35% receive a β-blocker and 42% are referred for cardiology consultation (Yoon et al., 2010) This emphasizes the importance of appropriate communication between the oncologist and cardiologist and highlights that early detection and treatment of cardiac injury is critical to a successful outcome Drug-induced myocardial injury: pathogenesis and manifestations For preclinical structural cardiotoxicity, in the absence of a clear target-driven liability, the underlying molecular mechanism(s) are rarely known It is crucial therefore to build an understanding of the pathogenesis of the toxicity, the monitorability and safety margin based on efficacious exposures, all to inform assessment of the potential risk to man Understanding the temporal progression of the lesion provides valuable information in understanding the pathogenesis It is also important to consider drug–target relationship, any functional correlates which may be driving the structural changes, the interplay between the cardiac and vascular systems, translational relevance to patients and to recognize that results of a repeat-dose general toxicity study (mainly macroscopic and histological data at the end of the treatment period) provide only a static picture of a process that may be temporally dynamic The best understanding therefore comes from integrating all relevant pieces of data together to reveal a wider picture Ultimately, a better understanding of the pathogenesis may help with the development of a risk mitigation strategy to include a biomarker component for clinical BJP use Although an understanding of pathogenesis can help in the management of liabilities, the identification of defined (and ideally common) molecular mechanisms of structural cardiotoxicity are required to aid in better drug design Cardiac cell injury is a continuum (Figure 1) as in many other organs and normally progresses from degeneration, necrosis, responding inflammatory changes and eventually fibrosis, which can be considered the repair process although it does not result in functional contractile tissue The ultimate impact of cellular injury on myocardial contractile function is highly dependent on the number and distribution of cells involved A non-lethal cell injury, generally considered ‘degeneration’, can be characterized by cytoplasmic vacuolation of cardiac myocytes and may be caused by lipid accumulation, mitochondrial swelling or dilation of sarcoplasmic reticulum Although a non-lethal injury suggests there is an opportunity for some reversibility of the condition, this can only be viewed in the context of the tissue; the low inherent regenerative capability of the heart suggests that any sort of adaptive response mounted to the injury may become a source of subclinical or occult change in cardiovascular function This condition may predispose to an impaired ability over time to cope with stressors such as hypertension or treatment with cardiotoxic agents leading potentially to the development of HF A lethal injury to the myocardium results in myocellular necrosis characterized by a terminal irreversible stage of cell injury (cardiomyocyte death), loss of membrane integrity and release of cytosolic proteins (potential biomarkers of cardiac injury such as troponin), in which the adverse morphological change is temporally progressive and includes an inflammatory cell infiltrate and regions of myocardium replaced by fibrosis Extensive fibrosis can affect myocardial compliance and contractility and play a direct role in the development of chronic progressive cardiomyopathies It is important Figure Schematic representation of the morphological continuum of myocardial injury and repair British Journal of Pharmacology (2015) 172 957–974 963 BJP M J Cross et al however to recognize the difference between extensive regional myocardial necrosis (i.e infarct) and the multifocal lesions often seen in response to drug-induced injury To demonstrate the usefulness of various modalities for characterizing the pathogenesis of cardiovascular injury, Casartelli et al (2011) reported an integrated and longitudinal study to investigate the onset, progression, and reversibility of an off-target cardiac lesion caused by a neurokinin (NK)-1 receptor antagonist (casopitant) in dogs, after longterm (6 months) administration with intermittent data collection Transmission electron microscopy examination revealed changes in cardiac cells with multi-lamellar bodies in sarcoplasm (associated with a progressive impairment and perturbation of cardiomyocytes) after only weeks of treatment and this coincided with an initial rise in cardiac troponin I (cTnI) After 20–26 weeks, some necrotic myofibres, filled with multi-lamellar bodies, were also observed at a time when light microscopy observations were first made The most informative picture of cardiac changes was obtained by integrating cTnI alterations (as a biomarker of cardiac damage) with EM findings as these changes preceded evidence of injury at the light microscopic level Elevations were also seen in N-terminal pro-brain natriuretic peptide (NT-pro BNP), a biomarker for the onset and evolution of cardiac hypertrophy, which started to increase after weeks of treatment, preceding most, if not all, the anatomical and functional (ECG) changes Thus, the integration of different investigative tools (in addition to the standard regulatory requirement of histopathology) provided early evidence of cardiac cell injury and a means of accurately characterizing the onset and progression of the lesion with a clear translatability to a clinical setting (i.e cTnI and NT-pro-BNP increases) Early recognition of important liabilities facilitates early decision-making around progression or strategies for mitigating risk in patients It is however unfeasible to perform EM routinely as part of a high-volume toxicity screening process and measurement of circulating predictable and specific biomarkers remains the goal Preclinical cardiotoxicity (by light microscopy) was not apparent during the development studies with the Abelson murine leukemia viral oncogene homologue (c-Ab1), PDGF and stem cell factor receptor (CD117) (c-Kit) inhibitor, imatinib although clinical findings suggestive of decreased LVEF and HF in patients without previous heart disease were reported after launch (Kerkelä et al., 2006) Taking a more translational and innovative approach, Kerkelä et al (2006) demonstrated, using transmission EM, that mitochondrial abnormalities and accumulation of membrane whorls in both vacuoles and the sarco-(endo-)plasmic reticulum of human and mouse cardiomyocytes, in vitro, were suggestive of the clinical presentation of toxic myopathy Similarly, the cardiac dysfunction (LVD, LVEF and HF) seen in patients with the multi-targeted receptor tyrosine kinase inhibitor (TKI) sunitinib (Chu et al., 2007), was subsequently ascribed, using transmission EM, to depletion of coronary microvascular pericytes resulting in changes such as increased endothelial permeability in the coronary microvasculature Pericyte loss is not a feature of cardiotoxicity reported by other agents in the TKI class and this observation indicates that injury to non-contractile elements can still progress to cardiomyopathy These findings also highlight the need for in vitro screens, 964 British Journal of Pharmacology (2015) 172 957–974 which reconstitute different cellular components to aid in specific liability identification (see section ‘Novel human cellbased models to predict cardiac microvascular toxicity’) Although there is currently significant cancer biomarker trial activity, most is related to prognostics and pharmacodynamics with relatively few studies in the area of safety biomarkers To date, little has been done to assist general practitioners in identifying cardiovascular adverse effects of cancer treatments, although there is a general awareness regarding growing late toxicity from cancer treatment as patient survival increases Investigators at the Cancer Research UK Manchester Institute (University of Manchester), in collaboration with scientists at AstraZeneca (Alderley Park, UK), have initiated a study to identify predictive biomarkers of safety in rodents in one of the few studies to capture functional change, biomarkers and histology in a longitudinal fashion Rats showed a significant reduction in LVEF after 43 days during an week continual dosing study with doxorubicin (iv), which continued after cessation of dosing with no evidence of reversibility although the point at which irreversibility occurred was not determined (Cove-Smith et al., 2014) Overt histological changes were observed after 29 days dosing although EM changes (mitochondrial damage and myocyte ultrastructural changes) occurred after a single dose to rats Functional decline (decrease of LVEF and diastolic dysfunction measured by E/A ratio) preceded the rise in cTnI and histological damage (light microscopy) However, despite the incremental decline in systolic function, the LVEF remained above the normal clinical threshold of 55% until the end of study It is envisaged that a future panel of biomarkers will help determine when cardiac damage presents initially and resolves Mechanisms of structural cardiotoxicity Understanding the mechanisms behind the cardiomyopathies that arise as a result of targeted cancer therapies and developing strategies to treat these complications are important for the cardiovascular care of the cancer patient as well as to enable future development of non-cardiotoxic drugs Furthermore, an understanding of these cardiomyopathies may also have implications for more common types of HF and may provide unexpected insights into the biology of the heart After many years of little advance in the understanding of the mechanism of toxicity of anthracyclines, recent novel findings point to a role for topoisomerase II β in inducing DNA damage in cardiomyocytes, mitochondrial dysfunction and generation of reactive oxygen species leading to cardiotoxicity (Zhang et al., 2012) There are currently over 100 TKIs in discovery or development (Broekman et al., 2011) Approximately 100 genes have been implicated in driving cancers with ∼50 being potential anti-cancer targets and a proportion are also likely to play an important role in cardiomyocyte homeostasis (see Table 2) Off-target toxicity is also a major issue as ATP competitive inhibitors demonstrate significant kinase promiscuity leading to undesirable off-target effects This lack of Drug-induced cardiac injury BJP Table Kinase/phosphatase conditional knockout mouse models associated with cardiovascular functional effects (adapted from Mellor et al., 2011) Protein Signalling role PTEN Lipid phosphatase Negative regulator of PI3-kinase signalling AMPK Knockout animal model Effect on cardiac function Reference Muscle-specific PTEN knockout mouse Basal hypertrophy Mild reduction in contractility Reduced hypertrophy in response to pressure overload compared with wt Crackower et al (2002) Oudit et al (2008) Serine/threonine kinase Activated by increase in AMP: ATP Acts to preserve/generate ATP Heterozygous AMPKα2 knockout mouse Mild reduction in contractility Worsened hypertrophy in response to pressure overload compared with wt Zhang et al (2008) SHP2 Tyrosine phosphatase Regulates leptin and insulin signalling Muscle-specific Shp2 knockout mouse Severe dilated cardiomyopathy HF and premature death Kontaridis et al (2008) Princen et al (2009) ERB2 Receptor tyrosine kinase Co-receptor in neuregulin/EGRF signalling Ventricular myocyte-specific ERB2 knockout mouse Severe dilated cardiomyopathy Decreased contractility HF and sudden death Crone et al (2002) Ozcelik et al (2002) PDK1 AGC serine/threonine kinase Activates AKT and p70S6K Muscle-specific PDK1 knockout mouse Tamoxifen-inducible heart-specific PDK1 knockout mouse Apoptotic death of cardiomyocytes Impaired LV contractility Severe and lethal HF Ito et al (2009) Mora et al (2003) Pim1 Serine/threonine kinase Acts downstream of AKT to block apoptosis Induction and stabilization of c-myc Cardiac-specific Pim-1 dominant-negative in mouse Progressive dilation Reduced contractility Increased LVEDP Decreased LVDP Alterations in Ca2+ handling Muraski et al (2008) Raf-1 (c-Raf) Serine/threonine kinase Involved in the ERK signalling pathway Cardiac-specific Raf-1 knockout mouse Reduced contractility Increased heart size Decreased posterior wall thickness Yamaguchi et al (2004) ILK Serine/threonine kinase Phosphorylates Akt and GSK-3β Muscle-specific ILK knockout mouse Increased heart size Dilated cardiomypathy Cardiac fibrosis Sudden death White et al (2006) AK1 Kinase/phosphotransferase Adenine nucleotide homeostasis AK1 knockout mouse Reduced contractility – coronary flow relationship Recovery of flow after I/R was compromised Dzeja et al (2007) p38α MAPK phosphorylates MAPKAP kinase 2, ATF-2, Mac and MEF2 Cardiac-specific p38α dominant-negative in mouse Cardiac hypertrophy reduced fractional shortening LV and septal wall thinning Lethal cardiomyopathy Braz et al (2003) ERK5 MAPK (serine/threonine kinase) phosphorylates MEF2C, Sap1a, p90RSK ERK5 knockout mouse ERK5 −/− cardiomyocyte knockout Embryonically fatal at E9.5–10.5 Defective cardiac development, heart looping, angiogenesis and vascular maturation Mice develop normally but have reduced cardiac hypertrophic remodelling Regan et al (2002) Kimura et al (2010) AMPK, AMP-activated protein kinase; ATF-2, activating transcription factor 2; GSK-3β, glycogen synthase kinase β; ILK, integrin-linked kinase; I/R, ischaemia/reperfusion; LVDP, left ventricular diastolic pressure; LVEDP, left ventricular end-diastolic pressure; MEF2, myocyte enhancer factor 2; wt, wild type; PDK1, 3-phosphoinositide-dependent PK-1; PTEN, phosphatase and tensin homolog; Shp2, src homology region British Journal of Pharmacology (2015) 172 957–974 965 BJP M J Cross et al selectivity is not limited to kinases, but includes non-kinase targets, which also bind ATP This general problem and apparent ‘class effect’ has been observed for a number of approved kinase inhibitors, as summarized in Table See Force and Kolaja (2011) for a comprehensive review of kinase cardiac biology and potential mechanistic links to cardiotoxicity Mechanisms of functional and/or structural cardiotoxicity may fall into several major categories: (a) Electrophysiological perturbations, mediated via ion channel inhibition (Na, K or Ca channel interactions; e.g hERG/KCNH2) and represents a significant cause of early compound attrition as a result of the implementation of early screening strategies) (b) Cytotoxicity [molecular inactivation of cell processes, altered energetics, oxidative stress/free radical generation, may be primary (target) or secondary (off-target) pharmacology related] (c) Primary pharmacology (an undesirable target-mediated activity and a common preclinical and clinical mechanism, e.g hyper-pharmacology of cardio- and vasoactive drugs) The workshop focused largely on cytotoxic and pharmacological mechanisms of drug-induced on- and off-target cardiotoxicity as primary mediators of structural injuries In the pharmaceutical industry, to identify potential safety liabilities early in drug development, initiation of new discovery programmes includes a review of the published target biology information This enables identification of potential toxicological issues because of primary pharmacology, planning of hypothesis-based experiments to confirm or refute potential issues and generation of toxicological data to support or reject target validity Secondary pharmacology screening for compound interactions with key cardiovascular homeostatic proteins and receptors is also becoming increasingly important for identifying off-target liabilities associated with a particular compound or series Case examples of pharmacological mechanisms (on-target and off-target) of structural cardiotoxicity On-target A number of companies have pursued activin receptor-like kinase (ALK5 also known as TGFBR1) as an oncology and fibrosis target It has previously been shown that the TGF-β superfamily signalling pathways play a key role in cardiac development, and that ablation of ALK5 in the endocardium of mice results in defects in epithelial-mesenchymal transformation and an early stage of cardiac valve formation (Sridurongrit et al., 2008) Nevertheless, a role for ALK5 in the developed heart was poorly understood, but a potential role in cardiac valve homeostasis represented a safety concern As a result, safety scientists at AstraZeneca (Anderton et al., 2011) undertook an acute (5–8 days) study in rodents using selective inhibitors of ALK5 to assess this potential target liability Importantly, early ALK5 inhibitors were available 966 British Journal of Pharmacology (2015) 172 957–974 from different chemical scaffolds, enabling clear separation of target/off-target effects A comprehensive evaluation of the heart was performed to assess all four heart valves in each animal Histopathological heart valve lesions were observed in all animals, in all heart valves and from two distinct chemical series Valves were distorted with severe haemorrhage, fibrin deposition and neutrophil infiltration and valvular interstitial cells were enlarged with increased cytoplasm Immunohistochemistry analysis revealed the heart valve, but not the myocardium was positive for ALK5 expression The compounds were inactive against 5-HT receptors, previously implicated in drug-induced valvulopathy As a result of these findings, the project was terminated in the discovery phase because of unacceptable target-related toxicity No safety margin was expected, the lesion was considered to be un-monitorable and there was no defined hypothesis to support humans being different from rodents in respect of the ALK5 inhibitor-mediated pathology Anecdotally, this experience was shared by at least two other pharmaceutical companies, but not published The publication by Anderton et al (2011) alerted other organizations working in this area or considering initiating discovery efforts on this target to the safety implications This represents an excellent example of the benefit of sharing adverse target safety information in order to reduce further animal experimentation, resource and industry attrition, and is a position encouraged greatly by all of the workshop representatives Off-target A safety concern relating to compound promiscuity is that off-target pharmacological activity unrelated to the primary drug action might be associated with adverse cardiac effects An example is the c-Met inhibitor (PF-04254644), which leads to myocardial pathological changes in rats within h after a single dose, resulting in replacement fibrosis after days (Hu et al., 2012) Myocardial EM changes (necrosis of myofibres, intra-mitochondrial densities and lipid deposition) were detected at very early time points post-dosing (within h) These time points were coincident with peak elevations of serum troponin and an associated functional increase in heart rate and BP within 2–7 h post-dose As other c-Met inhibitors currently in clinical use are not associated with adverse cardiac effects, it was clear this represented an off-target effect of the compound Wide ligand binding profiling revealed that PF-04254644 is a potent inhibitor of PDE3 and also 2, 5, 10 and 11 (Aguirre et al., 2010) It is well recognized that inhibition of multiple PDEs leads to increased heart rate, contractility and sheer stress force and may result in secondary myocardial degeneration (Larson et al., 1996) These observations enabled the identification of alternative c-Met inhibitors without off-target PDE activity and the associated cardiovascular liability New approaches to the mechanistic understanding of cardio-protection Dexrazoxane is the only clinically approved cardioprotective agent used to reduce the cardiotoxicity associated with anthracyclines such doxorubicin (Lipshultz et al., 2004) The Sunitinib and its target receptors in mice BJP MALDI-MSI and for haematoxylin and eosin (HE) staining (Supporting information, Figures S1 and S2) Sections #1–2 and #4–5 were labelled sequentially with either of the following primary antibodies: anti-VEGFR-2 (1:50, Cell Signaling Technology, Danvers, MA, USA; Catalogue number: 55B11), anti-PDGFR-α (1:50, Cell Signaling Technology; Catalogue number: D1E1E), anti-PDGFR-β (1:50, Cell Signaling Technology; Catalogue number: C82A3) or anti-FGFR-1 (1:50, Cell Signaling Technology; Catalogue number: D8E4) All the primary antibodies were labelled with a fluorescent secondary antibody (anti-rabbit Alexa-488, 1:1000, Cell Signaling Technology; Catalogue number: 4412) Nuclei were stained with Hoechst 33342 (Molecular Probes, Eugene, OR, USA) and tumour sections were covered with ProlongGold Antifade Reagent (20 μL, Invitrogen, Carlsbad, CA, USA; Catalogue number: P36930) Slides were scanned by TissueFAXS (TissueGnostics GmbH, Vienna, Austria) and VEGFR-2, PDGFR-α, -β and FGFR-1 expression patterns were analysed by two pathologists (BD and TF) Data analysis Statistical analysis was performed to evaluate the in vivo effects of sunitinib Two diameters of the tumours were measured three times a week and tumour volume was calculated with the formula: width2 × length × π / Difference between the treated and the control groups in tumour volume and weight was analysed by the Mann–Whitney U-test Data were considered significant when P ≤ 0.05 Data are based on five independent experiments Results Sunitinib treatment inhibits tumour growth Syngeneic subcutaneous mouse tumour models are ideal and widely used in translational medicine studies allowing us to evaluate the efficacy of various anticancer agents including anti-angiogenic drugs (Paku et al., 2011; Wong et al., 2012) Therefore, we decided to compare the effect of sunitinib treatment on tumour development with measures of drug distributions within the tumours Balb/C mice were injected s.c with C-26 mouse colon adenocarcinoma cells and weeks later were dosed daily with sunitinib over a week period Tumours and other tissues were then obtained and analysed The mean tumour weights in the control and sunitinibtreated groups were 0.274 and 0.090 g respectively (Figure 1A; P = 0.0635) More importantly, a week sunitinib treatment resulted in a significant (P = 0.0159) relative tumour growth inhibition as well (Figure 1B) MALDI-MSI identification of sunitinib and its fragment ions We started our MALD-MSI studies by identifying the monoisotopic mass of pure stock sunitinib compound dried as a droplet at m/z 399.218 (Figure 2A) Subsequent MS/MS fragmentation of the precursor ions led to the loss of the terminal diethylamino group, generating a fragment ion at m/z 326.1, while the presence of fragment ion at m/z 283.1 indicated a cleavage at the amide group (Figure 2B) Figure Sunitinib reduces the in vivo growth of C-26 mouse colon adenocarcinoma cells in Balb/C mice (A) Tumour weights and (B) percentage of change of tumour volumes of control and sunitinib-treated groups (100% refers to day #1 of the treatments) Data are shown as box (first and third quartiles) and whisker (maximum to minimum) plots with the median (horizontal bar) from animals per group *P = 0.0635, **P = 0.0159, versus control Identification of sunitinib and its metabolites in blood Adsorption of the drug was examined in peripheral blood Sunitinib was measured in all plasma samples taken just before killing the animals Moreover, metabolites of the precursor compound were also traceable and could be characterized Presumed structures and MS/MS spectra of the precursor compound and its metabolites in blood plasma are presented in Figure The previously described bis-desethylated metabolite (M1) of sunitinib (Speed et al., 2012), with a monoisotopic mass at m/z 343.000 could be detected only in a few blood samples performing full mass scans However, isolating and fragmenting the proposed monoisotopic peak of that metabolite resulted in fragment ions at m/z 326.2 and 283.1 in all samples Stepwise elevation of the collision energy proved that the detected fragment ions are formed by the fragmentation of M1 The missing precursor ion in full mass spectra may be explained by the low concentration of M1 British Journal of Pharmacology (2015) 172 1148–1163 1151 BJP S Torok et al Figure (A) Full mass spectrum of sunitinib and images of the distribution of the precursor molecule in tumour, liver and kidney tissues after weeks of treatment Signal of sunitinib is normalized to total ion current (TIC) (B) MS/MS spectrum of sunitinib and images of the distribution of the fragment ions (m/z 326.1 and 283.1) in tumour, liver and kidney tissues that appeared to be below the detection limit of the FT analyser compared with the linear ion trap The signal generated at m/z 358.120 of M2 indicates the loss of the terminal diethylamine group, with the oxidation of the molecule This resulted in a fragment ion at m/z 283.1, but not at m/z 326.1 The presence of fragment ion at m/z 340.2 refers to the terminal dehydroxilation of the molecule 1152 British Journal of Pharmacology (2015) 172 1148–1163 M3, an active metabolite of sunitinib (SU012662) (Rais et al., 2012) was formed by the mono-desethylation of the molecule, resulting a monoisotopic mass of m/z 371.188 and the same fragment ions as sunitinib Two mono-hydroxylated variations of the active metabolite were detected at m/z 387.182 M4 was modified at the indolylidene-dimethylpyrrole moiety, resulting a fragment ion at m/z 299.1 M5 was hydroxylated at the carbon next to Detection of sunitinib and its metabolites in blood samples MS/MS spectra of sunitinib and its metabolites (A) from m/z 343.00 to m/z 401.00 and (B) from m/z 415.214 to m/z 591.243 with the proposed structure and fragmentation properties Figure Sunitinib and its target receptors in mice BJP British Journal of Pharmacology (2015) 172 1148–1163 1153 1154 British Journal of Pharmacology (2015) 172 1148–1163 Continued S Torok et al Figure BJP Sunitinib and its target receptors in mice the amide nitrogen, which generated a fragment ion at m/z 283.1 The detected fragment ion peak at m/z 369.1 could be derived from both molecules by dehydroxylation, such as m/z 342.2 by the loss of the etylamino group Loss of two hydrogen atoms of the terminal ethyl groups of sunitinib generated a metabolite (M6) at m/z 397.202 Fragmentation of the molecule generated ions at m/z 326.1 and 283.1 Fragment ions of a previously described metabolite with the monoisotopic mass of m/z 397.224 (M7) could also be detected by MS/MS (Speed et al., 2012) Signals of fragments were generated at m/z 324.2 and 281.2, suggesting defluorination and subsequent dehydroxylation of the molecule M7 was not traceable by full MS, probably because of the signal suppression of M6 at m/z 397.202 As with M1, the saturated metabolite of sunitinib, M8, was detected by Speed et al at m/z 401.00 in rat and monkey faeces (Speed et al., 2012) This could only be rarely measured in our mouse model by full MS However, when isolating the presumed metabolite peak, the detected fragment ions at m/z 285.1 and 328.2 indicated the presence of the molecule, and that the saturation occurred at the indolylidenedimethylpyrrole moiety Mono-hydroxylated metabolites of sunitinib were also measured at m/z 415.214 Fragmentation of the molecule indicated the oxidation on the indolylidene-dimethylpyrrole group (M9) with 16 Da higher fragments than the corresponding ions of sunitinib at m/z 342.2 and 299.2 Moreover, upon fragmentation of the detected metabolite peak, ions at m/z 326.1 and 283.1 were also formed, indicating that the oxidation occurred either at one of the terminal carbons of the diethylamine group (M10) or at the amine moiety (M11) M11 was previously synthesized as SU012487 (Speed et al., 2012) Dehydroxylation of any of the mono- hydroxylated metabolites could result in a fragment ion at m/z 397.1 M12 at m/z 495.283 was identified as a sulphate conjugate of M9 Desulphuration of the molecule gave rise to the fragment ion at m/z 415.2, while dehydroxylation resulted in a fragment ion at m/z 477.3 The glucuronide metabolite, M13, was detected at m/z 575.252 The cleavage at the amide group and the loss of the terminal diethylamino moiety resulted in fragment ions at 459.2 and 502.2 respectively The metabolite at m/z 591.243 (M14) was generated by both the oxidation and the glucuronidation of sunitinib When the molecule fragmentized as the unmodified compound, ions at m/z 518.2 and 475.1 were generated Dehydroxylation eventuated in a signal at m/z 573.2, while the fragment ion at m/z 415.2 was formed by the loss of the dehydrated glucuronic acid Deglucuronidation and dehydroxylation of the molecule resulted in an ion at m/z 342.2 M3, the active metabolite generated a two- to threefold less-intensive signal than the precursor molecule in blood samples All the other metabolites were only traceable, with less than 5% of the signal intensity of the unmodified compound (data not shown) Distribution of administered sunitinib in tumour, liver and kidney tissue sections The distribution of sunitinib in tumour, liver and kidney tissue samples was examined by MALDI-MSI The precursor BJP compound with its fragment ions could be detected in all of the tissues mentioned earlier Representative examples showing the distribution of sunitinib and its fragment ions are shown in Figure The intratumour localization of the compound was predominantly peripheral, which can either be related to the histological or to the capillary network structures of the tissues No major intertumour heterogeneity was seen among the sunitinib-treated replicates Sunitinib and its fragment ions showed co-localization within the tissues This co-localization can be interpreted as a molecular fingerprint that confirms the identity of sunitinib in these measurements We also identified several sunitinib metabolites within the tumour tissue In particular, the mono-desethylated (m/z 371.188), the desaturated (m/z 397.203), and the monohydroxylated (m/z 415.215) metabolites were observable by imaging (Figure 4) The precursor compound, its fragment ions and all the measured metabolites showed an overlapping tissue pattern Quantification of sunitinib in tumour, liver and kidney tissue samples Quantification of the drug compound on tissue sections displayed a linear correlation between concentration and signal intensity when normalized to the matrix signal (m/z 379.093) This linearity was found to be between the concentration range of 0.16 nmol·mL−1 and 0.5 μmol·mL−1 in the case of liver and tumour tissues, while it was in the range of 0.16 nmol·mL−1 and 0.1 μmol·mL−1 in the case of kidney sections The signal intensity of the manually deposited drug solution was the highest from kidney tissue and the lowest from the tumour section Possible explanations of this phenomenon could be variations in cell density and/or in the physicochemical properties of these tissue types Calibration curves of sunitinib obtained on tumour, liver and kidney tissue sections are shown in Figure Co-localization of drug compound and its target receptors in tumour tissue The receptor proteins targeted by sunitininb were expressed by C-26 adenocarcinoma cells grown s.c In these tumour cells, the patterns of expression of these targets was focal for VEGFR-2 or diffuse, for PDGFR-α, PDGFR-β and FGFR-1 Typical patterns of immunofluorescent stainings in frozen tumour tissue samples are shown in Figure In line with the finding mentioned earlier that drug treatments resulted in significantly slower tumour growth in vivo, we also found reduced intratumour expressions of the key angiogenic receptor VEGFR-2 in sunitinib-treated animals (Figure 6A), compared with controls (Figure 6C) However, this phenomenon was not accompanied by alterations in the VEGFR-2 staining pattern, which remained focal (Figure 6A) It is also important to mention that sunitinib treatments did not affect the expression of PDGF or FGF receptors (Figure 6A) Sunitinib was measured by MALDI-MSI by monitoring the m/z 399.218 ion mass, using 100 μm rastering over the entire tumour cryosection In Figure 6B, an intensity map is shown, generated by point-by-point sampling, locating the major depots of the drug In serial sections of sunitinibtreated tumours, the drug distribution as visualized by MALDI-MSI did not show an obvious overlap with the tissue British Journal of Pharmacology (2015) 172 1148–1163 1155 BJP S Torok et al Figure Distribution properties of sunitinib and its metabolites Precursor molecule, desethylated metabolite (SU012662, M3), desaturated metabolite (M6) and mono-hydroxylated metabolites (M9, M10 and/or M11) in tumour, liver and kidney tissue sections labelling patterns of any of its target receptors However, composite pictures made from the combination of MALDI-MS and immunofluorescent images identified areas where the highest concentrations of sunitinib were found in the same locations that expressed the highest concentrations of VEGFR-2 (Figure 6B) Nevertheless, this latter preliminary observation has to be confirmed by further in-depth studies Discussion Sunitinib is metabolically transformed by cytochrome P450 3A4 (CYP3A4) to its active, desethylated metabolite, SU012662 (M3), which is then further modified by CYP3A4 to inactive forms (Rock et al., 2007) After administration of a single oral dose, 23–37% of sunitinib is converted to SU012662 in humans (Houk et al., 2010), underlining the importance of studies evaluating the metabolism of such antitumour drugs in appropriate preclinical settings Our study confirmed that M3 is the major plasma metabolite present, not only in rats, monkeys and humans, as found by 1156 British Journal of Pharmacology (2015) 172 1148–1163 Speed et al (Speed et al., 2012), but also in mice In plasma samples, the signal of this desethylated metabolite was an order of magnitude higher than that of other modified compounds Although SU012662 generated an order of magnitude lower signal intensity in tissue than sunitinib, this was not necessarily higher than that generated by the other detectable metabolites This observation can be explained not only by the potential difference in concentration, but also by the different ionizing properties of sunitinib and its derivatives in different tissues In the present study, the drug compound and its metabolites were not directly quantified As the calibration curves we developed for this study showed linear correlation between concentration and signal intensity, such analysis could also be performed by MALDI-MSI by carefully considering the differences of signal intensities originating from different tissues By preparing calibration curves of synthetic metabolites, accurate studies can be implemented to follow the fate of the original molecule and each of its derivatives in the body The observed overlap in the distribution pattern of sunitinib and its metabolites, as detected in the tissue, suggests Sunitinib and its target receptors in mice BJP Figure Quantification of sunitinib Diagrams of MS signal intensities of sunitinib (normalized to matrix) in a concentration range of 0.064–1000 μg·mL−1 obtained from (A) tumour, (B) liver and (C) kidney tissue sections British Journal of Pharmacology (2015) 172 1148–1163 1157 BJP S Torok et al Figure Intratumour distribution patterns of sunitinib and its target RTKs in sunitinib-treated (A, B) and control (C) mice as visualized by MALDI-MSI and immunofluorescent labelling respectively In both (A) and (C), the tumours are immunolabelled for VEGFR-2, PDGFR-α, PDGFR-β and FGFR-1 (green) Nuclei are counterstained with Hoechst 33342 (blue) Note the focal (VEGFR-2) and diffuse (PDGFR-α, PDGFR-β, FGFR-1) expression patterns of the tumour cells in both animal groups Panel B shows an example for coincidence of drug location and targeted receptor in tumour MALDI-MSI detected sunitinib (m/z 399.218) at high signal intensities in the mantle and in this case in a central area as well Signal intensity gradients of the drug were seen in discrete compartments throughout the tissue (left picture) In order to investigate the occurrence of cells bearing VEGFR-2 and the distribution of the drug, we first imaged the isolated VEGFR-2 signal from the RGB signal and then overlaid this image with the drug contour map The highest density of VEGFR-2 bearing cells (red dots) was congruent with the highest concentrations of the drug (right picture) In (A) and (C), the three columns of immunofluorescent pictures (captured by a 20× objective) represent different magnifications of the same image (100, 2000 and 8000%) White rectangles in the lower-power micrographs show the corresponding areas of the higher magnification images that the chemical properties responsible for drug dispersion remain similar in the case of the metabolites, and accordingly, that they may contribute to the tumour growth inhibitory activity of the precursor compound as well Alternatively, the co-localization of sunitinib and its metabolites may indicate that the drug is being taken up and metabolized locally rather than being transported from other sites of metabolism, such as the liver, back to the same location as the precursor drug Further studies in tissue are warranted to confirm or rule out these assumptions 1158 British Journal of Pharmacology (2015) 172 1148–1163 Most of the techniques that have analysed sunitinib and its derivatives are based on liquid chromatography coupled with mass spectrometric detection (Baratte et al., 2004; de Bruijn et al., 2010; Zhou and Gallo, 2010; Lankheet et al., 2011; Rodamer et al., 2011; Rais et al., 2012; Speed et al., 2012; Qiu et al., 2013) However, Etienne-Grimaldi et al described an HPLC method linked to UV detection of sunitinib and SU12662 in human plasma (Etienne-Grimaldi et al., 2009) The m/z values of the precursor drug and its derivatives in our study are consistent with these earlier results The Sunitinib and its target receptors in mice BJP Figure Continued present study showed that MALDI-MS is also a powerful tool to detect the drug compound ions and its metabolites The MALDI-MS experimental parts showed a slightly different fragmentation pattern from electrospray ionization-MS (Speed et al., 2012) Moreover, an advantage of MALDI-MSI compared with other previously used methods is that the earlier techniques require either fluid samples (such as blood or sweat) or the homogenization of the tissue Therefore, they are not capable of analysing the spatial tissue distribution of a compound in an organ or in a solid tumour Although the last half century has witnessed dramatic advances in the field of medical imaging, there is still an urgent need for the development of more advanced techniques for imaging compounds in the drug discovery process This is particularly important in the narrowing of the selection of potential hits and leads as candidates for further development One of the reasons this has been difficult to accomplish in the past is that until recently, the only avenue for visualizing the in vivo distribution of drugs in targeted tissues was to use labels, which are commonly radioactive, British Journal of Pharmacology (2015) 172 1148–1163 1159 BJP S Torok et al and as such a safety risk Methods such as PET and autoradiography can provide information on the distribution of a radiolabelled compound, even at the cellular level (Solon et al., 2010; Solon, 2012) However, both of these methods rely on quantitative data based upon the relative strength of the label rather than the relative concentration of the drug For these reasons, unlabelled, that is ‘cold’ compounds will provide evidence that relate to the drug structure only and not to the labelling chemistry in a modified drug molecule If a drug is metabolized such that the label follows on the fragment that is neither active, nor the precursor of an active form, then the readout of distribution may have little to with the mode of action or the actual efficacy of the drug (Solon, 2012) Other methods rely on the use of isotopes with relatively short half-lives or fluorescent tags, which makes long-term pharmacological analysis impossible or alters the chemical structure and thus the binding affinity and/or avidity to its target molecule (Solon et al., 2010) From this point of view, it is particularly important that methods be used that investigate the characteristics of the unaltered native compound (i.e the same agent as that being administered to patients) MS is one such powerful technique, enabling the parallel determination of label-free drugs and their metabolites The Orbitrap mass analyser in the hybrid instrument used in our study provides very high levels of mass accuracy, to the tens of thousands fraction on a single atomic mass unit (Strupat et al., 2009) This high accuracy in identification allows strong statistical support for the mass values that we have reported here for sunitinib as either precursor ions, fragment ions, or metabolites formed in situ The MALDI-MSI technology also allowed label-free identification of this small molecule compound, negating the concern that drug properties could have been altered by the labelling procedure In principle, MALDI-MSI is not limited to the analysis of low MW compounds, but it might also be suitable for the localization of therapeutic macromolecules, such as peptides (Craik et al., 2013) and antibodies (Glassman and Balthasar, 2014) In practice, however, the identification of specific antibodies by MALDI-MSI is a challenge as timeof-flight instruments with broad mass range (over m/z million) not have sufficient resolution at high mass range, while Orbitraps operate up to m/z 4000 (and thus unable to detect singly charged peptides over kDa) Enzymic in situ digestion (Groseclose et al., 2007; Casadonte and Caprioli, 2011; Gustafsson et al., 2013) may provide unique peptides that can help in their precise localization within tissue sections However, the identification of these peptides is still restricted to matching the accurate precursor masses in MALDI-MS analysis with those observed in an LC-MS/MS experiment used for peptide sequencing The current study is the first describing the tissue distribution of an unlabelled anti-angiogenic RTKI and its metabolites by MSI In our study, the combination of the resolving power of the Orbitrap with the sensitivity of the linear ion trap made it an ideal technique for drug and metabolite detection We observed that oral administration of sunitinib resulted in a systemic distribution of the drug throughout the body with significant levels being observed in the blood, liver, kidneys and tumour tissue In this study, we have investigated the patterns of drug distribution in the animals following weeks of daily sunitinib dosing As such, we have 1160 British Journal of Pharmacology (2015) 172 1148–1163 not studied the kinetics of drug accumulation in specific tissue sites, or the kinetics of changes in the biological/ histological makeup of the tumours throughout the course of treatment We have clearly shown that sunitinib-treated tumours showed areas of higher (typically peripheral) and lower (tumour centre) drug signal intensities rather than a homogeneous dispersal across the entire tumour Of note, this distribution pattern (i.e higher signal intensity at the tumour periphery vs relatively lower levels in the central tumour regions) proved to be reproducible throughout the drug-treated tumour sample replicates In accordance with the findings of Domingues et al., we observed that VEGFR-2 expression was significantly reduced in treated tumours, compared with untreated ones (Domingues et al., 2011) The relationship between this reduction and the exposure to the drug cannot be investigated in this study because of a single time point of analysis However, we can say that the time point represented a window showing a clear biological effect of the drug treatment, as seen by both a reduction in tumour weight and volume Today, our understanding of the mode of action and the efficacy of antivascular agents in oncology is especially complex and peculiar Accordingly, when interpreting our findings, we need to take into consideration that both the tumour tissue levels of sunitininb and the expression pattern of its target receptors vary both spatially and temporally The actual tumour tissue level of an anticancer drug is always influenced by the global blood supply of the tumour mass and also by local intratumour blood flow changes (i.e by the distinct vascularization patterns of different intratumour areas as well) Although they also have direct effect against autocrine tumour cell signalling, the main effect of antivascular agents (such as sunitinib) is exerted on the tumour vasculature itself and, consequently, sunitinib influences the efficacy of its own delivery Additional key background information is that sunitinib binds to its target receptors reversibly and, moreover, that it may also result in significant changes in the expression levels and patterns of its target receptors (Roskoski, 2007) Our approach can contribute to the elucidation of this complex biology in order to further develop anti-angiogenic treatment strategies To the best of our knowledge, the current study provides the first direct evidence that an anti-angiogenic drug given orally is transported to, taken up and metabolized within the targeted compartment, the adenocarcinoma tumour Moreover, the presented results are the first demonstrating that MALDI-MSI is a versatile and simple method of conducting ADME studies on an anti-angiogenic RTKI Hence, the current study warrants further investigations to define the precise and optimal role of MALDI-MSI in elucidating the mechanisms of drug action and for validating transport to sites of intended effect Acknowledgements The authors were supported by Kutatási és Technológiai Innovációs Alap (Research and Technology Innovation Fund) AIK 12-1-2013-0041 (B D., V L., S P.); Országos Kutatási Tudományos Alapprogramok (Hungarian Scientific Research Fund) K109626, K108465 (B D., B H.), MOB80325 (B H.), Sunitinib and its target receptors in mice and K84173 (J T.); EUREKA_HU_12-1-2012-0057 (B D.); ÖNB Jubiläumsfondsprojekt No 14043 (B D., V L.); and the Vienna Fund for Innovative Interdisciplinary Cancer Research (B D., V L.) S T was recipient of an EACR Travel Fellowship and a Hungarian Pulmonology Foundation Research Fellowship A V is grateful for the Innovative Support 2011-039226 for CREATE Health This work was also supported by grants from the Mrs Berta Kamprad Foundation, Ingabritt & Arne Lundbergs forskningsstiftelse and the Crafoord Foundation Author contributions S T was responsible for the implementation of the animal experiment, for the immunohistochemical and MALDI data acquisition She contributed in the preparation of the paper A V was responsible for the MALDI-MS data analysis and interpretation, and was also involved in the preparation of the paper M R was involved in the MALDI-MS data acquisition and analysis T E F was responsible for the immunohistochemical data analysis and interpretation He was also involved in the preparation of the paper J T was responsible for the design and data analysis of the in vivo animal experiment S P was responsible for the design and expertise of the 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