The automated micronucleus assay for early assessment of genotoxicity in drug discovery

Mutation Research 751 (2013) 1–11

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Mutation Research/Genetic Toxicology and Environmental Mutagenesis journal homepage: www.elsevier.com/locate/gentox Community address: www.elsevier.com/locate/mutres

The automated micronucleus assay for early assessment of genotoxicity in drug discovery K. Tilmant a,b,∗ , H.H.J. Gerets a , P. De Ron a , C. Cossu-Leguille b , P. Vasseur b , S. Dhalluin a , F.A. Atienzar a a b

UCB Pharma, Investigative, Chemical and Environmental Safety, Chemin du Foriest, 1420 Braine l’Alleud, Belgium CNRS Université Paul Verlaine, 57050 Metz, France

a r t i c l e

i n f o

Article history: Received 7 July 2012 Received in revised form 24 September 2012 Accepted 14 October 2012 Available online 15 November 2012 Keywords: Micronucleus Cellular imaging Flow cytometry CHO HepaRG HepG2

a b s t r a c t Recent publications on the automated in vitro micronucleus assay show predictive values higher than 85% for the classification of in vitro aneugens, clastogens and non-genotoxic compounds. In the present work, the CHO-k1 micronucleus assay in combination with cellular imaging was further evaluated. Firstly, the effect of a range of S9 concentrations on micronucleus formation and cytotoxicity was investigated. Subsequently, the reproducibility and predictivity of the micronucleus assay on CHO-k1 cells was investigated with a set of four compounds. Then, a larger set of compounds (n = 44) was tested on CHO-k1 cells and inter-laboratory correlation was calculated. Finally, cellular imaging was compared with flow cytometry for in vivo assessment of micronucleus formation. The concentration of S9 had a significant impact on micronucleus formation and cytotoxicity. In addition, calculations of relative cell count (RCC) and cytokinesis-block proliferation index (CBPI) showed to be complementary to cytotoxicity assessment. The CHO-k1 micronucleus assay correctly classified the four reference compounds, with a dose–response relationship and low variability. Based on a larger set of compounds, the assay proved to be reliable with a sensitivity of 94% (n = 31) and a specificity of 85% (n = 13). A correlation coefficient of 97% was obtained when the lowest observable adverse effect levels (LOAELs) from our study were compared with those published by Diaz et al. (2007) [10]. In conclusion, the in vitro CHO-k1 micronucleus assay combined with cellular imaging is a predictive assay appropriate for genotoxicity screening at early stages of drug development. In addition, for in vivo assessment of micronucleus formation, we preferred to use flow cytometry rather than cell imaging. © 2012 Elsevier B.V. All rights reserved.

1. Introduction To reduce costs and time, predictive preclinical models using in vivo [1] and in vitro [2,3] approaches are being developed to discard toxic molecules at early stages of drug development. In order to improve the screening efficiency, innovation is needed which hopefully will change the inefficient ‘big pharma’ model, as reported by Kola [4]. The main causes of drug attrition due to safety issues are cardio- and hepatotoxicity [5,6], but genotoxicity is also a main

Abbreviations: S9, Aroclor 1254 induced male Sprague-Dawley rat liver S9 fraction; % MN frequency, percentage micronucleus frequency; LOAEL, lowest observable adverse effect level; RCC, relative cell count; CBPI, cytokinesis-block proliferation index; MN-RET, micronucleated reticulocytes. ∗ Corresponding author at: UCB Pharma SA, Non-Clinical Development, Investigative, Chemical and Environmental Safety, Building R9, Chemin Du Foriest, 1420 Braine l’Alleud, Belgium. Tel.: +32 02 3866492; fax: +32 02 3862798. E-mail addresses: [email protected] (K. Tilmant), [email protected] (H.H.J. Gerets), [email protected] (P. De Ron), [email protected] (C. Cossu-Leguille), [email protected] (P. Vasseur), [email protected] (S. Dhalluin), [email protected] (F.A. Atienzar). 1383-5718/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.mrgentox.2012.10.011

concern in drug discovery. Indeed, alterations to DNA can lead to cancer and heritable effects [7]. In the pharmaceutical industry, a battery of genotoxicity tests is required by the regulatory agencies. A gene-mutation test in bacteria, e.g. the Salmonella reverse-mutation (Ames) test, is compulsory, with two possible options [7]. The first approach comprises one in vitro mammalian test (e.g. the mouse lymphoma Tk gene-mutation assay) and one in vivo test (e.g. the micronucleus assay in rodent haematopoietic cells). The second option consists of two in vivo tests on two different tissues (e.g. the micronucleus assay with rodent haematopoietic cells and a DNA strand-breakage assay in liver) according to the ICH guideline S2 (R1) [7]. Therefore, it is key to screen for genotoxic potential as early as possible in drug discovery, because genotoxicity investigations are generally not performed during the clinical phase. Kirkland [8] showed that a set of assays consisting of the Ames test and the in vitro micronucleus assay was sufficient to detect rodent in vivo genotoxins and carcinogens. This predictivity was not increased by the addition of the mouse lymphoma assay (MLA) [8]. Interestingly, Sistare et al. [9] proposed for non-genotoxic carcinogens to refine regulatory criteria for conducting two-year rat studies based

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K. Tilmant et al. / Mutation Research 751 (2013) 1–11

on (1) assessment of histopathological findings from six-month rat studies, (2) evidence of hormonal perturbation, (3) genetic toxicology results, and (4) the findings of a six-month transgenic mouse carcinogenicity study. This approach is worth considering, as it would eliminate over 40% of two-year rat testing of new pharmaceuticals without compromising patient safety. In the present publication, the use of the automated micronucleus assay (in vitro and in vivo) for genotoxicity screening was investigated. The micronucleus assay detects genotoxic carcinogens inducing chromosome breaks (clastogens) and whole chromosome loss (aneugens). Recent publications propose the automated in vitro micronucleus assay on cultured cells as a powerful genotoxicity screening assay in combination with cellular imaging [10,11] or flow cytometry [12,13]. Both approaches reach sensitivities and specificities higher than 85% for assessment of micronucleus formation in CHO-k1 cells [10–13]. This is in contrast to the low specificity (range, 31–54%) with a set of 26 compounds reported by Kirkland et al. [14]. However, these data were compiled from 15 different literature references that used different cellular models and thresholds [14]. The selection of CHO-k1 cells seems obvious considering the extensive studies that have been done with this model [15]. In addition, the OECD guideline [16] favors the use of cell lines from Chinese hamsters (CHO-k1, V79, CHL/IU), as well as mouse lymphoma cells (L5178Y) and cultured primary human peripheral blood lymphocytes for the micronucleus assay. Furthermore, the guideline stresses that the use of another model should clearly have additional value compared with the recommended cell lines. In the present study, we first explore key parameters to optimize the cellular imaging method in CHO-k1 cells. For instance, the variability of the frequency of micronucleated binucleated cells (% MN frequency) was monitored in 12 independent experiments. In addition, as a case study, the effect of different concentrations of the metabolic activation system (S9) on % MN frequency and cytotoxicity was evaluated in CHO-k1 cells exposed to cyclophosphamide. The latter compound was used because it only induces micronuclei after metabolism [17]. Subsequently, a preliminary test was performed on CHO-k1 cells exposed to four drugs (i.e. etoposide, camptothecin, cyclophosphamide and amiodarone) in the absence and in the presence of S9. Triplicates of the experiment were performed in order to evaluate the reproducibility of the data as well as predictivity. Then, in order to expand the data set and evaluate inter-laboratory correlation of the assay, 44 compounds of which 42 are in common with the study of Diaz et al. [10], were tested in CHO-k1 cells (−/+S9). Finally, we explore the use of cellular imaging as well as flow cytometry for in vivo assessment of micronucleus formation in rat blood cells. Four-day rat toxicity studies were performed with four reference compounds (i.e. etoposide, colchicine, cyclophosphamide and amiodarone). 2. Materials and methods 2.1. Chemicals The following reference products, with CAS numbers provided in brackets, were purchased from Sigma Aldrich (Bornem, Belgium): 1,2:5,6-dibenzanthracene (DBA) (53-70-3), 2-aminoanthracene (613-13-8), 2-nitrofluorene (607-57-8), 4-nitroquinoline-1-oxide (4NQO) (56-57-5), 5-fluorouracil (51-21-8), 7,12dimethyl-1,2-benzanthracene (DMBA) (57-97-6), actinomycin D (50-76-0), aflatoxin B1 (1162-65-8), amiodarone (1951-25-3), ampicillin sodium (69-52-3), benzo[a]pyrene (50-32-8), benzyl acetate (140-11-4), bleomycin sulfate (904193-4), boric acid (10043-35-3), cadmium sulfate (10124-36-4), camptothecin (7689-03-4), carbendazim (10605-21-7), catechol (120-80-9), colchicine (6486-8), crotonaldehyde (4170-30-3), cyclophosphamide (6055-19-2), diclofenac sodium salt (15307-79-6), ethylenediaminetetraacetic acid (EDTA) (10378-22-0), erythromycin (114-07-8), etoposide (33419-42-0), glycine (56-40-6), griseofulvin (126-07-8), hydrogen peroxide (7722-84-1), methylurea (598-50-5), mitomycin C (50-07-7), methyl methanesulfonate (MMS) (66-27-3), m-phenylenediamine (10845-2), nalidixic acid (389-08-02), N-diethylnitrosamine (N-nitrosodiethylamine) (684-93-5), nickel acetate tetrahydrate (6018-89-9), N-nitroso-N-methylurea (NNMU) (759-73-9), paclitaxel (taxol) (33069-62-4), simvastatin (79902-63-9),

sodium chloride (7647-14-5), sucrose (57-50-1), tamoxifen (10540-29-1), triamterene (396-01-0), and vinblastin (143-67-9). The following products were purchased from different suppliers. Vincristine sulfate (2068-78-2) was purchased from Sequoia Research Products (Pangbourne, UK), Hoechst 33342 trihydrochloride trihydrate from Invitrogen (Merelbeke, Belgium), S9 (Aroclor 1254-induced male Sprague-Dawley rat liver S9) from Celsis In Vitro (Neuss, Germany), Rat MicroFLOW® plus kit from Becton Dickinson Benelux (Erembodegem, Belgium) and DPBS from BioWhittaker (Lonza, Verviers, Belgium). Formaldehyde and cytochalasin B were purchased from Sigma (Bornem, Belgium). 2.2. Cellular imaging in vitro micronucleus assay 2.2.1. CHO-k1 cell-culture conditions The Chinese hamster ovary (CHO-k1) cell line was purchased from the European Collection of Cell Cultures (ECCAC, Salisbury, UK via Sigma, Belgium). The CHO-k1 cell line is a sub-clone of the parental CHO cell line, initiated from an adult Chinese hamster ovary. CHO-k1 cells were cultured according to the providers’ recommendations in F12-K Nutrient Mixture (Kaighn’s modification) (Invitrogen, Merelbeke, Belgium) supplemented with 10% fetal bovine serum (FBS) and 2 mM l-glutamine. All supplements were purchased from BioWhittaker (Lonza, Verviers, Belgium). Incubation conditions were: 37 ◦ C, 5% CO2 , 95% air atmosphere and 80% humidity. Cells were passaged as needed by use of 0.5% trypsin-EDTA. Cells used in the experiments were between passage 10 and 35. Compounds were diluted in normal culture medium for the MN assay without metabolic activation (−S9). The medium for the MN assay with metabolic activation (+S9) consists of culture medium for CHO-k1 cells deprived of serum and supplemented with 6% isocitrate core mix. To this medium, a percentage of reconstituted S9 homogenate (Celsis In Vitro, Neuss, Germany) was added, depending on the study. For the optimization of the CHO-k1 micronucleus assay different concentrations of S9 were tested, i.e. 1.1% (222 ␮g/mL), 1.2% (250 ␮g/mL), 1.3% (268 ␮g/mL), 1.7% (333 ␮g/mL), 2% (400 ␮g/mL), 2.5% (500 ␮g/mL), 3.3% (666 ␮g/mL) and 5% (1000 ␮g/mL). We considered 1.3% or 268 ␮g/mL S9 to be optimal and this concentration was used in subsequent experiments. Isocitrate core mix consists of 121 mg NADP, 226 mg isocitric acid dl-isocitric acid trisodium salt in 9 mL water [mixed and filtered (0.22 ␮m) before use]. 2.2.2. Cell seeding, compound addition and staining CHO-k1 cells were seeded at 10,000 cells per well in black, collagen-coated 96well cell-culture plates (Collagen I, Beckton Dickinson, Erembodegem, Belgium). After seeding, plates were left in the laminar flow cabinet for 20 min, before overnight incubation to allow an equal distribution of the cells in the plate. Incubation conditions were as follows: 37 ◦ C, 5% CO2 , 95% air atmosphere and 80% humidity. All compounds were first diluted in 100% DMSO except for glycine and H2 O2 , which were directly diluted into medium. Medium was discarded and 50 ␮l of appropriate medium (with or without S9) was added. Subsequently, 50 ␮l of medium containing compound (2X concentrated and diluted in the appropriate medium) was added to each well. In the preliminary test (triplicate experiment) on CHO-k1 cells six concentrations (2-fold dilutions) per compound were tested in triplicate. In the larger study on CHO-k1 cells, four concentrations (3-fold dilutions) per compound were tested in triplicate. The choice of the concentration range to test positive compounds was based on published LOAEL values [10]. The non-genotoxic compounds were tested up to a concentration of 2 mM, except when solubility or cytotoxicity problems were encountered at lower concentrations. For all experiments, six negative control wells (reference wells) were used: 50 ␮L of 1% dimethyl sulfoxide (DMSO) (Sigma, Bornem, Belgium) was added to reach a final DMSO concentration of 0.5%. Compounds were incubated for 24 h in the assay without S9 and for 3 h in the assay with S9. In the latter, the medium was then replaced by fresh medium for an additional 21 h of incubation. Medium was discarded and cytochalasin-B (6 ␮g/mL) was added in both conditions. After 24 h of incubation, cytochalasin-B was discarded and 100 ␮L of a warm (37 ◦ C) solution containing 3.7% formaldehyde and 2 ␮g/mL Hoechst 33342 was added. After 10 min of incubation at room temperature, plates were washed three times with DPBS and finally filled with 100 ␮L of DPBS. Plates were sealed and scanned with the ArrayScanVTI instrument (Cellomics Inc., Pittsburgh, USA) within 72 h after staining. 2.2.3. Cellomics ArrayScanVTI scanning details Each plate was scanned by use of the micronucleus and target-activation bio-applications (Cellomics Inc., Pittsburgh, USA). Firstly, the micronucleus bioapplication was used for analysis of micronucleus formation and for measuring cytotoxicity based on the cytokinesis-block proliferation index (CBPI). Secondly, the target-activation bio-application was used to assess cytotoxicity by means of cell counting, i.e. relative cell count (RCC). 2.2.3.1. Micronucleus bio-application. Assessment of micronucleus frequencies (% MN frequency). The number of cells to analyze within this bio-application was arbitrarily fixed at 400 cells per well (i.e. 1200 cells per concentration). An objective of 20× was used for image analysis. To avoid extensive scanning time in sparse wells due to cytotoxicity, a well was skipped after 9 consecutive sparse fields (containing less than 2 cells). The nuclear dye (Hoechst) was detected in channel 1 with excitation/emission filter 365/515 nm. The cytoplasm was defined by expanding the circular region of

K. Tilmant et al. / Mutation Research 751 (2013) 1–11 the nuclei. The ArrayScanVTI (Cellomics Inc., Pittsburgh, USA) output feature “percentage of binucleated cells with at least one micronucleus” (% MN frequency) was used to analyze the scans. This output feature % MN frequency was retrieved for all wells and the average value of the six control wells (0.5% DMSO) was used as a reference level. The fold-increase of the % MN frequency was calculated as follows: the % MN frequency in treated wells (average of triplicate) is expressed as a fold-increase of the % MN frequency in control wells (average of six control wells). Consequently, values of 2 and 3 represent a 2- and 3-fold increase of the % MN frequency, respectively, compared with the control value. Assessment of cytotoxicity based on the CBPI-method. The cytokinesis-block proliferation index (CBPI) is the proliferation index calculated from the number of binucleated and mononucleated cells. CBPI =

number of mononucleated cells + 2x number of binucleated cells total number of cells

The addition of cytochalasin B (an actin-polymerization inhibitor and cytokinesis blocker) prior to the mitosis allows identification of cells that completed mitosis but did not divide (binucleated cells) for micronucleus analysis. In addition, the CBPI is a measure of cytotoxicity of compounds that induce cell-cycle arrest. The cytotoxicity index based on CBPI is calculated as follows:



100 − 100

CBPIt − 1 CBPIc − 1



where CBPIc and CBPIt , refer to the CBPI of control and treated wells, respectively. 2.2.3.2. Target-activation bio-application. Assessment of cytotoxicity based on the relative cell-count (RCC) method. Cells in four fields per well (objective 5x) were counted by detection of the nuclear dye Hoechst (excitation/emission filter, 365/515 nm). The output feature “valid object count” was used for cytotoxicity calculations. The average of the six vehicle treated-wells (without S9) served as the control value and was rescaled to 0% cytotoxicity. Subsequently, the average of each concentration value (three wells) was expressed relative to this reference. The cytotoxicity index based on RCC is calculated as follows:



100 − 100

CCt CCc



where CCt and CCc refer to the average number of cells in control and treated wells respectively 2.2.4. Data analysis 2.2.4.1. Statistical analysis. The % MN frequency was analyzed with a one-way analysis of variance (ANOVA). If the ANOVA detected statistical significant differences among treatments, individual comparisons with the control were performed with the least significant difference t-test (LSD), which takes into account the global intraplate variability. Values that are found significantly different are represented by probability *p < 0.05, **p < 0.01 and ***p < 0.001. 2.2.4.2. Classification of compounds. In Tables 1 and 2, , the % MN frequencies are reported only for wells with less than or equal to 50% cytotoxicity. Cytotoxicity is calculated with the RCC and CBPI methods and the cytotoxicity index that gives the highest cytotoxicity value is taken into account. A 2-fold increase is highlighted in light gray (Tables 1 and 2). We consider that a compound has the potential to induce micronuclei (positive classification) when the number of micronuclei is 3-fold higher compared with the control, with p < 0.05 and cytotoxicity ≤50% (highlighted in dark gray in Tables 1 and 2). The lowest observable adverse effect level (LOAEL) is the lowest test concentration reaching the threshold. To compare our data with those of Diaz et al. [10], the correlation coefficient (r2 ) of the LOAELs for all positive compounds (3-fold threshold applied in both studies) was calculated with Microsoft Excel 2010. Tables 1 and 2 report the maximum cytotoxicity (max. cytotoxicity) induced with the tested concentration-range for both the CBPI and RCC method in our study, and the RCC approach in the study of Diaz et al. [10]. The fold-inductions at the LOAEL and at the concentration with the maximum increase of % MN frequency (max. % MN frequency) as well as the top concentration tested are included for both studies. 2.2.4.3. Specificity, sensitivity, predictivity. The sensitivity is defined as the ability of a test system to predict the positive outcome under evaluation (i.e. genotoxicity). The specificity represents the ability of a test system to predict the negative outcome under evaluation (i.e. non-genotoxicity). The predictivity is the ability of a test system to correctly classify chemicals (i.e. genotoxic and non-genotoxic compounds). 2.3. In vivo 4-day rat toxicity study The 4-day rat toxicity tests were conducted according to the generic guidelines reviewed by the ethical committee at UCB Pharma (Braine l’Alleud, Belgium). Briefly, Wistar rats [Crl:WI (Glx/Brl/Han)] were purchased from Charles River Laboratories (l’Arbresle, France). The animals were housed one rat per cage in the preliminary

3

phase and three rats per cage in the main study, in standard cages (Makrolon Eurostandard type III cages, Tecniplast, Italy) provided with aspen bedding (Tecniplast, Italy). Rats were kept under a 12:12 h light–dark cycle (lights on at 06:00 a.m.), with controlled temperature (22 ± 2 ◦ C) and humidity (55 ± 15%). Standard rodent food pellets (S.D.S. France) and ultra-filtered ultraviolet (UV)-treated water was available ad libitum for the duration of the study. After acclimatization for one week, the test phase started. The rats were 6–7 weeks old on the first day of administration. Compounds were administrated daily, by gavage (10 mL/kg bw). In the preliminary study, two doses (low and high) per compound were administered on four consecutive days to one (male) rat: cyclophosphamide (2.5 and 10 mg/kg/day), etoposide (12.5 and 50 mg/kg/day), colchicine (2.5 and 10 mg/kg/day) and amiodarone (5 and 20 mg/kg/day). Control rats were exposed to the vehicle (saline) for four days. Clinical signs were monitored post-administration at different time points. On day 5, blood samples for flow-cytometry measurement of micronuclei were obtained via the vena cava under isoflurane anesthesia (Isoflo® , Abbott, Belgium). The animals were then sacrificed by exsanguination from the abdominal aorta. Findings from the preliminary study were used to choose dose levels for the main study. In the main study, three male rats per group were exposed to two doses of the four compounds: cyclophosphamide (10 and 20 mg/kg bw/day), etoposide (12.5 and 25 mg/kg bw/day), colchicine (3.25 and 7.5 mg/kg bw/day), amiodarone (5 and 20 mg/kg bw/day). Control rats were exposed to the vehicle for four days. On day 5, blood samples for cellular imaging and flow cytometry were obtained via the vena cava under isoflurane anesthesia (Isoflo® , Abbott, Belgium). The animals were then sacrificed by exsanguination from the abdominal aorta. 2.3.1. Cellular imaging A small drop of blood from the vena cava was used to produce a blood smear. Smears were air-dried and fixed in methanol. The smears were stained with acridine orange (125 mg/mL in phosphate buffer, pH 6.8) for 1 min according to Celik et al. [18]. Reticulocytes (immature or polychromatic erythrocytes) are detected in the orange-red spectrum, erythrocytes (mature or normochromatic) in the green spectrum and micronuclei appear in yellow. The Cellomics ArrayScanVTI bio-application “spot detector” was used to perform micronucleus detection on reticulocytes. Two channels of the four XF93 dichroic-emitter pairs were used. Reticulocytes were identified in channel 1 by red fluorescence (TRITC; excitation/emission filter, 549/600 nm) and micronuclei were greenish-yellow fluorescent. Erythrocytes were identified in channel 2 by green fluorescence (FITC; excitation/emission filter, 475/515 nm). 2.3.2. Flow-cytometry measurement Blood samples were treated following the recommendations of Litron Inc. (Rochester, USA) and shipped to Fluofarma (Pessac, France) for flow-cytometry measurements and analysis. In brief, measurements were performed with a three-laser flow cytometer LSRFortessaTM cell analyzer (BD Biosciences, France). Two lasers (488 nm and 561 nm) were used. The cells of interest (RETs) were labeled with an FITC-conjugated antibody directed against a cell-surface antigen (transferrin receptor, CD71). Micronucleated cells were detected based on their red fluorescent color following DNA staining with propidium iodide. Scoring was only taken into account when arbitrarily a minimum of 300 reticulocytes was scored. Animals with a significantly (t-test) different percentage of micronucleated reticulocytes (% MN-RET) are indicated by probability: *p < 0.05, **p < 0.01 and ***p < 0.001.

3. Results 3.1. Optimization of the in vitro cellular imaging micronucleus assay in CHO-k1 cells 3.1.1. Reproducibility study: % MN frequency in vehicle-treated cells (12 independent experiments) Within the 12 independent experiments, 18 plates were analyzed in the absence (−S9) and in the presence (+S9) of S9 (data not shown). In the absence of S9, the average % MN frequency of the vehicle-treated cells (0.5% DMSO) was 0.9 ± 0.2% with a minimum of 0.6% and a maximum of 1.2%. In the presence of S9, the variability was more pronounced; the average % MN frequency was 1.6 ± 0.5% with a minimum of 0.6% and a maximum of 2.9%. 3.1.2. Influence of S9 concentration on % MN frequency Fig. 1a and b show the % MN frequencies in cyclophosphamidetreated cells as a function of the S9 concentration. In Fig. 1a the % MN frequency in all control wells is set to 1 in order to compare all conditions. There is a clear dose-response in the range 1.1–1.7% S9 (Fig. 1a). The 3-fold threshold was reached when 1.1–2% S9 was

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Table 1 % MN frequency in CHO-k1 cells treated with non-genotoxic compounds (n = 13). Experiments were performed without (-S9) and with (+S9) metabolic activation. A 2-fold increase is highlighted in light grey and a 3-fold increase is highlighted in dark grey. Statistical significance is added: *: p < 0.05, **: p < 0.01, ***: p < 0.001. A compound is considered as positive when the 3-fold threshold is reached with p < 0.05 and cytotoxicity ≤ 60%. The compounds were tested up to a concentration of 1mM, except when this was impeded by their solubility or cytotoxicity. LOAEL, maximum cytotoxicity, top concentrations tested and specificity are reported for the current study as well as for the study of Diaz et al. [10]. For more details please refer to the M&M section.

Tilmant et al. Max % MN frequency

Amiodarone Ampicilin sodium Diclofenac Erythromycin Nalidixic acid Sodium chloride Benzyl acetate Boric acid EDTA Simvastatin Sucrose Glycine Methylurea Specificity -

not applicable

Fold-increase at max % MN frequency

LOAEL (µM)

-S9

+S9

-S9

+S9

-S9

1.1 1.0 14.3*** 1.1 1.7 2.0 1.7 1.1 6.1*** 1.6 1.0 1.2 1.4

1.4 4.5 1.4 5.8* 6.6* 3.5 4.2 4.7 1.6 1.8 1.4 2.3 2.3

1.4 0.9 13.4 1.1 1.6 1.8 1.8 1 6.8 1.6 1 1.1 1.4

1.6 1.4 0.5 1.9 2.1 1.1 1.3 1.5 0.5 1.1 0.8 1.3 1.4

150 880 -

+S9

Fold increase at LOAEL

Max cytotoxicity CBPI

RCC

-S9

+S9

-S9

+S9

-S9

+S9

6.5 74 6.8 11/13 (85%)

2.1 -

99 0 75 0 0 0 0 7 83 100 0 0 0

62 0 0 0 0 0 0 0 0 100 1 4 2

100 0 73 38 0 6 0 5 64 58 1 2 2

64 0 8 0 0 0 0 0 0 100 0 1 0

Top Conc. (µM)

125 2000 600 2000 2000 2000 2000 2000 2000 75 1200 2000 2000

Max % MN frequency (µM)

LOAEL (µM)

-S9

+S9

-S9

2.6 1.7 2.3 2.3 1.6 1.3 1.4 1.6 1.8 1.7 1.4 1.5 1.3

2.9 2.7 3.7 4.3 2.8 1.9 1.7 2.7 2.3 3.6 1.6 2.9 1.6

-

+S9

Max cytotoxicity RCC -S9

97 0 0 0 6.4 0 10 2.7 0 78 0 0 3.4 13/13 (100%)

Top Conc. (µM)

+S9 93 40 28.4 46 39 33 43 33 24 70 31 30 4.6

25 200 100 100 400 200 200 200 200 25 200 200 200

K. Tilmant et al. / Mutation Research 751 (2013) 1–11

Compounds

Diaz et al. (2007)

Table 2 % MN frequency in CHO-k1 cells treated with clastogens and aneugens (n = 33). Experiments were performed without (-S9) and with (+S9) metabolic activation. A 2-fold increase is highlighted in light grey and a 3-fold increase is highlighted in dark grey. Statistical significance is added: *: p < 0.05, **: p <0.01, ***: p <0.001. A compound is considered as positive when the 3-fold threshold is reached with p < 0.05 and cytotoxicity ≤ 60%. The compounds were tested up to a concentration of 1mM, except when this was impeded by their solubility or cytotoxicity. LOAEL, maximum cytotoxicity, top concentrations tested and sensitivity are reported for the current study as well as for the study of Diaz et al. [10]. For more details please refer to the M&M section.

Tilmant et al. Compounds

Max % MN frequency

LOAEL (µM)

Fold increase at LOAEL

+S9 5.6 16.6

-S9 0.02 100

+S9 0.06 11.11

-S9 6.0 6.4

Fold increase at max % mn frequency

+S9 10*** 13.9*

-S9 6.0 6.4

Diaz et al. (2007)

+S9 5.6 16.6

Max Cytotoxicity

CBPI -S9 98 12

+S9 34 90

RCC -S9 77 8

+S9 67 79

Top Conc. (µM)

Max % MN frequency (µM)

LOAEL (µM)

0.18 100

-S9 12.9 Nd

+S9 11.2 nd

-S9 0.02 nd

+S9 0.02 nd

Max cytotoxicity RCC

Top Conc. (µM)

-S9 73* nd

+S9 80.7* nd

7.96 nd

2-Aminoanthracene 1c

19,3***

nd

24.6

-

133.3

-

24.6

-

64

95

36

78

1200

1.9

2.1

-

-

10*

51.1*

800

Benzo[a]pyrene 1c Bleomycin c Cadmium sulfate c Camptothecin c Carbendazim a Catechol c Colchicin a Crotonaldehyde c Cyclophosphamide c DBA1c Diethylnitrosamine c DMBA1c Etoposide a 5-Fluorouracil c Griseofulvin a

nd 30.8*** 3.6** 30.2*** 13.1** 4.2* 8.8*** 4.1*** 1.1 2.3 1.2 6.4** 27.6*** 5.7*** 23.9**

7.4*** 4.3* 3.7 10.4*** 4.2 5.6** 13.1*** 3* 34.7*** 1.7 3.7 1.6 14.5*** 9.4** 1.4

32.4 3.8 47 13.8 6.5 13.8 6.8 1.4 2.2

8.8 2.4 2.1 4.7 2.4 2.5 5.9 2.1 41 1.5

6.1 43.2 5.3 25.2

1.4 6.5 3.0 0.8

0.29 2.22 0.04 13.3 22.2 0.31 66.9 60.0 111.2 0.14 667 70.8

14.8 2.58 2.22 1 120 200 0.93 66.9 11.3 0.41 667 -

8.2 3.8 16.6 13.8 6.5 13.8 6.8 2.2 6.1 11.9 3.7 17.5

5.2 2.4 2.1 4.7 2.4 2.5 4.0 2.1 7.3 3.1 3.0 -

34 33 90 61 68 90 69 73 0 0 0 77 58 30 63

35 0 91 59 36 68 40 73 33 0 0 0 30 64 10

49 47 76 90 70 79 33 77 2 4 3 71 66 60 7

46 0 69 12 7 14 0 76 38 0 0 0 3 46 0

400 7.74 6.67 1 120 200 2.79 201 102 180 2000 333 1.22 2000 637

1.1 30 6.9 28.3 12.5 7.2 9 8.3 2.2 4.5 1.8 11.7 22 2.7 21

5.3 5 8.1 4.5 1.8 3.1 15 7.2 27 8.9 2.8 8.4 13 3.7 7.4

0.86 1.11 0.11 13.3 22.2 0.31 22.3 100 66.7 0.09 400 70.8

44.4 3.33 0.31 11.3 100 7.41 0.18 -

7.0* 51.2 74.1* 89.2* 70.1 53.0 63.2 79.9* 0.0 0.0 0.0 72.4* 42.2 4.0 74.4

56.7 36.6 76.7* 91* 12.6 54.2 75.7 75.9 46.7 38.6 27.4 55.2 67.6 43.1 76.8

400 13.8 10 28.7 40 200 1.2 1427 181 100 200 200 0.3 400 283

Hydrogen peroxide c

3.8*

4.6

4.2

1.4

800

-

4.2

-

98

13

73

10

1800

2.9

2.5

500

-

0.0

31.0

500

Mitomycin c c MMS c Nickel acetate c 2-Nitrofluorene c NNMU c 4NQO c Paclitaxel (Taxol) a

3.3*** 3.8*** 6.3*** 3.9** 2.7* 14.1*** 20.3***

1.8* 7.6*** 2.1 2.6* 6.3*** 8.3*** 3.9

4.2 5.8 7.1 5.0 3.1 16 31.8

2.1 7.6 1.3 3.1 4.0 5.3 1.8

0.18 32.9 502 119 1080 1.03 0.21

0.01 297 119 1080 9.3 -

4.2 4.0 7.1 5.0 3.1 16 19.3

2.1 7.6 3.1 4.0 5.3 -

8 82 47 92 0 99 60

26 40 2 70 0 77 0

1 73 63 36 0 87 5

2 63 6 21 11 75 0

0.18 888 1506 1066 1080 27.81 0.63

21 17.5 5.3 2.5 6.4 12.6 17.9

1.3 16.6 3.2 4.2 6.7 12.1 4.4

0.02 49.4 502 1000 0.62 0.07

148 1000 5.56 -

0.0 48.0* 76.8* 56.1 15.4 71.4* 81.5

18.3 68.5* 87.6* 43.9 40.1 60.5* 58.6

0.2 4000 4018 237 1000 50 1.17

m-Phenylenediamine c Tamoxifen a c 2 Triamterene c Vinblastine a Vincristine a

16.6*** 5.4*** 7.7*** 8.18*** 23.7***

1.5 21.5*** 1.5 3.5 2

18.9 8.2 8.8 12.8 24.9

0.9 21.5 0.9 1.6 1.1

231 33.33 300 0.03 0.03

100 -

3.8 8.2 8.8 12.8 13.6

21.5 -

58 100 67 61 70

0 97 0 16 1

31 100 42 10 48

0 32 0 3 0

2079 100 300 0.09 0.9

15.3 Nd 1.4 10.7 7.5

1.9 nd 1.7 1.5 2.2

231 nd 0.01 0.1

nd -

65.3 nd 0.0* 71.4 75.6

27.6 nd 51.3 24.4 28.7

925 nd 200 0.1 0.1

Sensitivity c

21/23 (92%)

19/23 (83%)

Sensitivity a

8/8 (100%)

7/7 (100%)

29/31 (94%)

26/30 (87%)

Overall

c&a

clastogens, a aneugens, 1 fluorescent precipitations, 2 Tamoxifen was classified as aneugen for sensitivity calculation, - not applicable, cytotoxicity was reached at higher concentrations but either very few or no more of the cells survived and were available for scoring [10] c

nd

K. Tilmant et al. / Mutation Research 751 (2013) 1–11

Actinomycin D c Aflatoxin b1 c

-S9 5.7*** 5***

no data, * Higher

5

6

K. Tilmant et al. / Mutation Research 751 (2013) 1–11

Fig. 1. Influence of different concentrations of S9 on % MN frequency in CHO-k1 cells exposed to cyclophosphamide. The different concentrations of cyclophosphamide are represented as bars of different colors (+SD, n = 3): light blue: 0 ␮M; red: 12.5 ␮M; green: 25 ␮M; purple: 50 ␮M; dark blue: 100 ␮M and orange: 200 ␮M. The % of S9 is ranging from 1.1 to 5% as indicated in the figure. The 3-fold threshold for % MN frequency is shown in red. (a) Relative % MN frequencies, the % MN frequency of the control is rescaled to 1 in each S9 condition. (b) Real values of % MN frequencies.

used but not at higer concentrations of S9 (2.5–5%). Nevertheless, when 2% S9 was used, the fold-increase of the % MN frequencies was close to the 3-fold threshold in cells exposed to cyclophosphamide at all concentrations. The difference in micronucleus formation was very significant when 1.7 or 2% S9 was used. The fold-increase of the % MN frequency was much smaller with S9 concentrations higher than 2% (Fig. 1a). This was mainly due to the higher % MN frequency in the control cells (Fig. 1b). The vehicle-treated cells (0.5% DMSO) showed low % MN frequencies (0.9–1.4%) at lower concentrations of S9 (≤2% S9) and higher % MN frequencies (4.9–6.4%) at higher concentrations of S9 (≥2.5% S9). Interestingly, the highest % MN frequency was observed in the range 15–20% in cells exposed to cyclophosphamide with all S9 concentrations except when 2% of S9 was used (Fig. 1b).

3.1.3. Influence of S9 concentration on cytotoxicity based on two methods According to the RCC method, concentrations from 2% S9 were cytotoxic to control CHO-k1 cells (Fig. 2a). For instance, cytotoxicity (RCC) in vehicle-treated cells increased to ± 65% at 2.5, 3.3 and 5% S9 in control and treated conditions (Fig. 2a). The cytotoxicity induced by S9 (≥2.5% S9) was less apparent according to the cytokinesis-block proliferation index (CBPI). Indeed, cytotoxicity in vehicle-treated cells calculated with CBPI increased only to ±35% at 2.5, 3.3 and 5% S9 (Fig. 2b). Interestingly, according to the RCC method, dose–response relationships for cytotoxicity due to cyclophosphamide was lost at higher concentrations of S9 (≥3.3% S9), in contrast to dose–response relationship observed with the CBPI method in the full range of S9 (1.1–5% S9) (Fig. 2a and b). It was decided to use 1.3% S9 for subsequent experiments. Indeed, this concentration was considered to be optimal based on the results presented in Figs. 1 and 2.

3.2. % MN frequency in CHO-k1 cells exposed to four compounds CHO-k1 cells were exposed to etoposide, camptothecin, cyclophosphamide and amiodarone. The experiment was performed in triplicate. Pictures of the micronucleated cells are presented in Fig. 3 after treatment with vehicle (−S9), camptothecin (−S9, 0.06 ␮M) and cyclophosphamide (+S9, 100 ␮M). The arrow indicates the presence of a micronucleus in a binucleated cell. In the absence of S9, 0.5% DMSO induced a maximum micronucleus frequency of 1.8% (Fig. 4a). Both etoposide and camptothecin were classified as positive in the range of 0.06–1 and 0.03–1 ␮M, respectively in the three independent experiments. A maximum % MN frequency of ca. 50% was reached with both compounds. Cyclophosphamide and amiodarone were classified as negative up to 200 and 25 ␮M, respectively. In presence of S9, in one control replicate, the % MN frequency reached 2.9 whereas it was around 1.2% for the two other replicates (Fig. 4b). Etoposide and camptothecin were also classified as positive but at higher concentrations (1, 0.25–1 ␮M, respectively) compared to the condition without S9. The % MN frequency was also low (ca. 10–20%) compared to the ca. 50% obtained in absence of S9 with these two compounds. Cyclophosphamide was classified as positive at 100 and 200 ␮M, in three independent experiments. Cyclophosphamide induced the highest % MN frequency ca. 35% in presence of S9 among the four drugs tested. Amiodarone was the only compound to be classified as negative up to 25 ␮M (in presence of S9). For both conditions (−/+S9), dose responses were generally observed for the genotoxic compounds and the level of variability was optimal in the triplicate experiments (Fig. 4a and b). Fig. 5 displays the % MN frequency as well as the % of cytotoxicity according to RCC and CBPI methods in CHO-k1 cells exposed to etoposide (−S9, Fig. 5a), camptothecin (−S9, Fig. 5b), cyclophosphamide (+S9, Fig. 5c) and amiodarone (−S9, Fig. 5d). The

K. Tilmant et al. / Mutation Research 751 (2013) 1–11

7

Fig. 2. Influence of cytotoxicity assessment according to the RCC and CBPI calculation in CHO-k1 cells exposed to different concentrations of S9 and cyclophosphamide. Cytotoxicity data generated with the RCC (a) and CBPI (b) methods. In both graphs, the first bar (light blue) represents the cytotoxicity in vehicle treated cells in absence of S9 and all data are calculated relative to this value. The different concentrations of cyclophosphamide are represented as bars of different colors (+SD, n = 3): light blue: 0 ␮M, red: 12.5 ␮M, green: 25 ␮M, purple: 50 ␮M, dark blue: 100 ␮M and orange: 200 ␮M. The % of S9 is ranging from 1.1 to 5% as indicated in the figures.

data presented originate from one of the triplicate experiments (i.e. experiment 2). In cells exposed to etoposide (−S9), the % MN frequency increased in a linear fashion from 4.3 to 51.2% in the range 0.03–0.5 ␮M (Fig. 5a). Significant cytotoxicity occurred at 0.5 ␮M (30–50%) and 1 ␮M (55–70%) according to the RCC and CBPI methods. The % MN frequency was 19.2% at 1 ␮M. Etoposide (−S9) was classified as positive at four concentrations in the range of 0.06–0.5 ␮M according to the criteria described in Section 2. In brief, ≤60% according to the RCC and CBPI methods. Consequently, amiodarone was classified as negative.

3.3. Predictivity and inter-laboratory comparison of the CHO-k1 micronucleus assay 3.3.1. Predictivity of the micronucleus assay in CHO-k1 cells (44 compounds) Forty-four compounds were tested including 31 genotoxic (clastogens and/or aneugens) and 13 non-genotoxic compounds. Of the 13 non-genotoxic compounds, 11 were classified as negative whereas diclofenac and EDTA were classified as ‘false’ positive (Table 1). Of the 31 genotoxic compounds, 27 were classified as

Fig. 3. Images of CHO-k1 cells treated with the vehicle, camptothecin and cyclophosphamide. From left to right: vehicle (0.5% DMSO) −S9, camptothecin (0.06 ␮M) −S9, and cyclophosphamide (100 ␮M) +S9. The arrows indicate micronuclei.

8

K. Tilmant et al. / Mutation Research 751 (2013) 1–11

Fig. 4. % MN frequency in CHO-k1 cells treated with 4 different compounds in three independent experiments. Experiments were done in the absence of S9 (a) and the presence of S9 (b). The three independent experiments are represented in blue, red and gray bars with their corresponding 3-fold thresholds. The name and concentration of each compound is indicated in the graphs. Average % MN frequencies (+SD, n = 3) are presented. For more details please refer to Section 2.

positive without metabolic activation (−S9). Four compounds, i.e. DBA, diethylnitrosamine, B[a]P and cyclophosphamide were not classified as positive without S9 fraction (Table 2). Only 13 of the 31 genotoxic compounds were classified as positive with S9. Two compounds were exclusively detected in the presence of S9, namely cyclophosphamide and benzo[a]pyrene. Overall, this leads to a false negative classification for two clastogens, i.e. DBA and diethylnitrosamine. In summary, the overall predictivity of the CHO-k1 micronucleus assay (−/+S9) is 91% (40/44) with a sensitivity of 94% (29/31) and a specificity of 85% (11/13). 3.3.2. Inter-laboratory comparison of the CHO-k1 micronucleus assay Out of the 44 compounds tested, 42 were in common with those tested by Diaz et al. [10]. This includes 29 genotoxic and 13 non-genotoxic compounds. It is noteworthy that Diaz et al. [10] used a 2-fold threshold for the classification of the compounds, to include weak positives, whereas in our study a 3-fold threshold was used. In our study, the % MN frequency was only reported for concentrations that induced cytotoxicity ≤50% (CBPI and RCC). Four genotoxic compounds (2-nitrofluorene, triamterene, 2aminoanthracene and benzo[a]pyrene) were detected as positive in the present study but not in Diaz et al. [10]. Fluorouracil and hydrogen peroxide were positive in our test and weakly positive in Diaz et al. [10] (p < 0.05 and a 2-fold increase). For both compounds, in our experimental conditions, the lowest observable adverse effect level (LOAEL) was higher than the maximum concentration tested by Diaz et al. [10]. Indeed, in the present study, the LOAEL for fluorouracil was 667 ␮M and the highest concentration tested by Diaz et al. [10] was 400 ␮M. Similarly, the LOAEL for hydrogen peroxide

was 800 ␮M whereas 500 ␮M was tested as a top concentration by Diaz et al. [10]. Finally, in contrast to the findings of Diaz et al. [10], DBA was not detected in our study due to fluorescent precipitations (data not shown). DBA was classified as a micronucleus inducer in the absence and in the presence of S9 [10]. With the same set of compounds, a specificity of the same magnitude was found in both studies i.e. 100% (13/13) in Diaz et al. [10] and 85% (11/13) in the present study (Table 1). The sensitivity was also comparable i.e. 87% (26/30) in Diaz et al. [10] and 94% (29/31) in our study (Table 2). The correlation coefficient (r2 ) was calculated in order to quantify the reproducibility of the results in both studies. All compounds that reached the 3-fold threshold in both studies were included, i.e. 20 compounds in the absence of S9 and five compounds in the presence of S9. A correlation coefficient of 97% was obtained between both studies (data not shown). 3.4. In vivo rat micronucleus assay with four reference compounds 3.4.1. Cellular imaging The assessment of micronucleus formation in reticulocytes by means of the cellular-imaging approach was extremely complicated due to technical limitations. Indeed, the reticulocytes (the population to be scored) represent only ca. 3.7% of the whole population in rat blood cells (data not shown). Cell smears were made manually and were very different among animals (data not shown). The acridine-orange staining allowed to distinguish the erythrocytes and reticulocytes due to the green and orange colorations, respectively. Micronuclei were stained in yellow. The overlap between different cell types (e.g. red and white cells,

K. Tilmant et al. / Mutation Research 751 (2013) 1–11

9

Fig. 5. % MN frequency and cytotoxicity in CHO-k1 cells treated with four different compounds. The cytotoxicity (%) is calculated according to the RCC and CBPI method. The compounds and concentrations are indicated in the graphs: etoposide −S9 (a), camptothecin −S9 (b), cyclophosphamide +S9 (c) and amiodarone −S9 (d). Red triangle: % MN frequency (±SD, n = 3), green bar: % cytotoxicity by RCC (+SD, n = 3), blue bar: % cytotoxicity by CBPI (+SD, n = 3). For more details please refer to Section 2.

thrombocytes) in blood smears was a clear confounding factor for accurate assessment of micronuclei in reticulocytes. Consequently, analysis with cellular imaging was discontinued as a more appropriate method (flow cytometry) was used in parallel (see below). 3.4.2. Flow cytometry A preliminary study (one rat/group) was performed to define the appropriate concentrations to use in the main study (three rats/group). Cyclophosphamide (10 mg/kg bw/day), etoposide (12.5 and 50 mg/kg bw/day), and colchicine (10 mg/kg bw/day) induced micronuclei after four days of exposure. All four compounds were correctly classified (data not shown). Nevertheless, colchicine was only administered for two days because the animal was found in poor health condition and had to be sacrificed (data not shown). Amiodarone (5 and 20 mg/kg bw/day) did not induce micronuclei. In the main experiment (three rats/group), micronuclei in reticulocytes were significantly increased in animals treated with cyclophosphamide (10 and 20 mg/kg bw/day) and etoposide (25 mg/kg bw/day) (Fig. 6). Colchicine (3.25 and 7.5 mg/kg bw/day) and amiodarone (5 and 20 mg/kg bw/day) were classified as negative. Cyclophosphamide significantly induced micronuclei at 10 and 20 mg/kg bw/day whereas only the top concentration of etoposide (25 mg/kg bw/day) generated micronuclei. It was chosen arbitrarily that at least 350 reticulocytes had to be analyzed to

take into account the results. Consequently, 1/3 rats treated with cyclophosphamide 20 mg/kg bw/day (43 reticulocytes, 9.30% MNRET) and 1/3 rats treated with etoposide 25 mg/kg bw/day (338 reticulocytes, 8.88% MN-RET) were not used for the analysis.

Fig. 6. % Micronucleated reticulocytes (% MN-RET) obtained by flow cytometry measurements of rat blood cells. Rats were treated with two doses of four reference compounds as indicated in the graph with three rats per dose. Average % MN-RET (+SD, n = 3) is presented with statistical significance: *p < 0.05, **p < 0.01, ***p < 0.001. For more details please refer to Section 2.

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K. Tilmant et al. / Mutation Research 751 (2013) 1–11

4. Discussion Genotoxicity investigations should be performed as early as possible in drug development. The battery of assays should include a bacterial and mammalian assay with high a predictive value (i.e. a high sensitivity and specificity). Recent publications [8,10,11] reveal that the automated micronucleus test is a reliable genotoxicity assay. The main objective of this manuscript was to further evaluate the usefulness of the CHO-k1 micronucleus assay in drug discovery. The work presented in this manuscript is original for various reasons. First of all, we evaluated the influence of two methods for cytotoxicity (namely RCC and CBPI) on compound classification as well as the effect of different S9 concentrations on micronucleus formation in CHO-k1 cells exposed to cyclophosphamide. Secondly, the reproducibility and inter-laboratory comparison were examined in this manuscript. Finally, both cell-imaging and flow-cytometry methodologies were compared to measure micronucleus formation in reticulocytes from rat blood cells. Technical optimization of any assay is an important step to better understand the factors that impact on the outcome. The basal levels of micronucleus formation in CHO-k1 cells remained relatively constant in 12 independent experiments in the absence or the presence of S9 (1.3%). However, more variability was observed in the presence of S9 in control cells. The influence of different S9 concentrations on micronucleus formation and cytotoxicity was studied in CHO-k1 cells exposed to 12.5–200 ␮M cyclophosphamide. Very significant differences in micronucleus formation were observed when 1.7 or 2% S9 was used. It is noteworthy that the fold-increase % MN frequency was reduced at higher S9 concentrations, and did not reach the 3-fold increase cut-off in the range 2.5–5% S9 in cells exposed to cyclophosphamide. This was mainly due to the higher levels of micronucleus formation in the control cells. Concerning the cytotoxicity assessment, two methods were used, namely the relative cell count (RCC) and the cytokinesis-block proliferation index (CBPI). In the present study, in the range 2.5–5% S9, cytotoxicity was more pronounced according to the RCC method in comparison with the CBPI results in CHOk1 cells exposed to cyclophosphamide. Nevertheless, RCC could also underestimate cytotoxicity in certain cases [19]. At optimal S9 concentration (i.e. 1.3%) any of the two methods can reveal more cytotoxicity effects depending on the chemical used (see Fig. 5b and c). This was also clearly shown in the publication of Diaz et al. [10]. Consequently, our recommendation would be to use both CBPI and RCC approaches for cytotoxicity evaluation and to take into account the method showing the highest cytotoxic effects. In addition, cytotoxicity should always be expressed relative to the vehicle-treated cells without S9 to evaluate cytotoxicity due to S9. The evaluation of cytotoxicity is certainly of key importance because results should only be taken into account when cytotoxicity is less than 50% [7]. At higher levels of cytotoxicity, results should be ignored as nonspecific micronuclei could be induced. Thus, incorrect estimation of cytotoxicity could lead to false interpretations. The preliminary test on CHO-k1 cells was performed with four reference drugs (etoposide, camptothecin, cyclophosphamide and amiodarone) selected for their ability to induce micronuclei in the presence or absence of metabolic activation (−/+S9) [10]. Amiodarone is a non-genotoxic drug. Etoposide induced micronuclei in the presence and absence of S9, camptothecin only in the absence of S9 and cyclophosphamide only in the presence of S9 [10]. Nevertheless in our study in CHO-k1 cells, camptothecin induced micronuclei under both conditions (−/+S9). In the CHO-k1 cells, etoposide, camptothecin and cyclophosphamide as well as the nongenotoxic compound (amiodarone) were correctly identified. In the absence and presence of S9, the results were reproducible and dose responses for % MN frequency were observed in CHO-k1 cells.

Our objectives were to evaluate (i) the predictivity of the CHOk1 micronucleus assay with a larger set of compounds and (ii) the inter-laboratory reproducibility by comparing our results with those of Diaz et al. [10]. Overall, in our hands, the predictivity of the automated micronucleus assay in CHO-k1 cells was optimal with a sensitivity of 94% (29/31), a specificity of 85% (11/13) and an overall predictivity of 91% (40/44). In the same cellular model (CHO-k1), Diaz et al. [10] obtained an equal predictivity (91%, 42/46) with a sensitivity and specificity of 88% (29/33) and 100% (13/13), respectively. When the LOAEL were compared in both studies, the coefficient of correlation was 97% (n = 25). Interestingly, Westerink et al. [11] obtained predictivity values quite close to our figures in CHO-k1, with a sensitivity of 80% (n = 20) and a specificity of 88% (n = 42) despite the use of another cell-imaging system (Operetta imaging system, PerkinElmer, Hamburg, Germany) with only a few compounds in common (seven genotoxic and three non-genotoxic). The study of Westerink et al. [11] is interesting for the evaluation of the automated micronucleus assay because it was performed on 62 reference compounds recommended by ECVAM for the validation of new in vitro genotoxicity testing. In our study, diclofenac and EDTA, two non-genotoxic compounds according to FDA [20] were classified as positive. Nevertheless, there are some conflicting data for both compounds. Diclofenac significantly increased chromosome aberrations in Chicken DT40 cells at 10 and 20 mg/L [21], EDTA was reported to be clastogenic in animals [22,23] and positive in GreenScreen HC at 2 mM [24]. Kirkland et al. [14] reported a low specificity for in vitro mammalian genotoxicity assays and particularly for the in vitro micronucleus assay with a specificity ranging from 31 to 54% (n = 26) depending on the thresholds used. This is in contrast with the high specificities (≥85%) obtained in the present manuscript and in other studies [10–13]. Reasons for specificity differences could be the use of different cellular models, thresholds, experimental conditions (e.g. concentrations > 1 mM; cytotoxicity > 50%) and improvement in data interpretation by automation. Other explanations for artifactual positive responses in mammalian genotoxicity assays could be due to the high osmolarity, high ionic strength and extreme pH-values that could lead to non-specific genotoxicity [8]. Finally, p53-deficiency in a cell line could also play an important role in the generation of false positives. Fowler et al. [25] have compared several rodent cell lines (V79, CHL, CHO) with p53-competent human peripheral blood lymphocytes (HuLy), TK6 human lymphoblastoid cells, and HepG2 cells. They concluded that the rodent cell lines (V79, CHO and CHL) in comparison to the p53-competent cells were more susceptible to give misleading positive results. Nevertheless, Westerink et al. [11] reported an equal specificity of 88% on both, HepG2 and CHO-k1 cells with a set of 42 non-genotoxic compounds including the 19 ‘problematic’ compounds from the ECVAM list that are frequently scored as false-positive [26]. In addition, HepG2 cells were reported to have a lower sensitivity (60%) compared with the CHO-k1 cells (80%) with a set of 20 compounds [11]. The present study also supports the use of CHO-k1 cells for genotoxicity investigations. Finally, our intention was to extend the use of the cellularimaging system for the analysis of micronuclei in rat blood cells. Indeed, according to the ICH guideline S2 (R1) [7], systems for automated analysis (image analysis and flow cytometry) can be used if appropriately validated. For that purpose, rats were exposed to cyclophosphamide, etoposide, colchicine and amiodarone. In the in vitro reproducibility study, the same compounds were used except for camptothecin. For the in vivo study, it was decided to replace camptothecin by colchicine because the latter is known to be a challenging compound as it induces micronuclei in a very narrow range [27]. Micronucleus assessment was done in reticulocytes because spleen eliminates micronucleated erythrocytes [28,29]. In our study, the % of erythrocytes containing micronuclei

K. Tilmant et al. / Mutation Research 751 (2013) 1–11

varied between 0.01 and 0.04%, all treatments included (data not shown). Nevertheless, due to the low fraction of analyzable cells i.e. ±3.7% reticulocytes [30] and technical issues such as cell overlap, we decided to use the flow-cytometric approach. The assessment of micronucleated reticulocytes in blood by flow cytometry with CD71-labeling, has been reported as a sensitive method with high analysis throughput [31]. In one experiment, colchicine at 7.25 mg/kg bw/day increased the % MN frequency in reticulocytes by a factor 8 compared with the control, but this was not significant due to the large variability. Two of the three genotoxic compounds (cyclophosphamide, etoposide, but not colchicine) and the nongenotoxic compound (amiodarone) were correctly classified. In summary, we preferred to use the flow cytometry approach for the measurement of micronuclei in blood reticulocytes, compared with cell imaging. In conclusion, the choice of the method to assess cytotoxicity is particularly important and we recommend to use both RCC and CBPI approaches for that purpose. To estimate toxicity due to S9 itself, we also recommend to compare cytotoxicity in the +S9 condition with that in the vehicle-treated cells in the absence of S9. Our micronucleus data compare well with those reported by Diaz et al. [10] with a set of 42 compounds. The CHO-k1 micronucleus assay is well suited for the screening of new chemical entities as it displays an overall predictivity of 91% (n = 44). Finally, we preferred to assess in vivo micronucleus formation by means of flow cytometry compared with cellular imaging, due to important technical issues with the latter method. Conflict of interest

[10] [11]

[12]

[13]

[14]

[15]

[16] [17]

[18]

[19]

[20] [21]

The author claims there is no conflict of interest. [22]

Acknowledgements We would like to thank Jean-Marie Frequin and the In life Unit of UCB for their valuable help. Loïc Cerf and colleagues are acknowledged for the flow cytometric measurements at Fluofarma (Pessac, France). Nick Billinton and Matthew Tate (Gentronix) are acknowledged for the helpful comments during the achievement of this article.

[23]

[24]

[25]

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