Patent Publication Number: US-2013244896-A1

Title: In vitro method for predicting whether a compound is genotoxic in vivo

Description:
PRIORITY CLAIM 
     This application claims the benefit of the filing date of European Patent Application Serial No. 12159546.6, filed Mar. 14, 2012, the entire contents of which is incorporated herein by this reference. 
     TECHNICAL FIELD 
     The invention is in the field of genomics and it provides an in vitro method for predicting whether a compound is genotoxic in vivo. 
     BACKGROUND 
     The classic two-year rodent bioassay is the standard test for identifying the carcinogenic potential of chemical compounds. Such tests are time-consuming and costly. Moreover, they require the sacrifice of many animal lives. In vitro systems are therefore preferred; however, there is no reliable in vitro method for accurately predicting the genotoxicity of a compound in vivo. (1, 2)    
     Well-established in vitro systems frequently used to identify the genotoxic potential of chemical compounds are for instance the bacterial Ames test, the mouse lymphoma assay, the micronucleus test and the chromosomal aberration test. (3)    
     These classic in vitro genotoxicity tests, however, have been shown to generate an extremely high false positive rate when compared to in vivo carcinogenicity data. (3)  False positive in this context means that the compound yields a positive result in the in vitro assay whereas it is negative for genotoxicity in an in vivo assay. 
     Because of the low predictive value of current in vitro assays, a compound that tested positive in an in vitro assay has to be retested in an in vivo assay in order to verify whether the compound is a true genotoxic (GTX) compound. This generates a lot of extra costs and efforts, as well as the sacrifice of many animal lives. 
     Therefore, new and more predictive in vitro systems are desired in the art which are capable of reliably discriminating genotoxins from non-genotoxins. 
     DISCLOSURE 
     The present invention employs the analysis of expression profiles of microRNAs in human hepatocellular carcinoma cells under the influence of potentially genotoxic compounds. In that way we were able to discriminate true in vivo GTX compounds from non-GTX compounds (NGTX). 
     Hence, the invention relates to an in vitro method for distinguishing between genotoxic and non-genotoxic compounds by determining the expression level of at least microRNA 1262 and comparing the expression level thus obtained with a reference value of expression of microRNA 1262 wherein it is concluded that a compound is genotoxic if the expression of said microRNA 1262 is below the reference value. 
    
    
     DETAILED DESCRIPTION 
     Chemical compounds, which are able to cause gene mutations or chromosomal damage in vivo are herein defined as true genotoxins (true GTX). (6, 12)  False positive genotoxins (false positive GTX or false GTX) are herein defined as compounds that are not capable of causing gene mutations or chromosomal damage in vivo, but are positive in a conventional in vitro assay for genotoxicity. 
     Gene mutations or chromosomal damage may occur when the compound covalently binds to DNA in vivo. Such binding to DNA may be not or incorrectly repaired which may lead to mutations accumulating in time and ultimately inducing the formation of tumors. (6, 12)    
     The present invention employs the analysis of expression profiles of microRNA 1262 as an in vitro system to discriminate GTX compounds from non-GTX compounds. 
     It was found that differential expression of microRNA 1262 could reliably predict whether a compound was a true genotoxic compound. So as a first step in the method according to the invention, a cell or cell line is provided, preferably a human cell line, even more preferably a human hepatocellular carcinoma cell line. Most preferred is a HepG2 cell line (ATCC HB-6065). 
     The skilled person is aware of the various methods that may be used to obtain a suitable cell or cell line. The examples provided herein may provide additional guidance. 
     In a further step of the method according to the invention, an assay is provided capable of determining the expression level of microRNA 1262 (miR 1262). 
     Assays that may determine expression of miR 1262 are also known in the art. Such an assay may consist of a single PCR-based assay or a hybridization assay. In the alternative, a multiplex assay may be used, consisting of a plurality of different assays that can be performed simultaneously. This allows for the determination of simultaneous expression of more than one gene. Even more advantageously, the assay is a nucleic acid microarray such as a DNA microarray, such as a GENECHIP® provided by Affymetrix. Preferred is the use of a miRCURY™ locked-nuclei acid array (LNA) array as provided by Exiqon, Denmark. 
     In another step of the method according to the invention, the compound to be tested for genotoxicity is contacted with the cell line. The time of contact may differ somewhat depending on the particular cell line chosen and should be determined empirically. For the HepG2 cell line, 12 to 24 hours appeared a suitable time, this is however not critical. The skilled person will be aware of the metes and bounds of this step. 
     In the examples section, the concentrations used for three GTX compounds and six non-GTX (NGTX) compounds are provided as guidance. In general, the use of cytotoxic concentrations should be avoided. The skilled person will know how to avoid using cytotoxic concentrations of test compounds. 
     In order to obtain reproducible results, it was found advantageous to obtain at least three independent readings of the gene expression. Hence, the above steps may be repeated at least twice to obtain a more reproducible and reliable result. 
     Hence, the invention relates to an in vitro method for determining whether a compound is genotoxic or non-genotoxic compounds said method comprising the steps of:
         a. exposing a cell to the compound for a certain amount of time,   b. determining the expression level of at least one microRNA marker in said cell,   c. comparing said expression level with a predetermined reference value and determining whether the expression level of the at least one microRNA marker is below or above the reference value,   d. determining whether the compound is a genotoxic compound or a non-genotoxic compound,   wherein the at least one microRNA marker is microRNA 1262.       

     It appeared that the method could be improved as described herein below by measuring the expression levels of at least three microRNAs. In a preferred embodiment, the invention therefore relates to an in vitro method as described above wherein the at least one microRNA is microRNA 1262, microRNA 98 and microRNA 30c-1. 
     The method could be further improved by employing the expression levels of ten microRNAs. In a further preferred embodiment, the invention relates to an in vitro method as described above wherein the at least one microRNA is microRNA 1262, microRNA 98, microRNA 30c-1, microRNA 885-3p, microRNA 888*, microRNA 1229, microRNA 891b, microRNA302b, microRNA 1246 and microRNA 502-3p. 
     It is preferred to use a HepG2 cell line in the above invention, the preferred incubation times for the compound is in the order of 12-24 hours. 
     Particularly good results were obtained when the above method steps a-d are performed at least in triplicate thereby obtaining expression levels at least in triplicate and wherein the step of determining whether the compound is a genotoxic compound or a non-genotoxic compound is based on the average of such at least in triplicate expression levels. 
     EXAMPLES 
     Example 1 
     Cells and Culture 
     Human hepatocellular carcinoma HepG2 cells (ATCC HB-6065) were used in all the experiments. HepG2 cells were maintained as a monolayer culture in 95% humidity, atmosphere with 5% of CO2 and 37° C. HepG2 cells were passaged at pre-confluent densities with trypsin-EDTA solution. Cells were cultured and passaged in Minimal Essential Medium (MEM) supplemented with 10% of Foetal Bovine serum, 1% penicillin/streptomycin, 1% sodium-pryruvate and 1% non-essential amino acids. All media compounds were obtained from Gibco BRL (Breda, the Netherlands). Two milliliters of cells (7×10 4 /mL) were seeded into each well in a six-well microtiter plate. HepG2 cells were exposed to nine compounds at IC20-72 hours values as specified in Table 1 and to a vehicle control (0.5% DMSO and PBS) during 12 hours. All measurements were performed in triplicate. 
     Example 2 
     RNA Isolation 
     Total RNA was isolated after 24 hours of incubation with the nine compounds (AFB1, BaP, Cispl, 8HQ, Que, E2, AmpC, CsA, TCDD) or controls (DMSO and PBS). Isolation of total RNA was done by using miRNeasy mini Kit (Qiagen Westburg by, Leusden, the Netherlands) according to the manufacturer&#39;s instructions and followed by a DNAse I (Qiagen Inc.) treatment. RNA quantity was measured on a spectrophotometer and quality was determined by BioAnalyzer (Agilent Technologies, Breda, the Netherlands). Only RNA samples which showed clear 18S and 28S peaks and with a RIN level higher than 8 were used. 
     Example 3 
     Determining MicroRNA Expression Using Exiqon Arrays 
     The miRCURY™ locked-nuclei acid array (LNA), fifth generation (Exiqon, Denmark) contains probes that detect mature forms of all microRNAs present in miRBase 15.0 (http://www.mirbase.org/). The Exiqon platform has been validated and is shown to reliably detect microRNA expression. The microarray contains 9360 reporters, each present four times on the microarray. In our analysis 1326 human and viral reporters were used, of which 880 are unique human mature microRNAs. The other 8024 reporters represent microRNAs from other species. cDNA was generated using 1 μg of total RNA per sample. RNA was labeled only with Hy3 containing dye using the mercury LNA™ microRNA Hy3 Power labeling kit (Exiqon, Denmark) according to the manufacturer&#39;s protocol in a total volume of 25 μl. To adjust the volume to 100 μl, a hybridization buffer provided in miRCURY LNA™ microRNA Array, fifth generation kit (Exiqon, Denmark) was used. In a total volume of 100 μl the sample was incubated for 5 minutes at 95° C., spinned for 2 minutes at maximal speed and injected in the hybridization station. Hybridization was performed in a Tecan HS4800 Pro Hybridization station according to manufacturer protocol. 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Compounds used in the study 
               
            
           
           
               
               
               
               
               
               
               
            
               
                 Compound 
                 Abbreviation 
                 CAS no 
                 Dose 
                 Solvent 
                 Ames test result 
                 GTX in vivo 
               
               
                   
               
               
                 Aflatoxin B1 
                 AFB1 
                 1162-65-8 
                  1 μM 
                 DMSO 
                 + 
                 + 
               
               
                 Benzo[a]pyere 
                 BaP 
                 50-32-8 
                  2 μM 
                 DMSO 
                 + 
                 + 
               
               
                 Cisplatin 
                 CisPl 
                 15663-27-1 
                  7 μM 
                 PBS 
                 + 
                 + 
               
               
                 8-quinolinol 
                 8HQ 
                 148-24-3 
                 15 μM 
                 DMSO 
                 + 
                 − 
               
               
                 Quercetin 
                 Que 
                 117-39-5 
                 50 μM 
                 DMSO 
                 + 
                 − 
               
               
                 17 beta-estradiol 
                 E2 
                 50-28-2 
                 30 μM 
                 DMSO 
                 − 
                 − 
               
               
                 Ampicillin trihydrate 
                 AmpC 
                 7177-48-2 
                 250 μM  
                 DMSO 
                 − 
                 − 
               
               
                 Cyclosporine A 
                 CsA 
                 59865-13-3 
                  3 μM 
                 DMSO 
                 − 
                 − 
               
               
                 2,3,7,8-tetrachloro dibenzo-p-dioxin 
                 TCDD 
                 1746-01-6 
                 10 nM 
                 DMSO 
                 − 
                 − 
               
               
                   
               
            
           
         
       
     
     For each biological experiment, one hybridization per time point was conducted and one sample per array. After hybridization, the microarray slides were washed accordingly Exiqon instructions. Then arrays were scanned using the GenePix 4000A scanner (Axon Instruments, Foster City, Calif.). To quantify the signals, the images were processed to TXT files through the GenePix Pro Software Suite version 3.0 by using the GAL file for probe annotation as obtained from Exiqon. 
     The GAL file is based on miRBase version 15.0. These GPR files were then imported in R 2.11.0, for quality control and statistical analysis. R package is freely available for academic use from the Comprehensive R Archive Network (on the World Wide Web at cran.r-project.org/). 
     First, the quality of all arrays was inspected using arrayQC, an in-house quality control pipeline that generates virtual images, boxplots, correlation plots, clustering images, MvA and PCA plots. Spike-ins were used for all arrays as an extra quality check. Within this dataset, no arrays were technically deviating. 
     During data analysis the spot intensities were background-corrected and then filtered for low signals (i.e., intensity &lt;10). Only the viral and human microRNA reporter intensities (1.326 unique reporters×four technical replicates) were used further. If for a reporter less than three of the four technical replicates were left, then the reporter intensity on that specific reporter was set to NA. The data were log 2 transformed, followed by a quantile normalization and a summarization step. In the summarization step, the median intensity from the remaining technical replicates per condition was calculated. Finally, for each reporter a cut-off filtering was applied using the median of the three biological replicates. Only reporters that had a median intensity ≧50 for at least one condition of the nine compounds tested, or their respective controls, passed this filtering per time point. A microRNA was considered as differentially expressed when the absolute Fold Change (FC)&gt;1.5 and the p-value for a paired t-test was &lt;0.1. 
     Example 4 
     GTX or NGTX Class Prediction Using microRNAs 
     In order to predict the class of a compound, average log 2 ratios of expression values of 10 selected microRNAs were calculated for the GTX and NGTX compounds listed in Table 1. A compound was regarded as GTX or NGTX, when the microRNA was differentially expressed below or above a certain threshold value. Table 2 shows the threshold values applied herein for the ten selected microRNAs. This was done for every microRNA separately. A compound was predicted to be in vivo GTX when more than 50% of the microRNAs gave the prediction in vivo GTX than in vivo NGTX. A compound was predicted to be in vivo NGTX when more than 50% of the microRNAs gave the prediction in vivo NGTX than in vivo GTX. If number of predictions for both classes were equal, the compound could not be assigned to a class. 
     
       
         
           
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                 MicroRNAs and their reference values 
               
               
                 for predicting in vivo genotoxicity 
               
            
           
           
               
               
               
               
            
               
                   
                   
                 Prediction if 
                 Prediction if 
               
               
                   
                 Reference 
                 Expression is above 
                 Expression is below 
               
               
                 miRNA_ID 
                 Value 
                 Reference value 
                 Reference value 
               
               
                   
               
            
           
           
               
               
               
               
            
               
                 hsa-miR-885-3p 
                 0.407 
                 NGTX 
                 GTX 
               
               
                 hsa-miR-888* 
                 −0.046 
                 GTX 
                 NGTX 
               
               
                 hsa-miR-98 
                 −0.043 
                 GTX 
                 NGTX 
               
               
                 hsa-miR-1262 
                 −0.060 
                 NGTX 
                 GTX 
               
               
                 hsa-miR-1229 
                 0.224 
                 NGTX 
                 GTX 
               
               
                 hsa-miR-30c-1* 
                 −0.093 
                 GTX 
                 NGTX 
               
               
                 hsa-miR-891b 
                 0.109 
                 GTX 
                 NGTX 
               
               
                 hsa-miR-302b 
                 0.096 
                 NGTX 
                 GTX 
               
               
                 hsa-miR-1246 
                 0.554 
                 NGTX 
                 GTX 
               
               
                 hsa-miR-502-3p 
                 −0.151 
                 GTX 
                 NGTX 
               
               
                   
               
            
           
         
       
     
     Example 5 
     microRNA 1262 Perfectly Distinguishes GTX from NGTX Compounds 
     Prediction analysis with miR-1262 was conducted as described above using the reference value presented in Table 2. The results are shown in Table 3. 
     
       
         
           
               
             
               
                 TABLE 3 
               
             
            
               
                   
               
               
                 Prediction analysis with microRNA 1262 
               
            
           
           
               
               
            
               
                   
                 miRNA 1262 
               
            
           
           
               
               
               
               
               
            
               
                   
                 Abbre- 
                 GTX in 
                 Pre- 
                   
               
               
                 Compound 
                 viation 
                 vivo 
                 diction 
                 Score* 
               
               
                   
               
               
                 Aflatoxin B1 
                 AFB1 
                 GTX 
                 GTX 
                 (2/3) 
               
               
                 Benzo[a]pyere 
                 BaP 
                 GTX 
                 GTX 
                 (2/3) 
               
               
                 Cisplatin 
                 CisPl 
                 GTX 
                 GTX 
                 (2/3) 
               
               
                 8-quinolinol 
                 8HQ 
                 NGTX 
                 NGTX 
                 (2/3) 
               
               
                 Quercetin 
                 Que 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 17beta-estradiol 
                 E2 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 Ampicillin trihydrate 
                 AmpC 
                 NGTX 
                 NGTX 
                 (2/3) 
               
               
                 Cyclosporine A 
                 CsA 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 2,3,7,8-tetrachloro dibenzo- 
                 TCDD 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 p-dioxin 
               
               
                 Correctness of prediction 
                   
                   
                 100% 
                 22/27 (81%) 
               
               
                   
               
               
                 *Score indicates the number of correct predictions of three independent experiments. 
               
            
           
         
       
     
     MicroRNA 1262 scored each of the nine compounds correctly, albeit that five out of nine compounds were classified based on a score of two correct classifications out of three independent experiments. This resulted in a score of 81% when the score was averaged over nine compounds. 
     Example 6 
     Inclusion of Other miRNAs in the Analysis Improves the Correctness of Prediction 
     When the expression levels of microRNAs 98 and 30c-1 were included in the prediction analysis, the results improved. Notwithstanding the fact that microRNA 98 and 30c-1 on their own did not predict the genotoxicity of the compounds 100% correctly (Tables 4 and 5), when their results were combined with those of microRNA 1262, their overall accuracy improved to 93% (Table 6). 
     
       
         
           
               
             
               
                 TABLE 4 
               
             
            
               
                   
               
               
                 Prediction analysis with microRNA 98 
               
            
           
           
               
               
            
               
                   
                 miRNA 98 
               
            
           
           
               
               
               
               
               
            
               
                   
                 Abbre- 
                 GTX in 
                 Pre- 
                   
               
               
                 Compound 
                 viation 
                 vivo 
                 diction 
                 Score* 
               
               
                   
               
               
                 Aflatoxin B1 
                 AFB1 
                 GTX 
                 GTX 
                 (2/3) 
               
               
                 Benzo[a]pyere 
                 BaP 
                 GTX 
                 GTX 
                 (2/3) 
               
               
                 Cisplatin 
                 CisPl 
                 GTX 
                 GTX 
                 (3/3) 
               
               
                 8-quinolinol 
                 8HQ 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 Quercetin 
                 Que 
                 NGTX 
                 GTX 
                 (1/3) 
               
               
                 17beta-estradiol 
                 E2 
                 NGTX 
                 NGTX 
                 (2/3) 
               
               
                 Ampicillin trihydrate 
                 AmpC 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 Cyclosporine A 
                 CsA 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 2,3,7,8-tetrachloro dibenzo- 
                 TCDD 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 p-dioxin 
               
               
                 Correctness of prediction 
                   
                   
                 89% 
                 22/27 (81%) 
               
               
                   
               
            
           
         
       
     
     
       
         
           
               
             
               
                 TABLE 5 
               
             
            
               
                   
               
               
                 Prediction analysis with microRNA 30c-1 
               
            
           
           
               
               
            
               
                   
                 miRNA 30c-1 
               
            
           
           
               
               
               
               
               
            
               
                   
                 Abbre- 
                 GTX in 
                 Pre- 
                   
               
               
                 Compound 
                 viation 
                 vivo 
                 diction 
                 Score* 
               
               
                   
               
               
                 Aflatoxin B1 
                 AFB1 
                 GTX 
                 GTX 
                 (2/3) 
               
               
                 Benzo[a]pyere 
                 BaP 
                 GTX 
                 GTX 
                 (2/3) 
               
               
                 Cisplatin 
                 CisPl 
                 GTX 
                 GTX 
                 (2/3) 
               
               
                 8-quinolinol 
                 8HQ 
                 NGTX 
                 GTX 
                 (1/3) 
               
               
                 Quercetin 
                 Que 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 17beta-estradiol 
                 E2 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 Ampicillin trihydrate 
                 AmpC 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 Cyclosporine A 
                 CsA 
                 NGTX 
                 NGTX 
                 (3/3) 
               
               
                 2,3,7,8-tetrachloro dibenzo- 
                 TCDD 
                 NGTX 
                 NGTX 
                 (2/3) 
               
               
                 p-dioxin 
               
               
                 Correctness of prediction 
                   
                   
                 89% 
                 21/27 (78%) 
               
               
                   
               
            
           
         
       
     
     
       
         
           
               
             
               
                 TABLE 6 
               
             
            
               
                   
               
               
                 Aggregated prediction using three different microRNAs. 
               
            
           
           
               
               
               
               
               
            
               
                   
                   
                   
                 correctness of miRNA 
                   
               
               
                   
                 Abbre- 
                 GTX in 
                 prediction 
                 Aggregate result 
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                 Compound 
                 viation 
                 vivo 
                 1262 
                 98 
                 30c-1 
                 result 
                 correct 
               
               
                   
               
               
                 Aflatoxin B1 
                 AFB1 
                 GTX 
                 (2/3) 
                 (2/3) 
                 (2/3) 
                 GTX 
                 3/3 
               
               
                 Benzo[a]pyere 
                 BaP 
                 GTX 
                 (2/3) 
                 (2/3) 
                 (2/3) 
                 GTX 
                 3/3 
               
               
                 Cisplatin 
                 CisPl 
                 GTX 
                 (2/3) 
                 (3/3) 
                 (2/3) 
                 GTX 
                 3/3 
               
               
                 8-quinolinol 
                 8HQ 
                 NGTX 
                 (2/3) 
                 (3/3) 
                 (1/3) 
                 NGTX 
                 2/3 
               
               
                 Quercetin 
                 Que 
                 NGTX 
                 (3/3) 
                 (1/3) 
                 (3/3) 
                 NGTX 
                 2/3 
               
               
                 17beta-estradiol 
                 E2 
                 NGTX 
                 (3/3) 
                 (2/3) 
                 (3/3) 
                 NGTX 
                 3/3 
               
               
                 Ampicillin 
                 AmpC 
                 NGTX 
                 (2/3) 
                 (3/3) 
                 (3/3) 
                 NGTX 
                 3/3 
               
               
                 trihydrate 
               
               
                 Cyclosporine A 
                 CsA 
                 NGTX 
                 (3/3) 
                 (3/3) 
                 (3/3) 
                 NGTX 
                 3/3 
               
               
                 2,3,7,8-tetrachloro 
                 TCDD 
                 NGTX 
                 (3/3) 
                 (3/3) 
                 (2/3) 
                 NGTX 
                 3/3 
               
               
                 dibenzo-p-dioxin 
               
               
                 Correctness of 
                   
                   
                 22/27 
                 22/27 
                 21/27 
                 100% 
                 25/27 
               
               
                 prediction 
                   
                   
                 (81%) 
                 (81%) 
                 (78%) 
                   
                 (93%) 
               
               
                   
               
            
           
         
       
     
     Example 7 
     Inclusion of Further miRNAs in the Analysis Improves the Robustness of Prediction 
     When the expression levels of microRNAs 885-3p, 888*, 98, 1262, 1229, 30c-1*, 891b, 302b, 1246, and 502-3p were included in the prediction analysis, the overall results did not further improve, however, the test was found to be more robust. In particular, the use of human microRNAs is preferred when using human samples, such microRNAs are designated hsa-miR-885-3p, hsa-miR-888*, hsa-miR-98, hsa-miR-1262, hsa-miR-1229, hsa-miR-30c-1*, hsa-miR-891b, hsa-miR-302b, hsa-miR-1246, and hsa-miR-502-3p. 
     MicroRNAs hsa-miR-885-3p, hsa-miR-888*, hsa-miR-1229, 891b, 302b, 1246, and 502-3p on their own did not predict the genotoxicity of the compounds 100% correctly. However, when combined with other miRNAs the combined robustness or accuracy of prediction improved. Table 8 provides some additional information on the microRNAs used. 
     
       
         
           
               
               
               
               
               
             
               
                   
                 TABLE 7 
               
             
            
               
                   
                   
               
               
                   
                 Ab- 
                   
                   
                 Aggregate 
               
               
                   
                 bre- 
                   
                   
                 result 
               
            
           
           
               
               
               
               
               
               
            
               
                   
                 via- 
                 GTX in 
                 correctness of microRNA prediction 
                   
                 cor- 
               
            
           
           
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
            
               
                 Compound 
                 tion 
                 vivo 
                 1262 
                 98 
                 30c-1 
                 885-3p 
                 888* 
                 1229 
                 891b 
                 302b 
                 1246 
                 502-3p 
                 result 
                 rect 
               
               
                   
               
               
                 Aflatoxin B1 
                 AFB1 
                 GTX 
                 (2/3) 
                 (2/3) 
                 (2/3) 
                 (1/3) 
                 (3/3) 
                 (1/3) 
                 (2/3) 
                 (2/3) 
                 (1/3) 
                 (2/3) 
                 GTX 
                 17/30 
               
               
                 Benzo[a]pyere 
                 BaP 
                 GTX 
                 (2/3) 
                 (2/3) 
                 (2/3) 
                 (2/3) 
                 (2/3) 
                 (3/3) 
                 (3/3) 
                 (2/3) 
                 (3/3) 
                 (2/3) 
                 GTX 
                 23/30 
               
               
                 Cisplatin 
                 CisPl 
                 GTX 
                 (2/3) 
                 (3/3) 
                 (2/3) 
                 (3/3) 
                 (1/3) 
                 (3/3) 
                 (3/3) 
                 (3/3) 
                 (2/3) 
                 (2/3) 
                 GTX 
                 24/30 
               
               
                 8-quinolinol 
                 8HQ 
                 NGTX 
                 (2/3) 
                 (3/3) 
                 (1/3) 
                 (1/3) 
                 (3/3) 
                 (3/3) 
                 (3/3) 
                 (1/3) 
                 (0/3) 
                 (2/3) 
                 NGTX 
                 19/30 
               
               
                 Quercetin 
                 Que 
                 NGTX 
                 (3/3) 
                 (1/3) 
                 (3/3) 
                 (1/3) 
                 (1/3) 
                 (1/3) 
                 (2/3) 
                 (1/3) 
                 (2/3) 
                 (1/3) 
                 NGTX 
                 16/30 
               
               
                 17beta- 
                 E2 
                 NGTX 
                 (3/3) 
                 (2/3) 
                 (3/3) 
                 (1/3) 
                 (0/3) 
                 (2/3) 
                 (1/3) 
                 (2/3) 
                 (2/3) 
                 (1/3) 
                 NGTX 
                 17/30 
               
               
                 estradiol 
               
               
                 Ampicillin 
                 AmpC 
                 NGTX 
                 (2/3) 
                 (3/3) 
                 (3/3) 
                 (3/3) 
                 (3/3) 
                 (3/3) 
                 (2/3) 
                 (2/3) 
                 (1/3) 
                 (3/3) 
                 NGTX 
                 25/30 
               
               
                 trihydrate 
               
               
                 Cyclosporine A 
                 CsA 
                 NGTX 
                 (3/3) 
                 (3/3) 
                 (3/3) 
                 (2/3) 
                 (2/3) 
                 (2/3) 
                 (2/3) 
                 (3/3) 
                 (2/3) 
                 (2/3) 
                 NGTX 
                 24/30 
               
               
                 2,3,7,8-tetra- 
                 TCDD 
                 NGTX 
                 (3/3) 
                 (3/3) 
                 (2/3) 
                 (3/3) 
                 (1/3) 
                 (2/3) 
                 (2/3) 
                 (2/3) 
                 (3/3) 
                 (2/3) 
                 NGTX 
                 23/30 
               
               
                 chloro dibenzo- 
               
               
                 p-dioxin 
               
               
                 Correctness of 
                   
                   
                 22/27 
                 22/27 
                 21/27 
                 17/27 
                 16/27 
                 20/27 
                 20/27 
                 18/27 
                 16/27 
                 17/27 
                 100% 
                 188/270 
               
               
                 prediction 
                   
                   
                 (81%) 
                 (81%) 
                 (78%) 
                 (63%) 
                 (59%) 
                 (74%) 
                 (74%) 
                 (67%) 
                 (59%) 
                 (63%) 
                   
                 (70%) 
               
               
                   
               
            
           
         
       
     
     
       
         
           
               
             
               
                 TABLE 8 
               
             
            
               
                   
               
               
                 Additional Information (microRNA sequences, MiRBase) 
               
            
           
           
               
               
               
               
            
               
                 v15 miRBase_ID 
                 v18 miRBase_ID 
                 Mature_Acc 
                 Sequence 
               
               
                   
               
            
           
           
               
               
               
               
               
            
               
                 hsa-miR-885-3p 
                 hsa-miR-885-3p 
                 MIMAT0004948 
                 AGGCAGCGGGGUGUAGUGGAUA 
                 SEQ ID NO: 1 
               
               
                   
               
               
                 hsa-miR-888* 
                 hsa-miR-888-3p 
                 MIMAT0004917 
                 GACUGACACCUCUUUGGGUGAA 
                 SEQ ID NO: 2 
               
               
                   
               
               
                 hsa-miR-98 
                 hsa-miR-98 
                 MIMAT0000096 
                 UGAGGUAGUAAGUUGUAUUGUU 
                 SEQ ID NO: 3 
               
               
                   
               
               
                 hsa-miR-1262 
                 hsa-miR-1262 
                 MIMAT0005914 
                 AUGGGUGAAUUUGUAGAAGGAU 
                 SEQ ID NO: 4 
               
               
                   
               
               
                 hsa-miR-1229 
                 hsa-miR-1229 
                 MIMAT0005584 
                 CUCUCACCACUGCCCUCCCACAG 
                 SEQ ID NO: 5 
               
               
                   
               
               
                 hsa-miR-30c-1* 
                 hsa-miR-30c-1-3p 
                 MIMAT0004674 
                 CUGGGAGAGGGUUGUUUACUCC 
                 SEQ ID NO: 6 
               
               
                   
               
               
                 hsa-miR-891b 
                 hsa-miR-891b 
                 MIMAT0004913 
                 UGCAACUUACCUGAGUCAUUGA 
                 SEQ ID NO: 7 
               
               
                   
               
               
                 hsa-miR-302b 
                 hsa-miR-302b-5p 
                 MIMAT0000714 
                 ACUUUAACAUGGAAGUGCUUUC 
                 SEQ ID NO: 8 
               
               
                   
               
               
                 hsa-miR-1246 
                 hsa-miR-1246 
                 MIMAT0005898 
                 AAUGGAUUUUUGGAGCAGG 
                 SEQ ID NO: 9 
               
               
                   
               
               
                 hsa-miR-502-3p 
                 hsa-miR-502-3p 
                 MIMAT0004775 
                 AAUGCACCUGGGCAAGGAUUCA 
                 SEQ ID NO: 10 
               
               
                   
               
            
           
         
       
     
     LITERATURE INCORPORATED BY REFERENCE 
     Cited References 
     
         
         1. Dambach, et al.,  Toxicol. Pathol.,  2005, 33(1):17-26. 
         2. Tsujimura K., et al.,  Cancer Sci.,  2006, 97(10):1002-10. 
         3. Kirkland D., et al.,  Mutat. Res.,  2005, 584(1-2):1-256. 
         4. Chhabra R. S.,  Environ. Health Perspect.,  1979, 33:61-9. 
         5. Le Fevre A. C., et al.,  Mutat. Res.,  2007, 619(1-2):16-29. 
         6. Eun J. W., et al.,  Toxicology,  2008, 249(2-3):176-83. 
         7. Aubrecht J., et al.,  Toxicol. Appl. Pharmacol.,  1999, 154(3):228-35. 
         8. Ellinger-Ziegelbauer H., et al.,  Toxicol. Lett.,  2009, 186(1):36-44. 
         9. Ellinger-Ziegelbauer H., et al.,  Mutat. Res.,  2007. 
         10. Ellinger-Ziegelbauer H., et al.,  Toxicol. Sci.,  2004, 77(1):19-34. 
         11. Ellinger-Ziegelbauer H., et al.,  Mutat. Res.,  2005, 575(1-2):61-84. 
         12. Nioi P., et al.,  Chem. Biol. Interact.,  2008, 172(3):206-15. 
         13. Waterston R. H., et al.,  Nature,  2002, 420(6915):520-62. 
         14. Koike M., et al.,  J. Radiat. Res.  (Tokyo), 2008. 
         15. Rogakou E. P., et al.,  J. Biol. Chem.,  1998, 273(10):5858-68. 
         16. Seglen P. O.,  Methods Cell. Biol.,  1976, 13:29-83. 
         17. Casciano D. A.,  Drug Metab. Rev.,  2000, 32(1):1-13. 
         18. Mathijs K., et al.,  Drug Metab. Dispos.,  2009. 
         19. Koebe H. G., et al.,  Int. J. Artif. Organs,  1994, 17(2):95-106. 
         20. Beken S., et al.,  Methods Mol. Biol.,  1998, 107:303-9. 
         21. Hamer G., et al.,  Biol. Reprod.,  2003, 68(2):628-34. 
         22. Tong W., et al.,  Environ. Health Perspect.,  2003, 111(15):1819-26. 
         23. Tong W., et al.,  Mutat. Res.,  2004, 549(1-2):241-53. 
         24. Irizarry R. A., et al.,  Biostatistics,  2003, 4(2):249-64. 
         25. Affymetrix,  Statistical Algorithms Description Document, technical report.  2002. 
         26. Shi L., et al.,  Nat. Biotechnol.,  2006, 24(9):1151-61. 
         27. Tibshirani R., et al.,  Proc. Natl. Acad. Sci. U.S.A.,  2002, 99(10):6567-72. 
         28. Fernandez-Capetillo O., et al.,  DNA Repair  ( Amst ), 2004, 3(8-9):959-67. 
         29. Rogakou E. P., et al.,  J. Cell. Biol.,  1999, 146(5):905-16. 
         30. Mladenov E., I. Tsaneva, and B. Anachkova,  J. Cell. Physiol.,  2007, 211(2):468-76. 
         31. Yamamoto K., et al.,  Mol. Med.,  2008, 14(3-4):167-74. 
         32. Zhou C., et al.,  Mutat. Res.,  2006, 604(1-2):8-18. 
         33. Hoogervorst E. M., et al.,  DNA Repair  ( Amst ), 2005, 4(1):3-9. 
         34. Schrenk D., et al.,  Carcinogenesis,  1994, 15(11):2541-6. 
         35. Jenkins G. J. and J. M. Parry,  Teratog. Carcinog. Mutagen,  2000, 20(3):107-17. 
         36. Moller M. E., et al.,  Carcinogenesis,  1984, 5(6):797-804. 
         37. Vu V. T., et al.,  Carcinogenesis,  1985, 6(1):45-52. 
         38. Heflich R. H. and R. E. Neft,  Mutat Res,  1994, 318(2):73-114. 
         39. Sionov R. V. and Y. Haupt,  Oncogene,  1999, 18(45):6145-57. 
         40. Iida M., et al.,  Carcinogenesis,  2005, 26(3):689-99. 
         41. Uehara T., et al.,  Toxicology,  2008, 250(1):15-26. 
         42. van Delft J. H., et al.,  Carcinogenesis,  2004, 25(7):1265-76.