Data quality in predictive toxicology: reproducibility of rodent carcinogenicity experiments.

We compared 121 replicate rodent carcinogenicity assays from the two parts (National Cancer Institute/National Toxicology Program and literature) of the Carcinogenic Potency Database (CPDB) to estimate the reliability of these experiments. We estimated a concordance of 57% between the overall rodent carcinogenicity classifications from both sources. This value did not improve substantially when additional biologic information (species, sex, strain, target organs) was considered. These results indicate that rodent carcinogenicity assays are much less reproducible than previously expected, an effect that should be considered in the development of structure-activity relationship models and the risk assessment process.

Data quality in predictive toxicology: identification of chemical structures and calculation of chemical properties.

Every technique for toxicity prediction and for the detection of structure-activity relationships relies on the accurate estimation and representation of chemical and toxicologic properties. In this paper we discuss the potential sources of errors associated with the identification of compounds, the representation of their structures, and the calculation of chemical descriptors. It is based on a case study where machine learning techniques were applied to data from noncongeneric compounds and a complex toxicologic end point (carcinogenicity). We propose methods applicable to the routine quality control of large chemical datasets, but our main intention is to raise awareness about this topic and to open a discussion about quality assurance in predictive toxicology. The accuracy and reproducibility of toxicity data will be reported in another paper.

Knowledge discovery and data mining in toxicology.

Knowledge discovery and data mining tools are gaining increasing importance for the analysis of toxicological databases. This paper gives a survey of algorithms, capable to derive interpretable models from toxicological data, and presents the most important application areas. The majority of techniques in this area were derived from symbolic machine learning, one commercial product was developed especially for toxicological applications. The main application area is presently the detection of structure-activity relationships, very few authors have used these techniques to solve problems in epidemiological and clinical toxicology. Although the discussed algorithms are very flexible and powerful, further research is required to adopt the algorithms to the specific learning problems in this area, to develop improved representations of chemical and biological data and to enhance the interpretability of the derived models for toxicological experts.

Detection of genotoxic effects of heavy metal contaminated soils with plant bioassays.

Aim of the present study was the development of a bioassay which enables the detection of genotoxic effects of heavy metal contaminated soils. In the first part of the present study, the data base on metal effects in plant bioassays was extended. Four metal salts, namely Cr(VI)O3, Cr(III)Cl3, Ni(II)Cl2 and Sb(III)Cl3 were tested comparatively in MN tests with pollen tetrad cells of Tradescantia clone #4430 and in meristematic root tip cells of Vicia faba. With Cr6+ and Ni2+, clear-cut dose-effects were observed in a range between 0.75 and 10.0 mM, whereas this was not the case with Cr3+ (range tested 1.25-10 mM) and Sb3+ (range 0.30-5.25 mM). In Vicia, negative results were obtained with the four metal salts under all conditions of test. To compare the mutagenic potencies of the metals, the increases of the regression curves (k-values) were calculated, they indicate the number of MN induced per mM in 100 tetrad cells. The corresponding values for Cr6+ and Ni2+ are 0.87 and 1.05, respectively. It appears that the Tradescantia system is in particular sensitive towards those metal species which cause DNA damage in animals and man such as Cr6+, Cd2+, Ni2+, and Zn2+, whereas no clear positive results were obtained with less harmful metal ions such as Cu2+, Cr3+ or Sb3+. In the second part of the study, the mutagenic effects of four metal contaminated soils and two types of standardized leachates (pH 4.0 and pH 7.0) of these soils were tested in Tradescantia and in Vicia. In addition, chemical analyses were carried out to determine the metal concentrations in the soils and in the extracts. Two of the samples contained highly elevated levels of a number of metals (Zn, Pb, Cu, Cd, Sb, As), one soil came from the Central Austrian Alps and contained high As levels only. Direct exposure of the Tradescantia plants in the soils resulted in a drastic increase of the MN frequencies over the background. The lowest effect was seen with the Slovakian soil which contained in particular Sb and As (4.5-fold increase over the background), with the other soils, the induced frequencies were 11-15-fold over the control values. On the contrary, negative results were obtained upon exposure of Tradescantia cuttings in the leachates and upon implantation of germinated Vicia beans in the soils. The results of the present study indicate that Trad-MN assays with direct exposure of intact plants is an appropriate method which enables to detect genotoxic effects of metal contaminated soils in situ. This simple and fast biomonitoring assays might be a valuable supplement to analytical analyses of contaminated soils.

Investigations on genotoxic effects of groundwater from the Mitterndorfer Senke and from the vicinity of Wiener Neustadt.

INTRODUCTION: This report describes the first study on genotoxic effects of Austrian ground- and drinking waters. Samples from the Mitterndorfer Senke (MS) and the vicinity of Wiener Neustadt were tested over a three years period. The MS is the largest aquifer in Austria. Due to deposition of industrial and community wastes, chemicals have polluted the groundwater in this area. Aim of the present study was to elucidate if consumption of these waters might pose a carcinogenic risk to humans. METHODS: 43 Water samples were tested in a test battery which consisted of bacterial gene mutation assays (Salmonella strains TA100 and TA98), micronucleus (MN) assays with cultures of primary rat hepatocytes and plant bioassays (MN tests with Tradescantia and Vicia faba). For the bacterial assays, the water samples were extracted with XAD resins. RESULTS: In total, 27.9% of the samples caused positive effects; 8 samples were active in Salmonella microsome assays, Strain TA100 was particularly sensitive upon addition of metabolic activation mix (6 positive samples). Four samples were positive exclusively in MN assays with cultures of primary rat hepatocytes; one sample gave positive results in all three bioassays. Finished waters from waterworks were consistently devoid of mutagenic activity under all experimental conditions. DISCUSSION: Overall, only a small fraction of the groundwaters caused mutagenic effects and in all cases the activities were moderate. Comparison of the results of the present study with data obtained in other investigations under similar experimental conditions shows that the genotoxicity of groundwaters of the MS area are lower than the effects caused by ground- and drinking waters from other countries. The fact that no genotoxic activity was detected in any of the finished drinking waters can be taken as an indication that consumption of these waters does not pose a health hazard arising from contamination with genotoxic carcinogens to humans.

Molecular analysis and predictive testing in retinoblastoma.

Predictive testing using molecular analysis is an integral part of contemporary retinoblastoma management. We have made extensive use of segregation analysis for risk assessment in both familial and sporadic disease. Investigation of loss of heterozygosity in tumor samples proved to be invaluable for the identification of linkage phase. In many families, however, accurate carrier risk assessment depends on direct identification of the causative R B I mutation. Consequently, we have developed methods for rapid mutation screening. Using these techniques, mutation analysis can now be offered to an increasing number of individuals.