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R Benigni

Publications and source records attributed to R Benigni.

At least 55 records · Page 3Linked to original sources
PubMed1991

What indication is common to different genotoxicity data bases?

This paper studies the relationships among 4 in vitro assays: Salmonella mutation (STY), mouse lymphoma L5178Y cell mutation (MLY), chromosomal aberrations in CHO cells (CHA), and sister-chromatid exchanges in CHO cells (SCE), in 3 different data bases: U.S. National Toxicology Program (NTP), International Program for the Evaluation of Short-Term Tests for Carcinogens (IPESTTC), and International Program on Chemical Safety (IPCS). The analysis is performed by modeling each data base with factor analysis. With this tool, it has been possible to separate the different elements (or components) which play a role in each data base. It has also been possible to demonstrate that--together with some specificities of the data bases--there is a common effect which is independent of the data bases, and which typically represents the 'true' relationships among the assays. This element explains 69% of the information contained in NTP, 50% of that of IPESTTC, and 30% of that of IPCS. This common evidence indicates that the responses of STY and CHA to the 'universe' of chemicals are relatively similar, although STY is a bacterial mutation system and CHA is a mammalian cell test for chromosomal damage. The other similarity apparent from this analysis is the one between MLY (mutation in mouse cells) and SCE (cytogenetic evidence in hamster cells). The implication of this result is 2-fold. On the one hand, it is extremely reassuring that the 3 most important comparative studies agree and show common evidence, and this can be recognized rationally. On the other hand, this evidence implies that the scientists involved in mutagenicity research must face the task of exploring and explaining such relationships.

Animals↗
PubMed1991

The ability of short-term tests to predict carcinogenicity can be summarized in a single index.

This paper presents a new procedure aimed at quantifying the ability of short-term tests (STT) to discriminate between carcinogens and noncarcinogens. While the sensitivity, specificity, and accuracy indices provide an estimate that is not biased by the relative proportion of carcinogens and noncarcinogens of the different databases, the new index, called Relative Operating Characteristics (ROC), goes a step further, and overcomes the problem of the decision criterion bias. In fact, if the threshold--that is, minimum increase over the control above which an STT result is positive--is varied, sensitivity and other factors are also consequently affected. A similar problem occurs when the STTs are assembled in batteries: the performance of the battery in discriminating between carcinogens and noncarcinogens depends on the preliminary decision of how many and which assays should be positive for considering a chemical as positive in the battery. The ROC analysis produces a single value, which places the performance of different systems on a common, easily interpreted scale (instead of using several different indices such as sensitivity, etc.). Most importantly, this index is independent of the decision criterion bias; consequently it is the best measure of the true ability of STTs to discriminate between carcinogens and noncarcinogens. To illustrate the approach, the ROC analysis is applied to a battery composed of the four in vitro assays studied by the U.S. National Toxicology Program: the analysis confirmed the previous results, pointing to the limited ability of this battery to discriminate between carcinogens and noncarcinogens.

Animals↗
PubMed1991

Relationship between chlorofluorocarbon chemical structure and their Salmonella mutagenicity.

This paper is a quantitative analysis of the relationship between the chemical structure and the Salmonella mutagenicity of a number of chlorofluorocarbons (CFC). The molecules were characterized by both molecular orbital and physical chemical parameters. The results of the analysis indicated that the CFC mutagenicity is correlated with two parameters: the free energy of binding to biological receptors, and the energy of the highest occupied molecular orbital (HOMO). Since these are the same factors that would favor the cytochrome P-450-catalyzed metabolism, it would appear that the CFC mutagenicity is determined more by the rate of initial activation than by the rate of DNA attack.

Biotransformation↗
PubMed1991

QSAR prediction of rodent carcinogenicity for a set of chemicals currently bioassayed by the US National Toxicology Program.

A QSAR model based on the combination of two molecular descriptors--estimated electrophilic reactivity and Ashby's structural alerts--was used to predict the carcinogenicity of 44 chemicals currently bioassayed by the US National Toxicology Program. These predictions will be compared with the rodent carcinogenicity assay results as the assays are completed.

Animals↗
PubMed1991

Mathematical models for exploring different aspects of genotoxicity and carcinogenicity databases.

One great obstacle to understanding and using the information contained in the genotoxicity and carcinogenicity databases is the very size of such databases. Their vastness makes them difficult to read; this leads to inadequate exploitation of the information, which becomes costly in terms of time, labor, and money. In its search for adequate approaches to the problem, the scientific community has, curiously, almost entirely neglected an existent series of very powerful methods of data analysis: the multivariate data analysis techniques. These methods were specifically designed for exploring large data sets. This paper presents the multivariate techniques and reports a number of applications to genotoxicity problems. These studies show how biology and mathematical modeling can be combined and how successful this combination is.

Animals↗
PubMed1990

Strategies and governmental regulations.

An overview of testing strategies for the detection of genotoxins under OECD Guidelines and the EEC Directive 79/831 (VI Amendment) is outlined. The viewpoint of the Italian National Advisory Committee on Toxicology is also presented. In this context, the main issues of Genetic Toxicology (e.g., role of tests, tests recommended, classification of mutagens) are discussed.

Animals↗
PubMed1990

Rodent tumor profiles, Salmonella mutagenicity and risk assessment.

The tumorigenesis profiles of 116 chemicals, which proved to induce cancer in the NCI/NTP experimentation, were studied by multivariate data analysis methods. Three main patterns of tumor induction were evident. One chemical (benzene) was not classifiable in any of the 3 clusters of chemicals. The carcinogen classes based on patterns of tumor induction did not reflect a repartition between Ames-positive and Ames-negative chemicals. Therefore any classification of carcinogens as either 'primary' (genotoxic, hence assumed to pose a greater risk) or 'secondary' (presumably carcinogenic via non-genotoxic mechanisms) would seem to be a subject for research and speculation, and, for the present, an unsuitable basis for risk assessment.

Animals↗
PubMed1990

Inhibition of replicative DNA synthesis and induction of DNA repair in human fibroblasts by the intercalating drugs proflavine and 9-aminoacridine.

The induction of unscheduled DNA synthesis (UDS) and the alteration of semiconservative DNA replication by the structurally related intercalating agents proflavine and 9-aminoacridine were studied in MRC-5 human fibroblasts in culture. Autoradiographic determinations of both parameters were carried out simultaneously in the same culture specimens. Proflavine affected DNA synthesis, but did not elicit any UDS. 9-Aminoacridine inhibited DNA synthesis only at the highest concentration and caused UDS to a low but significant extent. These results suggest that the ability to induce UDS is not a general property of the intercalating agents and that the alterations of the DNA structure, typical of the "pure" intercalative process, are not handled by pathways involving unscheduled synthesis.

Aminacrine↗
PubMed1989

A bootstrap analysis of four in vitro short-term test performances.

The present analysis is aimed at estimating the confidence intervals of a number of association measures that describe the relationships of 4 in vitro short-term tests with rodent carcinogenicity, as well as with each other. The measures considered were: sensitivity, specificity and accuracy of the short-term tests with respect to chemical carcinogens, and performance dissimilarity indices (Hamming distances). The analysis refers to Salmonella, mouse lymphoma L5178Y cell mutation, chromosomal aberrations and sister-chromatid exchanges in Chinese hamster ovary cells, and is based on the data generated in the frame of the U.S. National Toxicology Program (NTP). It exploits the properties of a statistical technique, called bootstrap, to derive from only one sample of chemicals the variability intervals of the associations that the biological systems (mutagenicity assays and rodent carcinogenicity) would show in the 'universe' of the chemical compounds. The combination of the bootstrap technique with multivariate statistical methods pointed to a remarkable robustness and reliability of the information derived from the NTP data base, and provided descriptive insights into the data.

Animals↗
PubMed1989

Interrelationships among carcinogenicity, mutagenicity, acute toxicity, and chemical structure in a genotoxicity data base.

The interrelationships among carcinogenicity, mutagenicity, acute toxicity (LD50), and a number of molecular descriptors were studied by computerized data analysis methods on the data base generated by the International Program for the Evaluation of Short-Term Tests for Carcinogens (IPESTTC). With the use of statistical regression methods, three main associations were evidenced: (1) the well-known correlation between carcinogenicity and mutagenicity; (2) a correlation between mutagenicity and toxicity (LD50 ip in mice); and (3) a correlation between toxicity and a recently introduced estimator of the free energy of binding of the molecules to biological receptors. As expected on the basis of the large variety of chemical classes represented in the IPESTTC data base, no simple relationship between mutagenicity or carcinogenicity and chemical descriptors was found. To overcome this problem, a new pattern recognition method (REPAD), developed by us for structure-activity studies of noncongeneric chemicals, has been used. This allowed us to highlight a significant difference between the whole patterns of relationships among chemicophysical variables in the two groups of active (mutagenicity and/or carcinogenic) and inactive chemicals. This approach generated a classification rule able to correctly assign about 80% of carcinogens or mutagens.

Carcinogens↗
PubMed1989

Comparison of different computerized classification methods for predicting carcinogenicity from short-term test results.

A major obstacle to the use of short-term test results for predicting carcinogenicity is the nonavailability of methods that generate unequivocal estimations of potential carcinogenicity, even in the case of contrasting test results. We compared different mathematical classification methods such as linear discriminant analysis, the K-nearest neighbor rule (KNN), and a new ad hoc classification method called dynamic carcinogenicity assessment (DYCA). The DYCA was developed by us to explicitly reflect the biological results. Through an analysis of a real data base we pointed out the advantages and limitations of these methods. KNN was clearly inferior to the other two algorithms. The novel DYCA approach was more sensitive to carcinogens, whereas linear discriminant analysis proved better for the identification of noncarcinogens.

Carcinogenicity Tests↗
PubMed1989

Structure-activity studies of chemical carcinogens: use of an electrophilic reactivity parameter in a new QSAR model.

Electrophilic reactivity data for 142 compounds were obtained from the literature, and were used to establish the contribution of different functional groups and molecular determinants to this property. An equation containing approximately 20 molecular determinants was derived (r = 0.89); this provided a system for estimating the electrophilic reactivity for other compounds on the basis of their molecular structure. The contribution of the estimated electrophilicity to the structure-activity relationship (SAR) studies of carcinogens was tested. In a previous work, we studied a set of 137 carcinogens and non-carcinogens belonging to different chemical classes, and established an SAR on the basis of four physical-chemical descriptors. The mathematical model consisted of a pattern recognition method specifically designed by us for the non linear situations typical of large non congeneric sets of chemicals. The addition of the estimated electrophilicity parameter increased the overall performance of the system (from the previous 85-90% retrospective correct classification). In particular, the estimated electrophilicity remarkably contributed to the identification of carcinogens (their correct classification increasing from the previous 86% to 97%). The derived SAR was tested by applying it to 11 human carcinogens not included in the training set. Their carcinogenicity was correctly predicted for 10 chemicals out of 11.

Carcinogens↗
PubMed1989

Analysis of the National Toxicology Program data on in vitro genetic toxicity tests using multivariate statistical methods.

A series of multivariate statistical methods have been used to explore the results of a set of four in vitro short-term tests (STT) on 73 chemicals reported by the US National Toxicology Program (NTP). Cluster analysis showed that the mouse lymphoma mutation (MLY) and sister-chromatid exchange (SCE) were similar in performance, as were the Salmonella (STY) and chromosomal aberration test (CHA). The lack of association between tests using the same genetic end-point or at the same phylogenetic level found in previous analyses was confirmed in this study. Factor analysis was used to derive a scale of genetic damage. This measure was contrasted with rodent carcinogenicity; only a limited association was found (rank correlation coefficient, rs = 0.32). Linear discriminant analysis was used to study whether the STTs could be used to complement one another. The combination of STY with the other STTs did not improve significantly the prediction of rodent carcinogenicity of STY alone. In the entire set of chemicals, 33% were negative in STY and positive in at least two other STT, and 11% was negative in STY and positive in the three other tests. SCE and MLY were complementary to STY for identifying the most genotoxic chemicals, but CHA was not a useful complement. The presence of potential electrophilic sites in the chemicals was highly correlated with the STY results, but did not improve the ability of STY to identify genotoxic chemicals or predict rodent carcinogens. In conclusion, the other in vitro STTs did not complement STY for predicting carcinogenicity, but were an important complement for describing the potential genotoxicity of chemicals.

Animals↗
PubMed1989

Short-term tests, genotoxicity and carcinogenicity in light of a multivariate statistical exploration.

This is a brief overview on a series of studies performed in the Istituto Superiore di Sanità (Italian National Institute of Health), all focusing on the ability of mutagenicity short-term assays of identifying genotoxic agents and predicting carcinogenicity. The analytical tools of such studies were the multivariate data analysis statistical techniques. The overall picture points to three main classes of assays, on the basis of their responses to the chemical agents in the available data bases (mainly the comparative studies). The implications for practical chemical testing and battery design are discussed.

Animals↗
PubMed1988

Statistical exploration of four major genotoxicity data bases: an overview.

This report puts into perspective a series of exploratory statistical analyses carried out on the major genotoxicity data bases. While large compilations of data, even though computerized, suffer from their own size and are quite intractable to scientific reflection and judgement, the multivariate data analysis methods used by us are specifically designed for reorganising the information in a rational way and highlighting the underlying regularities of the data. The analyses reported here refer to the following data bases: the International Program for the Evaluation of Short-Term Tests for Carcinogens, the International Program on Chemical Safety Collaborative Study on In Vitro Assays, the Gene-Tox data base, and a subset of the U.S. National Toxicology Program data. Although the various data bases consisted of different sets of chemicals and had different underlying rationales, a number of invariant associations among short-term test performances were highlighted. The overall evidence indicated that the traditional classification of assays (according to the criteria of genetic end-point and phylogenetic position of the assays) was in contrast with the actual, operational similarities among assay performances, in that the experimental responses of the tests to the large variety of chemicals under consideration pointed to an alternative classification scheme. This consisted of three major classes: 1) a class comprising the in vivo assays; 2) a class grouping together many of the most widely used in vitro assays (Salmonella, chromosomal aberrations, and sister chromatid exchanges in Chinese hamster ovary cells, the various mutation tests in mammalian cell systems, etc.); 3) a second in vitro assay class (with Syrian hamster embryo cell transformation, Saccharomyces cerevisiae XV185-14C, B. subtilis rec-, Escherichia coli pol A). Such classes had clearly differentiated features with respect to carcinogenicity prediction. The implications of these findings for the current debate on mutagenicity testing are discussed.

Carcinogens↗