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R Benigni

Publications and source records attributed to R Benigni.

At least 19 recordsLinked to original sources
PubMed2004

Chemical structure of mutagens and carcinogens and the relationship with biological activity.

Chemical carcinogenicity has been the target of numerous attempts to create predictive models alternative to the animal ones, ranging from short-term biological assays (e.g. mutagenicity tests) to theoretical models. Among the theoretical models, the application of the science of Structure-Activity Relationships (SAR) has earned special prominence. SAR has been applied both in a qualitative way (for example as simple recognition of suspected sub-structures or Structural Alerts), and in a quantitative way (Quantitative SAR, QSAR) to build mathematical models linking the physical chemical or structural properties of the molecules to the toxicological endpoints. This paper summarizes the contribution that the two approaches can provide in different situations. It concludes that the study of the structure of the chemicals generates predictions with limited reliability for the individual chemicals, however it has been demonstrated to be an extremely powerful tool for priority setting relative to large samples of chemicals.

Carcinogenicity Tests↗
PubMed2002

AI and SAR approaches for predicting chemical carcinogenicity: survey and status report.

A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR) approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoint, the shared challenge of these approaches is to accurately delineate classes of active chemicals representing distinct biological and chemical mechanism domains, and within those classes determine the structural features and properties responsible for modulating activity. In the following discussion, we present a survey of AI and SAR approaches that have been applied to the prediction of rodent carcinogenicity, and discuss these in general terms and in the context of the results of two organized prediction exercises (PTE-1 and PTE-2) sponsored by the US National Cancer Institute/National Toxicology Program. Most models participating in these exercises were successful in identifying major structural-alerting classes of active carcinogens, but failed in modeling the more subtle modifiers to activity within those classes. In addition, methods that incorporated mechanism-based reasoning or biological data along with structural information outperformed models limited to structural information exclusively. Finally, a few recent carcinogenicity-modeling efforts are presented illustrating progress in tackling some aspects of the carcinogenicity prediction problem. The first example, a QSAR model for predicting carcinogenic potency of aromatic amines, illustrates that success is possible within well-represented classes of carcinogens. From the second example, a newly developed FDA/OTR MultiCASE model for predicting the carcinogenicity of pharmaceuticals, we conclude that the definitions of biological activity and nature of chemicals in the training set are important determinants of the predictive success and specificity/sensitivity characteristics of a derived model.

Animals↗
PubMed2001

Prediction of rodent carcinogenicity of aromatic amines: a quantitative structure-activity relationships model.

The aromatic amines are widely used industrial chemicals and can be found in tobacco smoke as well as in products generated during cooking. In a previous study, we established quantitative structure-activity relationship (QSAR) models linking the carcinogenic potency of non-heterocyclic carcinogenic aromatic amines to a series of molecular determinants. We also found that QSAR models for carcinogenic potency were inadequate in describing the difference between carcinogenic and non-carcinogenic amines [Benigni,R., Giuliani,A., Franke,R. and Gruska,A. (2000) CHEM: Rev., 100, 3697-3714]. In this paper, we derived specific QSAR models for separating active from inactive amines. It appeared that hydrophobicity (as measured by the octanol/water partition coefficient, logP) played a major role in modulating the potency of the carcinogens, whereas mainly electronic (reactivity) and steric characteristics separated the carcinogens from the non-carcinogens. Interestingly, a similar pattern was previously demonstrated by us regarding their mutagenic activity [Benigni,R., Passerini,L., Gallo,G., Giorgi,F. and Cotta-Ramusino,M. (1998) ENVIRON: Mol. Mutagen., 32, 75-83]. Based on the QSAR models found, the molecular determinants of the mechanisms of action of aromatic amines are discussed in detail. The QSAR models obtained can be used directly for estimating the carcinogenicity of other non-heterocyclic aromatic amines for which experimental data are not available. With the QSARs in Benigni et al. (2000) and the present results, a two-step prediction of carcinogenicity of aromatic amines is possible: (i) step 1, yes/no activity from the discriminant functions; and (ii) step 2, if the answer from step 1 is yes then prediction of the degree of potency from the equations in Benigni et al. (2000). Thus, QSAR models can contribute to the following: the direct synthesis of safer chemicals; the estimation of the risk posed by amines present in the environment; setting priorities for further experimentation, thus also reducing the use of experimental animals. Whereas the quality of in vivo experimental data is often questioned, the robustness and interpretability of the present results strongly support the reliability of the rodent carcinogenicity assay.

Amines↗
PubMed2001

The sex difference in tumor incidence is related to the female condition: models for Europe and Italy.

A remarkable aspect of cancer distribution in Europe is the large spatial variability of the male-female incidence ratio, from no difference up to 50%. Given the evidence of the predominantly environmental origin of cancer, we studied the ability of a set of socioeconomic indicators of the female condition to model the spatial variability of the sex difference in tumor incidence at two different scales: between countries (Europe) and between provinces (Italy). The sex difference in tumor incidence correlated with female socioeconomic condition indicators at the same extent (r = 0.73) in both situations, but in opposite directions. In the European study the higher the sexual social equality the lower the differential tumor incidence, whereas the opposite result was shown by the between-provinces Italian study. We also investigated the relation of the female condition indicator with other social and cultural descriptors of the same populations, and we suggest explanatory models linking female condition and pathology at the continental and local scales. Overall, our analysis supports the predominantly environmental origin of cancer and stresses the importance of relating cancer patterns to societal determinants. Our analysis also suggests that the sex difference in tumor incidence is a very useful probe for exploring the social-economic cultural correlates of cancer in human populations. We emphasize the need for a thorough analysis of the empirical correlations highlighted in ecologic studies.

Adult↗
PubMed2000

Deriving a quantitative chirality measure from molecular similarity indices.

A versatile new method has been developed as a continuous symmetry measure for chiral compounds. The application of principal component analysis (PCA) to the complete N x N pairwise similarity matrices (electrostatic potential and shape indices) of a series of dihydropyridine calcium channel antagonists allowed to single out a chirality component and to compute a chirality score in terms of the between-enantiomers difference on the component value. The possibility to have chirality defined continuously at the series level could be of importance in eudismic analyses where the relative potency of two enantiomers is studied as well as in QSAR studies dealing with chiral molecules in order to improve the power of the generated models.

Calcium Channel Blockers↗
PubMed2000

Nonlinear methods in the analysis of protein sequences: a case study in rubredoxins.

Two computational methods widely used in time series analysis were applied to protein sequences, and their ability to derive structural information not directly accessible through classical sequence comparisons methods was assessed. The primary structures of 19 rubredoxins of both mesophilic and thermophilic bacteria, coded with hydrophobicity values of amino acid residues, were considered as time series and were analyzed by 1) recurrence quantification analysis and 2) spectral analysis of the sequence major eigenfunctions. The results of the two methods agreed to a large extent and generated a classification consistent with known 3D structural characteristics of the studied proteins. This classification separated in a clearcut manner a thermophilic protein from mesophilic proteins. The classification of primary structures given by the two dynamical methods was demonstrated to be basically different from classification stemming from classical sequence homology metrics. Moreover, on a more detailed scale, the method was able to discriminate between thermophilic and mesophilic proteins from a set of chimeric sequences generated from the mixing of a mesophilic (Rubr Clopa) and a thermophilic (Rubr Pyrfu) protein. Overall, our results point to a new way of looking at protein sequence comparisons.

Amino Acid Sequence↗
PubMed2000

Mapping protein sequence spaces by recurrence quantification analysis: a case study on chimeric structures.

Recurrence quantification analysis (RQA) was used to characterize the folding properties of 22 chimeric sequences derived from two parent proteins of similar length but different three-dimensional arrangement. A non-linear relation between sequence data and their RQA representation was revealed, which points to new information carried by this method as compared with classical best-alignment methods. This new information is significantly correlated with the folding properties of the hybrid polypeptide chains, as substantiated by careful statistical analysis of the recurrence plots' numerical descriptors, thus encouraging their systematic use to complement sequence data in both proteomics and protein engineering tasks. Even the direct visual screening of the qualitative graphical features of recurrence plots is shown to provide useful hints to discriminate between different recurrence structures of protein sequences.

Amino Acid Sequence↗
PubMed2000

The cultural heritage shapes the pattern of tumour profiles in Europe: a correlation study.

STUDY OBJECTIVE: This study investigates the spatial pattern of tumours in Europe to check the feasibility of a large scale ecological epidemiology approach to cancer in Europe. SETTING: The tumour types relative frequencies and cancer incidence (for men and women) reported in the European cancer registries were investigated by exploratory data analysis techniques. Socioeconomical descriptors of the female condition were considered as well. MAIN RESULTS: The classification of the European regional areas covered by the cancer registries followed almost exactly the boundaries set by the long and intermingled European history in terms of life styles and cultural heritage. This result supports the notion of a predominant role of environmental factors in cancer induction. Further support to the above result was given by the finding of a correlation between differential male-female cancer incidence, and socioeconomic descriptors of the female condition. CONCLUSIONS: From a methodological point of view, the consistency of these results pointed to the feasibility of an ecological approach to tumour epidemiology.

Cultural Diversity↗
PubMed1998

Profiles of chemically-induced tumors in rodents: quantitative relationships.

The rodent carcinogenicity bioassay has been used for several decades for evaluating hundreds of chemicals, with the two aims of better understanding the etiologies of cancer, and of assessing the hazard posed by environmental and industrial chemicals. This has generated an enormous wealth of data and information on the phenomenon of chemical carcinogenicity. However, this information cannot be appreciated easily, since too many details may obscure the general trends present in the data; on the contrary, the use of computerized data analysis techniques suitable for the exploration of large databases makes its investigation much more fruitful, and its results more reliable. For this work, we collected a database of 536 rodent carcinogens, and we investigated the profiles of tumors (target organs) induced in the four experimental systems which are usually employed (rat and mouse, male and female). The analysis was performed with an Artificial Neural Network called Kohonen Self-Organizing Map, which is a computer-intensive method aimed at making the relevant information emerge automatically from the data itself. The analysis generated a global view, as well as a quantitative measure of the associations among the individual tumor types, and among the tumor profiles induced by the chemicals. In the complex interplay between the organ and species specificity of tumor induction, the species specificity generally overcame organ specificity, except for a few tumors (namely Lymphatic System, Brain, Forestomach, Stomach and Thyroid Gland). Moreover, the species specificity was remarkably stronger than the trans-species sex specificity. For three chemical classes (Aromatic Amines, Electrophilic/Alkylating Agents, Nitroarenes) most represented in the database, we investigated the hypothesis that a single mechanism of interaction with DNA would produce one, or a few very similar tumor profiles. Our analysis pointed out that no obvious association exists between chemical/mode of action class, and tumor profile. On the contrary, none of these classes induces a single tumor or pattern of tumors, but rather it appears that each class produces tumors at a wide range of sites. This suggests that an important determinant of the differences in tumor profile are the events that surround the ultimate mechanism of interaction with DNA.

Animals↗
PubMed1998

QSAR models for discriminating between mutagenic and nonmutagenic aromatic and heteroaromatic amines.

In a previous article, we demonstrated that the structure-activity relationship model for the mutagenic potency of aromatic amines is different from that for discriminating between mutagens and nonmutagens. In this work, we present further analyses on the molecular determinants of the mutagenicity of aromatic amines. Based on the use of various methodological approaches, our results indicate that mutagenic activity is influenced by different molecular characteristics in different subclasses of aromatic amines. Thus, the general lesson of this article is that 1) in genetic toxicology, it is necessary to separately investigate the structure-activity relationships for discrimination between positive and negative chemicals, and the structure-activity relationships for the potency of the positive chemicals; 2) in structure-activity studies, it is necessary to investigate the degree of homogeneity (congenericity) of apparently similar chemicals in order to assess and describe the various mechanisms of action that may be elicited by the chemicals.

Amines↗
PubMed1998

Quantitative structure-based modeling applied to characterization and prediction of chemical toxicity.

Quantitative modeling methods, relating aspects of chemical structure to biological activity, have long been applied to the prediction and characterization of chemical toxicity. The early linear free-energy approaches of Hansch and Free Wilson provided a fundamental scientific framework for the quantitative correlation of chemical structure with biological activity and spurred many developments in the field of quantitative structure-activity relationships (QSARs). In addition to modeling of chemical toxicity, these methods have been extensively applied to modeling of medicinal properties of chemicals. However, there are important differences in the nature and objectives of these two applications, which have led to the evolution of different modeling approaches (namely, the need for treating sets of noncongeneric toxic compounds). In this paper are discussed those approaches to chemical toxicity that have taken a more "personalized" configuration and have undergone implementation into software programs able to perform the various steps of the assessment of the hazard posed by the chemicals. These models focus both on a variety of toxicological endpoints and on key elements of toxicity mechanisms, such as metabolism.

Automation↗
PubMed1997

The first US National Toxicology Program exercise on the prediction of rodent carcinogenicity: definitive results.

A few years ago, the US National Toxicology Program sponsored an exercise aimed at comparing different prediction approaches for carcinogenicity by challenging them on a common set of chemicals. The exercise was considered to be sufficiently completed when 40 (out of 44) chemicals were actually experimentally tested, and the experimental and estimated carcinogenicity were compared. More recently, the rodent results for the remaining 4 chemicals have been disclosed, making it possible to draw definitive conclusions on the comparative exercise. Having analyzed the first subset of results with multivariate statistical methods, we present here the analysis of the complete set of results. The present analysis also considers aspects (e.g., the complementarity of the different systems in identifying the carcinogens), which had not been investigated previously. The conclusion of this study were: (a) the expansion of the data base from 40 to 44 chemicals did not significantly change the results of the exercise; (b) the structure-activity approaches generated prediction profiles different from those generated by the prediction systems mainly relying on the use of experimental data (in vitro and in vivo); (c) the performance of the predictive systems was generally rather limited; (d) the prediction systems were affected by over sensitivity; they were generally capable of identifying the molecules containing the potentially alerting substructures, but were not so refined as to be able to discriminate between potential and actual carcinogenicity; (e) the combination of the systems into batteries did not permit a significant increase in the performance of the individual methods. The need for, and possible approaches to finely tuning the systems are discussed.

Animals↗
PubMed1996

QSARS of mutagens and carcinogens: two case studies illustrating problems in the construction of models for noncongeneric chemicals.

There is a strong motivation to develop QSAR models for toxicity prediction for use in screening, for setting testing priorities, and for reducing reliance on animal testing. Decisions must be made daily by toxicologists in governments and industry to direct limited testing to the most urgent public health problems, and to direct the types of chemical synthesis and product development efforts undertaken. This need has motivated attempts to construct general QSAR models (e.g., for rodent carcinogenicity), not tailored to congeneric series of chemicals. These various attempts have provided interesting and important scientific evidence; however, they have also shared a limited overall performance. The goal of this paper is to illustrate, by two unrelated actual examples of QSARs for mutagens and carcinogens, some fundamental problems relative to the application of general QSAR approaches to noncongeneric chemicals. Both examples consider data sets that are noncongeneric in a chemical structure and mechanism of action sense: in the first case, a mean mutagenic potency defined as an average over multiple genetic toxicity endpoints, and, in the second case, the NTP two-sexes, two species rodent carcinogenicity bioassay results for 280 carcinogens and noncarcinogens. The problems encountered with the QSAR analyses of these two cases indicate that a successful approach to the problem of QSAR modeling of noncongeneric data will need to consider the multidimensional nature of the problem in both a chemical and a biological sense. Since different chemical classes represent largely independent action mechanisms, some means for extracting local QSARs for constituent classes will be necessary. Alternatively, a general QSAR derived for a noncongeneric data set will need to be scrutinized and decomposed along chemical class lines in order to establish boundaries for application and confidence levels for prediction.

Animals↗
PubMed1996

Synthesis report of the step project detection of germ cell mutagens.

The project 'Detection of Germ Cell Mutagens' was designed with three major goals: (1) Detection and characterization of germ-cell mutagens; (2) standardization and validation of new germ-cell tests; and (3) development of a data base on germ-cell mutagenicity. All three goals were achieved. The classical germ-cell tests were applied to characterize the genetic effects of acrylamide (AA), 1,3-butadiene (BD), trophosphamide (TP) and urethane (UR). All but UR were found to cause heritable genetic damage. The experimental data obtained for AA and BD were the basis for genetic risk evaluations during the EC/US Workshop on Risk Assessment 'Human Genetic Risk from Exposure to Chemicals, Focusing on the Feasibility of the Parallelogram Approach'. Nine chemicals were employed to validate the spermatid micronucleus assay with mice and rats: AA, BD and its metabolites 1,2-epoxybutene-3 and 1,2:3,4-diepoxybutane, chlorambucil, mitomycin C, methylnitrosourea, TP and UR. The spermatid micronucleus test was combined with micronucleus tests in somatic cells such as bone marrow or peripheral blood erythrocytes, and splenocytes which allowed a comparison of effects in somatic and germinal cells. Improvements of the spermatid micronucleus test included BrdU-labelling of premeiotic S-phase for the determination of stage sensitivity and fluorescence in situ hybridization with pancentromeric DNA-probes to distinguish between clastogenic and aneugenic events. The results indicate that the spermatid micronucleus test with its improvements is an adequate procedure to detect germ-cell clastogenicity and to compare the activity of chemicals in different tissues and between species, i.e., rats and mice. Other germ cell methods under study were the flow cytometric measurement of testicular sperm DNA and the cytogenetic analysis of preimplantation embryos for chromosomal aberrations and micronuclei. The collection of a reliable germ-cell data base was accomplished through a critical evaluation of the literature and with the data obtained in the present project. Remarkable concordance between responses of germ cell tests to chemical mutagens was the most striking conclusion to be drawn from the present data base.

Acrylamide↗
PubMed1996

Prediction of rodent carcinogenicity of further 30 chemicals bioassayed by the U.S. National Toxicology Program.

Recently the U.S. National Toxicology Program (NTP) sponsored a comparative exercise in which different prediction approaches (both biologically and chemically based) were challenged for their predictive abilities of rodent carcinogenicity of a common set of chemicals. The exercise enjoyed remarkable scientific success and stimulated NTP to sponsor a second challenging round of tests, inviting participants to present predictions relative to the rodent carcinogenicity of a further 30 chemicals; these are currently being tested. In this article, we present our predictions based on structure-activity relationship considerations. In our procedure, first each chemical was assigned to an activity mechanism class and then, with semiquantitative considerations, was assigned a probability carcinogenicity score, taking into account simultaneously the hypothesized action mechanism and physical chemical parameters.

Animals↗
PubMed1995

Toxicology of halogenated aliphatic hydrocarbons: structural and molecular determinants for the disturbance of chromosome segregation and the induction of lipid peroxidation.

The induction of mitotic chromosome malsegregation, mitotic arrest and lethality by a set of 55 halogenated hydrocarbons was investigated. To this aim, genetic assays in the mould Aspergillus nidulans, able to provide precise quantitative information on the end-points studied, were used throughout the work. The experimental data obtained were used to develop QSAR models for the induction of aneuploidy, which pointed to a major role of electrophilicity as molecular determinant for the aneugenic potential of the halogenated hydrocarbons investigated. Within the hypothesis of a link between the electrophilicity of haloalkanes and their propensity to undergo a reductive biotransformation, with production of free radical species, a subset of 27 compounds was also tested for the ability to induce lipid peroxidation in rat liver microsomes in vitro. The results obtained indicate a partial coincidence between the abilities to initiate lipid peroxidation and to disturb chromosome segregation at mitosis. The data base obtained was also used to investigate the relationship between chemical structure and peroxidative potential. The analysis indicated that electronic and structural parameters related to the ease of homolitic cleavage of the carbon-halogen bond play a pivotal role as determinants for the peroxidative character of haloalkanes.

Aneuploidy↗