Prediction Of Rodent Carcinogenicity Research Articles

Prediction of rodent carcinogenicity using the DEREK system for 30 chemicals currently being tested by the National Toxicology Program. The DEREK Collaborative Group.

DEREK is a knowledge-based expert system for the qualitative prediction of toxicity. The DEREK system has been used to predict the carcinogenicity in rodents of the 30 chemicals in the second National Toxicology Program (NTP) carcinogenicity prediction exercise. Seven of the chemicals were predicted to be carcinogens. For 23 chemicals, there was no evidence in the DEREK knowledge base to suggest carcinogenic activity. Supplementary data from a variety of sources have been evaluated by human experts to assess confidence in each DEREK prediction. These sources included standard toxicology reference texts, genotoxicity and subchronic toxicity assay results for each chemical, as well as Salmonella mutagenicity and carcinogenicity data for close structural analogues. This process has led to the proposal of a number of improvements to the DEREK carcinogenicity knowledge base.

Prediction of Rodent Carcinogenicity Using the DEREK System for 30 Chemicals Currently Being Tested by the National Toxicology Program

Prediction of Rodent Carcinogenicity Using the DEREK System for 30 Chemicals Currently Being Tested by the National Toxicology Program

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.

Prediction of Rodent Carcinogenicity of Further 30 Chemicals Bioassayed by the U.S. National Toxicology Program

Prediction of Rodent Carcinogenicity of Further 30 Chemicals Bioassayed by the U.S. National Toxicology Program

The potential of organ specific toxicity for predicting rodent carcinogenicity

Relationships between organ specific toxicity (specifications of the presence or absence of 43 morphological effects in 32 organs) observed from 13-week subchronic studies and rodent carcinogenicity were investigated by manually measuring the concordance of each feature and also automatically using the RL (Rule Learner) induction program. Of the 32 organs, the presence or absence of any effect in liver or kidney was found very relevant to rodent carcinogenicity. While the concordance of Salmonella genotoxicity with rodent carcinogenicity was only 60%, the battery of liver and kidney was 74% accurate with 75% sensitivity and 71% specificity. Further, using the RL program, rule sets based on organ specific toxicity together with the default predictions based on Salmonella mutagenicity were on average 80% accurate with 83% sensitivity and 82% specificity.

Learning rules to predict rodent carcinogenicity of non-genotoxic chemicals

The results of short-term assays (induction of chromosomal aberrations and sister-chromatid exchanges, oncogenic transformations and cellular toxicity) together with MTD (maximum tolerated dose) values and physical chemical properties of non-genotoxic (i.e. Salmonella non-mutagens) carcinogens and non-carcinogens were submitted to RL, an inductive learning program. RL was able to learn rules that correctly predicted between 70 and 80% of non-genotoxic chemicals. This is a marked improvement over current predictions using only the results of short-term assays and exceeds the predictions of human experts that used the whole spectrum of acute and subchronic toxicity results as well as human knowledge and intuition.

Capacity of the metabolic cooperation assay using V79 cells to predict rodent carcinogenicity - results for 119 chemicals

Capacity of the metabolic cooperation assay using V79 cells to predict rodent carcinogenicity - results for 119 chemicals

Predicting Chemical Carcinogenesis in Rodents

Research ArticleOpen AccessPredicting chemical carcinogenesis in rodents. J T Wachsman, D W Bristol, J Spalding, M Shelby, and R W Tennant J T Wachsman National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709. Search for more papers by this author , D W Bristol National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709. Search for more papers by this author , J Spalding National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709. Search for more papers by this author , M Shelby National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709. Search for more papers by this author , and R W Tennant National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709. Search for more papers by this author Published:1 October 1993https://doi.org/10.1289/ehp.93101444Cited by:16AboutSectionsPDF ToolsDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InReddit "Predicting chemical carcinogenesis in rodents.." Environmental Health Perspectives, 101(5), pp. 444–445FiguresReferencesRelatedDetailsCited By Greene N (2007) Computational Models to Predict Toxicity Comprehensive Medicinal Chemistry II, 10.1016/B0-08-045044-X/00155-3, (909-932), . Ward E, Schulte P, Bayard S, Blair A, Brandt-Rauf P, Butler M, Dankovic D, Hubbs A, Jones C, Karstadt M, Kedderis G, Melnick R, Redlich C, Rothman N, Savage R, Sprinker M, Toraason M, Weston A, Olshan A, Stewart P and Zahm S (2018) Priorities for development of research methods in occupational cancer., Environmental Health Perspectives, 111:1, (1-12), Online publication date: 1-Jan-2003. Ward E, Schulte P, Bayard S, Blair A, Brandt-Rauf P, Butler M, Dankovic D, Hubbs A, Jones C, Karstadt M, Kedderis G, Melnick R, Redlich C, Rothman N, Savage R, Sprinker M, Toraason M and Weston A (2002) Priorities for Development of Research Methods in Occupational Cancer, Environmental Health Perspectives, 10.1289/ehp.5537, 111:1, (1-12) Woo Y and Lai D (2001) Structure–Activity Relationship (SAR) and Its Roles in Cancer Risk Assessment Genetic Toxicology and Cancer Risk Assessment, 10.1201/9780203904237.ch4, (73-91), Online publication date: 31-Aug-2001. Richard A (1998) Structure-based methods for predicting mutagenicity and carcinogenicity: are we there yet?, Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, 10.1016/S0027-5107(98)00068-2, 400:1-2, (493-507), Online publication date: 1-May-1998. Schwetz B and Gaylor D (2018) Alternative tests: carcinogenesis as an example., Environmental Health Perspectives, 106:suppl 2, (467-471), Online publication date: 1-Apr-1998. Schwetz B and Gaylor D (1997) New directions for predicting carcinogenesis, Molecular Carcinogenesis, 10.1002/(SICI)1098-2744(199711)20:3<275::AID-MC3>3.0.CO;2-K, 20:3, (275-279), Online publication date: 1-Nov-1997. Benigni R and Richard A (1996) QSARS of mutagens and carcinogens: Two case studies illustrating problems in the construction of models for noncongeneric chemicals, Mutation Research/Genetic Toxicology, 10.1016/S0165-1218(96)90092-0, 371:1-2, (29-46), Online publication date: 1-Nov-1996. McKinney J (2018) Reactivity parameters in structure-activity relationship-based risk assessment of chemicals., Environmental Health Perspectives, 104:8, (810-816), Online publication date: 1-Aug-1996.Bristol D, Wachsman J and Greenwell A (2018) The NIEHS Predictive-Toxicology Evaluation Project., Environmental Health Perspectives, 104:suppl 5, (1001-1010), Online publication date: 1-Oct-1996.Marchant C (2018) Prediction of rodent carcinogenicity using the DEREK system for 30 chemicals currently being tested by the National Toxicology Program. The DEREK Collaborative Group., Environmental Health Perspectives, 104:suppl 5, (1065-1073), Online publication date: 1-Oct-1996.Tennant R and Spalding J (2018) Predictions for the outcome of rodent carcinogenicity bioassays: identification of trans-species carcinogens and noncarcinogens., Environmental Health Perspectives, 104:suppl 5, (1095-1100), Online publication date: 1-Oct-1996.Huff J, Weisburger E and Fung V (2018) Multicomponent criteria for predicting carcinogenicity: dataset of 30 NTP chemicals., Environmental Health Perspectives, 104:suppl 5, (1105-1112), Online publication date: 1-Oct-1996. Woo Y, Lai D, Argus M and Arcos J (1995) Development of structure-activity relationship rules for predicting carcinogenic potential of chemicals, Toxicology Letters, 10.1016/0378-4274(95)03373-S, 79:1-3, (219-228), Online publication date: 1-Sep-1995. Bristol D (1995) Summary and recommendations for session B: activity classification and structure-activity relationship modeling for human health risk assessment of toxic substances, Toxicology Letters, 10.1016/0378-4274(95)03377-W, 79:1-3, (265-280), Online publication date: 1-Sep-1995. Haseman J (2014) Animal Screening Systems Wiley StatsRef: Statistics Reference Online, 10.1002/9781118445112.stat05460 Vol. 101, No. 5 October 1993Metrics About Article Metrics Publication History Originally published1 October 1993Published in print1 October 1993 Financial disclosuresPDF download License information EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted. Note to readers with disabilities EHP strives to ensure that all journal content is accessible to all readers. 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Predicting rodent carcinogenicity of halogenated hydrocarbons by in vivo biochemical parameters

Forty halogenated hydrocarbons of known rodent carcinogenicity (24 carcinogens, 16 noncarcinogens), including many promoters of carcinogenesis, nongenotoxic carcinogens, and hepatocarcinogens, were selected for study. The chemicals were administered by gavage in two dose levels to female Sprague-Dawley rats. The effects of these 40 chemicals on four biochemical assays [hepatic DNA damage by alkaline elution (DD), hepatic ornithine decarboxylase activity (ODC), serum alanine aminotransferase activity (ALT), and hepatic cytochrome P-450 content (P450)] were determined. Composite predictive parameters are defined as follows: CP = [ODC and P450], CT = [ALT and ODC], and TS = [DD or CP or CT]. The operational characteristics of TS for predicting rodent cancer were sensitivity 58%, specificity 81%, positive predictivity 82%, negative predictivity 57%, and concordance 68%. The concordance for the Ames test (45%) and structural alerts (SA; 46%) was much lower. TS also outperformed the Ames test and SA in producing fewer false positives (the specificity of TS was 81% vs. only 63% for the Ames test and 57% for SA). For predicting the carcinogenicity of the most difficult halogenated hydrocarbons (Ames and SA negative chemicals), TS was capable of successfully predicting the carcinogenicity of 8 (carbon tetrachloride, chloroform, alpha-hexachlorocyclohexane, kepone, mirex, monuron, p,p'-DDE, and 2,4,6-trichlorophenol) out of 16 of these non-DNA-reactive halogenated hydrocarbon carcinogens. All 8 of these halogenated hydrocarbons were positive in either CP or CT. This evidence shows that nongenotoxic carcinogenesis is best predicted by nongenotoxic parameters such as CP or CT (components of the predictor TS).

Predictive assay for rodent carcinogenicity using in vivo biochemical parameters: operational characteristics and complementarity

111 chemicals of known rodent carcinogenicity (49 carcinogens, 62 noncarcinogens), including many promoters of carcinogenesis, nongenotoxic carcinogens, hepatocarcinogens, and halogenated hydrocarbons, were selected for study. The chemicals were administered by gavage in two dose levels to female Sprague-Dawley rats. The effects of these 111 chemicals on 4 biochemical assays (hepatic DNA damage by alkaline elution (DD), hepatic ornithine decarboxylase activity (ODC), serum alanine aminotransferase activity (ALT), and hepatic cytochrome P-450 content (P450) were determined. Composite parameters are defined as follows: CP = [ODC and P450), CT = [ALT and ODC), and TS = [DD or CP or CT]. The operational characteristics of TS for predicting rodent cancer were sensitivity 55%, specificity 87%, positive predictivity 77%, negative predictivity 71%, and concordance 73%. For these chemicals, the 73% concordance of this study was superior to the concordance obtained from published data from other laboratories on the Ames test (53%), structural alerts (SA) (46%), chromosome aberrations in Chinese hamster ovary cells (ABS) (48%), cell mutation in mouse lymphoma 15178Y cells (MOLY) (52%), and sister-chromatid exchange in Chinese hamster ovary cells (SCE) (60%). The 4 in vivo biochemical assays were complementary to each other. The composite parameter TS also shows complementarity to all 5 other predictors of rodent cancer examined in this paper. For example. the Ames test alone has a concordance of only 53%. In combination with TS, the concordance is increased to 62% (Ames or TS) or to 63% (Ames and TS). For the 67 chemicals with data available for SA, the concordance for predicting rodent carcinogenicity was 47% (for SA alone), 54% (for SA or TS), and 66% (for SA and TS). These biochemical assays will be useful: (1) to predict rodent carcinogenicity per se, (2) to ‘confirm’ the results of short-term mutagenicity tests by the high specificity mode of the biochemical assays (the specificity and positive predictivity are both 100%), and (3) to be a component of future complementary batteries of tests for predicting rodent carcinogenicity.

Electrophilicity as measured by Ke: molecular determinants, relationship with other physical-chemical and quantum mechanical parameters, and ability to predict rodent carcinogenicity

This paper analyzes electrophilicity data as measured by the Ke system for 205 chemicals including both rodent carcinogens and non-carcinogens. Multivariate statistical methods were used. The analysis identified atoms and substructures contributing to electrophilicity, and permitted to establish a theoretical method by which the Ke value (electrophilicity) of chemicals can be easily estimated. In a subset of chemicals, the Ke parameter was compared with other physical-chemical and quantum mechanical properties: Ke appeared to be mostly correlated with the energy of the lowest unoccupied molecular orbital and with the absolute electronegativity. The role of Ke in structure-activity studies was also investigated; in particular, a comparative analysis of the performance of Ke, Salmonella typhimurium and Ashby's structural alerts in predicting carcinogenicity was carried out. The Ke system performed better than the other systems. However, because of the many different mechanisms underlying carcinogenesis, the Ke system cannot predict the potential carcinogenicity of all kinds of chemicals. It is concluded that the main role of Ke in risk assessment consists in producing a probabilistic estimate of the rodent carcinogenicity of the chemicals: e.g. a chemical with Ke higher than 3.0 x 10(12) M-1S-1 has nearly 80% probability of being a carcinogen. Such a probability estimate can be used to rank the chemicals in a priority scale for subsequent and more detailed studies, either theoretical or experimental. In view of this, the role of our method for estimating Ke is particularly important: it gives rapidly and at no cost a chemical classification for risk assessment and priority setting.

Predicting Rodent Carcinogenicity From Four in Vitro Genetic Toxicity Assays: An Evaluation of 114 Chemicals Studied by the National Toxicology Program

Predicting Rodent Carcinogenicity From Four in Vitro Genetic Toxicity Assays: An Evaluation of 114 Chemicals Studied by the National Toxicology Program

Predicting Rodent Carcinogenicity from Four in vitro Genetic Toxicity Assays: An Evaluation of 114 Chemicals Studied by the National Toxicology Program

Abstract Four widely used in vitro assays for genetic toxicity were investigated for their ability to predict the carcinogenicity of chemicals evaluated in long-term rodent studies by the National Toxicology Program (NTP). These assays were mutagenesis in Salmonella typhimurium and in mouse lymphoma cells and chromosome aberrations and sister chromatid exchanges in Chinese hamster ovary cells. Our evaluation compared results previously reported for 73 chemicals (Tennant et al. 1987) with results of similar analyses carried out for 41 additional chemicals tested subsequently by the NTP (Zeiger, Haseman, Shelby, Margolin, and Tennant, in press). For the combined data, Salmonella performed best, achieving a 66% (75/114) concordance, an 89% (32/36) positive predictivity, and a 55% (43/78) negative predictivity with regard to rodent carcinogenicity. The predictivity of Salmonella was even higher when attention was restricted to the multisite and/or two-species carcinogens. Chromosome aberrations also showed a ...

Carcinogenicity results for 114 laboratory animal studies used to assess the predictivity of four in vitro genetic toxicity assays for rodent carcinogenicity

Carcinogenicity results are presented for 114 long-term rodent studies carried out by the National Toxicology Program. Tumor rates are given for each positive or equivocal effect observed in 67 studies judged to show carcinogenic effects and in the 17 studies that show equivocal effects. The liver was found to be the most common site of carcinogenicity for both mice and rats; other frequent target sites included the lung, kidney, hematopoietic system, forestomach, thyroid gland, and mammary gland. The evaluative approach used in reaching decisions regarding the carcinogenicity of chemicals is discussed. No rigid statistical decision rules were employed, and biological as well as statistical factors were considered in the overall evaluation of the data. These long-term studies were utilized in a comprehensive evaluation of the ability of four in vitro genetic toxicity tests to predict rodent carcinogenicity. Details concerning these procedures and the results of this investigation are given elsewhere [Zeiger E, Haseman JK, Shelby MD, Margolin BH, Tennant RW 1990: Environ Mol Mutagen 16 (Supp. 18):1-14]. Interestingly, those chemicals evaluated at relatively low doses in the rodent experiments (because of the underlying toxicity of the chemicals) were far more likely to be positive in each of the four genetic toxicity assays than were "less toxic" chemicals evaluated in higher doses in the rodent studies.

Evaluation of four in vitro genetic toxicity tests for predicting rodent carcinogenicity: Confirmation of earlier results with 41 additional chemicals

The effectiveness of four in vitro short-term tests (STT) for genetic toxicity, induction of mutations in Salmonella (SAL) and mouse lymphoma L5178Y cells (MLA), and induction of sister chromatid exchanges (SCE) and chromosome aberrations (ABS) in Chinese hamster ovary cells that are used for predicting rodent carcinogenicity were examined. The in vitro results were compared with the results from 41 rodent carcinogenicity studies performed by the National Toxicology Program. The predictive values of, and interrelationships among, the STT for these 41 chemicals were similar to those previously reported for 73 chemicals and confirm those earlier results [Tennant RW, Margolin BH, Shelby MD, Zeiger E, Haseman JK, Spalding J, Caspary W, Resnick M, Stasiewicz S, Anderson B, Minor R (1987): Science 236:933-941]. Because of this similarity among the two datasets, the chemicals were combined into a single dataset of 114. The results with 114 chemicals show that SAL had the lowest sensitivity (.48) and the highest specificity (.91), whereas MLA had the highest sensitivity (.72) and the lowest specificity (.40). The concordances of the test results with rodent carcinogenicity were .66, .61, .59, and .59, for SAL, ABS, SCE, and MLA, respectively. Salmonella was the most predictive for carcinogenicity; 89% of the chemicals mutagenic in SAL were carcinogenic in rodents, however a negative result in any or all of the STT was not indicative of noncarcinogenicity. The STT results reported here show good agreement with the potential electrophilicity of the chemicals, and the majority of carcinogens that are undetected by the STT do not have an electrophilic structure. There was no complementarity among the tests and no combination of the four tests was more effective than any single test for predicting carcinogenicity.

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.

Response : Do Short-Term Tests Predict Rodent Carcinogenicity?

<i>Response</i> : Do Short-Term Tests Predict Rodent Carcinogenicity?