QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors
Carcinogenicity is a crucial endpoint for the safety assessment of chemicals and products. During the last few decades, the development of quantitative structure–activity relationship ((Q)SAR) models has gained importance for regulatory use, in combination with in vitro testing or expert-based reaso...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/26/1/127 |
| _version_ | 1797543139237429248 |
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| author | Cosimo Toma Alberto Manganaro Giuseppa Raitano Marco Marzo Domenico Gadaleta Diego Baderna Alessandra Roncaglioni Nynke Kramer Emilio Benfenati |
| author_facet | Cosimo Toma Alberto Manganaro Giuseppa Raitano Marco Marzo Domenico Gadaleta Diego Baderna Alessandra Roncaglioni Nynke Kramer Emilio Benfenati |
| author_sort | Cosimo Toma |
| collection | DOAJ |
| description | Carcinogenicity is a crucial endpoint for the safety assessment of chemicals and products. During the last few decades, the development of quantitative structure–activity relationship ((Q)SAR) models has gained importance for regulatory use, in combination with in vitro testing or expert-based reasoning. Several classification models can now predict both human and rat carcinogenicity, but there are few models to quantitatively assess carcinogenicity in humans. To our knowledge, slope factor (SF), a parameter describing carcinogenicity potential used especially for human risk assessment of contaminated sites, has never been modeled for both inhalation and oral exposures. In this study, we developed classification and regression models for inhalation and oral SFs using data from the Risk Assessment Information System (RAIS) and different machine learning approaches. The models performed well in classification, with accuracies for the external set of 0.76 and 0.74 for oral and inhalation exposure, respectively, and r<sup>2</sup> values of 0.57 and 0.65 in the regression models for oral and inhalation SFs in external validation. These models might therefore support regulators in (de)prioritizing substances for regulatory action and in weighing evidence in the context of chemical safety assessments. Moreover, these models are implemented on the VEGA platform and are now freely downloadable online. |
| first_indexed | 2024-03-10T13:41:26Z |
| format | Article |
| id | doaj.art-359e8cca66f641ccbae31089f08ac5f9 |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-10T13:41:26Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-359e8cca66f641ccbae31089f08ac5f92023-11-21T03:01:13ZengMDPI AGMolecules1420-30492020-12-0126112710.3390/molecules26010127QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope FactorsCosimo Toma0Alberto Manganaro1Giuseppa Raitano2Marco Marzo3Domenico Gadaleta4Diego Baderna5Alessandra Roncaglioni6Nynke Kramer7Emilio Benfenati8Laboratory of Chemistry and Environmental Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milan, ItalyKode Chemoinformatics s.r.l., 56125 Pisa, ItalyLaboratory of Chemistry and Environmental Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milan, ItalyLaboratory of Chemistry and Environmental Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milan, ItalyLaboratory of Chemistry and Environmental Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milan, ItalyLaboratory of Chemistry and Environmental Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milan, ItalyLaboratory of Chemistry and Environmental Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milan, ItalyInstitute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80177, 3508 TD Utrecht, The NetherlandsLaboratory of Chemistry and Environmental Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milan, ItalyCarcinogenicity is a crucial endpoint for the safety assessment of chemicals and products. During the last few decades, the development of quantitative structure–activity relationship ((Q)SAR) models has gained importance for regulatory use, in combination with in vitro testing or expert-based reasoning. Several classification models can now predict both human and rat carcinogenicity, but there are few models to quantitatively assess carcinogenicity in humans. To our knowledge, slope factor (SF), a parameter describing carcinogenicity potential used especially for human risk assessment of contaminated sites, has never been modeled for both inhalation and oral exposures. In this study, we developed classification and regression models for inhalation and oral SFs using data from the Risk Assessment Information System (RAIS) and different machine learning approaches. The models performed well in classification, with accuracies for the external set of 0.76 and 0.74 for oral and inhalation exposure, respectively, and r<sup>2</sup> values of 0.57 and 0.65 in the regression models for oral and inhalation SFs in external validation. These models might therefore support regulators in (de)prioritizing substances for regulatory action and in weighing evidence in the context of chemical safety assessments. Moreover, these models are implemented on the VEGA platform and are now freely downloadable online.https://www.mdpi.com/1420-3049/26/1/127cancer slope factorin silico methodQSARprioritization |
| spellingShingle | Cosimo Toma Alberto Manganaro Giuseppa Raitano Marco Marzo Domenico Gadaleta Diego Baderna Alessandra Roncaglioni Nynke Kramer Emilio Benfenati QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors Molecules cancer slope factor in silico method QSAR prioritization |
| title | QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors |
| title_full | QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors |
| title_fullStr | QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors |
| title_full_unstemmed | QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors |
| title_short | QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors |
| title_sort | qsar models for human carcinogenicity an assessment based on oral and inhalation slope factors |
| topic | cancer slope factor in silico method QSAR prioritization |
| url | https://www.mdpi.com/1420-3049/26/1/127 |
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