title: In silico tools and transcriptomics analyses in the mutagenicity assessment of cosmetic ingredients: a proof-of-principle on how to add weight to the evidence.
abstract: Prior to the downstream development of chemical substances, including pharmaceuticals and cosmetics, their influence on the genetic apparatus has to be tested. Several in vitro and in vivo assays have been developed to test for genotoxicity. In a first tier, a battery of two to three in vitro tests is recommended to cover mutagenicity, clastogenicity and aneugenicity as main endpoints. This regulatory in vitro test battery is known to have a high sensitivity, which is at the expense of the specificity. The high number of false positive in vitro results leads to excessive in vivo follow-up studies. In the case of cosmetics it may even induce the ban of the particular compound since in Europe the use of experimental animals is no longer allowed for cosmetics. In this article, an alternative approach to derisk a misleading positive Ames test is explored. Hereto we first tested the performance of five existing computational tools to predict the potential mutagenicity of a data set of 132 cosmetic compounds with a known genotoxicity profile. Furthermore, we present, as a proof-of-principle, a strategy in which a combination of computational tools and mechanistic information derived from in vitro transcriptomics analyses is used to derisk a misleading positive Ames test result. Our data shows that this strategy may represent a valuable tool in a weight-of-evidence approach to further evaluate a positive outcome in an Ames test.
authors.forename: Gamze
authors.initials: G
authors.lastname: Ates
authors.affiliation: IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milan, Italy.
authors.forename: Giuseppa
authors.initials: G
authors.lastname: Raitano
authors.forename: Anja
authors.initials: A
authors.lastname: Heymans
authors.affiliation: Unit of Toxicology, Scientific Institute of Public Health (WIV-ISP), Juliette Wytsmanstraat 14, B-1050, Brussels, Belgium.
authors.forename: Melissa
authors.initials: M
authors.lastname: Van Bossuyt
authors.affiliation: Gentoxicon BVBA, Boskant 101, B-2350 Vosselaar, Belgium.
authors.forename: Philippe
authors.initials: P
authors.lastname: Vanparys
authors.affiliation: Unit of Toxicology, Scientific Institute of Public Health (WIV-ISP), Juliette Wytsmanstraat 14, B-1050, Brussels, Belgium.
authors.forename: Birgit
authors.initials: B
authors.lastname: Mertens
authors.affiliation: Biopredic International, Parc d'activité de la Bretèche Bâtiment A4, 35760 Saint Grégoire, France and.
authors.forename: Christophe
authors.initials: C
authors.lastname: Chesne
authors.affiliation: IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milan, Italy.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Roncaglioni
authors.affiliation: Super Stellar Solutions, Oudergem, B-1160 Brussels, Belgium.
authors.forename: Dimiter
authors.initials: D
authors.lastname: Milushev
authors.affiliation: IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milan, Italy.
authors.forename: Emilio
authors.initials: E
authors.lastname: Benfenati
authors.forename: Vera
authors.initials: V
authors.lastname: Rogiers
authors.affiliation: Unit of Toxicology, Scientific Institute of Public Health (WIV-ISP), Juliette Wytsmanstraat 14, B-1050, Brussels, Belgium.
authors.forename: Tatyana Y
authors.initials: TY
authors.lastname: Doktorova
mesh_terms: D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D003358:Cosmetics; D000068598:Data Accuracy; D020869:Gene Expression Profiling / Q000379:methods*; D009152:Mutagenicity Tests / Q000379:methods*; D012680:Sensitivity and Specificity
chemical_list: D003358:Cosmetics