Literature DB >> 9685694

Transgenic assays for mutations and cancer: current status and future perspectives.

J Vijg1, H van Steeg.   

Abstract

Transgenic mouse modelling has proved to be a powerful approach to explore the various steps involved in spontaneous and induced carcinogenesis. Some of the multitude of models currently available have the potential to become a substitute for the expensive, long-term rodent bioassay to predict carcinogenicity of environmental compounds. Here, we review the progress in the development and use of transgenic mouse models specifically for the purpose of carcinogenicity and mutagenicity testing. Copyright 1998 Elsevier Science B.V. All rights reserved.

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Year:  1998        PMID: 9685694     DOI: 10.1016/s0027-5107(98)00030-x

Source DB:  PubMed          Journal:  Mutat Res        ISSN: 0027-5107            Impact factor:   2.433


  6 in total

Review 1.  High-throughput sequencing in mutation detection: A new generation of genotoxicity tests?

Authors:  Alexander Y Maslov; Wilber Quispe-Tintaya; Tatyana Gorbacheva; Ryan R White; Jan Vijg
Journal:  Mutat Res       Date:  2015-04-20       Impact factor: 2.433

Review 2.  Direct mutation analysis by high-throughput sequencing: from germline to low-abundant, somatic variants.

Authors:  Michael Gundry; Jan Vijg
Journal:  Mutat Res       Date:  2011-10-12       Impact factor: 2.433

Review 3.  A high-fidelity method for genomic sequencing of single somatic cells reveals a very high mutational burden.

Authors:  Jan Vijg; Xiao Dong; Lei Zhang
Journal:  Exp Biol Med (Maywood)       Date:  2017-07

4.  In vivo suppressor mutations correct a murine model of hereditary tyrosinemia type I.

Authors:  K Manning; M Al-Dhalimy; M Finegold; M Grompe
Journal:  Proc Natl Acad Sci U S A       Date:  1999-10-12       Impact factor: 11.205

5.  Effect of Ames dwarfism and caloric restriction on spontaneous DNA mutation frequency in different mouse tissues.

Authors:  Ana Maria Garcia; Rita A Busuttil; R Brent Calder; Martijn E T Dollé; Vivian Diaz; C Alex McMahan; Andrzej Bartke; James Nelson; Robert Reddick; Jan Vijg
Journal:  Mech Ageing Dev       Date:  2008-05-13       Impact factor: 5.432

6.  Single-molecule, quantitative detection of low-abundance somatic mutations by high-throughput sequencing.

Authors:  Alexander Y Maslov; Sergey Makhortov; Shixiang Sun; Johanna Heid; Xiao Dong; Moonsook Lee; Jan Vijg
Journal:  Sci Adv       Date:  2022-04-08       Impact factor: 14.136

  6 in total

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