Peer-Reviewed Publications

      Towards the validation of a lung tumorigenesis model with mainstream cigarette smoke inhalation using the A/J mouse

      Stinn, W.; Berges, A.; Meurrens, K.; Buettner, A.; Gebel, S.; Lichtner, R. B.; Janssens, K.; Veljkovic, E.; Xiang, Y.; Roemer, E.; Haussmann, H.-J.
      Published
      Jan 24, 2013
      DOI
      10.1016/j.tox.2013.01.005
      PMID
      23357402
      Topic
      Summary

      A generally accepted and validated laboratory model for smoking-associated pulmonary tumorigenesis would be useful for both basic and applied research applications, such as the development of early diagnostic endpoints or the evaluation of modified risk tobacco products, respectively. The A/J mouse is susceptible for developing both spontaneous and induced lung adenomas and adenocarcinomas, and increased lung tumor multiplicities were also observed in previous cigarette smoke inhalation studies. The present study was designed to collect data useful towards the validation of an 18-month mainstream smoke (MS) inhalation model. Male and female A/J mice were exposed whole-body at three MS concentration levels for 6 h/day, and the results were compared to a previous study in the same laboratory and with a similar design. A linear MS concentration-dependent increase in lung tumorigenesis was observed with similar slopes for both sexes and both studies and a maximal 5-fold increase in multiplicity beyond sham control. The minimal detectable difference in lung tumor multiplicity for the current study was 37%. In the larynx, papillomas were detectable in all MS-exposed groups in a non-concentration dependent manner. No other extra-pulmonary MS-dependent neoplastic lesions were found. Gene expression signatures of lung tumor tissues allowed a clear differentiation of sham- and high dose MS-exposed mice. In combination with data from previous smoke inhalation studies with A/J mice, the current data suggest that this model for MS inhalation-induced pulmonary tumorigenesis is reliable and relevant, two crucial requirements towards validation of such a model.