Transcription profiling of mouse lung after exposure to 26 chemicals to identify transcriptional biomarkers for predicting lung tumors

ABSTRACT: The process for evaluating chemical safety is inefficient, costly, and animal intensive. There is growing consensus that the current process of safety testing needs to be significantly altered to improve efficiency and reduce the number of untested chemicals. In this study, the use of short-term gene expression profiles was evaluated for predicting the increased incidence of mouse lung tumors. Animals were exposed to a total of 26 diverse chemicals with matched vehicle controls over a period of three years. Upon completion, significant batch-related effects were observed. Adjustment for batch effects significantly improved the ability to predict increased lung tumor incidence. For the best statistical model, the estimated predictive accuracy under honest five-fold cross-validation was

ORGANISM(S): Mus musculus

SUBMITTER: Russell Scott Thomas 

PROVIDER: E-GEOD-17933 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress