Quantitative in vivo analyses reveal a complex pharmacogenomic landscape in lung adenocarcinoma

The lack of knowledge about the relationship between tumor genotypes and therapeutic responses remains one of the most important gaps in enabling the effective use of cancer therapies. Here, we couple a multiplexed and quantitative platform with robust statistical methods to enable pharmacogenomic mapping of lung cancer treatment responses in vivo. We uncover a surprisingly complex map of genotype-specific therapeutic responses, with over 20% of possible interactions showing significant resistance or sensitivity. We validate one of these interactions - the resistance of Keap1 mutant tumors to platinum therapy - using a large patient response dataset. Our results highlight the importance of understanding the genetic determinants of treatment responses in the development of precision therapies and define a strategy to identify such determinants. Overall design: We applied Tuba-seq to assess the genotype-specific therapeutic responses of 11 genotypes of lung tumors to a panel of eight single and combination therapies. KT;Cas9 mice with Lenti-sgTSPool/Cre-initiated lung tumors were treated for three weeks with one of the eight therapies followed by Tuba-seq analysis.