bioRxiv Science⌕ Search

Biology subjects

Winters, I. P.

Publications and source records attributed to Winters, I. P..

2 recordsLinked to original sources

Oncogenic context shapes the fitness landscape of tumor suppression

Tumors acquire alterations in oncogenes and tumor suppressor genes in an adaptive walk through the fitness landscape of tumorigenesis. However, the features of this landscape remain poorly understood and cannot be revealed by human cancer genotyping alone. Here, we use a multiplexed, autochthonous mouse platform to model and quantify the initiation and growth of more than one hundred genotypes of lung tumors across four oncogenic contexts: KRAS G12D, KRAS G12C, BRAF V600E, and EGFR L858R. The resulting fitness landscape is rugged (the effect of tumor suppressor inactivation often switches between beneficial and deleterious depending on the oncogenic context), shows no evidence of diminishing-returns epistasis within variants of the same oncogene, and is inconsistent with expectations of a simple linear signaling relationship among these three oncogenes. Our findings suggest that tumor suppressor effects are strongly context-specific, which limits the set of evolutionary paths that can be taken through the fitness landscape.

cancer biology↗

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

AbstractThe 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.

cancer biology↗