Combinatorial in vivo genome editing identifies widespread epistasis and an accessible fitness landscape during lung tumorigenesis
Lung adenocarcinoma, the most common subtype of lung cancer, is genomically complex, with tumors containing tens to hundreds of non-synonymous mutations. However, little is understood about how genes interact with each other to enable the evolution of cancer in vivo, largely due to a lack of methods for investigating genetic interactions in a high-throughput and quantitative manner. Here, we employed a novel platform to generate tumors with all pairwise inactivation of ten diverse tumor suppressor genes within an autochthonous mouse model of oncogenic KRAS-driven lung cancer. By quantifying the fitness of tumors with every single and double mutant genotype, we show that most tumor suppressor genetic interactions exhibited negative epistasis, with diminishing returns on tumor fitness. In contrast, Apc inactivation showed positive epistasis with the inactivation of several other genes, including synergistic effects on tumor fitness in combination with Lkb1 or Nf1 inactivation. Sign epistasis was extremely rare, suggesting a surprisingly accessible fitness landscape during lung tumorigenesis. These findings greatly expand our understanding the evolutionary interactions that drive tumorigenesis in vivo. Overall design: Ultra-deep sequencing of DNA barcode amplicon