A quantitative and multiplexed approach to uncover the fitness landscape of tumor suppression in vivo
Menée à l'aide d'une technique de séquençage ultra-profond appelée Tuba-Seq et de la technologie d'ingénierie du génome CRISPR-Cas9, cette étude identifie les effets de 11 voies de signalisation liées à des gènes suppresseurs de tumeurs fréquemment affectés par des mutations dans les adénocarcinomes du poumon
Cancer growth is a multistage, stochastic evolutionary process. While cancer genome sequencing has been instrumental in identifying the genomic alterations that occur in human tumors, the consequences of these alterations on tumor growth remain largely unexplored. Conventional genetically engineered mouse models enable the study of tumor growth in vivo, but they are neither readily scalable nor sufficiently quantitative to unravel the magnitude and mode of action of many tumor-suppressor genes. Here, we present a method that integrates tumor barcoding with ultradeep barcode sequencing (Tuba-seq) to interrogate tumor-suppressor function in mouse models of human cancer. Tuba-seq uncovers genotype-dependent distributions of tumor sizes. By combining Tuba-seq with multiplexed CRISPR-Cas9-mediated genome editing, we quantified the effects of 11 tumor-suppressor pathways that are frequently altered in human lung adenocarcinoma. Tuba-seq enables the broad quantification of the function of tumor-suppressor genes with unprecedented resolution, parallelization, and precision.