{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Rogers ZN"],"funding":["NHGRI NIH HHS","NCI NIH HHS","NIGMS NIH HHS","NIH HHS"],"pagination":["737-742"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC5495136"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["14(7)"],"pubmed_abstract":["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."],"journal":["Nature methods"],"pubmed_title":["A quantitative and multiplexed approach to uncover the fitness landscape of tumor suppression in vivo."],"pmcid":["PMC5495136"],"funding_grant_id":["R25 CA180993","R21 CA194910","P30 CA124435","R01 CA175336","S10 OD018220","R01 CA207133","R35 GM118165","T32 HG000044"],"pubmed_authors":["Winslow MM","Chuang CH","Winters IP","Rogers ZN","Naranjo S","McFarland CD","Petrov D"],"additional_accession":[]},"is_claimable":false,"name":"A quantitative and multiplexed approach to uncover the fitness landscape of tumor suppression in vivo.","description":"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.","dates":{"release":"2017-01-01T00:00:00Z","publication":"2017 Jul","modification":"2025-04-04T01:28:06.397Z","creation":"2019-03-27T02:49:12Z"},"accession":"S-EPMC5495136","cross_references":{"pubmed":["28530655"],"doi":["10.1038/nmeth.4297"]}}