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Docket #: S16-338

Barcoded viral platform for multiplexed functional validation of oncogenic cancer mutations in vivo and uses thereof

Researchers at Stanford University have developed a method which integrates cell barcoding and high-throughput sequencing to quantify tumor growth in genetically engineered mouse models of human cancer (called 'Tuba-seq” for Tumor barcoding coupled with sequencing). Unlike existing methods, this platform allows measurement of parameters of population (tumor) growth for a very large number of independent clonal populations (tumors) within the same mouse, providing exquisitely precise, cheap, and rapid estimate of effects of tumor-suppressors function modification on tumor growth in vivo. Because Tuba-seq enables the analysis of multiple pathways in the same animal using a very large number of independent tumors, it is much faster, much more precise, and is a much less expensive way to investigate tumor-suppressor function as well as genotype-specific therapeutic responses. This method is naturally adaptable for high-throughput profiling of drug responses of many tumor types growing in vivo.


Figure 1. (a) Schematic of Tuba-seq pipeline to assess lung tumor size distributions. (b) Fluorescence dissecting scope images of lung lobes from KT, KLT, and KPT mice with Lenti-mBC/Cre?initiated tumors. (c) Tumor size distributions in KT, KLT, and KPT mice.

Figure adapted from: Rogers, Z. N. et al. A quantitative and multiplexed approach to uncover the fitness landscape of tumor suppression in vivo.Nature Methods (2017). doi:10.1038/nmeth.4297

Applications

  • Interrogation of gene function in mouse models of human cancer
  • Profiling therapeutic effects of compounds/treatments on many major tumors genotypes in parallel, cheaply, rapidly, and precisely

Advantages

  • Rapid, quantitative method to determine functional importance of putative tumor suppressors on cancer growth in vivo
  • Ability to generate tumors in mice with different loss- and gain-of-function mutations, thus greatly reducing costs and time associated with pre-clinical testing in vivo
  • Provides sensitivity to identify tumor suppressors of small effect

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