Rapidly scalable platforms for direct in vivo screening of functional drivers in lethal cancers


Year of Award:
2019
Status:
Complete
Award Type:
R33
Project Number:
CA225498
RFA Number:
RFA-CA-18-003
Technology Track:
Molecular & Cellular Analysis Technologies
PI/Project Leader:
CHEN, SIDI
Other PI or Project Leader:
Not Applicable
Institution:
YALE UNIVERSITY

Project Summary: Cancer is a major cause of death worldwide with outstanding challenges for a cure. Suchchallenges are primarily due to the nature of tumor heterogeneity and evolvability. Thus, the ability to generateunbiased, quantitative and causal maps of functional drivers and their combinations in native tumormicroenvironment is a key to accelerate therapeutic discovery. To date, little has been done tocomprehensively and combinatorially test which of the mutations identified in human patients can indeedfunctionally drive tumorigenesis of normal cells in native organs. The major barriers include accurate delivery,precise genome manipulation, efficient massively parallel perturbation, and unbiased, high-sensitivityquantitative readout, all of which have to be achieved simultaneously in the native tissue microenvironment.We recently established a novel approach named Pooled AAV Screen with Targeted Amplicon Sequencing(PASTAS) for direct in vivo screening of causative cancer drivers and combinations. This method generatesprecision models of cancer that (1) spontaneously develop from tumor-originating cells in the native organmicroenvironment, (2) develop in fully immunocompetent animals and preserve the immune microenvironment,(3) genetically mimic significant mutations found in patients, (4) closely mimic the histopathology of humandisease and clinical features, (5) encompass high degree of genetic and cellular heterogeneity, (6) offerflexibility to target any choice of target genes and rapidly scalable as pooled mutant screens, and (7) is easy touse by the community. In this study, we will conduct advanced development, robust validation and fullestablishment of this screening system. We will first establish technical parameters for optimal performance ofthis technology by quantitative measurements using independent patient cohorts with two lethal cancer types:glioblastoma and liver hepatocellular carcinoma. Then, we will extend the utility for causative driver discoveryin therapeutic settings. Finally, we will advance the development of a lentiviral vector-based orthogonalapproach to open up larger screening capabilities. Such screening systems and models will enable rapididentification of causative factors that directly drive transformation of healthy cells, tumor initiation, progressionand therapeutic responses to treatments. More importantly, compared to existing alternatives, the fullyimmunocompetent setting allows robust pre-clinical testing of immunotherapies, in genetically matched animalavatars, as well as screening for genes that modulate the response to these therapies. Outcome and impact:This R33 will deliver optimized and validated PASTAS / PLeSTASS systems to link causative genes tooncogenesis in native TME; to enable autochthonous immunotherapy screen in fully immunocompetent settingfor identification of targets that modulate the response to these life-saving drugs; and to share resources andprotocols for the community to collectively yield novel and far-reaching insights in oncology.