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

> **NIH NIH R33** · YALE UNIVERSITY · 2021 · $407,025

## Abstract

Project Summary: Cancer is a major cause of death worldwide with outstanding challenges for a cure. Such
challenges are primarily due to the nature of tumor heterogeneity and evolvability. Thus, the ability to generate
unbiased, quantitative and causal maps of functional drivers and their combinations in native tumor
microenvironment is a key to accelerate therapeutic discovery. To date, little has been done to
comprehensively and combinatorially test which of the mutations identified in human patients can indeed
functionally drive tumorigenesis of normal cells in native organs. The major barriers include accurate delivery,
precise genome manipulation, efficient massively parallel perturbation, and unbiased, high-sensitivity
quantitative 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 generates
precision models of cancer that (1) spontaneously develop from tumor-originating cells in the native organ
microenvironment, (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 human
disease and clinical features, (5) encompass high degree of genetic and cellular heterogeneity, (6) offer
flexibility to target any choice of target genes and rapidly scalable as pooled mutant screens, and (7) is easy to
use by the community. In this study, we will conduct advanced development, robust validation and full
establishment of this screening system. We will first establish technical parameters for optimal performance of
this 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 discovery
in therapeutic settings. Finally, we will advance the development of a lentiviral vector-based orthogonal
approach to open up larger screening capabilities. Such screening systems and models will enable rapid
identification of causative factors that directly drive transformation of healthy cells, tumor initiation, progression
and therapeutic responses to treatments. More importantly, compared to existing alternatives, the fully
immunocompetent setting allows robust pre-clinical testing of immunotherapies, in genetically matched animal
avatars, 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 to
oncogenesis in native TME; to enable autochthonous immunotherapy screen in fully immunocompetent setting
for identification of targets that modulate the response to these life-saving drugs; and to share resources and
protocols...

## Key facts

- **NIH application ID:** 10129308
- **Project number:** 5R33CA225498-03
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Sidi Chen
- **Activity code:** R33 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $407,025
- **Award type:** 5
- **Project period:** 2019-04-01 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10129308

## Citation

> US National Institutes of Health, RePORTER application 10129308, Rapidly scalable platforms for direct in vivo screening of functional drivers in lethal cancers (5R33CA225498-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10129308. Licensed CC0.

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