# (PQ4) Novel tools for in vivo study of genetic interactions in cancer progression

> **NIH NIH R01** · YALE UNIVERSITY · 2021 · $576,627

## Abstract

PROJECT SUMMARY:
The evolution of human cancer is a complex process driven by multiple molecular and cellular events. Cancer cells often
harbor numerous aberrations that can act in additive, parallel, antagonistic, epistatic or synergistic fashion. Those
interactions contribute to tumorigenesis, progression, metastasis, drug resistance or other life-threatening features. While
these interactions can be weakly inferred from analysis of tumor sequence data, elucidating genetic interactions in vivo is
essential for rapidly building a robust map of cancer development and to accelerate therapeutic developments. However,
there are currently few effective tools for precise multigenic manipulation of cancer in vivo, limiting our scope for
accurately dissecting these interactions. We endeavored to harness single-effector RNA-guided endonucleases (RGNs) for
genome editing, parallel screening and in vivo modeling of human cancer. Recently, we generated a platform to
systematically interrogate several hundred loci directly in vivo. To overcome current limitations in multigene editing and
achieve more accurate control of simultaneity and sequentiality of multi-allelic tumor modeling, we utilized Cpf1, an
RGN that can edit its target simply with crRNAs independent of tracrRNA thus allowing simultaneous editing of multiple
genes with a single crRNA array. We developed a preliminary Cpf1-based crRNA array screening (CCAS) system in
mammalian cells, and applied it in mouse models of progression and metastasis. In our first aim, we will perform
validation and optimization of CCAS for in vivo double-knockout phenotyping of cancer co-drivers. We will establish its
technical rigor, efficiency and specificity for simultaneous editing, as well as developing a set of computational pipelines
for accurate calling of statistically significant gene pairs. We will apply this approach to study the genetic interactions of
tumor suppressors found in lung cancer patients at Yale Cancer Center and Hospital, and identify potential co-drivers of
metastasis to vital organs. In the second aim, we will carry out validation and optimization of a Cpf1-Flip system for
sequential mutagenesis of cancer targets. We will demonstrate its broader applicability by testing clinically relevant gene
sets identified from public studies of the genomics of metastasis as well as a large multi-sample metastasis dataset
gathered on Yale cancer patients. We will then apply this methodology as an unbiased depletion screen to identify targets
that are essential for survival in specific oncogenic backgrounds. We will develop novel versatile transgenic mouse strains
and companion viral vectors for direct modeling of multigenic tumorigenesis in mice. We will combine these tools to
enable high-throughput genetic interaction screening in healthy cells directly in the native organ to identify causative
mutation pairs that drive tumorigenesis. We anticipate that developing and establishing these tools will transf...

## Key facts

- **NIH application ID:** 10246861
- **Project number:** 5R01CA231112-04
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Sidi Chen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $576,627
- **Award type:** 5
- **Project period:** 2018-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10246861

## Citation

> US National Institutes of Health, RePORTER application 10246861, (PQ4) Novel tools for in vivo study of genetic interactions in cancer progression (5R01CA231112-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10246861. Licensed CC0.

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