It has been clear for over a decade that cancer is not a single disease and that this heterogeneity is a primary barrier to the understanding of oncogenic mechanisms and treatments. Cancers vary epigenetically and genetically at multiple length and time scales and between patients. There can be many distinct mechanisms driving oncogenic and metastatic processes, even within a single cancerous cell. The challenge researchers and clinicians face is how to understand cancer from the perspective of simultaneous perturbations to multiple genes and proteins. Risk variants identified through genome wide association studies and epiGWAS can be individually perturbed in large experiments comprised of many 384-well plates through RNAi and CRISPR libraries, and even be combinatorially perturbed and screened in `one-pot' using barcoding strategies. However, even state-of-the-art CRISPR screening methods are restricted to functional perturbations of 2 or 3 variants at a time per cell. These restrictions arise from the difficulties repetitive sequences in gRNA arrays present in both expression construct synthesis and stability. Here we propose a new method that will be capable of expressing randomized combinatorial libraries of thousands of distinct gRNAs, with each cell of a population expressing an array of over 30 gRNAs.

Public Health Relevance

Cancer is a complex class of highly heterogeneous diseases. Next generation sequencing and CRISPR libraries have expanded researchers' capabilities to measure and probe this heterogeneity; yet, it is still not possible to perturb large numbers of genetic or epigenetic loci simultaneously within individual cells. Here we propose a synthetic biology strategy to unlock this capability and to directly interrogate the function of networks of genes and proteins in cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21CA240162-01
Application #
9795162
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Li, Jerry
Project Start
2019-09-01
Project End
2022-08-31
Budget Start
2019-09-01
Budget End
2020-08-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
North Carolina State University Raleigh
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
042092122
City
Raleigh
State
NC
Country
United States
Zip Code
27695