CRISPR screens in cancer spheroids identify 3D growth-specific vulnerabilities

Kyuho Han (), Sarah E. Pierce, Amy Li, Kaitlyn Spees, Gray R. Anderson, Jose A. Seoane, Yuan-Hung Lo, Michael Dubreuil, Micah Olivas, Roarke A. Kamber, Michael Wainberg, Kaja Kostyrko, Marcus R. Kelly, Maryam Yousefi, Scott W. Simpkins, David Yao, Keonil Lee, Calvin J. Kuo, Peter K. Jackson, Alejandro Sweet-Cordero, Anshul Kundaje, Andrew J. Gentles, Christina Curtis, Monte M. Winslow and Michael C. Bassik ()
Additional contact information
Kyuho Han: Stanford University School of Medicine
Sarah E. Pierce: Stanford University School of Medicine
Amy Li: Stanford University School of Medicine
Kaitlyn Spees: Stanford University School of Medicine
Gray R. Anderson: Stanford University School of Medicine
Jose A. Seoane: Stanford University School of Medicine
Yuan-Hung Lo: Stanford University School of Medicine
Michael Dubreuil: Stanford University School of Medicine
Micah Olivas: Stanford University School of Medicine
Roarke A. Kamber: Stanford University School of Medicine
Michael Wainberg: Stanford University
Kaja Kostyrko: University of California San Francisco
Marcus R. Kelly: Stanford University School of Medicine
Maryam Yousefi: Stanford University School of Medicine
Scott W. Simpkins: Stanford University School of Medicine
David Yao: Stanford University School of Medicine
Keonil Lee: Stanford University School of Medicine
Calvin J. Kuo: Stanford University School of Medicine
Peter K. Jackson: Stanford University School of Medicine
Alejandro Sweet-Cordero: University of California San Francisco
Anshul Kundaje: Stanford University School of Medicine
Andrew J. Gentles: Stanford University School of Medicine
Christina Curtis: Stanford University School of Medicine
Monte M. Winslow: Stanford University School of Medicine
Michael C. Bassik: Stanford University School of Medicine

Nature, 2020, vol. 580, issue 7801, 136-141

Abstract: Abstract Cancer genomics studies have identified thousands of putative cancer driver genes1. Development of high-throughput and accurate models to define the functions of these genes is a major challenge. Here we devised a scalable cancer-spheroid model and performed genome-wide CRISPR screens in 2D monolayers and 3D lung-cancer spheroids. CRISPR phenotypes in 3D more accurately recapitulated those of in vivo tumours, and genes with differential sensitivities between 2D and 3D conditions were highly enriched for genes that are mutated in lung cancers. These analyses also revealed drivers that are essential for cancer growth in 3D and in vivo, but not in 2D. Notably, we found that carboxypeptidase D is responsible for removal of a C-terminal RKRR motif2 from the α-chain of the insulin-like growth factor 1 receptor that is critical for receptor activity. Carboxypeptidase D expression correlates with patient outcomes in patients with lung cancer, and loss of carboxypeptidase D reduced tumour growth. Our results reveal key differences between 2D and 3D cancer models, and establish a generalizable strategy for performing CRISPR screens in spheroids to reveal cancer vulnerabilities.

Date: 2020
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DOI: 10.1038/s41586-020-2099-x

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