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Nature
Cancer Genomics
James V. Neiswender, Samuel Maffa, Lisa Brenan, Dina ElHarouni, Yejie Yun, Isabella Boyle, Kirsty Wienand, Haider Inam, Tate Bertea, Ashley Anderson, Megan Wong, Matias Enriquez, Evan Lenz, Beatriz Villafranca, Nora Shanks, Mary Hager, Nia Lloyd, Hannah Shadmany, Sarah J. Wie, Harry Liang, Konnor Yunghans, Xiaomeng Zhang, Lauren Golden, Hannah Harris, Serena Day, Philip Montgomery, Samantha Stokes, Ross M. Giglio, Cynthia Hajal, James R. Whittle, Guadalupe Garcia, Caitlin E. Mills, Mehdi Touat, Kristine Pelton, Hongyu Li, Prem Sai Prabhakar, Sonja Herter, Zoe Hoffmann Kamrat, Dan Gui, Julien Dilly, Chen Khuan Wong, Jimmy A. Guo, Sangita Pal, Yossef Baidi, Ryan Johnston, Daniel D. Brown, Sonam Bhatia, Peter S. Winter, Srivatsan Raghavan, Rameen Beroukhim, Eva Colas, David L. Spector, Adam J. Bass, Peter K. Sorger, Yu Chen, Sarah J. Hill, Steffi Oesterreich, Adrian V. Lee, Himisha Beltran, Jesse S. Boehm, Yuen-Yi Tseng, David E. Root, William C. Hahn, Andrew J. Aguirre, Catarina D. Campbell, Keith L. Ligon, Joshua M. Dempster, Tsukasa Shibue, Francisca Vazquez
2026-08-05
TL;DR - This Nature study integrates genome-scale CRISPR screens from traditional cell lines and next-generation 3D cancer models to enhance the Cancer Dependency Map. The expanded models improve representation of tumour subtypes and genomic alterations.
- Combines CRISPR screening data across conventional and next-generation cancer models.
- Incorporates 3D models into systematic cancer dependency mapping.
- Broadens coverage of tumour diversity and cancer-associated genomic alterations.
- The provided abstract does not specify individual dependencies or quantitative improvements.
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