Project DRIVE: a compendium of cancer dependencies and synthetic lethal relationships uncovered by large-scale, deep RNAi screening
Open accessAbstract
Elucidation of the mutational landscape of human cancer has progressed rapidly and been accompanied by the development of therapeutics targeting mutant oncogenes. However, a comprehensive mapping of cancer dependencies has lagged behind and the discovery of therapeutic targets for counteracting tumor suppressor gene loss is needed. To identify vulnerabilities relevant to specific cancer subtypes, we conducted a large-scale RNAi screen in which viability effects of mRNA knockdown were assessed for 7,837 genes using an average of 20 shRNAs per gene in 398 cancer cell lines. We describe findings of this screen, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features. In addition, we describe robust gene-interaction networks recapitulating both protein complexes and functional cooperation among complexes and pathways. This dataset along with a web portal is provided to the community to assist in the discovery and translation of new therapeutic approaches for cancer.
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KRAS mutations at codon 12 are strongly associated with cellular KRAS dependency across human cell lines.
“The presence of KRAS mutations, especially the most common mutations at codon 12, is strongly associated with cellular KRAS dependency, as shown by functional genomic approaches across a large panel of human cell lines from different cancer types (16)”
From Expanding the Reach of Precision Oncology by Drugging All <i>KRAS</i> Mutants (2022) · cites this paper as [16]
RNAi and CRISPR studies in hundreds of cancer cell lines show KRAS mutant pancreatic, lung, and colorectal adenocarcinoma cells are more sensitive to loss of the KRAS oncogene than KRAS WT cancer cell lines.
“RNAi mediated gene knockdown studies and CRISPR mediated gene knockout studies in hundreds of cancer cell lines have shown that KRAS mutant pancreatic, lung and colorectal adenocarcinoma cells are more sensitive to the loss of the KRAS oncogene than KRAS WT cancer cell lines (64, 65) (Figure 4).”
From KRAS mutation in pancreatic cancer (2021) · cites this paper as [64]
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Cui, Y., Cheng, X., Chen, Q., Song, B., Chiu, A., Gao, Y., Dawson, T., Chao, L., Zhang, W., Li, D., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa809 · Cited by 24 · see citing works
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Self-citation
- Authors
- McDonald, E. R., de Weck, A., Schlabach, M. R., Billy, E., Mavrakis, K. J., Hoffman, G. R., Belur, D., Castelletti, D., Frias, E., Gampa, K., Golji, J., Kao, I., Li, L., Megel, P., Perkins, T. A., Ramadan, N., Ruddy, D. A., Silver, S. J., Sovath, S., Stump, M., Weber, O., Widmer, R., Yu, J., Yu, K., Yue, Y., Abramowski, D., Ackley, E., Barrett, R., Berger, J., Bernard, J. L., Billig, R., Brachmann, S. M., Buxton, F., Caothien, R., Caushi, J. X., Chung, F. S., Cortés-Cros, M., deBeaumont, R. S., Delaunay, C., Desplat, A., Duong, W., Dwoske, D. A., Eldridge, R. S., Farsidjani, A., Feng, F., Feng, J., Flemming, D., Forrester, W., Galli, G. G., Gao, Z., Gauter, F., Gibaja, V., Haas, K., Hattenberger, M., Hood, T., Hurov, K. E., Jagani, Z., Jenal, M., Johnson, J. A., Jones, M. D., Kapoor, A., Korn, J., Liu, J., Liu, Q., Liu, S., Liu, Y., Loo, A. T., Macchi, K. J., Martin, T., McAllister, G., Meyer, A., Mollé, S., Pagliarini, R. A., Phadke, T., Repko, B., Schouwey, T., Shanahan, F., Shen, Q., Stamm, C., Stephan, C., Stucke, V. M., Tiedt, R., Varadarajan, M., Venkatesan, K., Vitari, A. C., Wallroth, M., Weiler, J., Zhang, J., Mickanin, C., Myer, V. E., Porter, J. A., Lai, A., Bitter, H., Lees, E., Keen, N., Kauffmann, A., Stegmeier, F., Hofmann, F., Schmelzle, T., & Sellers, W. R.
- Affiliations
- Novartis (Switzerland) (CH)
- Novartis Institutes for BioMedical Research (CH)
- Corresponding author
- McDonald, E. Robert
- Schmelzle, Tobias
- ORCID
- McDonald, E. Robert
- Schlabach, Michael R.
- Castelletti, Deborah
- Li, Li
- Ruddy, David A.
- Silver, Serena J.
- Yu, Jianjun
- Barrett, Rosemary
- Brachmann, Saskia M.
- Caothien, Roger
- Caushi, Justina X.
- Cortés-Cros, Marta
- Delaunay, Clara
- Feng, JiaJia
- Forrester, William
- Galli, Giorgio G.
- Gao, Zhenhai
- Gibaja, Veronica
- Hattenberger, Marc
- Jones, Michael D.
- Korn, Joshua
- Liu, Jilin
- Liu, Shumei
- Liu, Yue
- Meyer, Amandine
- Mollé, Sandra
- Pagliarini, Raymond A.
- Shen, Qiong
- Stephan, Christine
- Tiedt, Ralph
- Varadarajan, Malini
- Venkatesan, Kavitha
- Weiler, Jan
- Zhang, Jing
- Myer, Vic E.
- Lai, Albert
- Bitter, Hans
- Lees, Emma
- Keen, Nicholas
- Kauffmann, Audrey
- Stegmeier, Frank
- Schmelzle, Tobias
- Sellers, William R.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2017-07
- Volume
- 170
- Issue
- 3
- Pages
- 577-592.e10
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2739511077
- Cited by
- 658
- References
- 58
- Citations by year
- 2026: 37 · 2025: 74 · 2024: 71 · 2023: 54 · 2022: 73 · 2021: 96 · 2020: 92 · 2019: 91 · 2018: 57 · 2017: 11
- FWCI
- 28.92
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Oncology › Cancer-related Molecular Pathways
- Keywords
- cancer dependency, synthetic lethality, RNAi screen, cancer cell lines, tumor suppressor loss, therapeutic target, gene interaction networks, protein complexes, tumor subtypes, shRNA knockdown
- MeSH terms
- Humans, Neoplasms, Oncogenes, Transcription Factors, Signal Transduction, Gene Library, RNA Interference, RNA, Small Interfering, Cell Line, Tumor, Multiprotein Complexes, Gene Regulatory Networks
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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