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Defining a Cancer Dependency Map
Open accessAbstract
Most human epithelial tumors harbor numerous alterations, making it difficult to predict which genes are required for tumor survival. To systematically identify cancer dependencies, we analyzed 501 genome-scale loss-of-function screens performed in diverse human cancer cell lines. We developed DEMETER, an analytical framework that segregates on- from off-target effects of RNAi. 769 genes were differentially required in subsets of these cell lines at a threshold of six SDs from the mean. We found predictive models for 426 dependencies (55%) by nonlinear regression modeling considering 66,646 molecular features. Many dependencies fall into a limited number of classes, and unexpectedly, in 82% of models, the top biomarkers were expression based. We demonstrated the basis behind one such predictive model linking hypermethylation of the UBB ubiquitin gene to a dependency on UBC. Together, these observations provide a foundation for a cancer dependency map that facilitates the prioritization of therapeutic targets.
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“In addition, the advent of the CRISPR/Cas9 system has enabled screens that cover whole genomes [17,96].”
From Functional unknomics: Systematic screening of conserved genes of unknown function (2023) · cites this paper as [96]
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“Notably, analysis of PTGES3 gene essentiality upon Cas9 knockout across 1,070 diverse cancer cell lines present in the Cancer Dependency Map53 demonstrated that PTGES3 is not classified as a commonly essential gene (Extended Data Fig. 10c).”
From Genome-scale CRISPR screens identify PTGES3 as a direct modulator of androgen receptor function in advanced prostate cancer (2025) · cites this paper as [53]
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“Although several large databases of perturbations with bulk readouts exist, single-cell perturbation technologies are newer and the data are not unified31,32.”
From scPerturb: harmonized single-cell perturbation data (2024) · cites this paper as [32]
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“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 [65]
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“Analysis of data for shRNA modulated PTK2 knockdown showed that, unlike any of the KRAS wild‐type cancer cell lines, all of the KRAS‐mutant‐dependent cell lines exhibited growth modulation related to PTK2 expression (Figure S2B, Supporting Information).”
From Focal Adhesion Kinase (FAK) Inhibition Synergizes with KRAS G12C Inhibitors in Treating Cancer through the Regulation of the FAK–YAP Signaling (2021) · cites this paper as [22]
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Metadata
- Authors
- Tsherniak, A., Vazquez, F., Montgomery, P. G., Weir, B. A., Kryukov, G., Cowley, G. S., Gill, S., Harrington, W. F., Pantel, S., Krill-Burger, J. M., Meyers, R. M., Ali, L., Goodale, A., Lee, Y., Jiang, G., Hsiao, J., Gerath, W. F. J., Howell, S., Merkel, E., Ghandi, M., Garraway, L. A., Root, D. E., Golub, T. R., Boehm, J. S., & Hahn, W. C.
- Affiliations
- Broad Institute (US)
- Corresponding author
- Hahn, William C.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2017-07
- Volume
- 170
- Issue
- 3
- Pages
- 564-576.e16
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC5667678
- OpenAlex
- W2741508285
- Cited by
- 3,276
- References
- 57
- Citations by year
- 2026: 464 · 2025: 678 · 2024: 521 · 2023: 406 · 2022: 342 · 2021: 334 · 2020: 244 · 2019: 171 · 2018: 91 · 2017: 22
- FWCI
- 49.24
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (U01 CA176058)
- NIH ICBP (U54 CA112962)
- The Carlos Slim Foundation
- Slim Initiative for Genomic Medicine
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- cancer dependency, dependency map, loss-of-function screen, Demeter, gene essentiality, prediction model, gene expression biomarkers, DNA hypermethylation, UBB, UBC, drug target prioritization, epithelial tumors, cancer cell lines
- MeSH terms
- Humans, Neoplasms, Software, Ubiquitin, RNA Interference, Cell Line, Tumor
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