ArticleeLife2021
shinyDepMap, a tool to identify targetable cancer genes and their functional connections from Cancer Dependency Map data.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
58 citing papers in PubMed.
- Essentiality-driven prediction of anticancer drug responses in preclinical and clinical contexts.iScience · 2026Article
- Phytochemical Characterization ofFood science & nutrition · 2026Article
- Using cancer profiles to identify synthetic lethal therapeutic targets and predictive biomarkers in cancer gene dependency data.Bioinformatics (Oxford, England) · 2026Article
- GEMap: A comprehensive gene essentiality map for drug discovery.Acta pharmaceutica Sinica. B · 2026Article
- A Chemical-Genetic Interaction Matrix Reveals Drug Mechanism and Genetic Architecture.bioRxiv : the preprint server for biology · 2026Article
- Olfactory receptors as tumor suppressors in cutaneous T-cell lymphoma via p38γ pathway modulation.Blood neoplasia · 2025Article
- Integrative Multi-Omics Analyses Reveal Mechanisms of Resistance to Hsp90β-Selective Inhibition.Cancers · 2025Article
- Integrating the secretome and interactome to identify novel biomarkers and therapeutic targets in colorectal cancer.Cell communication and signaling : CCS · 2025Article
- mCell · 2025Article
- ENO1-BACE2-mediated LDLR cleavage promotes liver cancer progression by remodelling cholesterol metabolism.Journal of molecular cell biology · 2025Article
- Identification and characterization of survival-dependent genes in esophageal cancer via the DepMap database: unraveling their association with immune infiltration.Discover oncology · 2025Article
- IDENTIFICATION OF DISEASE-SPECIFIC VULNERABILITY STATES AT THE SINGLE-CELL LEVEL.bioRxiv : the preprint server for biology · 2025Article
- NAA10 (N-Alpha-Acetyltransferase 10): A Multifunctional Regulator in Development, Disease, and Cancer.Cells · 2025Review
- Noncanonical PRC1.1 targets BTG2 to retain cyclin gene expression and cell growth in neuroblastoma.Oncogenesis · 2025Article
- WNK1 signalling regulates amino acid transport and mTORC1 activity to sustain acute myeloid leukaemia growth.Nature communications · 2025Article
- Genomic landscape of diffuse glioma revealed by whole genome sequencing.Nature communications · 2025Article
- The off‑target effect of loratadine triggers autophagy‑mediated apoptosis in lung adenocarcinoma cells by deactivating JNK, p38, and STAT3 signaling through both PP2A‑dependent and independent pathways.International journal of molecular medicine · 2025Article
- Article
- The present and future of the Cancer Dependency Map.Nature reviews. Cancer · 2025Review
- Evaluation of Spliceosome Protein SmD2 as a Potential Target for Cancer Therapy.International journal of molecular sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Individual cancers rely on distinct essential genes for their survival. The Cancer Dependency Map (DepMap) is an ongoing project to uncover these gene dependencies in hundreds of cancer cell lines. To make this drug discovery resource more accessible to the scientific community, we built an easy-to-use browser, shinyDepMap (https://labsyspharm.shinyapps.io/depmap). shinyDepMap combines CRISPR and shRNA data to determine, for each gene, the growth reduction caused by knockout/knockdown and the selectivity of this effect across cell lines. The tool also clusters genes with similar dependencies, revealing functional relationships. shinyDepMap can be used to (1) predict the efficacy and selectivity of drugs targeting particular genes; (2) identify maximally sensitive cell lines for testing a drug; (3) target hop, that is, navigate from an undruggable protein with the desired selectivity profile, such as an activated oncogene, to more druggable targets with a similar profile; and (4) identify novel pathways driving cancer cell growth and survival.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.