ArticleActa pharmaceutica Sinica. B2026
GEMap: A comprehensive gene essentiality map for drug discovery.
Article in Acta pharmaceutica Sinica. B, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Integrated metabolomics and machine learning identify predictive biomarkers via SHAP analysis for sintilimab-induced rash in lung cancer patients.Frontiers in pharmacology · 2026Article
- Traditional Chinese medicine as a potential barrier-oriented sensitization strategy for immune checkpoint blockade in microsatellite-stable colorectal cancer: from resistance mechanisms to translational validation.Frontiers in immunology · 2026Review
- Integrating chemokine signatures and multi-omic biomarkers to predict immunotherapy response in non-small cell lung cancer: a comprehensive narrative review.Frontiers in oncology · 2026Review
- Exploring traditional Chinese medicine to enhance the efficacy and reduce toxicity of immunotherapy for non-small cell lung cancer from the perspective of "spleen deficiency": a trial protocol for mechanism and clinical evidence.Frontiers in oncology · 2026Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene essentiality (synonymous with dependency) mapping reveals therapeutic vulnerabilities for intractable oncogenes, yet integrated platforms bridging CRISPR functional genomics with drug discovery remain limited. To address this gap, we developed GEMap, A Gene Essentiality-Guided Platform for Drug Discovery, by combining genome-wide CRISPR-Cas9 essentiality profiles (1912 screens across 1135 cancer cell lines) with multi-omics annotations, drug profiles and drug targets information (20,000+ compounds). GEMap can be used to (1) explore multimodal gene data (Dependency/Expression/CNV/Mutation) across cell lines and tissues; (2) prioritize context-specific therapeutic targets by quantifying differential genetic dependencies in molecularly stratified cancers, such as
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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.