ReviewNature reviews. Drug discovery2013
Objective assessment of cancer genes for drug discovery.
Review in Nature reviews. Drug discovery, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
65 citing papers in PubMed.
- Plant‑derived natural products alleviate dexamethasone‑induced skeletal muscle atrophy by modulating FoxO (Review).International journal of molecular medicine · 2026Review
- AI accelerate the identification of druggable targets by 3D structures of proteins and compounds.NPJ precision oncology · 2026Review
- Old drugs, new challenges: reassigning drugs for cancer therapies.Cellular & molecular biology letters · 2025Review
- Thio-2 Inhibits Key Signaling Pathways Required for the Development and Progression of Castration-resistant Prostate Cancer.Molecular cancer therapeutics · 2024Article
- Deep Learning Techniques to Characterize theBiomedicines · 2024Article
- Precision Oncology Comes of Age: Designing Best-in-Class Small Molecules by Integrating Two Decades of Advances in Chemistry, Target Biology, and Data Science.Cancer discovery · 2023Article
- The evidence for repurposing anti-epileptic drugs to target cancer.Molecular biology reports · 2023Review
- canSAR: update to the cancer translational research and drug discovery knowledgebase.Nucleic acids research · 2023Article
- Data-driven analysis and druggability assessment methods to accelerate the identification of novel cancer targets.Computational and structural biotechnology journal · 2023Review
- mTORC2 Is the Major Second Layer Kinase Negatively Regulating FOXO3 Activity.Molecules (Basel, Switzerland) · 2022Article
- A benchmark study of deep learning-based multi-omics data fusion methods for cancer.Genome biology · 2022Article
- SALL4 Oncogenic Function in Cancers: Mechanisms and Therapeutic Relevance.International journal of molecular sciences · 2022Review
- Repurposing clinical drugs is a promising strategy to discover drugs against Zika virus infection.Frontiers of medicine · 2021Review
- canSAR: update to the cancer translational research and drug discovery knowledgebase.Nucleic acids research · 2021Article
- Therapeutic strategies targeting FOXO transcription factors.Nature reviews. Drug discovery · 2021Review
- Path to Clonal Theranostics in Luminal Breast Cancers.Frontiers in oncology · 2021Article
- SystematicFrontiers in chemistry · 2021Article
- Solution structure of the Hop TPR2A domain and investigation of target druggability by NMR, biochemical and in silico approaches.Scientific reports · 2020Article
- PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas.Genome biology · 2020Article
- Overcoming cancer therapeutic bottleneck by drug repurposing.Signal transduction and targeted therapy · 2020Review
5 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Selecting the best targets is a key challenge for drug discovery, and achieving this effectively, efficiently and systematically is particularly important for prioritizing candidates from the sizeable lists of potential therapeutic targets that are now emerging from large-scale multi-omics initiatives, such as those in oncology. Here, we describe an objective, systematic, multifaceted computational assessment of biological and chemical space that can be applied to any human gene set to prioritize targets for therapeutic exploration. We use this approach to evaluate an exemplar set of 479 cancer-associated genes, reveal the tension between biological relevance and chemical tractability, and describe major gaps in available knowledge that could be addressed to aid objective decision-making. We also propose drug repurposing opportunities and identify potentially druggable cancer-associated proteins that have been poorly explored with regard to the discovery of small-molecule modulators, despite their biological relevance.
Indexed as
Identifiers
23274470What OpenQuestion holds
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.