ArticleNature genetics2016
Protein-structure-guided discovery of functional mutations across 19 cancer types.
Article in Nature genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 98 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
98 citing papers in PubMed, 150 citations in OpenAlex.
- Article
- The structural context of mutations in proteins predicts their effect on antibiotic resistance.eLife · 2026Article
- Interpreting human genetic variation at atomic resolution.Nature genetics · 2026Review
- Article
- Gene duplication is associated with gene diversification and potential neofunctionalization in lung cancer evolution.Genome research · 2026Article
- Multi-State Structural Genomics Enables Large-Scale, Mechanistic, and Context-Specific Classification of ABCC6 Genetic Variants Implicated in Calcification Diseases.International journal of molecular sciences · 2026Article
- Oncodrive3D: fast and accurate detection of structural clusters of somatic mutations under positive selection.Nucleic acids research · 2025Article
- Article
- Deep learning prioritizes cancer mutations that alter protein nucleocytoplasmic shuttling to drive tumorigenesis.Nature communications · 2025Article
- A multiscale functional map of somatic mutations in cancer integrating protein structure and network topology.Nature communications · 2025Article
- Pan-cancer analysis reveals age-associated genetic alterations in protein domains.American journal of human genetics · 2025Article
- CIBRA identifies genomic alterations with a system-wide impact on tumor biology.Bioinformatics (Oxford, England) · 2024Article
- A multiscale functional map of somatic mutations in cancer integrating protein structure and network topology.bioRxiv : the preprint server for biology · 2024Article
- Prediction of Deleterious Single Amino Acid Polymorphisms with a Consensus Holdout Sampler.Current genomics · 2024Article
- Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks.Briefings in bioinformatics · 2024Review
- Recurring EPHB1 mutations in human cancers alter receptor signalling and compartmentalisation of colorectal cancer cells.Cell communication and signaling : CCS · 2023Article
- A review of genetic variant databases and machine learning tools for predicting the pathogenicity of breast cancer.Briefings in bioinformatics · 2023Review
- A fully 3D-printed versatile tumor-on-a-chip allows multi-drug screening and correlation with clinical outcomes for personalized medicine.Communications biology · 2023Article
- Actionability classification of variants of unknown significance correlates with functional effect.NPJ precision oncology · 2023Article
- Pan-cancer clinical impact of latent drivers from double mutations.Communications biology · 2023Article
38 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
19 authors at 2 institutions in 1 country.
Funding
Abstract
Local concentrations of mutations are well known in human cancers. However, their three-dimensional spatial relationships in the encoded protein have yet to be systematically explored. We developed a computational tool, HotSpot3D, to identify such spatial hotspots (clusters) and to interpret the potential function of variants within them. We applied HotSpot3D to >4,400 TCGA tumors across 19 cancer types, discovering >6,000 intra- and intermolecular clusters, some of which showed tumor and/or tissue specificity. In addition, we identified 369 rare mutations in genes including TP53, PTEN, VHL, EGFR, and FBXW7 and 99 medium-recurrence mutations in genes such as RUNX1, MTOR, CA3, PI3, and PTPN11, all mapping within clusters having potential functional implications. As a proof of concept, we validated our predictions in EGFR using high-throughput phosphorylation data and cell-line-based experimental evaluation. Finally, mutation-drug cluster and network analysis predicted over 800 promising candidates for druggable mutations, raising new possibilities for designing personalized treatments for patients carrying specific mutations.
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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.