ReviewNature reviews. Cancer2020
A compendium of mutational cancer driver genes.
Review in Nature reviews. Cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 776 papers, 2 of them syntheses that pooled it.
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
776 citing papers in PubMed, 2 syntheses or guidelines pooled it, 1,316 citations in OpenAlex.
- Influence of KRAS mutation subtypes on response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: meta-analysis.BJS open · 2026Pooled it
- A meta-analysis identifies driver genes and characterizes the molecular epidemiology of colorectal cancer.Scientific reports · 2026Pooled it
- Heterogeneity in cancer: molecular mechanisms and therapeutic strategies.Signal transduction and targeted therapy · 2026Review
- Neoantigen cancer vaccines for gastrointestinal tumors: opportunities and challenges.MedScience · 2026Review
- YAP1 induces hepatocellular carcinoma via DNA demethylation rather than by canonical driver gene mutations.Communications biology · 2026Article
- Cancer-driver-agnostic targeting of amplified surface proteins identifies MPZL1 for selective CAR-T cell therapy.Nature communications · 2026Article
- TMO-Net+: An Enhanced Tumor Multi-Omics Pre-Trained Network for Multi-Task Learning in Oncology.Genes · 2026Article
- Article
- Commentary beyond the ATP site: Cryo-EM views of allosteric PI3KActa pharmaceutica Sinica. B · 2026Article
- Evaluation of BoostDM, a somatic variant prediction tool, for the interpretation of germline variants in hereditary cancer genes.European journal of human genetics : EJHG · 2026Article
- Lipid droplet-associated gene signatures classify metabolic subtypes and identify PLIN3 as a key driver in hepatocellular carcinoma.Genes & diseases · 2026Article
- Enabling Variant Proteogenomic Assay Development Through a Peptide Target Selection Pipeline and Web Application.Proteomics · 2026Article
- Article
- Deep molecular profiling of lung neuroendocrine tumours and supra-carcinoids.Molecular cancer · 2026Article
- Target-biology and interactome-derived signatures predict target-level associations with safety-related drug attrition.Scientific reports · 2026Article
- Pathway potency in methylation altered network reveals lung cancer branching evolution and hallmarks.iScience · 2026Article
- GNG12 overexpression inhibits triple-negative breast cancer cell proliferation, migration, and invasion.Scientific reports · 2026Article
- A Novel Cancer Driver Genes Identification Method Based on Self-Supervised Dual Masked Graph Autoencoder.Interdisciplinary sciences, computational life sciences · 2026Article
- Genome-wide annotation of human multi-nucleotide variants reveals widespread functional differences from single nucleotide variants.Nature communications · 2026Article
- Gene mutant dosage is associated with prognosis and metastatic tropism in 60,000 clinical cancer samples.Nature genetics · 2026Article
716 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
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.
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What Socratic 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 Socratic graph.