ArticleNature biotechnology2022
Genome-wide mapping of somatic mutation rates uncovers drivers of cancer.
Article in Nature biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed.
- Determinants of mutation susceptibility along the genome are largely invariant across human tissues.Genome biology · 2026Article
- Deciphering the genetic underlying causes of sex differences in multiple myeloma incidence and mortality.HGG advances · 2026Article
- The aging genome exhibits organized vulnerability to somatic mutations.bioRxiv : the preprint server for biology · 2026Article
- Topographical archetypes of somatic mutagenesis in cancer.bioRxiv : the preprint server for biology · 2026Article
- Constrained Diffusion as a Paradigm for Evolution.bioRxiv : the preprint server for biology · 2026Article
- Diagnosis of Lung Diseases in the Artificial Intelligence Era.International journal of molecular sciences · 2026Article
- DeepGene-BC: Deep Learning-Based Breast Cancer Subtype Prediction via Somatic Point Mutation Profiles.Cancers · 2026Article
- Integrative Genomic and AI Approaches to Lung Cancer and Implications for Disease Prevention in Former Smokers.International journal of molecular sciences · 2026Review
- AI-engineered multifunctional nanoplatforms: synergistically bridging precision diagnosis and intelligent therapy in next-generation oncology.Journal of nanobiotechnology · 2025Review
- Nucleotide Substitution Biases in Related Cancer Driver Genes.International journal of molecular sciences · 2025Article
- Precision Oncology: Current Landscape, Emerging Trends, Challenges, and Future Perspectives.Cells · 2025Review
- A review of the use of tumour DNA methylation for breast cancer subtyping and prediction of outcomes.Clinical epigenetics · 2025Review
- Progress and challenges of artificial intelligence in lung cancer clinical translation.NPJ precision oncology · 2025Review
- Cancer gene identification from RNA variant allelic frequencies using RVdriver.Genome biology · 2025Article
- Genomic landscape of multiple myeloma and its precursor conditions.Nature genetics · 2025Article
- Element-specific estimation of background mutation rates in whole cancer genomes through transfer learning.NPJ precision oncology · 2025Article
- Decoding the functional impact of the cancer genome through protein-protein interactions.Nature reviews. Cancer · 2025Review
- A commonly inherited human PCSK9 germline variant drives breast cancer metastasis via LRP1 receptor.Cell · 2025Article
- Single-Cell RNA Sequencing Integrated with Bulk-RNA Sequencing Analysis Reveals Prognostic Signatures Based on PANoptosis in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025Article
- Personalized medicine in triple-negative breast cancer: combining neoantigen vaccination and genomic profiling in a patient undergoing neoadjuvant chemotherapy.Frontiers in oncology · 2025Article
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Funding
Abstract
Identification of cancer driver mutations that confer a proliferative advantage is central to understanding cancer; however, searches have often been limited to protein-coding sequences and specific non-coding elements (for example, promoters) because of the challenge of modeling the highly variable somatic mutation rates observed across tumor genomes. Here we present Dig, a method to search for driver elements and mutations anywhere in the genome. We use deep neural networks to map cancer-specific mutation rates genome-wide at kilobase-scale resolution. These estimates are then refined to search for evidence of driver mutations under positive selection throughout the genome by comparing observed to expected mutation counts. We mapped mutation rates for 37 cancer types and applied these maps to identify putative drivers within intronic cryptic splice regions, 5' untranslated regions and infrequently mutated genes. Our high-resolution mutation rate maps, available for web-based exploration, are a resource to enable driver discovery genome-wide.
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