ArticleNucleic acids research2017
Exploring background mutational processes to decipher cancer genetic heterogeneity.
Article in Nucleic acids research, 2017. 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, 84 citations in OpenAlex.
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- Somatic mutations in 3929 HPV positive cervical cells associated with infection outcome and HPV type.Nature communications · 2024Article
- AI-derived comparative assessment of the performance of pathogenicity prediction tools on missense variants of breast cancer genes.Human genomics · 2024Article
- DNA polymerase ε and δ variants drive mutagenesis in polypurine tracts in human tumors.Cell reports · 2024Article
- Cancer driver mutations: predictions and reality.Trends in molecular medicine · 2023Review
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- NOS3 and CTH gene mutations as new molecular markers for detection of lung adenocarcinoma.PeerJ · 2023Article
- VariBench, new variation benchmark categories and data sets.Frontiers in bioinformatics · 2023Article
- The Mutational Landscape of Cancer's Vulnerability to Ionizing Radiation.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022Article
- Analysis of low-level somatic mosaicism reveals stage and tissue-specific mutational features in human development.PLoS genetics · 2022Article
- New Drug Development and Clinical Trial Design by Applying Genomic Information Management.Pharmaceutics · 2022Review
- A phylogenetic approach to study the evolution of somatic mutational processes in cancer.Communications biology · 2022Article
- Exome sequencing of hepatocellular carcinoma in lemurs identifies potential cancer drivers: A pilot study.Evolution, medicine, and public health · 2022Article
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- Mutational Signatures: From Methods to Mechanisms.Annual review of biomedical data science · 2021Article
- 2-kupl: mapping-free variant detection from DNA-seq data of matched samples.BMC bioinformatics · 2021Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Much remains unknown about the progression and heterogeneity of mutational processes in different cancers and their diagnostic and clinical potential. A growing body of evidence supports mutation rate dependence on the local DNA sequence context for various types of mutations. We propose several tools for the analysis of cancer context-dependent mutations, which are implemented in an online computational framework MutaGene. The framework explores DNA context-dependent mutational patterns and underlying somatic cancer mutagenesis, analyzes mutational profiles of cancer samples, identifies the combinations of underlying mutagenic processes including those related to infidelity of DNA replication and repair machinery, and various other endogenous and exogenous mutagenic factors. As a result, the combination of mutagenic processes can be identified in any query sample with subsequent comparison to mutational profiles derived from malignant and benign samples. In addition, mutagen or cancer-specific mutational background models are applied to calculate expected DNA and protein site mutability to decouple relative contributions of mutagenesis and selection in carcinogenesis, thus elucidating the site-specific driving events in cancer. MutaGene is freely available at https://www.ncbi.nlm.nih.gov/projects/mutagene/.
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