ArticleNature genetics2016
Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations.
Article in Nature genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
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Who cites it
56 citing papers in PubMed.
- Molecular basis of UV lesion binding and repair inhibition by ETS-family transcription factors.Nucleic acids research · 2026Article
- Molecular basis of UV lesion binding and repair inhibition by ETS-family transcription factors.bioRxiv : the preprint server for biology · 2026Article
- Regulatory non-coding somatic mutations as drivers of neuroblastoma.British journal of cancer · 2025Article
- Melanoma-specific mutation hotspots in distal, non-coding, promoter-interacting regions implicate novel candidate driver genes.British journal of cancer · 2024Article
- Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers.Science (New York, N.Y.) · 2024Article
- Oncogenic Enhancers in Leukemia.Blood cancer discovery · 2024Review
- Article
- Transcription Factor-Centric Approach to Identify Non-Recurring Putative Regulatory Drivers in Cancer.Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- ) · 2022Article
- AutoCoV: tracking the early spread of COVID-19 in terms of the spatial and temporal patterns from embedding space by K-mer based deep learning.BMC bioinformatics · 2022Article
- Theranostic Interpolation of Genomic Instability in Breast Cancer.International journal of molecular sciences · 2022Review
- Extracting phylogenetic dimensions of coevolution reveals hidden functional signals.Scientific reports · 2022Article
- A Network-Guided Approach to Discover Phytochemical-Based Anticancer Therapy: Targeting MARK4 for Hepatocellular Carcinoma.Frontiers in oncology · 2022Article
- A pan-cancer landscape of somatic mutations in non-unique regions of the human genome.Nature biotechnology · 2021Article
- Non-coding driver mutations in human cancer.Nature reviews. Cancer · 2021Review
- Scanning window analysis of non-coding regions within normal-tumor whole-genome sequence samples.Briefings in bioinformatics · 2021Article
- Approaches to Identify and Characterise the Post-Transcriptional Roles of lncRNAs in Cancer.Non-coding RNA · 2021Review
- Comprehensive characterization of amino acid positions in protein structures reveals molecular effect of missense variants.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Prediction of genome-wide effects of single nucleotide variants on transcription factor binding.Scientific reports · 2020Article
- A comparative analysis of chromatin accessibility in cattle, pig, and mouse tissues.BMC genomics · 2020Article
- Integrated structural and evolutionary analysis reveals common mechanisms underlying adaptive evolution in mammals.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Cancer sequencing studies have primarily identified cancer driver genes by the accumulation of protein-altering mutations. An improved method would be annotation independent, sensitive to unknown distributions of functions within proteins and inclusive of noncoding drivers. We employed density-based clustering methods in 21 tumor types to detect variably sized significantly mutated regions (SMRs). SMRs reveal recurrent alterations across a spectrum of coding and noncoding elements, including transcription factor binding sites and untranslated regions mutated in up to ∼ 15% of specific tumor types. SMRs demonstrate spatial clustering of alterations in molecular domains and at interfaces, often with associated changes in signaling. Mutation frequencies in SMRs demonstrate that distinct protein regions are differentially mutated across tumor types, as exemplified by a linker region of PIK3CA in which biophysical simulations suggest that mutations affect regulatory interactions. The functional diversity of SMRs underscores both the varied mechanisms of oncogenic misregulation and the advantage of functionally agnostic driver identification.
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