ArticlePloS one2017
Prominent features of the amino acid mutation landscape in cancer.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Exploring alternative approaches to precision medicine through genomics and artificial intelligence - a systematic review.Frontiers in medicine · 2023Pooled it
- FGFR4-associated APOBEC3 mutagenesis characterizes HER2-enriched subtype of human breast cancer.British journal of cancer · 2026Article
- Five dominant amino acid substitution signatures shape tumour immunity.Molecular systems biology · 2026Article
- Understanding exceptional response: The role of MINDY1 SNP in CDK4/6 inhibitor therapy for ERHGG advances · 2026Article
- Across deserts and Andes: a genetic exploration of GlyCam-1 in domestic camelids.BMC veterinary research · 2025Article
- Molecular and structural characterization of a novel β-hemoglobinopathy caused by in Cis β-globin mutations in a Thai individual.Scientific reports · 2025Article
- Biophysical Properties of Somatic Cancer Mutations in the S4 Transmembrane Segment of the Human Voltage-Gated Proton Channel hHBiomolecules · 2025Article
- DNA-binding proteins from MBD through ZF to BEN: recognition of cytosine methylation status by one arginine with two conformations.Nucleic acids research · 2024Article
- Chemoproteogenomic stratification of the missense variant cysteinome.Nature communications · 2024Article
- Evolution of pH-sensitive transcription termination inProceedings of the National Academy of Sciences of the United States of America · 2024Article
- Arginines of the CGN codon family are Achilles' heels of cancer genes.Scientific reports · 2024Article
- Evolution of pH-sensitive transcription termination during adaptation to repeated long-term starvation.bioRxiv : the preprint server for biology · 2024Article
- Computational investigation of missense somatic mutations in cancer and potential links to pH-dependence and proteostasis.PloS one · 2024Article
- Multi-omic stratification of the missense variant cysteinome.bioRxiv : the preprint server for biology · 2023Article
- Quantitative differentiation of benign and misfolded glaucoma-causing myocilin variants on the basis of protein thermal stability.Disease models & mechanisms · 2023Article
- Proteoglycans: a common portal for SARS-CoV-2 and extracellular vesicle uptake.American journal of physiology. Cell physiology · 2023Review
- Mediating and maintaining methylation while minimizing mutation: Recent advances on mammalian DNA methyltransferases.Current opinion in structural biology · 2022Review
- Differential ETS1 binding to T:G mismatches within a CpG dinucleotide contributes to C-to-T somatic mutation rate of the IDH2 hotspot at codon Arg140.DNA repair · 2022Article
- Arginine Depletion in Human Cancers.Cancers · 2021Article
- The structure-based cancer-related single amino acid variation prediction.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Cancer can be viewed as a set of different diseases with distinctions based on tissue origin, driver mutations, and genetic signatures. Accordingly, each of these distinctions have been used to classify cancer subtypes and to reveal common features. Here, we present a different analysis of cancer based on amino acid mutation signatures. Non-negative Matrix Factorization and principal component analysis of 29 cancers revealed six amino acid mutation signatures, including four signatures that were dominated by either arginine to histidine (Arg>His) or glutamate to lysine (Glu>Lys) mutations. Sample-level analyses reveal that while some cancers are heterogeneous, others are largely dominated by one type of mutation. Using a non-overlapping set of samples from the COSMIC somatic mutation database, we validate five of six mutation signatures, including signatures with prominent arginine to histidine (Arg>His) or glutamate to lysine (Glu>Lys) mutations. This suggests that our classification of cancers based on amino acid mutation patterns may provide avenues of inquiry pertaining to specific protein mutations that may generate novel insights into cancer biology.
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