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A pan-cancer analysis of synonymous mutations.

ABSTRACT: Synonymous mutations have been viewed as silent mutations, since they only affect the DNA and mRNA, but not the amino acid sequence of the resulting protein. Nonetheless, recent studies suggest their significant impact on splicing, RNA stability, RNA folding, translation or co-translational protein folding. Hence, we compile 659194 synonymous mutations found in human cancer and characterize their properties. We provide the user-friendly, comprehensive resource for synonymous mutations in cancer, SynMICdb ( http://SynMICdb.dkfz.de ), which also contains orthogonal information about gene annotation, recurrence, mutation loads, cancer association, conservation, alternative events, impact on mRNA structure and a SynMICdb score. Notably, synonymous and missense mutations are depleted at the 5'-end of the coding sequence as well as at the ends of internal exons independent of mutational signatures. For patient-derived synonymous mutations in the oncogene KRAS, we indicate that single point mutations can have a relevant impact on expression as well as on mRNA secondary structure.

SUBMITTER: Sharma Y

PROVIDER: S-EPMC6562042 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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A pan-cancer analysis of synonymous mutations.

Sharma Yogita Y Miladi Milad M Dukare Sandeep S Boulay Karine K Caudron-Herger Maiwen M Groß Matthias M Backofen Rolf R Diederichs Sven S

Nature communications 20190612 1

Synonymous mutations have been viewed as silent mutations, since they only affect the DNA and mRNA, but not the amino acid sequence of the resulting protein. Nonetheless, recent studies suggest their significant impact on splicing, RNA stability, RNA folding, translation or co-translational protein folding. Hence, we compile 659194 synonymous mutations found in human cancer and characterize their properties. We provide the user-friendly, comprehensive resource for synonymous mutations in cancer, ...[more]

PMID: 31189880

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Project description:BACKGROUND:Synonymous mutations have been identified to play important roles in cancer development, although they do not modify the protein sequences. However, relatively little research has specifically delineated the functionality of synonymous mutations in cancer. RESULTS:We investigated the nucleotide-based and amino acid-based features of synonymous mutations across 15 cancer types from The Cancer Genome Atlas (TCGA), and revealed novel driver candidates by identifying hotspot mutations. Firstly, synonymous mutations were analyzed between TCGA and 1000 Genomes Project at nucleotide and amino acid levels. We found that C:G → T:A transitions were the most frequent single-base substitutions, and leucine underwent the largest number of synonymous mutations in TCGA due to prevalent C → T transition, which induced the transformation between optimal and non-optimal codons. Next, 97 synonymous hotspot mutations in 86 genes were nominated as candidate drivers with potential cancer risk by considering the mutational rates across different sequence contexts. We observed that non-CpG-island GC transition sequence context was positively selected across most of cancer types, and different sequence contexts under which hotspot mutations occur could be significance for genetic differences and functional features. We also found that the hotspots were more conserved than neutral mutations of hotspot-mutation-containing-genes and frequently happened at leucine. In addition, we mapped hotspots, neutral and non-hotspot mutations of hotspot-mutation-containing-genes to their respective protein domains and found ion transport domain was the most frequent one, which could mediate the cell interaction and had relevant implication for tumor therapy. And the signatures of synonymous hotspots were qualitatively similar with those of harmful missense variants. CONCLUSIONS:We illustrated the preferences of cancer associated synonymous mutations, especially hotspots, and laid the groundwork for understanding the synonymous mutations act as drivers in cancer.

Dataset Information

A pan-cancer analysis of synonymous mutations.

Publications

A pan-cancer analysis of synonymous mutations.

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