Dataset Information

Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types.

ABSTRACT: Somatic synonymous mutations are one of the most frequent genetic variants occurring in the coding region of cancer genomes, while their contributions to cancer development remain largely unknown. To assess whether synonymous mutations involved in post-transcriptional regulation contribute to the genetic etiology of cancers, we collected whole exome data from 8,320 patients across 22 cancer types. By employing our developed algorithm, PIVar, we identified a total of 22,948 posttranscriptionally impaired synonymous SNVs (pisSNVs) spanning 2,042 genes. In addition, 35 RNA binding proteins impacted by these identified pisSNVs were significantly enriched. Remarkably, we discovered markedly elevated ratio of somatic pisSNVs across all 22 cancer types, and a high pisSNV ratio was associated with worse patient survival in five cancer types. Intriguing, several well-established cancer genes, including PTEN, RB1 and PIK3CA, appeared to contribute to tumorigenesis at both protein function and posttranscriptional regulation levels, whereas some pisSNV-hosted genes, including UBR4, EP400 and INTS1, exerted their function during carcinogenesis mainly via posttranscriptional mechanisms. Moreover, we predicted three drugs associated with two pisSNVs, and numerous compounds associated with expression signature of pisSNV-hosted genes. Our study reveals the prevalence and clinical relevance of pisSNVs in cancers, and emphasizes the importance of considering posttranscriptional impaired synonymous mutations in cancer biology.

SUBMITTER: Teng H

PROVIDER: S-EPMC7026592 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types.

Teng Huajing H Wei Wenqing W Li Qinglan Q Xue Meiying M Shi Xiaohui X Li Xianfeng X Mao Fengbiao F Sun Zhongsheng Z

Nucleic acids research 20200201 3

Somatic synonymous mutations are one of the most frequent genetic variants occurring in the coding region of cancer genomes, while their contributions to cancer development remain largely unknown. To assess whether synonymous mutations involved in post-transcriptional regulation contribute to the genetic etiology of cancers, we collected whole exome data from 8,320 patients across 22 cancer types. By employing our developed algorithm, PIVar, we identified a total of 22,948 posttranscriptionally ...[more]

PMID: 31950163

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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.

Project description:A massive amount of somatic mutations has been cataloged in large-scale projects such as The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium projects. The majority of the somatic mutations found in tumor genomes are neutral 'passenger' rather than damaging "driver" mutations. Now, understanding their biological consequences and prioritizing them for druggable targets are urgently needed. Thanks to the rapid advances in structural genomics technologies (e.g. X-ray), large-scale protein structural data has now been made available, providing critical information for deciphering functional roles of mutations in cancer and prioritizing those alterations that may mediate drug binding at the atom resolution and, as such, be druggable targets. We hypothesized that mutations at protein-ligand binding-site residues are likely to be druggable targets. Thus, to prioritize druggable mutations, we developed SGDriver, a structural genomics-based method incorporating the somatic missense mutations into protein-ligand binding-site residues using a Bayes inference statistical framework. We applied SGDriver to 746,631 missense mutations observed in 4997 tumor-normal pairs across 16 cancer types from The Cancer Genome Atlas. SGDriver detected 14,471 potential druggable mutations in 2091 proteins (including 1,516 recurrently mutated proteins) across 3558 cancer genomes (71.2%), and further identified 298 proteins harboring mutations that were significantly enriched at protein-ligand binding-site residues (adjusted p value < 0.05). The identified proteins are significantly enriched in both oncoproteins and tumor suppressors. The follow-up drug-target network analysis suggested 98 known and 126 repurposed druggable anticancer targets (e.g. SPOP and NR3C1). Furthermore, our integrative analysis indicated that 13% of patients might benefit from current targeted therapy, and this -proportion would increase to 31% when considering drug repositioning. This study provides a testable strategy for prioritizing druggable mutations in precision cancer medicine.

Dataset Information

Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types.

Publications

Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types.

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