Evidence map›Paper›PMID 31815613›Full record

ArticleBMC medical genetics2019

An analysis of mutational signatures of synonymous mutations across 15 cancer types.

Yannan Bin, Xiaojuan Wang, Le Zhao, Pengbo Wen, Junfeng Xia

Abstract read
In one paragraph

Article in BMC medical genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Whole Mitochondrial Genome Sequencing Analysis of Canine Testicular Tumours.International journal of molecular sciences · 2024
    Article
  3. Article
  4. Article
  5. Synonymous Variants of Uncertain Silence.International journal of molecular sciences · 2023
    Article
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  7. Article
  8. Article
  9. Article
  10. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yannan BinInstitutes of Physical Science and Information Technology, School of Computer Science and Technology, Anhui University, Hefei, 230601, Anhui, China.
Xiaojuan WangInstitutes of Physical Science and Information Technology, School of Computer Science and Technology, Anhui University, Hefei, 230601, Anhui, China.
Le ZhaoInstitutes of Physical Science and Information Technology, School of Computer Science and Technology, Anhui University, Hefei, 230601, Anhui, China.
Pengbo WenInstitutes of Physical Science and Information Technology, School of Computer Science and Technology, Anhui University, Hefei, 230601, Anhui, China.
Junfeng XiaInstitutes of Physical Science and Information Technology, School of Computer Science and Technology, Anhui University, Hefei, 230601, Anhui, China. jfxia@ahu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSynonymous 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.

resultsWe 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.

conclusionsWe illustrated the preferences of cancer associated synonymous mutations, especially hotspots, and laid the groundwork for understanding the synonymous mutations act as drivers in cancer.

Indexed as

MutationAmino AcidsDatasets as TopicHumansMutation RateNeoplasmsAmino AcidsCancerDriverHotspotSynonymous mutations

Identifiers

PMID31815613
PMCPMC6900878

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.