Evidence map›Paper›PMID 28176830›Full record

ArticleScientific reports2017

Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids.

Yang Pan, Cheng Yan, Yu Hu, Yu Fan, Qing Pan, Quan Wan, John Torcivia-Rodriguez, Raja Mazumder

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 50% of its field
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

4 citing papers in PubMed, 7 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Yang PanThe Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
Cheng YanThe Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
Yu HuThe Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
Yu FanThe Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
Qing PanThe Department of Statistics, The George Washington University, Washington, DC 20037, United States of America.
Quan WanThe Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
John Torcivia-RodriguezThe Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
Raja MazumderThe Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
George Washington University · USWashington University Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single nucleotide variations (SNVs) can result in loss or gain of protein functional sites. We analyzed the effects of SNVs on enzyme active sites, ligand binding sites, and various types of post translational modification (PTM) sites. We found that, for most types of protein functional sites, the SNV pattern differs between germline and somatic mutations as well as between synonymous and non-synonymous mutations. From a total of 51,138 protein functional site affecting SNVs (pfsSNVs), a pan-cancer analysis revealed 142 somatic pfsSNVs in five or more cancer types. By leveraging patient information for somatic pfsSNVs, we identified 17 loss of functional site SNVs and 60 gain of functional site SNVs which are significantly enriched in patients with specific cancer types. Of the key pfsSNVs identified in our analysis above, we highlight 132 key pfsSNVs within 17 genes that are found in well-established cancer associated gene lists. For illustrating how key pfsSNVs can be prioritized further, we provide a use case where we performed survival analysis showing that a loss of phosphorylation site pfsSNV at position 105 in MEF2A is significantly associated with decreased pancreatic cancer patient survival rate. These 132 pfsSNVs can be used in developing genetic testing pipelines.

Indexed as

Gene Expression Regulation, NeoplasticGerm-Line MutationPolymorphism, Single NucleotideProtein Processing, Post-TranslationalAcetylationCatalytic DomainDatabases, GeneticGene Expression ProfilingGene OntologyGlycosylationHumansMethylationMolecular Sequence AnnotationNeoplasm ProteinsNeoplasmsPhosphorylationNeoplasm Proteins

Identifiers

PMID28176830
PMCPMC5296879
OpenAlexW2587635981

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.