Evidence map›Paper›PMID 28357075›Full record

ArticleBiomedical reports2017

Rebecca J Stoll, Grace R Thompson, Mohammad D Samy, George Blanck

Open access · bronzeAbstract read
In one paragraph

Article in Biomedical reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 21% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

4 authors at 1 institution in 1 country.

Rebecca J StollDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA.
Grace R ThompsonDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA.
Mohammad D SamyDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA.
George BlanckDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA; Immunology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
University of South Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human mutagenesis is largely random, thus large coding regions, simply on the basis of probability, represent relatively large mutagenesis targets. Thus, we considered the possibility that large cytoskeletal-protein related coding regions (CPCRs), including extra-cellular matrix (ECM) coding regions, would have systemic nucleotide variants that are not present in common SNP databases. Presumably, such variants arose recently in development or in recent, preceding generations. Using matched breast cancer and blood-derived normal datasets from the cancer genome atlas, CPCR single nucleotide variants (SNVs) not present in the All SNPs(142) or 1000 Genomes databases were identified. Using the Protein Variation Effect Analyzer internet-based tool, it was discovered that apparent, systemic mutations (not shared among others in the analysis group) in the CPCRs, represented numerous deleterious amino acid substitutions. However, no such deleterious variants were identified among the (cancer blood-matched) variants shared by other members of the analysis group. These data indicate that private SNVs, which potentially have a medical consequence, occur

Indexed as

breast cancercytoskeleton-related protein coding regionsgenetic testingprivate variantssingle nucleotide variantssystemic mutationsThe Cancer Genome Atlas

Identifiers

PMID28357075
PMCPMC5351269
OpenAlexW2560543917

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.