Evidence map›Paper›PMID 26052455›Full record

ArticleSultan Qaboos University medical journal2015

Predicting the Pathogenic Potential of BRCA1 and BRCA2 Gene Variants Identified in Clinical Genetic Testing.

Clare Brookes, Stella Lai, Elaine Doherty, Donald R Love

Open access · diamondAbstract read
In one paragraph

Article in Sultan Qaboos University medical journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.7field-weighted citation impact, top 24% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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.

Clare BrookesDepartment of Diagnostic Genetics, LabPLUS, Auckland City Hospital, Auckland, New Zealand.
Stella LaiDepartment of Diagnostic Genetics, LabPLUS, Auckland City Hospital, Auckland, New Zealand.
Elaine DohertyDepartment of Diagnostic Genetics, LabPLUS, Auckland City Hospital, Auckland, New Zealand.
Donald R LoveDepartment of Diagnostic Genetics, LabPLUS, Auckland City Hospital, Auckland, New Zealand.
Auckland City Hospital · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMissense variants are very commonly detected when screening for mutations in the BRCA1 and BRCA2 genes. Pathogenic mutations in the BRCA1 and BRCA2 genes lead to an increased risk of developing breast, ovarian, prostate and/or pancreatic cancer. This study aimed to assess the predictive capability of in silico programmes and mutation databases in assisting diagnostic laboratories to determine the pathogenicity of sequence-detectable mutations.

methodsBetween July 2011 and April 2013, an analysis was undertaken of 13 missense BRCA gene variants that had been detected in patients referred to the Genetic Health Services New Zealand (Northern Hub) for BRCA gene analysis. The analysis involved the use of 13 in silico protein prediction programmes, two in silico transcript analysis programmes and the examination of three BRCA gene databases.

resultsIn most of the variants, the analysis showed different in silico interpretations. This illustrates the interpretation challenges faced by diagnostic laboratories.

conclusionUnfortunately, when using online mutation databases and carrying out in silico analyses, there is significant discordance in the classification of some missense variants in the BRCA genes. This discordance leads to complexities in interpreting and reporting these variants in a clinical context. The authors have developed a simple procedure for analysing variants; however, those of unknown significance largely remain unknown. As a consequence, the clinical value of some reports may be negligible.

Indexed as

Genes, BRCA1Genes, BRCA2HBOC SyndromeIn Silico

Identifiers

PMID26052455
PMCPMC4450785
OpenAlexW1591454212

What OpenQuestion holds

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Registered trials

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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.