Evidence map›Paper›PMID 25204323›Full record

ArticleJournal of experimental & clinical cancer research : CR2014

Design and validation of an oligonucleotide microarray for the detection of genomic rearrangements associated with common hereditary cancer syndromes.

Debora Mancini-DiNardo, Thaddeus Judkins, Nick Woolstenhulme, Collin Burton, Jeremy Schoenberger, Matthew Ryder, Adam Murray, Natalia Gutin, Aaron Theisen, Jayson Holladay and 4 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in Journal of experimental & clinical cancer research : CR, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact, top 87% of its field
1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 5 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

14 authors at 1 institution in 1 country.

Debora Mancini-DiNardo
Thaddeus Judkins
Nick Woolstenhulme
Collin Burton
Jeremy Schoenberger
Matthew Ryder
Adam Murray
Natalia Gutin
Aaron Theisen
Jayson Holladay
Jonathan Craft
Christopher Arnell
Kelsey Moyes
Benjamin Roa
Myriad Genetics · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundConventional Sanger sequencing reliably detects the majority of genetic mutations associated with hereditary cancers, such as single-base changes and small insertions or deletions. However, detection of genomic rearrangements, such as large deletions and duplications, requires special technologies. Microarray analysis has been successfully used to detect large rearrangements (LRs) in genetic disorders.

methodsWe designed and validated a high-density oligonucleotide microarray for the detection of gene-level genomic rearrangements associated with hereditary breast and ovarian cancer (HBOC), Lynch, and polyposis syndromes. The microarray consisted of probes corresponding to the exons and flanking introns of BRCA1 and BRCA2 (≈1,700) and Lynch syndrome/polyposis genes MLH1, MSH2, MSH6, APC, MUTYH, and EPCAM (≈2,200). We validated the microarray with 990 samples previously tested for LR status in BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, MUTYH, or EPCAM. Microarray results were 100% concordant with previous results in the validation studies. Subsequently, clinical microarray analysis was performed on samples from patients with a high likelihood of HBOC mutations (13,124), Lynch syndrome mutations (18,498), and polyposis syndrome mutations (2,739) to determine the proportion of LRs.

resultsOur results demonstrate that LRs constitute a substantial proportion of genetic mutations found in patients referred for hereditary cancer genetic testing.

conclusionThe use of microarray comparative genomic hybridization (CGH) for the detection of LRs is well-suited as an adjunct technology for both single syndrome (by Sanger sequencing analysis) and extended gene panel testing by next generation sequencing analysis. Genetic testing strategies using microarray analysis will help identify additional patients carrying LRs, who are predisposed to various hereditary cancers.

Indexed as

GenomicsOligonucleotide Array Sequence AnalysisTranslocation, GeneticExonsHumansMutationMutS Homolog 2 ProteinNeoplastic Syndromes, HereditaryReproducibility of ResultsMutS Homolog 2 Protein

Identifiers

PMID25204323
PMCPMC4174268
OpenAlexW2140325519

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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.