Evidence map›Paper›PMID 24838940›Full record

ArticleBreast cancer research and treatment2014

Microsatellite genotyping reveals a signature in breast cancer exomes.

L J McIver, N C Fonville, E Karunasena, H R Garner

Open access · hybridAbstract read
In one paragraph

Article in Breast cancer research and treatment, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

20 citing papers in PubMed, 32 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

4 authors at 1 institution in 1 country.

L J McIverVirginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg, VA, 24061, USA.
N C Fonville
E Karunasena
H R Garner
Virginia Tech · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic instability at microsatellite loci is a hallmark of many cancers, including breast cancer. However, much of the genomic variation and many of the hereditary components responsible for breast cancer remain undetected. We hypothesized that variation at microsatellites could provide additional genomic markers for breast cancer risk assessment. A total of 1,345 germline and tumor DNA samples from individuals diagnosed with breast cancer, exome sequenced as part of The Cancer Genome Atlas, were analyzed for microsatellite variation. The comparison group for our analysis, representing healthy individuals, consisted of 249 females which were exome sequenced as part of the 1,000 Genomes Project. We applied our microsatellite-based genotyping pipeline to identify 55 microsatellite loci that can distinguish between the germline of individuals diagnosed with breast cancer and healthy individuals with a sensitivity of 88.4 % and a specificity of 77.1 %. Further, we identified additional microsatellite loci that are potentially useful for distinguishing between breast cancer subtypes, revealing a possible fifth subtype. These findings are of clinical interest as possible risk diagnostics and reveal genes that may be of potential therapeutic value, including genes previously not associated with breast cancer.

Indexed as

Microsatellite InstabilityBreast NeoplasmsDNA, NeoplasmExomeFemaleGene FrequencyGenotypeHumansMaleMicrosatellite RepeatsMutationDNA, Neoplasm

Identifiers

PMID24838940
PMCPMC4031393
OpenAlexW2073212579

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.