Evidence map›Paper›PMID 19644022›Full record

ArticleThe Journal of molecular diagnostics : JMD2009

Evaluation of 13q14 status in multiple myeloma by digital single nucleotide polymorphism technology.

Katy Hanlon, Lorna W Harries, Sian Ellard, Claudius E Rudin

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of molecular diagnostics : JMD, 2009. 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
0.3field-weighted citation impact, top 38% 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, 3 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.

Katy HanlonInstitute of Biomedical and Clinical Sciences, Peninsula Medical School, Barrack Road, Exeter, EX2 5DW.
Lorna W Harries
Sian Ellard
Claudius E Rudin
Royal Devon & Exeter NHS Foundation Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chromosome 13q deletions are common in multiple myeloma and other cancers, demonstrating the importance of this region in tumorigenesis. We used a novel single nucleotide polymorphism (SNP)-based technique, digital SNP (dSNP), to identify loss of heterozygosity (LOH) at chromosome 13q in paraffin-embedded bone marrow biopsies from 22 patients with multiple myeloma. We analyzed heterozygous SNPs at 13q for the presence of allelic imbalances and examined the results by sequential probability ratio analysis. Where possible, dSNP results were confirmed by fluorescence in situ hybridization. Using dSNP, we identified 13q LOH in 16/18 (89%) (95% Confidence Interval; 65%, 99%) patients without the need for neoplastic cell enrichment. In 8/16 (50%) cases, either partial or interstitial patterns of LOH were observed. Both fluorescence in situ hybridization and dSNP data proved concordant in just 3/9 cases. Five of the six discrepancies showed LOH by dSNP occurring beyond the boundaries of the fluorescence in situ hybridization probes. Our findings show that dSNP represents a useful technique for the analysis of LOH in archival tissue with minimal infiltration of neoplastic cells. The high-resolution screening afforded by the dSNP technology allowed for the identification of complex chromosomal rearrangements, resulting in either partial or interstitial LOH. Digital SNP represents an attractive approach for the investigation of tumors not suitable for genomic-array analysis.

Indexed as

Chromosomes, Human, Pair 13HumansIn Situ Hybridization, FluorescenceLoss of HeterozygosityMultiple MyelomaPolymorphism, Single Nucleotide

Identifiers

PMID19644022
PMCPMC2729843
OpenAlexW2169020669

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.