Evidence map›Paper›PMID 25813150›Full record

ArticleTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2015

Development of a gLCR-based KRAS mutation detection approach and its comparison with other screening methods.

Stefan Jenner, Dieter Techel

Abstract read
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In one paragraph

Article in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2015. 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
0.3field-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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Review
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

2 authors at 1 institution in 1 country.

Stefan JennerDivision of Molecular Pathology, Department of Pathology, Katharinen Hospital Stuttgart, Kriegsbergstr. 60, 70374, Stuttgart, Germany, s.jenner@klinikum-stuttgart.de.
Dieter Techel
Katharinenhospital · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A gapped ligase chain reaction (gLCR)-based technique was developed and tested on clinical formalin-fixed, paraffin-embedded (FFPE) tissues from colorectal cancer patients. The technique was designed to detect low-level KRAS codon 12 or 13 mutations or confirming doubtful results gained by less sensitive KRAS screening techniques. The gLCR approach was compared with mutation screening techniques commonly used in routine diagnostics regarding sensitivity and specificity. The herein described monoplex gLCR technique is a useful and powerful tool for detecting low-level KRAS codon 12 and 13 mutations in a vast majority of wild type DNA. The gLCR has the capacity to detect one mutated allele in an excess of at least one million wild type alleles (0.0001 %) and is therefore an ideal technique for confirming doubtful KRAS mutation screening results obtained by other techniques. The variance of the gLCRs signal amplitude was very low and is showing a high reproducibility with constant sensitivity even at higher dilutions. The financial effort and the handling time for this technique are low and comparable to a standard cycle sequencing reaction. Additionally, the gLCR technique is easy extendable for the detection of many other clinical relevant mutation hotspots.

Indexed as

DNA Mutational AnalysisPolymerase Chain ReactionAgedAged, 80 and overCodonColorectal NeoplasmsFemaleFormaldehydeHumansMaleMiddle AgedMutationParaffin EmbeddingProto-Oncogene ProteinsProto-Oncogene Proteins p21(ras)ras ProteinsCodonFormaldehydeKRAS protein, humanProto-Oncogene ProteinsProto-Oncogene Proteins p21(ras)ras Proteins

Identifiers

PMID25813150
OpenAlexW2048272866

What OpenQuestion holds

Textmetadata
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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.