Evidence map›Paper›PMID 25918867›Full record

ArticleGenetic testing and molecular biomarkers2015

A mutation-sensitive switch assay to detect five clinically significant epidermal growth factor receptor mutations.

Bin Liu, Lin Zhou, Qian Wang, Kai Li

Open access · greenAbstract read
In one paragraph

Article in Genetic testing and molecular biomarkers, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. CRISPR/Cas9 for overcoming drug resistance in solid tumors.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2020
    Review
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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.

Bin LiuDepartment of Molecular Diagnostics and Biopharmaceutics, College of Pharmaceutical Science, Soochow University , Suzhou, China .
Lin ZhouDepartment of Molecular Diagnostics and Biopharmaceutics, College of Pharmaceutical Science, Soochow University , Suzhou, China .
Qian WangDepartment of Molecular Diagnostics and Biopharmaceutics, College of Pharmaceutical Science, Soochow University , Suzhou, China .
Kai LiDepartment of Molecular Diagnostics and Biopharmaceutics, College of Pharmaceutical Science, Soochow University , Suzhou, China .
Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epidermal growth factor receptor (EGFR) mutations can affect the therapeutic efficacy of drugs used to treat nonsmall-cell lung cancer (NSCLC). We aimed to develop methods to detect five common EGFR somatic mutations in tumor tissues from NSCLC patients by using a nanoscale mutation-sensitive switch consisting of a high-fidelity polymerase and phosphorothioate-modified allele-specific primers. The five clinically significant EGFR mutations examined here are S768I, T790M, L858R, and 15- and 18-bp deletion mutations in exon 19. Our assays showed sensitivities of 100 copies and specificities of more than three log scales for matched templates relative to mismatched templates by routine polymerase chain reaction (PCR), real-time PCR, and multiplex PCR. This assay would be superior to DNA sequencing in situations where mutant DNA is not abundant.

Indexed as

Genes, SwitchSequence DeletionBiological AssayCarcinoma, Non-Small-Cell LungCase-Control StudiesDNA PrimersErbB ReceptorsExonsGenes, erbB-1Genetic Carrier ScreeningHumansLung NeoplasmsReal-Time Polymerase Chain ReactionDNA PrimersEGFR protein, humanErbB Receptors

Identifiers

PMID25918867
PMCPMC4487682
OpenAlexW2050684050

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.