Evidence map›Paper›PMID 42149869›Full record

ArticlePloS one2026

SuperSelective PCR primers for determining cis/trans configurations of mutations within the same gene.

Diana Yaneth Vargas, Fred Russell Kramer

Abstract read
In one paragraph

Article in PloS one, 2026. 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
–field-weighted citation impact
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.

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

2 authors.

Diana Yaneth VargasPublic Health Research Institute, New Jersey Medical School, Rutgers University, Newark, New Jersey, United States of America.
Fred Russell KramerPublic Health Research Institute, New Jersey Medical School, Rutgers University, Newark, New Jersey, United States of America.ORCID https://orcid.org/0000-0002-7471-831X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In non-small cell lung cancer, the choice of an effective targeted therapy often depends on the presence of a somatic mutation that alters an amino acid in a key protein. However, if an additional somatic mutation occurs in the same mutant gene, causing an additional amino acid substitution to occur in that protein, the targeted therapy can become ineffective. A PCR assay has now been developed that utilizes two different SuperSelective primers, one primer for the amplification of the DNA strand containing the original somatic mutation, and a second primer for the amplification of the DNA strand containing the additional somatic mutation. Exponential amplification only occurs if these two somatic mutations occur in cis on the DNA molecule present in the same sister chromosome, and does not occur at all if the two different somatic mutations occur in trans on different DNA molecules in two different sister chromosomes. Significantly, if only one of these two mutations is present, amplification does not occur, thereby ensuring that the assay specifically detects the coexistence of both target mutations being present on the same DNA strand. This assay (demonstrated utilizing EGFR exon 20 mutations T790M and C797S) is extraordinarily sensitive, enabling the early substitution of a more effective therapy if the two mutations occur in a cis configuration. Moreover, these SuperSelective PCR assays can utilize DNA fragments isolated from noninvasive liquid biopsy samples, and they can be carried out on widely available spectrofluorometric thermal cyclers.

Indexed as

Carcinoma, Non-Small-Cell LungDNA PrimersLung NeoplasmsMutationPolymerase Chain ReactionDNA Mutational AnalysisErbB ReceptorsExonsHumansDNA PrimersErbB Receptors

Identifiers

PMID42149869
PMCPMC13183233

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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.