Evidence map›Paper›PMID 38472960›Full record

ArticleDiagnostics (Basel, Switzerland)2024

A Highly Sensitive XNA-Based RT-qPCR Assay for the Identification of ALK, RET, and ROS1 Fusions in Lung Cancer.

Bongyong Lee, Andrew Chern, Andrew Y Fu, Aiguo Zhang, Michael Y Sha

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2024. 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
0.4field-weighted citation impact, top 40% 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, 1 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

5 authors.

Bongyong LeeDiaCarta Inc., 4385 Hopyard Rd., Suite 100, Pleasanton, CA 94588, USA.ORCID 0000-0002-6370-393X
Andrew ChernDiaCarta Inc., 4385 Hopyard Rd., Suite 100, Pleasanton, CA 94588, USA.
Andrew Y FuDiaCarta Inc., 4385 Hopyard Rd., Suite 100, Pleasanton, CA 94588, USA.
Aiguo ZhangDiaCarta Inc., 4385 Hopyard Rd., Suite 100, Pleasanton, CA 94588, USA.
Michael Y ShaDiaCarta Inc., 4385 Hopyard Rd., Suite 100, Pleasanton, CA 94588, USA.ORCID 0000-0002-4552-6079

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is often triggered by genetic alterations that result in the expression of oncogenic tyrosine kinases. Specifically, ALK, RET, and ROS1 chimeric receptor tyrosine kinases are observed in approximately 5-7%, 1-2%, and 1-2% of NSCLC patients, respectively. The presence of these fusion genes determines the response to tyrosine kinase inhibitors. Thus, accurate detection of these gene fusions is essential in cancer research and precision oncology. To address this need, we have developed a multiplexed RT-qPCR assay using xeno nucleic acid (XNA) molecular clamping technology to detect lung cancer fusions. This assay can quantitatively detect thirteen ALK, seven ROS1, and seven RET gene fusions in FFPE samples. The sensitivity of the assay was established at a limit of detection of 50 copies of the synthetic template. Our assay has successfully identified all fusion transcripts using 50 ng of RNA from both reference FFPE samples and cell lines. After validation, a total of 77 lung cancer patient FFPE samples were tested, demonstrating the effectiveness of the XNA-based fusion gene assay with clinical samples. Importantly, this assay is adaptable to highly degraded RNA samples with low input amounts. Future steps involve expanding the testing to include a broader range of clinical samples as well as cell-free RNAs to further validate its applicability and reliability.

Indexed as

ALKfusionlung cancerRETROS1RT-qPCRXNA

Identifiers

PMID38472960
PMCPMC10930897
OpenAlexW4392155723

What OpenQuestion holds

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LicenceCC BY
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.