Evidence map›Paper›PMID 33435996›Full record

ArticleCancer cell international2021

Exosome-based detection of EGFR T790M in plasma and pleural fluid of prospectively enrolled non-small cell lung cancer patients after first-line tyrosine kinase inhibitor therapy.

Yoonjung Kim, Saeam Shin, Kyung-A Lee

Abstract read
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Article in Cancer cell international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Review
  2. A novel nanotechnology-based strategy using CNT-FeJournal, genetic engineering & biotechnology · 2026
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  15. Droplet Digital PCR as a Molecular Tool for the Detection of theBalkan journal of medical genetics : BJMG · 2023
    Article
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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

3 authors.

Yoonjung KimDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Saeam ShinDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Kyung-A LeeDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea. KAL1119@yuhs.ac.ORCID http://orcid.org/0000-0001-5320-6705

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe exosomal nucleic acid (exoNA) from the plasma and pleural fluid can potentially provide means to identify genomic changes in non-small cell lung cancer (NSCLC) patients who develop resistance to targeted epidermal growth factor receptor (EGFR) inhibitor therapy.

methodsWe compared the performance of the following tools to detect EGFR mutations in 54 plasma samples and 13 pleural fluid using cfDNA, combined TNA (exoTNA + cfTNA), or total cellular DNA: droplet digital PCR (ddPCR), the Cobas® EGFR Mutation Test v2 (Cobas) and NGS with Oncomine Pan-Cancer Cell-Free Assay.

resultsAll three of these platforms demonstrated 100% specificity in the detection of EGFR mutations in the plasma. In the detection of an activating mutation (exon 19 deletion and L858R), Cobas using cfDNA, ddPCR using combined TNA, and NGS using combined TNA showed a sensitivity of 93, 95.3, and 93.8%, respectively. For T790M mutation detection, the Cobas, ddPCR, and NGS showed a sensitivity of 64.7, 88.2, and 93.3%, respectively. Pleural fluid analysis revealed enrichment of the T790M mutant copies in the exosomes. ddPCR using exoTNA showed higher sensitivity than did total cellular DNA from the pleural fluid.

conclusionThese results demonstrated that combined TNA in the plasma and exoTNA in the pleural fluid can be used to evaluate low-abundant EGFR mutant copies in NSCLC.

Indexed as

Circulating tumor DNAEpidermal growth factor receptorExtracellular vesiclesLiquid biopsyNon-small cell lung cancerTyrosine kinase inhibitors

Identifiers

PMID33435996
PMCPMC7802208

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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.