Evidence map›Paper›PMID 30881500›Full record

ArticleOncology letters2019

Isolation of circulating tumor cells and detection of EGFR mutations in patients with non-small-cell lung cancer.

Qi Zhang, Jingying Nong, Jinghui Wang, Zhuohong Yan, Ling Yi, Xin Gao, Zhidong Liu, Hongtao Zhang, Shucai Zhang

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 18% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
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  8. CirculatingInternational journal of molecular sciences · 2022
    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

9 authors at 2 institutions in 1 country.

Qi ZhangDepartment of Oncology, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, P.R. China.
Jingying NongDepartment of Oncology, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, P.R. China.
Jinghui WangDepartment of Oncology, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, P.R. China.
Zhuohong YanDepartment of Central Laboratory, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, P.R. China.
Ling YiDepartment of Central Laboratory, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, P.R. China.
Xin GaoDepartment of Central Laboratory, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, P.R. China.
Zhidong LiuDepartment of Thoracic Surgery, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, P.R. China.
Hongtao ZhangDepartment of Central Laboratory, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, P.R. China.
Shucai ZhangDepartment of Oncology, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, P.R. China.
Beijing Chest Hospital · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the present study was to develop a procedure for the isolation of circulating tumor cells (CTCs), and to evaluate its application in the detection of epidermal growth factor receptor (EGFR) mutations, and potential heterogeneity in patients with non-small-cell lung cancer (NSCLC). Peripheral blood samples were collected from 91 patients with lung cancer, 10 patients with benign disease and 10 healthy volunteers. CTCs were enriched by positive immunomagnetic separation, detected by immunocytochemistry, and processed for single-cell capture. Pure CTC DNA was amplified, and the EGFR gene was analyzed using the amplification refractory mutation system (ARMS) and digital polymerase chain reaction (dPCR). The CTC capture rate in patients with lung cancer was 61.5% (56/91), whereas no CTCs were detected in patients with benign lung disease or in healthy volunteers. The CTC-positive detection rates were 69.3% (52/75) and 25.0% (4/16) in patients with TNM stage III and IV disease, respectively. Markedly more CTCs were captured from patients with small-cell lung cancer compared with patients with other types of cancer. In patients who were positive for EGFR mutations, the detection rate of these mutations was low (16.67%, 2/12), at the single CTC level. The sensitivity increased as the number of CTCs per sample increased. A total of four patients displayed consistent detection of EGFR mutations at the 10-cell level, and one patient exhibited a clear, inconsistent and rare mutation (G719×) between CTCs. A simplified technique for isolating CTCs from blood was established, though multiple CTCs were required to sensitively detect mutations in these cells. The detection of EGFR mutations in CTCs and tissue specimens was generally homogeneous, and therefore, the CTC-level mutation analysis may potentially contribute to the discovery of heterogeneous mutations.

Indexed as

circulating tumor cellsepidermal growth factor receptor mutationhomogeneitynon-small-cell lung cancer

Identifiers

PMID30881500
PMCPMC6403494
OpenAlexW2913134945

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.