Evidence map›Paper›PMID 33061436›Full record

ArticleOncoTargets and therapy2020

Molecular Analysis of Oncogenic Mutations in Resected Margins by Next-Generation Sequencing Predicts Relapse in Non-Small Cell Lung Cancer Patients.

Weitian Wei, Xingliang Li, Mengmeng Song, Changchun Wang

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2020. 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
0.1field-weighted citation impact, top 46% 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, 2 citations in OpenAlex.

  1. Article
  2. Review
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 2 institutions in 1 country.

Weitian WeiInstitute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou 310022, People's Republic of China.
Xingliang LiDepartment of Thoracic Disease Diagnosis and Treatment Center, Zhejiang Rongjun Hospital, Jiaxing, Zhejiang 314000, People's Republic of China.
Mengmeng SongGeneplus-Beijing Institute, Beijing 102206, People's Republic of China.
Changchun WangInstitute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou 310022, People's Republic of China.
Chinese Academy of Sciences · CNState Council of the People's Republic of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the genetic mutations in both tumor and marginal tissues in patients with non-small cell lung cancer (NSCLC), and to evaluate the potential prognostic value in patients with margins gene positive.

methodsNext-generation sequencing (NGS) technique was used to detect genetic mutation in tumor and marginal tissues of the bronchus in 88 patients with NSCLC. Correlation of genetic mutations with pathology, lymph node metastasis, disease-free survival and overall survival was analyzed.

resultsOf the 88 patients, 83 cases (94.3%) had gene mutations in the tumor samples and 12 cases (13.6%) had genetic alterations in their margins. Most of the gene mutations detected were cancer drivers. Six common driver genes between tumor and marginal tissues were identified, including

conclusionThese findings identify the presence of oncogenic alterations in microscopically negative margins in NSCLC patients associated with elevated risk of relapse and shorter survival time. Thus, examination of microscopically negative margins by NGS represents a valuable approach to predict the clinical outcome of NSCLC patients.

Indexed as

gene mutationlung cancernext-generation sequencingsurgical margin

Identifiers

PMID33061436
PMCPMC7526010
OpenAlexW3088884694

What OpenQuestion holds

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LicenceCC BY-NC
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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.