Evidence map›Paper›PMID 31387567›Full record

ArticleBMC cancer2019

Molecular features of lung adenocarcinoma in young patients.

Zhen Chen, Xiao Teng, Jing Zhang, Ke Huang, Qian Shen, He Cao, Huisong Luo, Yanting Yuan, Xiaodong Teng

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.6field-weighted citation impact, top 9% 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

19 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Primary lung cancer in children and adolescents.Journal of cancer research and clinical oncology · 2024
    Article
  6. Article
  7. Article
  8. Analysis of mScientific reports · 2022
    Article
  9. Review
  10. Article
  11. Article
  12. Molecular Pathology of Lung Cancer.Cold Spring Harbor perspectives in medicine · 2022
    Review
  13. Article
  14. Article
  15. Article
  16. Clinical characteristics of patients withTranslational cancer research · 2020
    Article
  17. Article
  18. Article
  19. Article
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 3 institutions in 1 country.

Zhen ChenDepartment of Pathology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, China.
Xiao TengDepartment of Thoracic Surgery, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, China.
Jing ZhangDepartment of Pathology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, China.
Ke HuangDepartment of Pathology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, China.
Qian ShenDepartment of Respiratory Diseases, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, China.
He CaoDepartment of Respiratory Diseases, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, China.
Huisong LuoSinglera Genomics Inc., Shanghai, 200000, China.
Yanting YuanSinglera Genomics Inc., Shanghai, 200000, China.
Xiaodong TengDepartment of Pathology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, China. teng1102069@zju.edu.cn.ORCID http://orcid.org/0000-0003-3717-3370
Zhejiang University · CNFirst Affiliated Hospital Zhejiang University · CNSinotech Genomics (China) · CN

Funding

Medicine and Health Project of Zhejiang Province 2018KY061Natural Science Foundation of Zhejiang Province LQ19H160038
6 · The paper itself

Abstract

backgroundLung cancer in young patients is rare and has unique clinicopathological features. However, the molecular features of lung cancer in these patients are unclear. In this study, we aimed to describe the molecular features and outcomes of lung adenocarcinoma in patients aged ≤35 years.

methodsA total of 89 patients aged ≤35 years with pathologically diagnosed lung adenocarcinoma were retrospectively evaluated. Mutations in 59 cancer-associated genes and fusions of ALK and ROS1 were analyzed to understand the molecular features of young patients with lung adenocarcinoma. The clinicopathological characteristics and prognosis of each patient were reviewed.

resultsOf the 89 young patients, 25 (28.1%) were male, 9 (10.1%) were smokers, and the median age was 32 years (range, 18-35 years). The authors analyzed 59 genes and a total of 6 mutations and 2 fusion genes were detected. These genes were distributed among 60 patients, 12 of which had two or more mutations. ERBB2 mutations were most common (24.7%), followed by EGFR mutation (21.3%), ALK fusion (16.9%), TP53 mutation (9.0%), BRAF mutation (3.4%), PIK3CA mutation (1.1%), CTNNB1 mutation (1.1%), and ROS1 fusion (1.1%). EGFR, ERBB2, and TP53 mutations, gene abnormalities, and ALK fusions all had significant correlations with histopathological differentiation (P < 0.01). ALK fusions and EGFR mutations conferred a significantly worse prognosis than did ERBB2 mutations and tumors that contained no mutations or fusions (P < 0.01).

conclusionsThe molecular features of lung adenocarcinoma in young patients are different from those of common adenocarcinoma, and the main driver genes are closely correlated with tumor differentiation and prognosis.

Indexed as

Biomarkers, TumorAdenocarcinoma of LungAdolescentAdultAge FactorsFemaleGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansMaleNeoplasm GradingNeoplasm StagingPrognosisProto-Oncogene ProteinsRisk FactorsYoung AdultBiomarkers, TumorProto-Oncogene ProteinsLung adenocarcinomaMolecular featuresNext-generation sequencingYoung age

Identifiers

PMID31387567
PMCPMC6685166
OpenAlexW2965062304

What OpenQuestion holds

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LicenceCC BY
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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.