Evidence map›Paper›PMID 32193503›Full record

ArticleCommunications biology2020

A miRNA-based diagnostic model predicts resectable lung cancer in humans with high accuracy.

Keisuke Asakura, Tsukasa Kadota, Juntaro Matsuzaki, Yukihiro Yoshida, Yusuke Yamamoto, Kazuo Nakagawa, Satoko Takizawa, Yoshiaki Aoki, Eiji Nakamura, Junichiro Miura and 4 more

Abstract readValidation Study
In one paragraph

Article in Communications biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 2 pooled it
–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

69 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Exosomes as Emerging Nanocarriers for Targeted Cancer Therapy.International journal of nanomedicine · 2026
    Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. MicroRNAs as Biomarkers and Therapeutic Targets in Female Infertility.International journal of molecular sciences · 2024
    Review

9 more citing papers are in PubMed but not listed here.

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

14 authors.

Keisuke Asakura *Department of Thoracic Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Tsukasa Kadota *Division of Molecular and Cellular Medicine, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.ORCID http://orcid.org/0000-0002-9533-7241
Juntaro MatsuzakiDivision of Molecular and Cellular Medicine, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.ORCID http://orcid.org/0000-0002-3204-5049
Yukihiro YoshidaDepartment of Thoracic Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.ORCID http://orcid.org/0000-0002-6494-2318
Yusuke YamamotoDivision of Molecular and Cellular Medicine, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Kazuo NakagawaDepartment of Thoracic Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Satoko TakizawaDivision of Molecular and Cellular Medicine, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Yoshiaki AokiDynacom Co., Ltd., World Business Garden E25, 2-6-1 Nakase, Mihama-ku, Chiba city, Chiba, 261-7125, Japan.
Eiji NakamuraDynacom Co., Ltd., World Business Garden E25, 2-6-1 Nakase, Mihama-ku, Chiba city, Chiba, 261-7125, Japan.
Junichiro MiuraDynacom Co., Ltd., World Business Garden E25, 2-6-1 Nakase, Mihama-ku, Chiba city, Chiba, 261-7125, Japan.
Hiromi SakamotoDepartment of Biobank and Tissue Resources, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
Ken KatoDepartment of Gastrointestinal Medical Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.ORCID http://orcid.org/0000-0002-1733-5072
Shun-Ichi WatanabeDepartment of Thoracic Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Takahiro OchiyaDivision of Molecular and Cellular Medicine, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan. tochiya@ncc.go.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer, the leading cause of cancer death worldwide, is most frequently detected through imaging tests. In this study, we investigated serum microRNAs (miRNAs) as a possible early screening tool for resectable lung cancer. First, we used serum samples from participants with and without lung cancer to comprehensively create 2588 miRNAs profiles; next, we established a diagnostic model based on the combined expression levels of two miRNAs (miR-1268b and miR-6075) in the discovery set (208 lung cancer patients and 208 non-cancer participants). The model displayed a sensitivity of 99% and specificity of 99% in the validation set (1358 patients and 1970 non-cancer participants) and exhibited high sensitivity regardless of histological type and pathological TNM stage of the cancer. Moreover, the diagnostic index markedly decreased after lung cancer resection. Thus, the model we developed has the potential to markedly improve screening for resectable lung cancer.

Indexed as

Early Detection of CancerGene Expression ProfilingTranscriptomeAgedBiomarkers, TumorCase-Control StudiesCirculating MicroRNAClinical Decision-MakingDatabases, GeneticFemaleHumansLung NeoplasmsMaleMicroRNAsMiddle AgedNeoplasm StagingBiomarkers, TumorCirculating MicroRNAMicroRNAs

Identifiers

PMID32193503
PMCPMC7081195

What OpenQuestion holds

Textmetadata
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.