Evidence map›Paper›PMID 28454243›Full record

ArticleOncology letters2017

Exosomal microRNA in plasma as a non-invasive biomarker for the recurrence of non-small cell lung cancer.

Hitoshi Dejima, Hisae Iinuma, Rie Kanaoka, Noriyuki Matsutani, Masafumi Kawamura

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
97citing papers in PubMed, 5 pooled it
7.3field-weighted citation impact, top 2% 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

97 citing papers in PubMed, 5 syntheses or guidelines pooled it, 166 citations in OpenAlex.

  1. The diagnostic and prognostic value of exosomal microRNAs in lung cancer: a systematic review.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024
    Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Review
  7. Significance of EVs in Prostate Cancer Bone Metastases.International journal of molecular sciences · 2025
    Review
  8. Article
  9. Review
  10. Article
  11. Relationship between exosomes and cancer: formation, diagnosis, and treatment.International journal of biological sciences · 2025
    Review
  12. Harmonising cellular conversations: decoding the vital roles of extracellular vesicles in respiratory system intercellular communications.European respiratory review : an official journal of the European Respiratory Society · 2024
    Review
  13. Review
  14. Article
  15. Review
  16. Review
  17. Review
  18. Review
  19. Review
  20. Review

37 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

5 authors at 1 institution in 1 country.

Hitoshi DejimaDepartment of Surgery, Teikyo University School of Medicine, Tokyo 173-0003, Japan.
Hisae IinumaDepartment of Surgery, Teikyo University School of Medicine, Tokyo 173-0003, Japan.
Rie KanaokaDepartment of Surgery, Teikyo University School of Medicine, Tokyo 173-0003, Japan.
Noriyuki MatsutaniDepartment of Surgery, Teikyo University School of Medicine, Tokyo 173-0003, Japan.
Masafumi KawamuraDepartment of Surgery, Teikyo University School of Medicine, Tokyo 173-0003, Japan.
Teikyo University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predictive biomarkers for the recurrence of non-small cell lung cancer (NSCLC) in patients who have received curative resection are important for cancer treatment. The functional microRNAs (miRNAs/miRs) in the exosomes of plasma and serum samples are of interest as stable and non-invasive biomarkers for recurrence in cancer patients. The aim of the present study was to clarify the usefulness of plasma exosomal miRNAs as biomarkers for the prediction of recurrence in NSCLC following curative resection. First, microarray-based expression profiling of miRNAs derived from exosomes in the plasma of 6 patients was employed to identify a biomarker that distinguishes between patients with and without NSCLC recurrence. In the miRNA microarray analyses, the exosomal miR-21 and miR-4257 levels of the NSCLC patients showed marked upregulation in those individuals with recurrence compared with those without recurrence and healthy individuals. These two miRNAs were thus selected as recurrence-specific biomarkers and their potential was evaluated in a separate cohort of 195 NSCLC patients. In comparison to the levels in 30 healthy individuals, exosomal miR-21 and miR-4257 levels showed a significant increase in the NSCLC patients (P<0.01). When evaluating the clinicopathological significance of these miRNAs, exosomal miR-21 showed a significant association with tumor size and tumor-node-metastasis (TNM) stage (P<0.05). Exosomal miR-4257 showed a significant association with histological type, lymphatic invasion and TNM stage (P<0.05). The disease-free survival (DFS) rates of high exosomal miR-21 patients were significantly worse than those of low exosomal miR-21 patients (P<0.05), and the DFS rates of patients with high exosomal miR-4257 levels were significantly worse than those with low exosomal miR-4257 levels (P<0.01). In the Cox multivariate analysis, plasma exosomal miR-21 and miR-4257 expression showed a significance association with DFS (P<0.05). These results suggest that plasma exosomal miR-21 and mir-4257 expression has potential as a predictive biomarker for recurrence in NSCLC patients who have received curative resection.

Indexed as

biomarkerexosomemicroRNA-21microRNA-4257non-small cell lung cancer

Identifiers

PMID28454243
PMCPMC5403401
OpenAlexW2568500582

What OpenQuestion holds

Textmetadata
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.