Evidence map›Paper›PMID 28002496›Full record

ArticlePloS one2016

Exosomal miRs in Lung Cancer: A Mathematical Model.

Xiulan Lai, Avner Friedman

Abstract read
In one paragraph

Article in PloS one, 2016. 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
–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

19 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Hallmarks of exosomes.Future science OA · 2022
    Review
  14. Article
  15. Exosomal microRNAs in non-small cell lung cancer.Translational cancer research · 2021
    Review
  16. Review
  17. Article
  18. Review
  19. Exosomes as Theranostics for Lung Cancer.Advances in cancer research · 2018
    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

2 authors.

Xiulan LaiInstitute for Mathematical Sciences, Renmin University of China, Beijing, P. R. China.
Avner FriedmanMathematical Bioscience Institute & Department of Mathematics, Ohio State University, Columbus, OH, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer, primarily non-small-cell lung cancer (NSCLC), is the leading cause of cancer deaths in the United States and worldwide. While early detection significantly improves five-year survival, there are no reliable diagnostic tools for early detection. Several exosomal microRNAs (miRs) are overexpressed in NSCLC, and have been suggested as potential biomarkers for early detection. The present paper develops a mathematical model for early stage of NSCLC with emphasis on the role of the three highest overexpressed miRs, namely miR-21, miR-205 and miR-155. Simulations of the model provide quantitative relationships between the tumor volume and the total mass of each of the above miRs in the tumor. Because of the positive correlation between these miRs in the tumor tissue and in the blood, the results of the paper may be viewed as a first step toward establishing a combination of miRs 21, 205, 155 and possibly other miRs as serum biomarkers for early detection of NSCLC.

Indexed as

Models, TheoreticalAntineoplastic AgentsBiomarkers, TumorCarcinoma, Non-Small-Cell LungHumansLung NeoplasmsMicroRNAsAntineoplastic AgentsBiomarkers, TumorMicroRNAs

Identifiers

PMID28002496
PMCPMC5176278

What OpenQuestion holds

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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.