Evidence map›Paper›PMID 32728103›Full record

ArticleScientific reports2020

Circulating miR-92b and miR-375 for monitoring the chemoresistance and prognosis of small cell lung cancer.

Ming Li, Wulin Shan, Bo Hong, Jinglu Zou, Hong Li, Dandan Han, Yang Zhang, Lailing Li, Dan Li, Wenchu Lin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

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

  1. miRNAs Related to Immune Checkpoint Inhibitor Response: A Systematic Review.International journal of molecular sciences · 2024
    Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. APE1 controls DICER1 expression in NSCLC through miR-33a and miR-130b.Cellular and molecular life sciences : CMLS · 2022
    Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Review
  16. Review
  17. Article
  18. 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

10 authors.

Ming Li *High Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, 230031, China.
Wulin Shan *Division of Life Sciences and Medicine, Department of Laboratory Diagnostics, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230031, China.
Bo HongHigh Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, 230031, China.
Jinglu ZouHigh Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, 230031, China.
Hong LiHigh Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, 230031, China.
Dandan HanDivision of Life Sciences and Medicine, Department of Laboratory Diagnostics, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230031, China.
Yang ZhangDivision of Life Sciences and Medicine, Department of Laboratory Diagnostics, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230031, China.
Lailing LiDivision of Life Sciences and Medicine, Department of Laboratory Diagnostics, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230031, China.
Dan LiDivision of Life Sciences and Medicine, Department of Laboratory Diagnostics, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230031, China.
Wenchu LinHigh Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, 230031, China. wenchu@hmfl.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

miRNAs have been reported to be stably detectable in plasma and to function as potent biomarkers in multiple cancers. The study aimed to evaluate the expression of candidate circulating miRNAs in patients with small cell lung cancer (SCLC) to identify potential noninvasive biomarkers. The expression of five miRNAs (miR-92b, miR-146a, miR-375, miR-1224, and miR-1246) was significantly upregulated in plasma after chemoresistance induction. Receiver operating characteristic curve (ROC) analysis showed that the area under the curve (AUC) values of miR-92b and miR-375 were 0.766 and 0.791, respectively. The data demonstrated that among the five miRNAs assessed, these two miRNAs had better diagnostic accuracy for monitoring drug resistance. In addition, miR-92b and miR-375 levels were decreased after effective chemotherapy. Furthermore, Kaplan-Meier survival analysis confirmed that high expression of miR-92b and miR-375 was closely related to shorter progression-free survival (PFS) in SCLC patients. In conclusion, these findings indicate that circulating miR-92b and miR-375 might be ideal noninvasive biomarkers for monitoring drug resistance during chemotherapy and evaluating the prognosis of patients with SCLC.

Indexed as

Drug Resistance, NeoplasmAgedAged, 80 and overBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansLung NeoplasmsMaleMicroRNAsMiddle AgedPrognosisROC CurveSmall Cell Lung CarcinomaSurvival AnalysisBiomarkers, TumorMicroRNAsMIRN375 microRNA, humanMIRN92 microRNA, human

Identifiers

PMID32728103
PMCPMC7391689

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.