Evidence map›Paper›PMID 28501849›Full record

ArticleOncotarget2017

miR-551b regulates epithelial-mesenchymal transition and metastasis of gastric cancer by inhibiting ERBB4 expression.

Guangyuan Song, Hongcheng Zhang, Chenlin Chen, Lijie Gong, Biao Chen, Shaoyun Zhao, Ji Shi, Ji Xu, Zaiyuan Ye

RetractedOpen access · diamondAbstract readRetracted Publication
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

20 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Expression and clinical significance ofJournal of gastrointestinal oncology · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. The role of ErbB4 in cancer.Cellular oncology (Dordrecht, Netherlands) · 2020
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Emerging insights into the biology of metastasis: A review article.Iranian journal of basic medical sciences · 2019
    Review
  16. Article
  17. Article
  18. Review
  19. Identification and Interaction Analysis of Molecular Markers in Colorectal Cancer by Integrated Bioinformatics Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2018
    Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Guangyuan SongThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Hongcheng ZhangThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Chenlin ChenThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Lijie GongThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Biao ChenThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Shaoyun ZhaoThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Ji ShiThe First Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Ji XuDepartment of Gastrointestinal and Pancreatic Surgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, China.
Zaiyuan YeDepartment of Gastrointestinal and Pancreatic Surgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, China.
Zhejiang Chinese Medical University · CNZhejiang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial-mesenchymal transition (EMT) is an important biological process that is characteristic of malignant tumor cells with metastatic potential. We investigated the role of miR-551b in EMT and metastasis in gastric cancer (GC). We found that low miR-551b levels were associated with EMT, metastasis and a poor prognosis in GC patients. Further, two GC cell lines, MNK45 and SGC7901, exhibited lower miR-551b levels than the GES normal stomach cell line. Exposing MNK45 and SGC7901 cells to TGF-β1 resulted in cell morphology changes characteristic of EMT, which was confirmed by Western blot analysis demonstrating low E-Cadherin and high N-Cadherin and Vimentin levels. Treatment with miR-551b mimics inhibited these EMT changes as well as Transwell migration and invasiveness. We identified ERBB4 as a potential target of miR-551b based on patient data from the TCGA. ERBB4 was upregulated in GC specimens, and its high expression correlated with a poor prognosis of GC patients. Dual luciferase assays revealed that miR-551b directly inhibited ERBB4 by binding to its 3'UTR. Moreover, treatment with miR-551b mimics or the ERBB4 inhibitor AST-1306 inhibited EMT in the GC cell lines. Finally, nude mice xenografted with GC cancer cell lines expressing miR-551b mimics exhibited smaller tumors and longer survival than mice engrafted with control GC cancer cells. These data indicate that miR-551b inhibits EMT and metastasis in GC by inhibiting ERBB4. miR-551b and ERBB4 are thus potential therapeutic targets for the treatment of GC.

Indexed as

Gene Expression Regulation, NeoplasticRNA Interference3' Untranslated RegionsAnimalsCell Line, TumorCell MovementDisease Models, AnimalEpithelial-Mesenchymal TransitionGene Expression ProfilingHeterograftsHumansMiceMicroRNAsNeoplasm MetastasisNeoplasm StagingPrognosis3' Untranslated RegionsERBB4 protein, humanMicroRNAsMIRN-551 microRNA, humanReceptor, ErbB-4Transforming Growth Factor beta1epithelial-mesenchymal transition (EMT)ERBB4gastric cancermetastasismiR-551b

Identifiers

PMID28501849
PMCPMC5542221
OpenAlexW2609603613

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.