Evidence map›Paper›PMID 31388313›Full record

ArticleCancer management and research2019

MicroRNA-3662 targets ZEB1 and attenuates the invasion of the highly aggressive melanoma cell line A375.

Lin Zhu, Zhifei Liu, Ruijia Dong, Xiaojun Wang, Mingzi Zhang, Xiao Guo, Nanze Yu, Ang Zeng

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

14 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. Article
  3. PIK3R2 predicts poor outcomes for patients with melanoma and contributes to the malignant progression via PI3K/AKT/NF-κB axis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Noncoding RNAs: emerging players in skin cancers pathogenesis.American journal of cancer research · 2021
    Article
  13. Review
  14. 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

8 authors at 1 institution in 1 country.

Lin ZhuDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, People's Republic of China.
Zhifei LiuDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, People's Republic of China.
Ruijia DongDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, People's Republic of China.
Xiaojun WangDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, People's Republic of China.
Mingzi ZhangDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, People's Republic of China.
Xiao GuoDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, People's Republic of China.
Nanze YuDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, People's Republic of China.
Ang ZengDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, People's Republic of China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCutaneous melanoma is the most aggressive form of skin cancer. It accounts for approximately 5% of all cutaneous malignancies and is currently responsible for the majority of skin cancer-related deaths. However, the exact mechanisms responsible for the occurrence of melanoma, in particular the invasive growth in normal skin or muscle tissue, remain unknown. MATERIALS AND

methodsmiR-3662, a microRNA is a potential tumor suppressor targeting zinc finger E-box binding homeobox 1 (ZEB1), which functions as a key regulator of the epithelial-mesenchymal transition (EMT) process. This microRNA was identified using an online database (miRDB) and expression was confirmed by Western blot analysis. Quantitative polymerase chain reaction (qPCR) was used to examine whether miR-3662 inhibits the EMT process in the aggressive melanoma cell line, A375, through the modification of the expression of invasion-related genes in A375 cells. The effects of miR-3662 on the in vivo growth of A375 cells were examined in a nude mouse model.

resultsUsing virtual screening of the miRDB database, miR-3662 was shown to target the 3' untranslated region (UTR) of the ZEB1 gene. Expression of miR-3662 via a lentivirus vector significantly decreased protein levels of ZEB1 and inhibited the growth of A375 cells in vitro and in vivo. The reduction in ZEB1 expression induced by miR-3662 resulted in EMT inhibition in A375 cells and decreased the relative expression of metastasis genes.

conclusionDown-regulation of ZEB1's expression via miR-3662 lentivirus vectors significantly decreased the in vitro and in vivo growth of the highly aggressive melanoma cell line A375.

Indexed as

melanomamicroRNAproliferation, invasive growthzinc finger E-box binding homeobox 1

Identifiers

PMID31388313
PMCPMC6607987
OpenAlexW2954502154

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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.