Evidence map›Paper›PMID 28277545›Full record

ArticleCell death & disease2017

miR-377 induces senescence in human skin fibroblasts by targeting DNA methyltransferase 1.

Hong-Fu Xie, Ying-Zi Liu, Rui Du, Ben Wang, Meng-Ting Chen, Yi-Ya Zhang, Zhi-Li Deng, Ji Li

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Cell death & disease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 2 pooled it
2.5field-weighted citation impact, top 10% 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

32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 53 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
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  9. Review
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  11. Hypertrophic cardiomyopathy inThe journal of cardiovascular aging · 2024
    Article
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  15. Article
  16. Review
  17. Article
  18. microRNA-377-3p inhibits osteosarcoma progression by targeting CUL1 and regulating Wnt/β-catenin signaling pathway.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2021
    Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Hong-Fu XieDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
Ying-Zi LiuDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
Rui DuDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
Ben WangDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
Meng-Ting ChenDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
Yi-Ya ZhangDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
Zhi-Li DengDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
Ji LiDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
Central South University · CNXiangya Hospital Central South University · CNSoil and Fertilizer Institute of Hunan Province · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skin aging is a complicated physiological process and epigenetic feature, including microRNA-mediated regulation and DNA methylation, have been shown to contribute to this process. DNA methylation is regulated by DNA methyltransferase, of which DNA methyltransferase 1 (DNMT1) is the most abundantly known. But evidence supporting its role in skin aging remains scarce, and no report regards its specifical upstream-regulating molecules in the process of skin aging so far. Here, we found that DNMT1 expression was markedly higher in young human skin fibroblasts (HSFs) than that in passage-aged HSFs, and DNMT1 knockdown significantly induced the senescence phenotype in young HSFs. We predicted the upstream miRNAs which could regulate DNMT1 with miRNA databases and found miR-377 had high homology with a sequence in the 3'-UTR of human DNMT1 mRNA. We confirmed that miR-377 was a potential regulator of DNMT1 by luciferase reporter assays. miR-377 expression in passage-aged HSFs was markedly higher than that in the young HSFs. miR-377 overexpression promoted senescence in young HSFs, and inhibition of miR-377 reduced senescence in passage-aged HSFs. Moreover, these functions were mediated by targeting DNMT1. Microfluidic PCR and next-generation bisulfite sequencing of 24 senescent-associated genes' promoters revealed alterations of the promoter methylation levels of FoxD3, p53, and UTF1 in HSFs treated with miR-377 mimics or inhibitors. We also verified that the miR-377-mediated changes in p53 expression could be reversed by regulation of DNMT1 in HSFs. Similarly, there was a negative correlation between miR-377 and DNMT1 expression in young and photoaged HSFs, HSFs, or skin tissues from UV-unexposed areas of different aged donors. Our results highlight a novel role for miR-377-DNMT1-p53 axis in HSF senescence. These findings shed new light on the mechanisms of skin aging and identify future opportunities for its therapeutic prevention.

Indexed as

AgingDNA (Cytosine-5-)-Methyltransferase 1DNA (Cytosine-5-)-MethyltransferasesDNA MethylationFibroblastsGene Expression RegulationGene Knockdown TechniquesHigh-Throughput Nucleotide SequencingHumansMicroRNAsPromoter Regions, GeneticSkinTumor Suppressor Protein p53DNA (Cytosine-5-)-Methyltransferase 1DNA (Cytosine-5-)-MethyltransferasesDNMT1 protein, humanMicroRNAsMIRN377 microRNA, humanTP53 protein, humanTumor Suppressor Protein p53

Identifiers

PMID28277545
PMCPMC5386568
OpenAlexW2593769422

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.