Evidence map›Paper›PMID 28121485›Full record

ArticleAutophagy2017

MIR506 induces autophagy-related cell death in pancreatic cancer cells by targeting the STAT3 pathway.

Longhao Sun, Limei Hu, David Cogdell, Li Lu, Chao Gao, Weijun Tian, Zhixiang Zhang, Ya'an Kang, Jason B Fleming, Wei Zhang

Open access · bronzeAbstract read
In one paragraph

Article in Autophagy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

33 citing papers in PubMed, 59 citations in OpenAlex.

  1. Unraveling the therapeutic landscape of miRNAs in pancreatic cancer.Naunyn-Schmiedeberg's archives of pharmacology · 2025
    Review
  2. Review
  3. Article
  4. miRNAs in pancreatic cancer progression and metastasis.Clinical & experimental metastasis · 2024
    Review
  5. Article
  6. Review
  7. Autophagy-Related ncRNAs in Pancreatic Cancer.Pharmaceuticals (Basel, Switzerland) · 2022
    Review
  8. Article
  9. Review
  10. Article
  11. The Role of Non-Coding RNAs in Autophagy During Carcinogenesis.Frontiers in cell and developmental biology · 2022
    Review
  12. Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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 at 3 institutions in 2 countries.

Longhao Suna Department of Cancer Biology , Comprehensive Cancer Center of Wake Forest Baptist Medical Center , Winston-Salem , NC , USA.
Limei Hub Department of Pathology , The University of Texas MD Anderson Cancer Center , Houston , TX , USA.
David Cogdellb Department of Pathology , The University of Texas MD Anderson Cancer Center , Houston , TX , USA.
Li Luc Department of General Surgery , Tianjin Medical University General Hospital , Tianjin , China.
Chao Gaoa Department of Cancer Biology , Comprehensive Cancer Center of Wake Forest Baptist Medical Center , Winston-Salem , NC , USA.
Weijun Tianc Department of General Surgery , Tianjin Medical University General Hospital , Tianjin , China.
Zhixiang Zhangc Department of General Surgery , Tianjin Medical University General Hospital , Tianjin , China.
Ya'an Kangd Department of Surgical Oncology , The University of Texas MD Anderson Cancer Center , Houston , TX , USA.
Jason B Flemingd Department of Surgical Oncology , The University of Texas MD Anderson Cancer Center , Houston , TX , USA.
Wei Zhanga Department of Cancer Biology , Comprehensive Cancer Center of Wake Forest Baptist Medical Center , Winston-Salem , NC , USA.
The University of Texas MD Anderson Cancer Center · USTianjin Medical University General Hospital · CNAtrium Health Wake Forest Baptist · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is the most aggressive and lethal cancer. The role of autophagy in the pathobiology of PDAC is intricate, with opposing functions manifested in different cellular contexts. MIR506 functions as a tumor suppressor in many cancer types through the regulation of multiple pathways. In this study, we hypothesized that MIR506 exerted a tumor suppression function in PDAC by inducing autophagy-related cell death. Our results provided evidence that downregulation of MIR506 expression was associated with disease progression in human PDAC. MIR506 triggered autophagic flux in PDAC cells, which led to autophagy-related cell death through direct targeting of the STAT3 (signal transducer and activator of transcription 3)-BCL2-BECN1 axis. Silencing and inhibiting STAT3 recapitulated the effects of MIR506, whereas forced expression of STAT3 abrogated the effects of MIR506. We propose that the apoptosis-inhibitory protein BCL2, which also inhibits induction of autophagy by blocking BECN1, was inhibited by MIR506 through targeting STAT3, thus augmenting BECN1 and promoting autophagy-related cell death. Silencing BECN1 and overexpression of BCL2 abrogated the effects of MIR506. These findings expand the known mechanisms of MIR506-mediated tumor suppression to activation of autophagy-related cell death and suggest a strategy for using MIR506 as an anti-STAT3 approach to PDAC treatment.

Indexed as

AdenocarcinomaApoptosisAutophagyBase SequenceCarcinoma, Pancreatic DuctalCell Line, TumorDisease ProgressionDown-RegulationGene Expression Regulation, NeoplasticHumansMicroRNAsModels, BiologicalPancreatic NeoplasmsSignal TransductionSTAT3 Transcription FactorMicroRNAsMIRN506 microRNA, humanSTAT3 Transcription Factorautophagyautophagy-related cell deathMIR506pancreatic ductal adenocarcinomaSTAT3

Identifiers

PMID28121485
PMCPMC5388243
OpenAlexW2581199609

What OpenQuestion holds

Textmetadata
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.