Evidence map›Paper›PMID 33213510›Full record

ReviewJournal of hematology & oncology2020

The promising role of noncoding RNAs in cancer-associated fibroblasts: an overview of current status and future perspectives.

Zengli Fang, Jin Xu, Bo Zhang, Wei Wang, Jiang Liu, Chen Liang, Jie Hua, Qingcai Meng, Xianjun Yu, Si Shi

Open access · goldAbstract readReview
In one paragraph

Review in Journal of hematology & oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.3field-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

30 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Detecting theBiomolecules · 2024
    Article
  8. Review
  9. Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Decoding the regulatory roles of non-coding RNAs in cellular metabolism and disease.Molecular therapy : the journal of the American Society of Gene Therapy · 2023
    Review
  17. Review
  18. Exosome-transmitted circMolecular and cellular biology · 2023
    Article
  19. Review
  20. 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

10 authors at 1 institution in 1 country.

Zengli FangDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, China.
Jin XuDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, China.
Bo ZhangDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, China.
Wei WangDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, China.
Jiang LiuDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, China.
Chen LiangDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, China.
Jie HuaDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, China.
Qingcai MengDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, China. mengqingcai@fudanpci.org.
Xianjun YuDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, China. yuxianjun@fudanpci.org.
Si ShiDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, China. shisi@fudanpci.org.ORCID 0000-0002-6652-0629
Shanghai Medical College of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the most important component of the stromal cell population in the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) are crucial players in tumor initiation and progression. The interaction between CAFs and tumor cells, as well as the resulting effect, is much greater than initially expected. Numerous studies have shown that noncoding RNAs (ncRNAs) play an irreplaceable role in this interplay, and related evidence continues to emerge and advance. Under the action of ncRNAs, normal fibroblasts are directly or indirectly activated into CAFs, and their metabolic characteristics are changed; thus, CAFs can more effectively promote tumor progression. Moreover, via ncRNAs, activated CAFs can affect the gene expression and secretory characteristics of cells, alter the TME and enhance malignant biological processes in tumor cells to contribute to tumor promotion. Previously, ncRNA dysregulation was considered the main mechanism by which ncRNAs participate in the crosstalk between CAFs and tumor cells. Recently, however, exosomes containing ncRNAs have been identified as another vital mode of interaction between these two types of cells, with a more direct and clear function. Gaining an in-depth understanding of ncRNAs in CAFs and the complex regulatory network connecting CAFs with tumor cells might help us to establish more effective and safer approaches for cancer therapies targeting ncRNAs and CAFs and offer new hope for cancer patients.

Indexed as

AnimalsCancer-Associated FibroblastsCell CommunicationExosomesGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansNeoplasmsRNA, UntranslatedTumor MicroenvironmentRNA, UntranslatedCancerCancer-associated fibroblastsCell–cell interactionExosomeLong noncoding RNAMicroRNANoncoding RNATumor microenvironment

Identifiers

PMID33213510
PMCPMC7678062
OpenAlexW3098432330

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.