Evidence map›Paper›PMID 35923466›Full record

ReviewFrontiers in molecular biosciences2022

The Role of Long Non-Coding RNAs in Epithelial-Mesenchymal Transition-Related Signaling Pathways in Prostate Cancer.

Dexin Shen, Hongwei Peng, Caixia Xia, Zhao Deng, Xi Tong, Gang Wang, Kaiyu Qian

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 47% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

7 authors at 3 institutions in 1 country.

Dexin ShenDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Hongwei PengDepartment of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
Caixia XiaPresident's Office, Zhongnan Hospital of Wuhan University, Wuhan, China.
Zhao DengDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Xi TongDepartment of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
Gang WangDepartment of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
Kaiyu QianDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Zhongnan Hospital of Wuhan University · CNWuhan Center for Disease Control and Prevention · CNWuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer (PCa) is one of the most common male malignancies with frequent remote invasion and metastasis, leading to high mortality. Epithelial-mesenchymal transition (EMT) is a fundamental process in embryonic development and plays a key role in tumor proliferation, invasion and metastasis. Numerous long non-coding RNAs (lncRNAs) could regulate the occurrence and development of EMT through various complex molecular mechanisms involving multiple signaling pathways in PCa. Given the importance of EMT and lncRNAs in the progression of tumor metastasis, we recapitulate the research progress of EMT-related signaling pathways regulated by lncRNAs in PCa, including AR signaling, STAT3 signaling, Wnt/β-catenin signaling, PTEN/PI3K/AKT signaling, TGF-β/Smad and NF-κB signaling pathways. Furthermore, we summarize four modes of how lncRNAs participate in the EMT process of PCa

Indexed as

androgen receptor (AR)epithelial-mesenchymal transition (EMT)long non-coding RNA (lncRNA)prostate cancer (PCa)wnt/β-catenin

Identifiers

PMID35923466
PMCPMC9339612
OpenAlexW4285726292

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.