Evidence map›Paper›PMID 36307864›Full record

ArticleBreast cancer research : BCR2022

RAB4A GTPase regulates epithelial-to-mesenchymal transition by modulating RAC1 activation.

Subbulakshmi Karthikeyan, Patrick J Casey, Mei Wang

Open access · goldAbstract read
In one paragraph

Article in Breast cancer research : BCR, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 38% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 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

3 authors at 2 institutions in 2 countries.

Subbulakshmi KarthikeyanProgram in Cancer Stem Cell Biology, Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore.
Patrick J CaseyProgram in Cancer Stem Cell Biology, Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore.
Mei WangProgram in Cancer Stem Cell Biology, Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore. mei.wang@duke-nus.edu.sg.
Duke-NUS Medical School · SGDuke University Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial-to-mesenchymal transition (EMT) is a critical underpinning process for cancer progression, recurrence and resistance to drug treatment. Identification of new regulators of EMT could lead to the development of effective therapies to improve the outcome of advanced cancers. In the current study we discovered, using a variety of in vitro and in vivo approaches, that RAB4A function is essential for EMT and related manifestation of stemness and invasive properties. Consistently, RAB4A suppression abolished the cancer cells' self-renewal and tumor forming ability. In terms of downstream signaling, we found that RAB4A regulation of EMT is achieved through its control of activation of the RAC1 GTPase. Introducing activated RAC1 efficiently rescued EMT gene expression, invasion and tumor formation suppressed by RAB4A knockdown in both the in vitro and in vivo cancer models. In summary, this study identifies a RAB4A-RAC1 signaling axis as a key regulatory mechanism for the process of EMT and cancer progression and suggests a potential therapeutic approach to controlling these processes.

Indexed as

Breast Neoplasmsrac1 GTP-Binding ProteinCell Line, TumorEpithelial-Mesenchymal TransitionFemaleHumansSignal Transductionrac1 GTP-Binding ProteinRAC1 protein, humanCancer cell self-renewalCell invasionEpithelial–mesenchymal transition (EMT)MetastasisRAB4ARAC1Stemness

Identifiers

PMID36307864
PMCPMC9615386
OpenAlexW4307714097

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.