Evidence map›Paper›PMID 34189363›Full record

ReviewNon-coding RNA research2021

Regulation of RUNX proteins by long non-coding RNAs and circular RNAs in different cancers.

Ammad Ahmad Farooqi, Kapanova Gulnara, Auyezova Ardak Mukhanbetzhanovna, Ubaidilla Datkhayev, Abay Z Kussainov, Aima Adylova

Open access · goldAbstract readReview
In one paragraph

Review in Non-coding RNA research, 2021. 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
1.0field-weighted citation impact, top 30% 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, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

6 authors at 5 institutions in 3 countries.

Ammad Ahmad FarooqiInstitute of Biomedical and Genetic Engineering (IBGE), Islamabad, Pakistan.
Kapanova GulnaraAl-Farabi Kazakh National University, 71 Al-Farabi Avenue, Almaty, 050040, Kazakhstan.
Auyezova Ardak MukhanbetzhanovnaDepartment of Healthcare Management, KSPH Kazakhstan Medical University, Almaty, Kazakhstan.
Ubaidilla DatkhayevAsfendiyarov Kazakh National Medical University, KazNMU, Tole Bi St 94, Almaty, 050000, Kazakhstan.
Abay Z KussainovKazakh National Medical University Named After S. D. Asfendiyarov, Kazakhstan.
Aima AdylovaGuangdong Key Laboratory for Genome Stability & Disease Prevention and Carson International Cancer Center, Shenzhen University School of Medicine, Shenzhen, Guangdong, 518060, China.
Kazakh National Medical University · KZAl-Farabi Kazakh National University · KZInstitute of Biomedical and Genetic Engineering · PKKazakhstan Medical University · KZShenzhen University Health Science Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RUNX proteins have been shown to behave as "double-edge sword" in wide variety of cancers. Discovery of non-coding RNAs has played linchpin role in improving our understanding about the post-transcriptional regulation of different cell signaling pathways. Several new mechanistic insights and distinct modes of cross-regulation of RUNX proteins and non-coding RNAs have been highlighted by recent research. In this review we have attempted to provide an intricate interplay between non-coding RNAs and RUNX proteins in different cancers. Better conceptual and mechanistic understanding of layered regulation of RUNX proteins by non-coding RNAs will be helpful in effective translation of the laboratory findings to clinically effective therapeutics.

Indexed as

ApoptosisCancerNon-coding RNAsSignalingTherapy

Identifiers

PMID34189363
PMCPMC8209647
OpenAlexW3168132890

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.