Evidence map›Paper›PMID 35846075›Full record

ReviewNon-coding RNA research2022

MicroRNAs as prognostic markers and therapeutic targets in gliomas.

Albert Sufianov, Sema Begliarzade, Tatiana Ilyasova, Yanchao Liang, Ozal Beylerli

Open access · goldAbstract readReview
In one paragraph

Review in Non-coding RNA research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

39 citing papers in PubMed, 42 citations in OpenAlex.

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  15. MicroRNAs as Biomarkers of Brain Tumor.Cancer management and research · 2024
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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

5 authors at 4 institutions in 2 countries.

Albert SufianovFederal Center of Neurosurgery, Tyumen, Russia.
Sema BegliarzadeRepublican Clinical Perinatal Center, Ufa, Republic of Bashkortostan, 450106, Russia.
Tatiana IlyasovaDepartment of Internal Diseases, Bashkir State Medical University, Ufa, Republic of Bashkortostan, 450008, Russia.
Yanchao LiangDepartment of Neurosurgery, the First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
Ozal BeylerliEducational and Scientific Institute of Neurosurgery, Рeoples' Friendship University of Russia (RUDN University), Moscow, Russia.
Bashkir State Medical University · RUFirst Affiliated Hospital of Harbin Medical University · CNPeoples' Friendship University of Russia · RUSechenov University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gliomas are invasive brain tumors characterized by high rates of recurrence and mortality. Glioblastoma (GBM), a grade IV brain tumor, is known for its heterogenicity and its resistance to the current treatment regimen. MicroRNA (miRNAs) are small non-coding sequences of RNA that regulate and influence the expression of multiple genes. The detection of certain types of micro-RNA in tissues and blood serum can be used for diagnosis and prognosis, including the response of a particular patient to therapy. The purpose of this review is to analyze studies and experimental results concerning changes in microRNA expression profiles characteristic of gliomas. Furthermore, miRNAs also contribute to autophagy at multiple stages. In this review, we summarize the functions of miRNAs in GBM pathways linked to dysregulation of cell cycle control, apoptosis and resistance to treatment, and the possible use of miRNAs in clinical settings as treatment and prediction biomarkers.

Indexed as

Brain tumorsGliomasmicroRNAsMolecular markersTherapeutic targets

Identifiers

PMID35846075
PMCPMC9271693
OpenAlexW4284882806

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.