Evidence map›Paper›PMID 35064290›Full record

ArticleMolecular genetics and genomics : MGG2022

Diagnostic, grading and prognostic role of a restricted miRNAs signature in primary and metastatic brain tumours. Discussion on their therapeutic perspectives.

Emiliya Nikolova, Christian Georgiev, Lili Laleva, Milko Milev, Toma Spiriev, Stoycho Stoyanov, Teodora Taseva-Mineva, Vanyo Mitev, Albena Todorova

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Article in Molecular genetics and genomics : MGG, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
0.7field-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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
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  7. Review
  8. Article
  9. Article
  10. Low Expression of miR-491-3p Is Correlated with Lymph Node Metastasis in Gastric Cancer.Evidence-based complementary and alternative medicine : eCAM · 2022
    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

9 authors at 4 institutions in 2 countries.

Emiliya NikolovaDepartment of Medical Chemistry and Biochemistry, Medical University Sofia, Sofia, Bulgaria. nikolova.emily@gmail.com.ORCID http://orcid.org/0000-0002-9098-6138
Christian GeorgievDepartment of Psychology, Educational, and Child Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands.
Lili LalevaDepartment of Neurosurgery, Acibadem City Clinic Tokuda University Hospital, Sofia, Bulgaria.
Milko MilevDepartment of Neurosurgery, Acibadem City Clinic Tokuda University Hospital, Sofia, Bulgaria.
Toma SpirievDepartment of Neurosurgery, Acibadem City Clinic Tokuda University Hospital, Sofia, Bulgaria.
Stoycho StoyanovDepartment of Neurosurgery, Acibadem City Clinic Tokuda University Hospital, Sofia, Bulgaria.
Teodora Taseva-MinevaLaboratory of Genome Dynamics and Stability, Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Sofia, Bulgaria.
Vanyo MitevDepartment of Medical Chemistry and Biochemistry, Medical University Sofia, Sofia, Bulgaria.
Albena TodorovaDepartment of Medical Chemistry and Biochemistry, Medical University Sofia, Sofia, Bulgaria.
Tokuda Hospital · BGMedical University of Sofia · BGBulgarian Academy of Sciences · BGErasmus University Rotterdam · NL

Funding

medical university of sofia Grant № D-127/2019
6 · The paper itself

Abstract

At present, brain tumours remain one of the "hard-to-treat" malignancies with minimal improvement in patients' survival. Recently, miRNAs have been shown to correlate with oncogenesis and metastasis and have been investigated as potential biomarkers for diagnosis, prognosis and therapy prediction in different brain malignancies. The aim of the current study was to select an accurate and affordable brain tumour detection and grading approach. In the present study, we analysed the applicability of a restricted miRNA signature that could differentiate among patients with primary as well as metastatic brain tumours. Fresh tumour tissues were collected from Bulgarian patients (n = 38), including high-grade gliomas (n = 23), low-grade gliomas (n = 10) and brain metastases (n = 5) from lung cancer. Total RNAs enriched with microRNAs were isolated and differentially expressed miRNAs were analyzed by RT-qPCR using TaqMan Advanced miRNA assay. We selected a signature of miR-21, miR-10b, miR-7, miR-491 that showed good diagnostic potential in high-grade gliomas, low-grade gliomas and brain metastases compared with normal brain tissues. Our results showed that miR-10b could reliably differentiate brain metastases from high-grade gliomas, while miR-491 could distinguish low-grade from high-grade gliomas and brain metastases from low-grade gliomas. We observed that miR-21 and miR-7 correlated with disease recurrence, survival status and the Karnofsky Performance Status. The selected signature of miR-7, miR-21, miR-10b and miR-491 could be used as a highly accurate diagnostic, grading and prognostic biomarker in differentiating various types of brain tumours. Our data suggest that the 4-miRNAs signature could be further analysed for predicting treatment response and for future miRs-based targeted therapy. The ongoing studies on miRs-based targeted therapy related to our selected miRNA signature are also reviewed.

Indexed as

Brain NeoplasmsMicroRNAsBiomarkers, TumorBrainGene Expression Regulation, NeoplasticHumansNeoplasm GradingPrognosisBiomarkers, TumorMicroRNAsDiagnosisHigh-grade gliomaLow-grade gliomaMetastasesmiRPrognosis

Identifiers

PMID35064290
OpenAlexW4206950188

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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.