Evidence map›Paper›PMID 35490305›Full record

ArticleIranian biomedical journal2022

A Signature of Three microRNAs Is a Potential Diagnostic Biomarker for Glioblastoma

Ali Hosein Yazdi, Vajiheh Zarrinpour, Elham Moslemi, Mohammad Mahdi Forghanifard

Abstract read
In one paragraph

Article in Iranian biomedical journal, 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
–field-weighted citation impact
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

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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.

  1. Article
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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

4 authors.

Ali Hosein YazdiDepartment of Biology, Damghan Branch, Islamic Azad University, Damghan, Iran.
Vajiheh ZarrinpourDepartment of Biology, Damghan Branch, Islamic Azad University, Damghan, Iran.
Elham MoslemiCellular and Molecular Biology Department, Islamic Azad University, Tehran East Branch, Tehran, Iran.
Mohammad Mahdi ForghanifardDepartment of Biology, Damghan Branch, Islamic Azad University, Damghan, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Glioblastoma is the most common primary malignant neoplasm of the central nervous system. Despite progress in diagnosis and treatment, glioblastoma still has a poor prognosis. This study aimed to examine whether a signature of three candidate miRNAs (i.e. hsa-let-7c-5p, hsa-miR-206-5p, and hsa-miR-1909-5p) can be used as a diagnostic biomarker for distinguishing glioblastoma from healthy brain tissues. Methods: In this study, 50 formalin‐fixed paraffin‐embedded (FFPE) glioblastoma tissue samples and 50 healthy tissue samples adjacent to tumor were included. The expression of each candidate miRNA (i.e. hsa-let-7c-5p, hsa-miR-206-5p, and hsa-miR-1909-5p) was measured using quantitative reverse transcription PCR. To show the roles of each miRNA and their biological effects on glioblastoma development and clinicopathological characteristics, in silico tools were used. ROC curves were performed to assess the diagnostic accuracy of each miRNA. Results: Based on the results, hsa-let-7c-5p and hsa-miR-206-5p were downregulated, while hsa-miR-1909-5p was upregulated in glioblastoma tumors compared to healthy samples. No association was detected between the expression of each candidate miRNA and sex. Except for hsa-let-7c-5p, other miRNAs did not correlate with age status. ROC curve analysis indicated that the signature of candidate miRNAs is a potential biomarker distinguishing between glioblastoma and healthy samples. Only hsa-miR-206-5p suggested the association with poor prognosis in glioblastoma patients. Conclusions: Our findings revealed that the signature of three miRNAs is capable of distinguishing glioblastoma tumor and healthy tissues. These results are beneficial for the clinical management of glioblastoma patients.

Indexed as

GlioblastomaMicroRNAsBiomarkersGene Expression ProfilingHumansROC CurveBiomarkersmicroRNA1909 microRNA, humanMicroRNAsMIRN206 microRNA, humanMIRNlet-7c microRNA, humanGastric cancerGene expressionInflammationPattern recognition receptorsRNA-seq

Identifiers

PMID35490305
PMCPMC9432466

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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.