Evidence map›Paper›PMID 39429673›Full record

ArticleIranian journal of public health2024

Long Non-Coding RNA

Arash Poursheikhani, Meysam Mosallaei, Mohammad Foad Heidari, Mohsen Rajaeinejad, Mohsen Chamanara, Mojtaba Yousefi Zoshk, Peyman Aslani, Ebrahim Hazrati, Mojgan Mohammadimehr, Javad Behroozi

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Article in Iranian journal of public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Arash PoursheikhaniDepartment of Genetics and Advanced Medical Technology, Faculty of Medicine, AJA University of Medical Sciences, Tehran, Iran.
Meysam MosallaeiStudent Research Committee, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
Mohammad Foad HeidariDepartment of Laboratory Sciences, School of Allied Health Medicine, AJA University of Medical Sciences, Tehran, Iran.
Mohsen RajaeinejadAJA Cancer Epidemiology Research and Treatment Center (AJA- CERTC), AJA University of Medical Sciences, Tehran, Iran.
Mohsen ChamanaraToxicology Research Center, AJA University of Medical Sciences, Tehran, Iran.
Mojtaba Yousefi ZoshkTrauma Research Center, AJA University of Medical Sciences, Tehran, Iran.
Peyman AslaniDepartment of Parasitology and Mycology, Faculty of Medicine, AJA University of Medical Sciences, Tehran, Iran.
Ebrahim HazratiDepartment of Anesthesiology and Critical Care, AJA University of Medical Sciences, Tehran, Iran.
Mojgan MohammadimehrDepartment of Laboratory Sciences, School of Allied Health Medicine, AJA University of Medical Sciences, Tehran, Iran.
Javad BehrooziDepartment of Genetics and Advanced Medical Technology, Faculty of Medicine, AJA University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Glioblastoma multiforme (GBM) is one of the most invasive types of brain cancer. LncRNAs can be considered a new prognostic and diagnostic biomarker in GBM. This study comprehensively explored the interaction of lncRNAs with mRNAs in the TCGA database and proposed a novel promising biomarker with favorable diagnostic and prognostic values. Methods: The public data of RNA-seq and related clinical data were downloaded from the TCGA database. Differential expression analysis was conducted in R. GO and KEGG signaling pathways were used for enrichment. The STRING database was used for PPI analysis. CE-network was constructed by STAR database. Kaplan-Meier survival analysis and ROC curve analysis to indicate the biomarkers' diagnostic and prognostic values. Results: Differentially expressed data illustrated that 4428 mRNAs were differentially expressed in GBM. The GO and KEGG pathway analysis showed that the differentially expressed mRNAs were enriched in critical biological processes. The PPI showed that Conclusion: Altogether, we demonstrated lncRNA, and mRNA interaction and mentioned regulatory networks, considered a therapeutic option in GBM. In addition, we proposed potential diagnostic and prognostic biomarkers for the patients.

Indexed as

Glioblastoma multiformeLong non-coding RNAsTumorigenesis

Identifiers

PMID39429673
PMCPMC11490338

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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.