Evidence map›Paper›PMID 38832259›Full record

ArticleHeliyon2024

The prognostic relevance of a gene expression signature in MRI-defined highly vascularized glioblastoma.

Víctor Montosa-I-Micó, María Del Mar Álvarez-Torres, Rebeca Burgos-Panadero, F Javier Gil-Terrón, Maria Gómez Mahiques, Carles Lopez-Mateu, Juan M García-Gómez, Elies Fuster-Garcia

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. 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

8 authors.

Víctor Montosa-I-MicóInstituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain.
María Del Mar Álvarez-TorresInstituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain.
Rebeca Burgos-PanaderoLaboratory of Cellular and Molecular Biology, Clinical and Translational Research in Cancer Group, La Fe Health Research Institute, Valencia, Spain.
F Javier Gil-TerrónInstituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain.
Maria Gómez MahiquesInstituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain.
Carles Lopez-MateuInstituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain.
Juan M García-GómezInstituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain.
Elies Fuster-GarciaInstituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The vascular heterogeneity of glioblastomas (GB) remains an important area of research, since tumor progression and patient prognosis are closely tied to this feature. With this study, we aim to identify gene expression profiles associated with MRI-defined tumor vascularity and to investigate its relationship with patient prognosis. Methods: The study employed MRI parameters calculated with DSC Perfusion Quantification of ONCOhabitats glioma analysis software and RNA-seq data from the TCGA-GBM project dataset. In our study, we had a total of 147 RNA-seq samples, which 15 of them also had MRI parameter information. We analyzed the gene expression profiles associated with MRI-defined tumor vascularity using differential gene expression analysis and performed Log-rank tests to assess the correlation between the identified genes and patient prognosis. Results: The findings of our research reveal a set of 21 overexpressed genes associated with the high vascularity pattern. Notably, several of these overexpressed genes have been previously implicated in worse prognosis based on existing literature. Our log-rank test further validates that the collective upregulation of these genes is indeed correlated with an unfavorable prognosis. This set of genes includes a variety of molecules, such as cytokines, receptors, ligands, and other molecules with diverse functions. Conclusions: Our findings suggest that the set of 21 overexpressed genes in the High Vascularity group could potentially serve as prognostic markers for GB patients. These results highlight the importance of further investigating the relationship between the molecules such as cytokines or receptors underlying the vascularity in GB and its observation through MRI and developing targeted therapies for this aggressive disease.

Indexed as

BiomarkerGlioblastomaHigh-grade gliomaMRIONCOhabitatsRelative cerebral blood volumeRNA-seqTumor vascularity

Identifiers

PMID38832259
PMCPMC11145239

What Socratic holds

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Registered trials

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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 Socratic graph.