Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Introduction: Brain neoplasms and central nervous system (CNS) disorders, particularly gliomas, have shown a notable increase in incidence over the last three decades, posing significant diagnostic and therapeutic challenges. MicroRNAs (miRNAs) have emerged as promising biomarkers due to their regulatory role in gene expression, offering potential enhancements in glioma diagnosis and prognosis.

Methods: This systematic review and meta-analysis, adhering to PRISMA guidelines, included 25 studies for diagnostic accuracy and 99 for prognostic analysis, published until August 27th, 2023. Studies were identified through comprehensive searches of PubMed, Web of Science, and Scopus databases. Inclusion criteria encompassed peer-reviewed original research providing sensitivity, specificity, and area under the curve (AUC) for miRNAs in glioma diagnosis, as well as survival outcomes with hazard ratios (HRs) or mean survival.

Results And Discussion: Meta-analysis demonstrated miRNAs' high diagnostic accuracy, with a pooled sensitivity of 0.821 (95% CI: 0.781-0.855) and specificity of 0.831 (95% CI: 0.792-0.865), yielding an AUC of 0.893. Subgroup analysis by specimen type revealed consistent accuracy across blood, cerebrospinal fluid (CSF), and tissue samples. Our results also showed miRNAs can be potential prognostic biomarkers. miRNAs showed significant associations with overall survival (OS) (pooled HR: 2.0221; 95% CI: 1.8497-2.2105), progression-free survival (PFS) (pooled HR: 2.4248; 95% CI: 1.8888-3.1128), and disease-free survival (DFS) (pooled HR: 1.8973; 95% CI: 1.1637-3.0933) in tissue specimens. These findings underscore miRNAs' potential as valuable biomarkers for improving glioma diagnosis and prognosis, offering insights for enhancing clinical decision-making and patient outcomes.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10937740PMC
http://dx.doi.org/10.3389/fneur.2024.1357321DOI Listing

Publication Analysis

Top Keywords

glioma diagnosis
12
systematic review
8
review meta-analysis
8
diagnostic accuracy
8
95%
5
microrna potential
4
diagnostic
4
potential diagnostic
4
diagnostic prognostic
4
prognostic biomarker
4

Similar Publications

Purpose: Amino acid PET with [F]-fluoroethylthyrosine ([F]FET-PET) is frequently utilized in gliomas. Most studies on prognostication based on amino acid PET comprise mixed cohorts of brain tumors with low- and high-grade features. The objective of this study was to assess the potential prognostic value of [F]FET-PET-based markers in the group of grade 2 adult-type diffuse gliomas, as defined by the WHO CNS 2021 classification.

View Article and Find Full Text PDF

Purpose: Glioblastoma (GBM) remains one of the most aggressive primary brain tumors with poor survival outcomes and a lack of approved therapies. A promising novel approach for GBM is the application of photodynamic therapy (PDT), a localized, light-activated treatment using tumor-selective photosensitizers. This narrative review describes the mechanisms, delivery systems, photosensitizers, and available evidence regarding the potential of PDT as a novel therapeutic approach for GBM.

View Article and Find Full Text PDF

Purpose: Resection of glioblastomas infiltrating the motor cortex and corticospinal tract (CST) is often linked to increased perioperative morbidity. Navigated transcranial magnetic stimulation (nTMS) motor mapping has been advocated to increase patient safety in these cases. The additional impact of patient frailty on overall outcome after resection of cases with increased risk for postoperative motor deficits as identified with nTMS needs to be investigated.

View Article and Find Full Text PDF

Background: The aim of this review is to present the role of intraoperative flow cytometry (IFC) in the intracranial tumor surgery. This scoping review aims to summarize current evidence on the intraoperative use of IFC in patients with intracranial tumors.

Methods: A comprehensive literature search was conducted in the Medline, Cochrane and Scopus databases up to January 21, 2025.

View Article and Find Full Text PDF

Background: The gut microbiota plays a crucial role in the development of glioma. With the evolution of artificial intelligence technology, applying AI to analyze the vast amount of data from the gut microbiome indicates the potential that artificial intelligence and computational biology hold in transforming medical diagnostics and personalized medicine.

Methods: We conducted metagenomic sequencing on stool samples from 42 patients diagnosed with glioma after operation and 30 non-intracranial tumor patients and developed a Gradient Boosting Machine (GBM) machine learning model to predict the glioma patients based on the gut microbiome data.

View Article and Find Full Text PDF