ArticleOncotarget2016
Classifying lower grade glioma cases according to whole genome gene expression.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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.
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.
Who cites it
24 citing papers in PubMed, 35 citations in OpenAlex.
- MRI features can predict EGFR expression in lower grade gliomas: A voxel-based radiomic analysis.European radiology · 2018Trial
- Establishment of a novel gene panel for prognosis assessment in patients with lower grade glioma.Medicine · 2026Article
- Article
- Phenotypic stratification of Low-grade Glioma using multimodal MRI via outcome-weighted integrative clustering.BMC neurology · 2025Article
- Radiomics Analysis of Quantitative Maps from Synthetic MRI for Predicting Grades and Molecular Subtypes of Diffuse Gliomas.Clinical neuroradiology · 2024Article
- Elucidating Cancer Subtypes by Using the Relationship between DNA Methylation and Gene Expression.Genes · 2024Article
- Protein Kinase Inhibitors as a New Target for Immune System Modulation and Brain Cancer Management.International journal of molecular sciences · 2022Review
- Article
- A pediatric cerebral tumor with MN1 alteration and pathological features mimicking carcinoma metastasis: may the terminology "high grade neuroepithelial tumor with MN1 alteration" still be relevant?Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2021Review
- Transcriptome-wide Mendelian randomization study prioritising novel tissue-dependent genes for glioma susceptibility.Scientific reports · 2021Article
- MN1 overexpression with varying tumor grade is a promising predictor of survival of glioma patients.Human molecular genetics · 2021Article
- Establishment of an Immune-Related Gene Signature for Risk Stratification for Patients with Glioma.Computational and mathematical methods in medicine · 2021Article
- Promoting Prognostic Model Application: A Review Based on Gliomas.Journal of oncology · 2021Review
- HOX gene cluster (de)regulation in brain: from neurodevelopment to malignant glial tumours.Cellular and molecular life sciences : CMLS · 2020Review
- Radiogenomics of lower-grade gliomas: machine learning-based MRI texture analysis for predicting 1p/19q codeletion status.European radiology · 2020Article
- Use of Genome-Scale Integrated Analysis to Identify Key Genes and Potential Molecular Mechanisms in Recurrence of Lower-Grade Brain Glioma.Medical science monitor : international medical journal of experimental and clinical research · 2019Article
- Identification of potential biomarkers related to glioma survival by gene expression profile analysis.BMC medical genomics · 2019Article
- Correlation of alteration of HLA-F expression and clinical characterization in 593 brain glioma samples.Journal of neuroinflammation · 2019Article
- Comprehensive analysis of genes based on chr1p/19q co-deletion reveals a robust 4-gene prognostic signature for lower grade glioma.Cancer management and research · 2019Article
- Prognostic Roles of Central Carbon Metabolism-Associated Genes in Patients With Low-Grade Glioma.Frontiers in genetics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo identify a gene-based signature as a novel prognostic model in lower grade gliomas.
resultsA gene signature developed from HOXA7, SLC2A4RG and MN1 could segregate patients into low and high risk score groups with different overall survival (OS), and was validated in TCGA RNA-seq and GSE16011 mRNA array datasets. Receiver operating characteristic (ROC) was performed to show that the three-gene signature was more sensitive and specific than histology, grade, age, IDH1 mutation and 1p/19q co-deletion. Gene Set Enrichment Analysis (GSEA) and GO analysis showed high-risk samples were associated with tumor associated macrophages (TAMs) and highly invasive phenotypes. Moreover, HOXA7-siRNA inhibited migration and invasion in vitro, and downregulated MMP9 at the protein level in U251 glioma cells.
methodsA cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group. TCGA RNA-seq and GSE16011 mRNA array datasets were used for validation. Regression analyses and linear risk score assessment were performed for the identification of the three-gene signature comprising HOXA7, SLC2A4RG and MN1. CO NCLUSIONS: We established a three-gene signature for lower grade gliomas, which could independently predict overall survival (OS) of lower grade glioma patients with higher sensitivity and specificity compared with other clinical characteristics. These findings indicate that the three-gene signature is a new prognostic model that could provide improved OS prediction and accurate therapies for lower grade glioma patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.