ArticleBiomedicines2022
A Novel 16-Genes Signature Scoring System as Prognostic Model to Evaluate Survival Risk in Patients with Glioblastoma.
Article in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled 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.
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.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Causal association between plasma proteins and lung adenocarcinoma: a two-sample mendelian randomization study.BMC pulmonary medicine · 2025Pooled it
- Elevated ICAM5 as a promising predictor of poor prognosis in bladder cancer via EMT, immune microenvironment, and therapy resistance.PloS one · 2026Article
- Identifying survival subtypes with autoencoder using multiple types of high-dimensional genomic data from studies of glioblastoma multiforme.Briefings in bioinformatics · 2025Article
- Predicting Treatment Outcomes in Glioblastoma: A Risk Score Model for TMZ Resistance and Immune Checkpoint Inhibition.Biology · 2025Article
- IGFBP-2 and IGF-II: Key Components of the Neural Stem Cell Niche? Implications for Glioblastoma Pathogenesis.International journal of molecular sciences · 2025Review
- A Rare Patient of SEZ6L2 Antibody-Associated Cerebellar Ataxia.Cerebellum (London, England) · 2025Article
- Knockdown of Anoikis-Associated Gene OCIAD2 Reduces Proliferation and Migration of Glioblastoma Cell Lines.Combinatorial chemistry & high throughput screening · 2025Article
- Knockdown of PGBD5 inhibits the malignant progression of glioma through upregulation of the PPAR pathway.International journal of oncology · 2024Article
- The construction of a novel prognostic prediction model for glioma based on GWAS-identified prognostic-related risk loci.Open medicine (Warsaw, Poland) · 2024Article
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- AVEN: a novel oncogenic biomarker with prognostic significance and implications of AVEN-associated immunophenotypes in lung adenocarcinoma.Frontiers in molecular biosciences · 2023Article
- Molecular signature to predict quality of life and survival with glioblastoma using Multiview omics model.PloS one · 2023Article
- A molecular signature for the G6PC3/SLC37A2/SLC37A4 interactors in glioblastoma disease progression and in the acquisition of a brain cancer stem cell phenotype.Frontiers in endocrinology · 2023Article
- CHRM3 is a novel prognostic factor of poor prognosis and promotes glioblastoma progression via activation of oncogenic invasive growth factors.Oncology research · 2023Article
- Anti-SEZ6L2 antibodies in paraneoplastic cerebellar syndrome: case report and review of the literature.Neurological research and practice · 2022Review
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- Comprehensive Analyses of Ferroptosis-Related Alterations and Their Prognostic Significance in Glioblastoma.Frontiers in molecular biosciences · 2022Article
- Advancing precision prognostication in neuro-oncology: Machine learning models for data-driven personalized survival predictions in IDH-wildtype glioblastoma.Neuro-oncology advancesArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Previous studies have found that gene expression levels are associated with prognosis and some genes can be used to predict the survival risk of glioblastoma (GBM) patients. However, most of them just built the survival-related gene signature, and personal survival risk can be evaluated only in group. This study aimed to find the prognostic survival related genes of GBM, and construct survival risk prediction model, which can be used to evaluate survival risk by individual. We collected gene expression data and clinical information from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Cox regression analysis and LASSO-cox regression analysis were performed to get survival-related genes and establish the overall survival prediction model. The ROC curve and Kaplan Meier analysis were used to evaluate the prediction ability of the model in training set and two independent cohorts. We also analyzed the biological functions of survival-related genes by GO and KEGG enrichment analysis. We identified 99 genes associated with overall survival and selected 16 genes (
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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 Socratic graph.