ArticleFrontiers in cell and developmental biology2020
Identification of Prognostic Model and Biomarkers for Cancer Stem Cell Characteristics in Glioblastoma by Network Analysis of Multi-Omics Data and Stemness Indices.
Article in Frontiers in cell and developmental biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.
- Survival prediction landscape: an in-depth systematic literature review on activities, methods, tools, diseases, and databases.Frontiers in artificial intelligence · 2024Pooled it
- Construction and validation of risk prediction model for glioblastoma associated with cancer stem cells and disulfidptosis.Translational cancer research · 2026Article
- RNA adenosine modification writers define characteristics of immunity and prognosis in head and neck squamous cell carcinoma.Discover oncology · 2025Article
- Multiomic traits reveal that critical irinotecan-related core regulator FSTL3 promotes CRC progression and affects ferroptosis.Cancer cell international · 2025Article
- Bioinformatic analysis of molecular expression patterns during the development and progression of metabolic dysfunction-associated steatotic liver disease (MASLD).Scientific reports · 2025Article
- Investigating combined hypoxia and stemness indices for prognostic transcripts in gastric cancer: Machine learning and network analysis approaches.Biochemistry and biophysics reports · 2025Article
- A novel TAp73-inhibitory compound counteracts stemness features of glioblastoma stem cells.Molecular oncology · 2025Article
- Integrative analysis of metabolism subtypes and identification of prognostic metabolism-related genes for glioblastoma.Bioscience reports · 2024Article
- Cuprotosis clusters predict prognosis and immunotherapy response in low-grade glioma.Apoptosis : an international journal on programmed cell death · 2024Article
- Article
- Identification of a Fibroblast-Related Prognostic Model in Glioma Based on Bioinformatics Methods.Biomolecules · 2022Article
- Article
- Construction and Validation of a Prognostic Model Based on mRNAsi-Related Genes in Breast Cancer.Computational and mathematical methods in medicine · 2022Article
- Ferroptosis-Related Gene Contributes to Immunity, Stemness and Predicts Prognosis in Glioblastoma Multiforme.Frontiers in neurology · 2022Article
- Establishment and Validation of a Peroxisome-related Gene Signature for Prognostic Prediction and Immune Distinction in Hepatocellular Carcinoma.Journal of Cancer · 2022Article
- Identification of Implications of Angiogenesis and m6A Modification on Immunosuppression and Therapeutic Sensitivity in Low-Grade Glioma by Network Computational Analysis of Subtypes and Signatures.Frontiers in immunology · 2022Article
- Extended Application of Genomic Selection to Screen Multi-Omics Data for the Development of Novel Pyroptosis-Immune Signatures and Predicting Immunotherapy of Glioma.Frontiers in pharmacology · 2022Article
- Identification of EMT-Related Genes and Prognostic Signature With Significant Implications on Biological Properties and Oncology Treatment of Lower Grade Gliomas.Frontiers in cell and developmental biology · 2022Article
- Multiomics Data Analysis and Identification of Immune-Related Prognostic Signatures With Potential Implications in Prognosis and Immune Checkpoint Blockade Therapy of Glioblastoma.Frontiers in neurology · 2022Article
- Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma.Frontiers in immunology · 2022Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The progression of most human cancers mainly involves the gradual accumulation of the loss of differentiated phenotypes and the sequential acquisition of progenitor and stem cell-like features. Glioblastoma multiforme (GBM) stem cells (GSCs), characterized by self-renewal and therapeutic resistance, play vital roles in GBM. However, a comprehensive understanding of GBM stemness remains elusive. Two stemness indices, mRNAsi and EREG-mRNAsi, were employed to comprehensively analyze GBM stemness. We observed that mRNAsi was significantly related to multi-omics parameters (such as mutant status, sample type, transcriptomics, and molecular subtype). Moreover, potential mechanisms and candidate compounds targeting the GBM stemness signature were illuminated. By combining weighted gene co-expression network analysis with differential analysis, we obtained 18 stemness-related genes, 10 of which were significantly related to survival. Moreover, we obtained a prediction model from both two independent cancer databases that was not only an independent clinical outcome predictor but could also accurately predict the clinical parameters of GBM. Survival analysis and experimental data confirmed that the five hub genes (CHI3L2, FSTL3, RPA3, RRM2, and YTHDF2) could be used as markers for poor prognosis of GBM. Mechanistically, the effect of inhibiting the proliferation of GSCs was attributed to the reduction of the ratio of CD133 and the suppression of the invasiveness of GSCs. The results based on an
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