ArticleFrontiers in cell and developmental biology2021
SUMOylation Regulator-Related Molecules Can Be Used as Prognostic Biomarkers for Glioblastoma.
Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses.BMC cancer · 2024Pooled it
- Tumor suppressor syntaxin binding protein 1 regulates alternative splicing of DNA repair genes related to radiation sensitivity in breast cancer cells.Oncology letters · 2026Article
- UBA2: the gatekeeper of the sumoylation pathway and its multifaceted roles in human diseases and therapeutic prospects.Clinical and experimental medicine · 2026Review
- Targeting SUMOylation in glioblastoma: A novel avenue for therapy and biomarker discovery.Genes & diseases · 2026Review
- Dual Regulation of Post-Translational Modification of Proteins: Bottlenecks and Breakthroughs in NK Cell Therapy for Glioblastoma.International journal of general medicine · 2026Review
- Nuclear pore complex protein RANBP2 and related SUMOylation in solid malignancies.Genes & diseases · 2025Review
- Expressions of the satellite repeat HSAT5 and transposable elements are implicated in disease progression and survival in glioma.Turkish journal of biology = Turk biyoloji dergisi · 2024Article
- Emerging role of SENP1 in tumorigenesis and cancer therapy.Frontiers in pharmacology · 2024Review
- PIAS family gene expression: implications for prognosis, immunomodulation, and chemotherapy response.American journal of translational research · 2024Article
- Transcription factor YY1 mediates self-renewal of glioblastoma stem cells through regulation of the SENP1/METTL3/MYC axis.Cancer gene therapy · 2023Article
- Non-Association of Driver Alterations in PTEN with Differential Gene Expression and Gene Methylation in IDH1 Wildtype Glioblastomas.Brain sciences · 2023Article
- AnIranian journal of basic medical sciences · 2023Article
- Cancer-Associated Dysregulation of Sumo Regulators: Proteases and Ligases.International journal of molecular sciences · 2022Review
- Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients.BMC cancer · 2022Article
- Molecular Insights and Prognosis Associated With RBM8A in Glioblastoma.Frontiers in molecular biosciences · 2022Article
- Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionSUMOylation is one of the post-translational modifications. The relationship between the expression of SUMOylation regulators and the prognosis of glioblastoma is not quite clear. MATERIALS AND
methodsThe single nucleotide variant data, the transcriptome data, and survival information were acquired from The Cancer Genome Atlas, Gene Expression Omnibus, and cBioportal database. Wilcoxon test was used to analyze differentially expressed genes between glioblastoma and normal brain tissues. Gene set enrichment analysis was conducted to find the possible functions. One risk scoring model was built by the least absolute shrinkage and selection operator Cox regression. Kaplain-Meier survival curves and receiver operating characteristic curves were applied to evaluate the effectiveness of the model in predicting the prognosis of glioblastoma.
resultsSingle-nucleotide variant mutations were found in SENP7, SENP3, SENP5, PIAS3, RANBP2, USPL1, SENP1, PIAS2, SENP2, and PIAS1. Moreover, UBE2I, UBA2, PIAS3, and SENP1 were highly expressed in glioblastoma, whereas PIAS1, RANBP2, SENP5, and SENP2 were downregulated in glioblastoma. Functional enrichment analysis showed that the SUMOylation regulators of glioblastoma might involve cell cycle, DNA replication, and other functions. A prognostic model of glioblastoma was constructed based on SUMOylation regulator-related molecules (ATF7IP, CCNB1IP1, and LBH). Kaplain-Meier survival curves and receiver operating characteristic curves showed that the model had a strong ability to predict the overall survival of glioblastoma.
conclusionThis study analyzed the expression of 15 SUMOylation regulators in glioblastoma. The risk assessment model was constructed based on the SUMOylation regulator-related genes, which had a strong predictive ability for the overall survival of patients with glioblastoma. It might provide targets for the study of the relationship between SUMOylation and glioblastoma.
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