Ubiquitin-Proteasome System-Related Prognostic Model and Immune Landscape in Glioblastoma.
Overview
- Department of Neurosurgery, General Hospital of Northern Theater Command, Shenyang, China, syjqzyy.com
- Department of General Practice, General Hospital of Northern Theater Command, Shenyang, China, syjqzyy.com
- Department of Laboratory, 32295 Army Hospital, Liaoyang, China
- Department of Nursing, General Hospital of Northern Theater Command, Shenyang, China, syjqzyy.com
Abstract
Background: Glioblastoma (GBM) is a highly aggressive brain tumor with poor prognosis. This study is aimed at establishing an ubiquitin‐proteasome system (UPS)–related prognostic model and investigating its link to immune infiltration and therapy response.
Materials and Methods: GBM datasets were obtained from public databases. Ubiquitin‐proteasome system–related genes (UPSGs) were identified from literature. Consensus clustering defined UPS‐based GBM subtypes. Differentially expressed genes (DEGs) were screened, and a prognostic model was constructed using univariate Cox, least absolute shrinkage and selection operator (LASSO), and stepwise regression. The model′s performance was validated using survival analysis and time‐dependent receiver operating characteristic (ROC) curves. Immune infiltration was assessed using single‐sample gene set enrichment analysis (ssGSEA), TIMER, and ESTIMATE. Drug sensitivity was assessed by correlating the half‐maximal inhibitory concentration (IC50) of candidate drugs with the risk score. Single‐cell RNA sequencing data were used to characterize UPSG expression across distinct cell subpopulations in GBM. For in vitro validation, key UPSGs were silenced in GBM cell lines, and cell proliferation, migration, and invasion were measured using Cell Counting Kit‐8 (CCK‐8), wound healing, and Transwell assays, respectively.
Results: Two UPS‐related GBM subtypes were identified. Six genes (IGFBP6, CTSD, SPAG4, ZNF560, COL22A1, and HOXC13) formed the prognostic model, where high Riskscore indicated poor survival. High Riskscore correlated with greater immune infiltration, including CD8+ T cells and macrophages. IC50 values of 24 drugs were significantly associated with Riskscore. Single‐cell analysis revealed seven GBM subpopulations; notably, COL22A1 was enriched in MES‐like cells, and CTSD in macrophages. IGFBP6 promoted GBM cell proliferation, migration, and invasion.
Conclusion: This study establishes a UPS‐based prognostic model for GBM that links immune infiltration and drug sensitivity, providing potential biomarkers and therapeutic targets for GBM.
Reproduced under the paper's license (CC BY), from the paper cited above.
Code
The paper links to its data, not to its authors' code: see the Data section.
Tracing map
A tracing map links a paper to the code its authors published: this paper has none, so it has no map.
Data
Datasets cited
- geo:GSE273274 — at NCBI GEO; found in the text, “2.1. Data Acquisition”
Other data links
- ncbi.nlm.nih.gov/
geo — NCBI; found in “Data Availability Statement”
Data Availability Statement
The datasets generated and/
Reproduced under the paper's license (CC BY), from the paper cited above.
Versions
The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.
Version 2, 28 September 2026
- Issue: — → 1
Version 1, 27 September 2026: the first record
Recorded: type, language, journal, volume, pages, dates, 5 authors, 6 keywords, 41 references.
Cite
This paper
Huo, D., Feng, Y., Yu, Z., Xie, W., & Jin, H. (2026). Ubiquitin-Proteasome System-Related Prognostic Model and Immune Landscape in Glioblastoma. International journal of genomics, 2026(1), 2045937. https://
BibTeX
@article{huo2026ubiquiti
author = {Huo, Da and Feng, Yue and Yu, Zheng and Xie, Wanting and Jin, Hai},
title = {{Ubiquitin-Proteasome System-Related Prognostic Model and Immune Landscape in Glioblastoma}},
journal = {International journal of genomics},
year = {2026},
month = jul,
volume = {2026},
number = {1},
pages = {2045937},
publisher = {Wiley},
issn = {2314-436X},
doi = {10.1155/
url = {https://
pmid = {42488132},
pmcid = {PMC13390022}
}
RIS
TY - JOUR
AU - Huo, Da
AU - Feng, Yue
AU - Yu, Zheng
AU - Xie, Wanting
AU - Jin, Hai
TI - Ubiquitin-Proteasome System-Related Prognostic Model and Immune Landscape in Glioblastoma
T2 - International journal of genomics
J2 - Int J Genomics
PY - 2026
DA - 2026/
VL - 2026
IS - 1
SP - 2045937
SN - 2314-436X
PB - Wiley
DO - 10.1155/
UR - https://
LA - en
ER -
CSL-JSON
{
"id": "10.1155/
"type": "article-journal",
"title": "Ubiquitin-Proteasome System-Related Prognostic Model and Immune Landscape in Glioblastoma",
"container-title": "International journal of genomics",
"author": [
{
"family": "Huo",
"given": "Da"
},
{
"family": "Feng",
"given": "Yue"
},
{
"family": "Yu",
"given": "Zheng"
},
{
"family": "Xie",
"given": "Wanting"
},
{
"family": "Jin",
"given": "Hai"
}
],
"container-title-short":
"volume": "2026",
"issue": "1",
"page": "2045937",
"DOI": "10.1155/
"PMID": "42488132",
"PMCID": "PMC13390022",
"ISSN": "2314-436X",
"publisher": "Wiley",
"URL": "https://
"language": "en",
"issued": {
"date-parts": [
[
2026,
7,
22
]
]
}
}
Similar papers
The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.
- [1] doi:10.3390/cancers18132092
- TGFB2 as a Prognostic Biomarker Associated with Myeloid-Enriched, Multi-Checkpoint-Activat
ed Immunosuppression in Diffuse Glioma: A Multi-Cohort Transcriptomic Study. Journal: CancersIn common: genetics / omics, other condition, 3 references - [2] doi:10.1111/jcmm.71154
- Mitophagy-Oxidative Stress Molecular Subtypes Define an Immunosuppressive Ecosystem and Vulnerabilities in Glioblastoma.Journal: Journal of cellular and molecular medicineIn common: genetics / omics, other condition, 3 references
- [3] doi:10.1186/s12880-026-02434-9 [code]
- Exploring the value of peritumoral brain zone for classification of two malignant brain tumors based on the MRI interpretable models.Journal: BMC medical imagingIn common: clinical / translational, other condition, 2 references
- [4] doi:10.1038/s41467-026-77170-3 [code]
- DNA methylation profiling identifies long-range epigenetic silencing of clustered protocadherins as a key determinant of meningioma progression.Journal: Nature communicationsIn common: genetics / omics, other condition, 2 references
- [5] doi:10.1186/s12974-026-03964-3
- Circulating immune profiling reveals impaired monocyte states and trajectories driving immunosuppression in glioblastoma.Journal: Journal of neuroinflammationIn common: clinical / translational, genetics / omics, other condition, 1 reference
- [6] doi:10.1093/neuonc/noag119 [code]
- Single-nucleus profiling of postmortem diffuse midline gliomas identifies mitochondrial biogenesis as a resistance mechanism to imipridone therapy.Journal: Neuro-oncologyIn common: genetics / omics, other condition, 2 references
- [7] doi:10.3389/fncel.2026.1713437 [code]
- Single-nucleus transcriptomics identifies cell cycle and synaptic pathway dysregulation during OPC-to-glioma progression.Journal: Frontiers in cellular neuroscienceIn common: genetics / omics, other condition, 2 references
- [8] doi:10.1177/11769351261460625
- GFAP-Dependent Transcriptional Dynamics and Cellular Heterogeneity in Primary, Recurrent, and Grade III Gliomas.Journal: Cancer informaticsIn common: genetics / omics, other condition, 2 references
- [9] doi:10.1021/acs.jproteome.5c01173
- Proteomic Analysis Identifies ATE1-Dependent Arginylation Dysregulation across Meningioma Grades.Journal: Journal of proteome researchIn common: genetics / omics, other condition, 2 references
- [10] doi:10.3390/ijms27136068 [code]
- Loss of Neuropeptide Y Signaling Accompanies the Neural-to-Mesenchymal Transcriptional Transition in Glioblastoma: A Multi-Scale Transcriptomic Analysis.Journal: International journal of molecular sciencesIn common: genetics / omics, other condition, 2 references
Contribute
The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.
Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.
Claim this paper
Correct its record
Say what each link of this record is, remove the ones that are not the paper's, add the ones that are missing. The correction becomes a new version of the record, in its Versions section.
Request its removal
To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).
Discussion, reproductions, activity
Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.
Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.
Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.
