ArticlePeerJ2022
Exploring the potential biomarkers for prognosis of glioblastoma via weighted gene co-expression network analysis.
Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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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
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses.BMC cancer · 2024Pooled it
- DARS expression in JAK2V617F-positive myeloproliferative neoplasms: immunohistochemical analysis and clinical associations.Annals of hematology · 2026Article
- Sphingomyelin regulates the transcriptional machinery in nuclear lipid microdomains.Communications biology · 2025Article
- T cell-mediated tumor killing based signature to predict the prognosis and immunotherapy for glioblastoma.Heliyon · 2024Article
- Identifying key biomarkers and therapeutic candidates for post-COVID-19 depression through integrated omics and bioinformatics approaches.Translational neuroscience · 2024Article
- Proteomic and metabolomic signatures of U87 glioblastoma cells treated with cisplatin and/or paclitaxel.Annals of medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGlioblastoma (GBM) is the most common malignant tumor in the central system with a poor prognosis. Due to the complexity of its molecular mechanism, the recurrence rate and mortality rate of GBM patients are still high. Therefore, there is an urgent need to screen GBM biomarkers to prove the therapeutic effect and improve the prognosis.
resultsWe extracted data from GBM patients from the Gene Expression Integration Database (GEO), analyzed differentially expressed genes in GEO and identified key modules by weighted gene co-expression network analysis (WGCNA). GSE145128 data was obtained from the GEO database, and the darkturquoise module was determined to be the most relevant to the GBM prognosis by WGCNA (
conclusionWe used two public databases to identify four valuable biomarkers for GBM prognosis, namely DARS/GDI2/P4HA2/TRUB1, which have potential clinical application value and can be used as prognostic markers for GBM.
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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 OpenQuestion graph.