ArticleACS omega2021
The Big Picture of Glioblastoma Malignancy: A Meta-Analysis of Glioblastoma Proteomics to Identify Altered Biological Pathways.
Article in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- MALDI-TOF Mass Spectrometry for Glioblastoma Secretome Biomarker Screening: A Review of Challenges and Perspectives.Current issues in molecular biology · 2026Review
- Ribosome plasticity in glioblastoma: a multi-omics framework for future investigation.Frontiers in genetics · 2025Review
- Proteomics Studies on Extracellular Vesicles Derived from Glioblastoma: Where Do We Stand?International journal of molecular sciences · 2024Review
- Bioenergetic Profiling in Glioblastoma Multiforme Patients with Different Clinical Outcomes.Metabolites · 2023Article
- Glioblastoma survival is associated with distinct proteomic alteration signatures post chemoirradiation in a large-scale proteomic panel.Frontiers in oncology · 2023Article
- Preclinical and Clinical Applications of Metabolomics and Proteomics in Glioblastoma Research.International journal of molecular sciences · 2022Review
- Article
- Membrane proteomic profiling to identify candidate therapy targets for glioblastoma infiltration.Neuro-oncology advancesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioblastoma is a highly malignant cancer with no effective treatment. It is vital to elucidate the mechanisms which drive glioblastoma in order to identify therapeutic targets. The differences in protein expression between glioblastoma, grade I-III glioma, and normal brain tissue reflect the functional alterations driving malignancy. However, proteomic analysis of glioblastoma has been hampered by the heterogeneity of glioblastoma and the variety of methodology used in its study. To reduce these inconsistencies, we performed a meta-analysis of the literature published since 2015, including 14 datasets from eight papers comparing the whole proteome of glioblastoma to normal brain or grade I-III glioma. We found that 154 proteins were commonly upregulated and 116 proteins were commonly downregulated in glioblastoma compared to normal brain. Meanwhile, 240 proteins were commonly upregulated and 125 proteins were commonly downregulated in glioblastoma compared to grade I-III glioma. Functional enrichment analysis revealed upregulation of proteins involved in mRNA splicing and the immune system and downregulation of proteins involved in synaptic signaling and glucose and glutamine metabolism. The identification of these altered biological pathways provides a basis for deeper investigation in the pursuit of an effective treatment for glioblastoma.
Identifiers
What OpenQuestion holds
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.