ArticleBMC cancer2025
Investigating potential drug targets for the treatment of glioblastoma: a Mendelian randomization study.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- eQTL analysis: A bridge from genome to mechanism.Genes & diseases · 2026Review
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.
Funding
Abstract
Glioblastoma (GBM), one of the most aggressive brain tumors, has a 5-year survival rate of less than 5%. Current standard therapies, including surgery, radiotherapy, and temozolomide (TMZ) chemotherapy, are limited by drug resistance and the blood-brain barrier. Integrating expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) data has shown promise in uncovering disease mechanisms and therapeutic targets. This study combined eQTL and pQTL analyses to identify potential GBM-related genes and circulating plasma proteins for therapeutic exploration. Using transcriptomic data from The Cancer Genome Atlas (TCGA), we identified 2,528 differentially expressed genes, including GPX7 and CXCL10. eQTL-MR analysis identifies GBM-associated differentially expressed genes and constructs a protein-protein interaction (PPI) network.Integrating pQTL data from the deCODE database, pQTL-MR, and colocalization analyses validated the therapeutic potential of GPX7 and CXCL10.These findings provide new perspectives on GBM biology and suggest actionable targets for therapy. Despite limitations due to sample size and population-specific data, this study highlights GPX7 and CXCL10 as promising candidates for further investigation and lays the foundation for targeted GBM treatments.
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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.