Investigating potential drug targets for the treatment of glioblastoma: a Mendelian randomization study

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 quant...

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Main Authors: Hongwei Zhang, Zixuan Wang, Xiaolong Qiao, Jiaxing Wu, Chuandong Cheng
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Cancer
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Online Access:https://doi.org/10.1186/s12885-025-13979-3
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author Hongwei Zhang
Zixuan Wang
Xiaolong Qiao
Jiaxing Wu
Chuandong Cheng
author_facet Hongwei Zhang
Zixuan Wang
Xiaolong Qiao
Jiaxing Wu
Chuandong Cheng
author_sort Hongwei Zhang
collection DOAJ
description 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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spelling doaj-art-ad68667e7e0047e1969acb977d4a67e92025-08-20T03:10:17ZengBMCBMC Cancer1471-24072025-04-0125111810.1186/s12885-025-13979-3Investigating potential drug targets for the treatment of glioblastoma: a Mendelian randomization studyHongwei Zhang0Zixuan Wang1Xiaolong Qiao2Jiaxing Wu3Chuandong Cheng4Department of Neurosurgery, Centre for Leading Medicine and Advanced Technologies of IHM, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of ChinaDepartment of Neurosurgery, Centre for Leading Medicine and Advanced Technologies of IHM, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of ChinaDepartment of Neurosurgery, Centre for Leading Medicine and Advanced Technologies of IHM, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of ChinaDepartment of Neurosurgery, Centre for Leading Medicine and Advanced Technologies of IHM, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of ChinaDepartment of Neurosurgery, Centre for Leading Medicine and Advanced Technologies of IHM, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of ChinaAbstract 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.https://doi.org/10.1186/s12885-025-13979-3GlioblastomaeQTLpQTLMendelian randomizationGPX7CXCL10
spellingShingle Hongwei Zhang
Zixuan Wang
Xiaolong Qiao
Jiaxing Wu
Chuandong Cheng
Investigating potential drug targets for the treatment of glioblastoma: a Mendelian randomization study
BMC Cancer
Glioblastoma
eQTL
pQTL
Mendelian randomization
GPX7
CXCL10
title Investigating potential drug targets for the treatment of glioblastoma: a Mendelian randomization study
title_full Investigating potential drug targets for the treatment of glioblastoma: a Mendelian randomization study
title_fullStr Investigating potential drug targets for the treatment of glioblastoma: a Mendelian randomization study
title_full_unstemmed Investigating potential drug targets for the treatment of glioblastoma: a Mendelian randomization study
title_short Investigating potential drug targets for the treatment of glioblastoma: a Mendelian randomization study
title_sort investigating potential drug targets for the treatment of glioblastoma a mendelian randomization study
topic Glioblastoma
eQTL
pQTL
Mendelian randomization
GPX7
CXCL10
url https://doi.org/10.1186/s12885-025-13979-3
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AT zixuanwang investigatingpotentialdrugtargetsforthetreatmentofglioblastomaamendelianrandomizationstudy
AT xiaolongqiao investigatingpotentialdrugtargetsforthetreatmentofglioblastomaamendelianrandomizationstudy
AT jiaxingwu investigatingpotentialdrugtargetsforthetreatmentofglioblastomaamendelianrandomizationstudy
AT chuandongcheng investigatingpotentialdrugtargetsforthetreatmentofglioblastomaamendelianrandomizationstudy