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Updated: Jul 10, 2025
A Rapid Screening Workflow to Identify Potential Combination Therapy for GBM using Patient-Derived Glioma Stem Cells
Published on: March 28, 2021
Pharmacogenomic Analysis of Combined Therapies against Glioblastoma Based on Cell Markers from Single-Cell Sequencing
Junying Liu1, Ruixin Wu2, Shouli Yuan3
1NatPro Center, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, D02 PN40 Dublin, Ireland.
Abstract:
Glioblastoma is the most common and aggressive form of primary brain cancer and the lack of viable treatment options has created an urgency to develop novel treatments. Personalized or predictive medicine is still in its infancy stage at present. This research aimed to discover biomarkers to inform disease progression and to develop personalized prophylactic and therapeutic strategies by combining state-of-the-art technologies such as single-cell RNA sequencing, systems pharmacology, and a polypharmacological approach. As predicted in the pyroptosis-related gene (PRG) transcription factor (TF) microRNA (miRNA) regulatory network, TP53 was the hub gene in the pyroptosis process in glioblastoma (GBM). A LASSO Cox regression model of pyroptosis-related genes was built to accurately and conveniently predict the one-, two-, and three-year overall survival rates of GBM patients. The top-scoring five natural compounds were parthenolide, rutin, baeomycesic acid, luteolin, and kaempferol, which have NFKB inhibition, antioxidant, lipoxygenase inhibition, glucosidase inhibition, and estrogen receptor agonism properties, respectively. In contrast, the analysis of the cell-type-specific differential expression-related targets of natural compounds showed that the top five subtype cells targeted by natural compounds were endothelial cells, microglia/macrophages, oligodendrocytes, dendritic cells, and neutrophil cells. The current approach-using the pharmacogenomic analysis of combined therapies-serves as a model for novel personalized therapeutic strategies for GBM treatment.
Insights
Researchers identified TP53 as a key gene in glioblastoma pyroptosis and developed a model to predict survival. They also found natural compounds that target specific brain cancer cells, paving the way for personalized therapies.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Background:
- Glioblastoma (GBM) is an aggressive brain cancer with limited treatment options.
- Personalized medicine approaches for GBM are still developing.
- Novel biomarkers and therapeutic strategies are urgently needed.
Purpose of the Study:
- To discover biomarkers for glioblastoma progression.
- To develop personalized treatment strategies using advanced technologies.
- To identify potential natural compound therapies for glioblastoma.
Main Methods:
- Integrated single-cell RNA sequencing, systems pharmacology, and polypharmacology.
- Constructed a pyroptosis-related gene (PRG) transcription factor (TF) microRNA (miRNA) regulatory network.
- Utilized a LASSO Cox regression model for survival prediction and analyzed cell-type-specific drug targets.
Main Results:
- TP53 was identified as a hub gene in glioblastoma pyroptosis.
- A LASSO Cox model accurately predicted glioblastoma patient survival rates.
- Top natural compounds (parthenolide, rutin, etc.) showed specific inhibitory properties, targeting endothelial cells, microglia/macrophages, and other brain cell types.
Conclusions:
- The study provides a novel pharmacogenomic approach for glioblastoma treatment.
- Identified key genes and natural compounds for personalized glioblastoma therapy.
- This integrated strategy serves as a model for future personalized cancer treatments.
