Related Experiment Video
Updated: Apr 24, 2026
A Rapid Screening Workflow to Identify Potential Combination Therapy for GBM using Patient-Derived Glioma Stem Cells
Published on: March 28, 2021
Systematic design of combination therapy by targeting master regulators of coexisting diffuse midline glioma cell
Ester Calvo Fernández1,2, Lorenzo Tomassoni1,3, Xu Zhang4
1Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA.
Abstract:
Intratumor heterogeneity fundamentally challenges cancer treatment, as coexisting, molecularly distinct cell states with non-overlapping drug sensitivities can drive therapeutic resistance. We establish and validate a generalizable, network-based framework to systematically identify combination therapies targeting complementary tumor cell states. Applied to diffuse midline glioma (DMG)-a universally fatal pediatric malignancy-this approach identified master regulator protein dependencies in seven coexisting cell states, confirmed by pooled CRISPR-Cas9 assays. Perturbational transcriptional profiles for 372 clinically relevant drugs prioritized candidates predicted to invert state-specific master regulator activity. State-selective drug sensitivity was validated for eight out of nine (89%) drugs in vivo, including avapritinib, ruxolitinib and larotrectinib. Compared with monotherapy, co-administering drugs targeting complementary states significantly prolonged survival across virtually all combinations, with avapritinib plus ruxolitinib extending median survival nearly threefold versus vehicle and 1.5-fold versus avapritinib alone. These findings establish clinically actionable DMG combinations and a tumor-agnostic and mutation-agnostic framework for rational combination therapy design.
Insights
This study presents a network-based framework to identify combination cancer therapies by targeting distinct tumor cell states. This approach successfully identified effective drug combinations for diffuse midline glioma, significantly improving survival rates.
Area of Science:
- Oncology
- Computational Biology
- Genomics
Background:
- Intratumor heterogeneity drives therapeutic resistance by presenting diverse cancer cell states with unique drug sensitivities.
- Diffuse midline glioma (DMG) is a pediatric malignancy with a poor prognosis, often complicated by treatment resistance.
Purpose of the Study:
- To develop and validate a generalizable, network-based framework for identifying combination therapies targeting complementary tumor cell states.
- To apply this framework to diffuse midline glioma to discover novel therapeutic strategies.
Main Methods:
- A network-based computational framework was developed to identify master regulator dependencies across distinct tumor cell states.
- Pooled CRISPR-Cas9 screens and perturbational transcriptional profiling of 372 drugs were used to identify candidate therapies.
- In vivo validation of drug sensitivity and combination efficacy was performed.
Main Results:
- The framework identified master regulator dependencies in seven coexisting cell states within DMG.
- Eight out of nine (89%) prioritized drugs demonstrated state-selective sensitivity in vivo.
- Combination therapies, particularly avapritinib plus ruxolitinib, significantly prolonged survival compared to monotherapy or vehicle control.
Conclusions:
- The study establishes a tumor-agnostic and mutation-agnostic framework for rational combination therapy design.
- Clinically actionable combination therapies for diffuse midline glioma were identified, offering new hope for this fatal pediatric cancer.
