Related Experiment Video
Updated: Sep 21, 2025
Author Spotlight: Patient-Informed 3D Model for Studying Glioblastoma Invasion via Interstitial Fluid Flow
Published on: October 18, 2024
Agent-based computational modeling of glioblastoma predicts that stromal density is central to oncolytic virus
Adrianne L Jenner1,2, Munisha Smalley3, David Goldman4
1Department of Mathematics and Statistics, Université de Montréal, Montréal, QC, Canada.
Abstract:
Oncolytic viruses (OVs) are emerging cancer immunotherapy. Despite notable successes in the treatment of some tumors, OV therapy for central nervous system cancers has failed to show efficacy. We used an ex vivo tumor model developed from human glioblastoma tissue to evaluate the infiltration of herpes simplex OV rQNestin (oHSV-1) into glioblastoma tumors. We next leveraged our data to develop a computational, model of glioblastoma dynamics that accounts for cellular interactions within the tumor. Using our computational model, we found that low stromal density was highly predictive of oHSV-1 therapeutic success, suggesting that the efficacy of oHSV-1 in glioblastoma may be determined by stromal-to-tumor cell regional density. We validated these findings in heterogenous patient samples from brain metastatic adenocarcinoma. Our integrated modeling strategy can be applied to suggest mechanisms of therapeutic responses for central nervous system cancers and to facilitate the successful translation of OVs into the clinic.
Insights
Oncolytic viruses (OVs) show promise for cancer immunotherapy but struggle with brain tumors. Low stromal density predicts success for herpes simplex OV rQNestin (oHSV-1) in glioblastoma, guiding future treatments.
Area of Science:
- Oncology
- Virology
- Computational Biology
Background:
- Oncolytic viruses (OVs) are a promising cancer immunotherapy approach.
- OV therapy has shown limited efficacy in central nervous system cancers, including glioblastoma.
- Understanding factors limiting OV efficacy in brain tumors is crucial for clinical translation.
Purpose of the Study:
- To evaluate the infiltration of herpes simplex OV rQNestin (oHSV-1) into human glioblastoma tumors ex vivo.
- To develop a computational model of glioblastoma dynamics to predict OV therapeutic success.
- To identify key tumor microenvironment factors influencing oHSV-1 efficacy in central nervous system cancers.
Main Methods:
- Utilized an ex vivo human glioblastoma tumor model to assess oHSV-1 infiltration.
- Developed a computational model incorporating cellular interactions within glioblastoma.
- Validated model predictions using patient samples from brain metastatic adenocarcinoma.
Main Results:
- Low stromal density was identified as a strong predictor of oHSV-1 therapeutic success in glioblastoma.
- Stromal-to-tumor cell regional density significantly influences oHSV-1 efficacy.
- Findings were validated in heterogeneous patient samples, including brain metastatic adenocarcinoma.
Conclusions:
- Stromal density is a critical determinant of oncolytic virus efficacy in glioblastoma.
- An integrated computational modeling strategy can predict OV response in central nervous system cancers.
- This approach facilitates the clinical translation of OV therapy for brain tumors.
