Comparative evaluation of oncolytic viruses reveals opposing preferences for glioblastoma subtypes

Tine Deconinck1, Tim Dierckx1, Frederik De Smet2

  • 1KU Leuven Department of Microbiology, Immunology and Transplantation, Molecular Genetics and Therapeutics in Virology and Oncology Research Group, Rega Institute, Leuven Cancer Institute, 3000 Leuven, Belgium.

Insights

Oncolytic viruses (OVs) show promise against glioblastoma (GBM), but tumor diversity limits effectiveness. This study identifies viral activity patterns linked to GBM subtypes, guiding personalized OV therapy selection for better outcomes.

Area of Science:

  • Neuro-oncology
  • Virology
  • Immunology

Background:

  • Glioblastoma (GBM) is an aggressive brain tumor with poor survival rates.
  • Oncolytic viruses (OVs) offer a promising therapeutic strategy by selectively targeting cancer cells and stimulating anti-tumor immunity.
  • Tumor heterogeneity in GBM presents a significant challenge to the efficacy of OV therapies.

Purpose of the Study:

  • To comparatively analyze the oncolytic efficacy of 15 clinically relevant viruses against a panel of 14 diverse GBM cell lines.
  • To identify determinants of OV effectiveness and understand OV activity profiles in relation to GBM subtypes.
  • To explore the potential for combinatorial or personalized OV therapies in GBM treatment.

Main Methods:

  • Comparative analysis of oncolytic virus efficacy.
  • Utilized a diverse panel of 14 patient-derived GBM cell lines.
  • Performed correlation analysis between viral activity and gene expression profiles.

Main Results:

  • Identified two distinct clusters of viruses with opposing oncolytic activity profiles and GBM subtype preferences.
  • Oncolytic activity correlated with gene expression related to interferon, neurodevelopment, and extracellular matrix.
  • Observed inverse correlations in activity between the two OV groups.

Conclusions:

  • Diverse oncolytic viruses share common determinants of efficacy.
  • GBM tumor subtype can guide the selection of the most effective OV.
  • Findings support the development of combinatorial or personalized OV therapies for glioblastoma.