Robust envelope exchange platform for oncolytic measles virus

S Neault1, S Bossow2, C Achard3

  • 1Ottawa Hospital Research Institute, Cancer Therapeutics Program, 501 Smyth Road, Ottawa, Ontario, Canada; University of Ottawa, Faculty of Medicine, 451 Smyth Rd, Ottawa, Ontario, Canada.

Insights

This study developed a platform to engineer oncolytic measles viruses (MeV) resistant to pre-existing antibodies. A chimeric MeV using canine distemper virus (CDV) envelope proteins successfully overcame immune barriers for potential cancer virotherapy.

Area of Science:

  • Oncolytic virotherapy
  • Viral immunology
  • Molecular virology

Background:

  • Oncolytic viruses (OV) offer a promising cancer treatment strategy.
  • Pre-existing immunity, particularly neutralizing antibodies against measles virus (MeV), hinders OV efficacy.
  • Antibodies target MeV envelope glycoproteins (hemagglutinin and fusion proteins).

Purpose of the Study:

  • To engineer oncolytic MeV resistant to pre-existing anti-MeV antibodies.
  • To develop a versatile platform for rapid envelope exchange in MeV.
  • To create chimeric MeV with altered surface glycoproteins for immune evasion.

Main Methods:

  • Developed a novel pseudotyping platform for MeV envelope exchange.
  • Exchanged MeV F and H proteins with glycoproteins from vesicular stomatitis virus (VSV), Newcastle disease virus (NDV), and canine distemper virus (CDV).
  • Assessed the functionality and propagation of engineered chimeric MeV.

Main Results:

  • Successfully generated a platform for rapid MeV envelope exchange.
  • Engineered MeV-VSV and MeV-NDV pseudotypes were non-functional.
  • An MeV-CDV pseudotype was successfully propagated to high titers, demonstrating functionality.
  • Highlighted the platform's pseudotyping tolerance and limitations.

Conclusions:

  • A robust platform for engineering immune-evasive oncolytic MeV was established.
  • Chimeric MeV expressing CDV envelope proteins show potential for overcoming anti-MeV immunity.
  • Further research is needed to optimize pseudotyping and assess therapeutic efficacy.