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Oncolytic Viruses in the Era of Omics, Computational Technologies, and Modeling: Thesis, Antithesis, and Synthesis

Laura Menotti1, Andrea Vannini1

  • 1Department of Pharmacy and Biotechnology, University of Bologna, 40126 Bologna, Italy.

International Journal of Molecular Sciences
|December 23, 2023
PubMed

Insights

Oncolytic viruses (OVs) offer advanced cancer therapy. Big data analysis and computational modeling are key to personalizing OV engineering for effective cancer immunovirotherapy.

Area of Science:

  • Oncology
  • Virology
  • Computational Biology
  • Systems Biology

Background:

  • Oncolytic viruses (OVs) represent a promising frontier therapy for refractory cancers.
  • Integrating OVs with immunomodulation strategies enhances their therapeutic potential.
  • Cancer immunovirotherapy generates vast amounts of complex 'omic' data.

Purpose of the Study:

  • To review how big data analysis and computational technologies aid in interpreting 'omic' data for cancer immunovirotherapy.
  • To discuss the role of simulation, modeling, and synthetic biology in engineering personalized OVs.
  • To explore the development of OVs as patient-tailored theranostic agents.

Main Methods:

  • Review of current literature on big data analysis in cancer immunovirotherapy.
  • Discussion of simulation and modeling approaches for OV design.
  • Exploration of synthetic biology and personalized OV engineering strategies.

Main Results:

  • Big data analysis and computational tools are crucial for integrating complex 'omic' information.
  • These technologies facilitate the development of novel synthetic biology and personalized OV engineering approaches.
  • The integration of data and computational methods enables the creation of patient-tailored OV recombinants.

Conclusions:

  • Computational technologies and big data analysis are indispensable for advancing cancer immunovirotherapy.
  • These tools support the engineering of personalized oncolytic viruses for effective tumor clearance.
  • Future advancements may involve artificial intelligence to further personalize OV theranostics.
Keywords:
OV combination therapycancer theranosticscancer therapyimmunopeptidomicsinfection computational modelinginfection mathematical modelingoncolytic immunovirotherapyoncolytic virusvirus synthetic biology

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