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<p>Cancer immunotherapy has transformed oncology; however, its efficacy remains limited in immunologically “cold” tumors with poor immune infiltration. Oncolytic virotherapy (OVT) offers a promising solution through dual mechanisms of selective tumor lysis and immune activation, with advances in genetic engineering further enhancing specificity and therapeutic potency. Despite encouraging clinical progress, the translation of OVT remains constrained by the limited predictive capacity of preclinical models. The concept of translational fidelity refers to the extent to which preclinical models accurately replicate human tumor biology and reliably predict clinical therapeutic responses. This review provides a systematic evaluation of OVT through a four-dimensional framework encompassing structural complexity, immune representation, microenvironmental gradients, and translational predictivity. Using this framework as an integrative lens, we compare conventional and advanced platforms, including three-dimensional organoids, hydrogels, and patient-derived xenografts, highlighting their ability to recapitulate tumor architecture and heterogeneity. However, persistent limitations such as incomplete immune integration, inadequate characterization of physicochemical gradients, and species-specific discrepancies continue to hinder reliable clinical translation and may lead to overestimation of therapeutic efficacy. We further examine emerging engineering strategies in oncolytic viruses and emphasize the need to incorporate immune dynamics, delivery constraints, and patient-specific variability into model design. Future directions focus on developing humanized, multi-dimensional platforms integrating bioengineering, artificial intelligence, and real-time microenvironmental monitoring. Collectively, this review underscores that improving translational fidelity through integrative modeling frameworks is critical for bridging the gap between preclinical findings and clinical outcomes, thereby advancing OVT as a reliable modality in cancer immunotherapy.</p> Graphical abstract <p></p>

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Oncolytic viruses in cancer therapy development: the evolution of cell culture models in preclinical research

  • 期刊论文

  • 发表日期：

    2026年6月2日

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  • Sneh Bhalani,
  • Prashant Parmar,
  • Ishita Modasiya,
  • Abhishek Padhi,
  • Ashwini Agarwal

摘要

Cancer immunotherapy has transformed oncology; however, its efficacy remains limited in immunologically “cold” tumors with poor immune infiltration. Oncolytic virotherapy (OVT) offers a promising solution through dual mechanisms of selective tumor lysis and immune activation, with advances in genetic engineering further enhancing specificity and therapeutic potency. Despite encouraging clinical progress, the translation of OVT remains constrained by the limited predictive capacity of preclinical models. The concept of translational fidelity refers to the extent to which preclinical models accurately replicate human tumor biology and reliably predict clinical therapeutic responses. This review provides a systematic evaluation of OVT through a four-dimensional framework encompassing structural complexity, immune representation, microenvironmental gradients, and translational predictivity. Using this framework as an integrative lens, we compare conventional and advanced platforms, including three-dimensional organoids, hydrogels, and patient-derived xenografts, highlighting their ability to recapitulate tumor architecture and heterogeneity. However, persistent limitations such as incomplete immune integration, inadequate characterization of physicochemical gradients, and species-specific discrepancies continue to hinder reliable clinical translation and may lead to overestimation of therapeutic efficacy. We further examine emerging engineering strategies in oncolytic viruses and emphasize the need to incorporate immune dynamics, delivery constraints, and patient-specific variability into model design. Future directions focus on developing humanized, multi-dimensional platforms integrating bioengineering, artificial intelligence, and real-time microenvironmental monitoring. Collectively, this review underscores that improving translational fidelity through integrative modeling frameworks is critical for bridging the gap between preclinical findings and clinical outcomes, thereby advancing OVT as a reliable modality in cancer immunotherapy.

Graphical abstract