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<p>Ovarian cancer poses a persistent therapeutic challenge due to late-stage diagnosis, frequent relapse, and resistance to standard therapies. While oncolytic viruses (OVs) offer a promising immunotherapeutic approach, their clinical efficacy remains limited by an immunosuppressive tumor microenvironment (TME) and inefficient delivery. To address these barriers, we developed a dynamic microfluidic-based 3D ex vivo tumor model to evaluate a systemic, multimodal treatment strategy in ovarian cancer. The model incorporates perfusable tumor spheroids cocultured with peripheral blood mononuclear cells (PBMCs) and endothelial cells (HUVECs), enabling the simulation of vascularized tumor environments and systemic drug perfusion. All therapeutic agents—including the oncolytic adenovirus Ad5/3-D24-ICOSL-CD40L, cisplatin, paclitaxel, and nintedanib—were administered through flow-based circulation to more accurately replicate human pharmacokinetic conditions and tumor-drug interactions. Our results demonstrated that a priming regimen—where Ad5/3-D24-ICOSL-CD40L was administered 48&#xa0;h before chemotherapy—significantly outperformed the co-administration strategy, reducing spheroid areas and mitigating tumor rebound. Enhanced therapeutic response was associated with increased viral replication, sustained immunogenic cell death, and improved immune cell infiltration, underscoring the importance of sequencing and microenvironment preconditioning. This tumor-on-a-chip platform provides a physiologically relevant tool for real-time monitoring of treatment response, immune activation, and drug delivery under continuous flow. By bridging the gap between traditional in vitro models and in vivo studies, it offers a powerful preclinical system for optimizing combination regimens and advancing personalized therapies in ovarian cancer.</p> Graphical abstract <p></p>

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Dynamic 3D microfluidic platform for exploring combined targeted therapy, chemotherapy, and virotherapy delivery in ovarian cancer

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月3日

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  • Lukasz Kuryk,
  • Sara Mathlouthi,
  • Lisa Casagrande,
  • Cristiano Pesce,
  • Francesco Tognetti,
  • Alessio Malfanti,
  • Aleksander Masny,
  • Paolo Caliceti,
  • Mariangela Garofalo

摘要

Ovarian cancer poses a persistent therapeutic challenge due to late-stage diagnosis, frequent relapse, and resistance to standard therapies. While oncolytic viruses (OVs) offer a promising immunotherapeutic approach, their clinical efficacy remains limited by an immunosuppressive tumor microenvironment (TME) and inefficient delivery. To address these barriers, we developed a dynamic microfluidic-based 3D ex vivo tumor model to evaluate a systemic, multimodal treatment strategy in ovarian cancer. The model incorporates perfusable tumor spheroids cocultured with peripheral blood mononuclear cells (PBMCs) and endothelial cells (HUVECs), enabling the simulation of vascularized tumor environments and systemic drug perfusion. All therapeutic agents—including the oncolytic adenovirus Ad5/3-D24-ICOSL-CD40L, cisplatin, paclitaxel, and nintedanib—were administered through flow-based circulation to more accurately replicate human pharmacokinetic conditions and tumor-drug interactions. Our results demonstrated that a priming regimen—where Ad5/3-D24-ICOSL-CD40L was administered 48 h before chemotherapy—significantly outperformed the co-administration strategy, reducing spheroid areas and mitigating tumor rebound. Enhanced therapeutic response was associated with increased viral replication, sustained immunogenic cell death, and improved immune cell infiltration, underscoring the importance of sequencing and microenvironment preconditioning. This tumor-on-a-chip platform provides a physiologically relevant tool for real-time monitoring of treatment response, immune activation, and drug delivery under continuous flow. By bridging the gap between traditional in vitro models and in vivo studies, it offers a powerful preclinical system for optimizing combination regimens and advancing personalized therapies in ovarian cancer.

Graphical abstract