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.

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

Kuryk, Lukasz;Mathlouthi, Sara;Casagrande, Lisa;Tognetti, Francesco;Malfanti, Alessio;Caliceti, Paolo;Garofalo, Mariangela
2025

Abstract

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.
2025
File in questo prodotto:
File Dimensione Formato  
Kuryk et al. DDTR.pdf

accesso aperto

Tipologia: Published (Publisher's Version of Record)
Licenza: Creative commons
Dimensione 4.26 MB
Formato Adobe PDF
4.26 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3567365
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 2
  • OpenAlex 2
social impact