PARRINI, M. C. | Search bioRxiv

bioRxiv2025

Tumor-on-Chip as a Personalised Platform for Rapid Drug-Testing in Breast Cancer

Breast cancer (BC) remains one of the most common malignancies worldwide and continues to pose major therapeutic challenges, emphasizing the need for functional models that can inform fast treatment selection. Currently, patient-derived xenografts (PDXs) and organoids (PDOs) are valuable biological models for functional precision oncology; however, variable success rates of establishment and prolonged timelines limit their clinical application for real-time drug testing. To overcome this, we developed a Tumor-on-Chip (ToC) platform that enables functional drug sensitivity profiling within a clinically actionable 4-day timeframe. We compared ToC models with PDX results, and demonstrated high reproducibility and strong concordance with in vivo PDX responses. Drug sensitivity was correctly identified ex vivo in 88% of PDX-responsive cases, while resistance was detected in 91%, with no false positives at clinically relevant drug concentrations. To facilitate clinical translation, we engineered a custom microfluidic chip optimized for minimal breast cancer biopsy material, yielding results similar to those obtained from resection samples. We ultimately demonstrated the proof-of-concept for applying this platform to patient samples as a further tool for guiding clinical decision-making and discriminated between resistance and sensitive profiles among patients. These findings demonstrate the feasibility and translational potential of ToC models for personalized drug profiling in breast cancer, laying the groundwork for their integration into real-time clinical decision-making workflows.

bioengineering↗

bioRxiv2023

Ex vivo quantification of anti-tumor T-cell activity upon anti-PD-1 treatment in patient-derived lung tumor-on-chip

There is a compelling need for new approaches to predict efficacy of immunotherapy drugs. Tumor-on-chip technology exploits microfluidics to generate 3D cell co-cultures embedded in hydrogels that recapitulate immune and stromal characteristics of a simplified tumor ecosystem. Here, we present the development and validation of lung-tumor-on-chip platforms to quickly and precisely measure ex vivo the effects of immune check-point inhibitors on T-cell-mediated cancer cell death, by exploiting the power of live imaging and advanced image analysis algorithms. These tumor-on-chips were generated with patient-derived autologous primary cells isolated from fresh lung cancer samples, opening the path for applications in personalized medicine. Moreover, cancer-associated fibroblasts were shown to impair the response to anti-PD-1, indicating that tumor-on-chips are capable of recapitulating stroma-dependent mechanisms of immunotherapy resistance. This interdisciplinary combination of microfluidic devices, clinically-relevant cell models, and advanced computational methods, can innovatively improve both the fundamental understanding and clinical efficacy of immuno-oncology drugs.

cancer biology↗