bioRxivBioengineeringPreprint
Tumor-on-Chip as a Personalised Platform for Rapid Drug-Testing in Breast Cancer
Clara HelaliD, Léa PinoniD, Juliette Jin, Niccolo Schintu, Ana Vazquez, Martin NurmikiD, Gianni AntonelliiD, Maxime SimoniD, Élodie MontaudoniD, Laura SourdiD, Héloïse DerrieniD, Gérard ZalcmaniD, Angela BelliniiD, Andreia GoncalvesiD, Anne Vincent‐SalomoniD, Toulsie RamtohuliD, Elisabetta MarangoniiD, Maria Carla ParriniiD, Luc CabeliD, Stéphanie DescroixiD
Abstract
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.
- organism: human
- assay: organoid / primary culture
- research focus: drug response / drug discovery
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- approach: experimental assay
- Citations
- 0
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