A 3D Patternoid Model for the Reproducible Characterization of Invasive Phenotypes and Drug Sensitivity in PDAC

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a highly invasive and heterogeneous malignancy, posing challenges for reproducible modeling and functional phenotypic analysis. To address these limitations, we developed a standardized 3D patternoid platform using collagen-based microcavity arrays to enhance organoid formation consistency and quantify subtype-specific invasion mechanisms. We utilized murine primary PDAC cells stratified by epithelial-mesenchymal transition (EMT) into three subtypes: epithelial (\textit{E-9591}), hybrid EMT (\textit{Mlow-8028}), and mesenchymal (\textit{M-16992}). The platform’s sensitivity was verified by a strong correlation between EMT scores and invasive phenotypes, as well as responses to physiological concentrations of the protease inhibitor Batimastat. Key invasion parameters—including invasive area, maximum invasion distance, and branching complexity—were measured under both genomic and drug-induced conditions. The platform demonstrated high inter-organoid reproducibility, with precise control over initial cell numbers ensuring batch-to-batch comparability. Invasion dynamics analysis revealed that epithelial cells (\textit{E-9591}) primarily relied on spatial constraints within the microcavity to invade. Batimastat drug sensitivity assays further distinguished invasion dependencies of the mesenchymal subtypes, confirming that \textit{M-16992} patternoids exhibit a stronger sensitivity towards MMP inhibition compared to \textit{Mlow-8028} patternoids. Concurrentlty, both subtypes experienced a shift towards epithelial-like spatial constraint triggered invasion morphology, reflecting the plasticity of PDAC invasiveness. This scalable and adaptable 3D patternoid platform enables high-throughput analysis of invasive behaviors and therapeutic responses, offering significant potential for preclinical cancer research and personalized medicine.