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 (<i>E-9591</i>), hybrid EMT (<i>Mlow-8028</i>), and mesenchymal (<i>M-16992</i>). 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 (<i>E-9591</i>) primarily relied on spatial constraints within the microcavity to invade. Batimastat drug sensitivity assays further distinguished invasion dependencies of the mesenchymal subtypes, confirming that <i>M-16992</i> patternoids exhibit a stronger sensitivity towards MMP inhibition compared to <i>Mlow-8028</i> 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.