Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second leading cause of cancer-related death. Hallmarks include desmoplasia with variable extracellular matrix (ECM) architecture and a complex microenvironment with spatially defined tumor, stromal, and immune populations. Nevertheless, the role of desmoplastic spatial organization in patient/tumor variability remains underexplored, which we elucidate using two technologies. First, we quantify ECM patterning in 437 patients, revealing architectures associated with disease-free and overall survival. Second, we spatially profile the cellular milieu of 78 specimens using codetection by indexing, identifying an axis of pro-inflammatory cell interactions predictive of poorer outcomes. We discover that clinical characteristics, including neoadjuvant chemotherapy status, tumor stage, and ECM architecture, correlate with differential stromal-immune organization, including fibroblast subtypes with distinct niches. Lastly, we define unified signatures that predict survival with areas under the receiver operating characteristic curve (AUCs) of 0.872-0.903, differentiating survivorship by 655 days. Overall, our findings establish matrix ultrastructural and cellular organizations of fibrosis linked to poorer outcomes.
Keywords: architecture; cancer; cell interactions; cell networks; codex; desmoplasia; fibrosis; machine learning; pancreatic ductal adenocarcinoma; spatial biology.
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