Toruner, Merih D.

Abstract Pancreatic ductal adenocarcinoma (PDAC) remains among the most aggressive cancers, due to its limited therapeutic options and poor prognosis. Even with the adoption of total neoadjuvant therapy (TNT) and potentially curative surgical resection, PDAC relapse rates remain unacceptably high. Current systems for evaluating tumor response are valuable but limited, as they fail to capture the ecological complexity and broader architecture of the tumor microenvironment (TME). This results in uncertainty regarding the prognosis and recurrence risk of patients. To address this and to capture the complexity of the PDAC TME, we developed the Tumor Landscape Analysis (TLA). Using digitized H&E slides from 203 PDAC patients who received TNT and surgical resection at our institution, we applied a machine-learning pipeline to segment tumor and stromal compartments. We then quantified the TME architecture using ecological frameworks to assess the disease in multiple scales: individual patches, whole-slide landscapes, and aggregated patient-level summaries. Our analysis revealed that higher-order spatial features are independently prognostic of disease-free survival (DFS). Two statistical models showed different but complementary spatial characteristics that predict disease risk. In the first model, patients with more irregular cancer patch shapes and lower variability in stromal shape had significantly better DFS, with high-risk patients relapsing in a median of 7.2 months compared to 11.6 months in the low-risk group (HR=1.82, p=0.0003). In the second model, smaller stromal patch areas combined with greater tumor-stroma edge density identified patients at elevated risk, with high-risk individuals showing a median DFS of 8.0 months versus 15.7 months in low-risk patients (HR=1.73, p=0.0007). Importantly, these associations persisted even after adjustment for the T and N stage, showing that spatial features provide unique information beyond traditional pathology measures. These models help visualize PDAC as a comprehensive ecosystem that carries clinical significance. By quantifying tumor conformation and configuration, our models reveal prognostic information not available through CAP grading, percent tumor burden, or routine cell counts. This study suggests that tumor-stroma interactions and their spatial organizations are potentially biologically important for recurrence. We present a new, ecologically inspired approach to digital pathology for PDAC that not only improves our ability to predict recurrence and survival in PDAC but also sheds light on cancer as a complex, evolving ecosystem. Citation Format: Merih D. Toruner, Luis H. Cisneros, Miranda Lin, Andrea Maraone, Carlo Maley, Paul Dizona, Qian Shi, Martin E. Fernandez-Zapico, Ryan M. Carr. Ecological landscape analysis of the tumor microenvironment predicts recurrence risk in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Cancer Evolution: The Dynamics of Progression and Persistence; 2025 Dec 4-6; Albuquerque, NM. Philadelphia (PA): AACR; Cancer Res 2025;85(23_Suppl):Abstract nr B027.

Carcinoma-associated fibroblasts (CAFs) play an important role in the progression of multiple malignancies. Secretion of cytokines and growth factors underlies the pro-tumoral effect of CAFs. Although this paracrine function has been extensively documented, the molecular mechanisms controlling the expression of these factors remain elusive. In this study, we provide evidence of a novel CAF transcriptional axis regulating the expression of SDF1, a major driver of cancer cell migration, involving the transcription factor GLI1 and histone acetyltransferase p300. We demonstrate that conditioned media from CAFs overexpressing GLI1 induce the migration of pancreatic cancer cells, and this effect is impaired by an SDF1-neutralizing antibody. Using a combination of co-immunoprecipitation, proximity ligation assay and chromatin immunoprecipitation assay, we further demonstrate that GLI1 and p300 physically interact in CAFs to co-occupy and drive SDF1 promoter activity. Mapping experiments highlight the requirement of GLI1 N-terminal for the interaction with p300. Importantly, knockdowns of both GLI1 and p300 reduce SDF1 expression. Further analysis shows that knockdown of GLI1 decreases SDF1 promoter activity, p300 recruitment, and levels of its associated histone marks (H4ac, H3K27ac, and H3K14ac). Finally, we show that the integrity of two GLI binding sites in the SDF1 promoter is required for p300 recruitment. Our findings define a new role for the p300–GLI1 complex in the regulation of SDF1, providing new mechanistic insight into the molecular events controlling pancreatic cancer cells migration.

BACKGROUND A patient-derived organoid (PDO) platform may serve as a promising tool for translational cancer research. In this study, we evaluated PDO’s ability to predict clinical response to gastrointestinal (GI) cancers. METHODS We generated PDOs from primary and metastatic lesions of patients with GI cancers, including pancreatic ductal adenocarcinoma, colorectal adenocarcinoma, and cholangiocarcinoma. We compared PDO response with the observed clinical response for donor patients to the same treatments. RESULTS We report an approximately 80% concordance rate between PDO and donor tumor response. Importantly, we found a profound influence of culture media on PDO phenotype, where we showed a significant difference in response to standard-of-care chemotherapies, distinct morphologies, and transcriptomes between media within the same PDO cultures. CONCLUSION While we demonstrate a high concordance rate between donor tumor and PDO, these studies also showed the important role of culture media when using PDOs to inform treatment selection and predict response across a spectrum of GI cancers. TRIAL REGISTRATION Not applicable. FUNDING The Joan F. & Richard A. Abdoo Family Fund in Colorectal Cancer Research, GI Cancer program of the Mayo Clinic Cancer Center, Mayo Clinic SPORE in Pancreatic Cancer, Center of Individualized Medicine (Mayo Clinic), Department of Laboratory Medicine and Pathology (Mayo Clinic), Incyte Pharmaceuticals and Mayo Clinic Hepatobiliary SPORE, University of Minnesota-Mayo Clinic Partnership, and the Early Therapeutic program (Department of Oncology, Mayo Clinic).