Fernández-Zapico, Martín E.

Abstract Introduction Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers. While total neoadjuvant therapy (TNT) has improved outcomes, recurrence rates remain high. Major pathologic response after TNT is prognostic of better survival, but is rarely achieved. Current pathologic systems primarily consider residual tumor percentage, nodal status, and perineural invasion but overlook spatial organization within the tumor microenvironment (TME). We aimed to evaluate spatial features of the TME to identify biologically and clinically relevant patterns of TME conformation and configuration after TNT and surgical resection of PDAC. Methods We retrospectively analyzed patients with PDAC treated with TNT followed by surgery at Mayo Clinic (2010-2022) with partial or no response per College of American Pathologists (CAP) criteria. Hematoxylin and eosin-stained whole slide images (WSIs) were processed using PathExplore™ PDAC (v1.0) to quantify spatial TME features. These were correlated with disease-free survival (DFS). Results A total of 203 patients were included: 47.3% female, median age 66.5 years. All received TNT; 73.4% had neoadjuvant chemotherapy followed by chemoradiation. Surgical procedures included pancreaticoduodenectomy (62.1%), distal pancreatectomy (22.2%), and total pancreatectomy (15.8%). CAP-defined response was partial in 82.1% and absent in 17.9%. As expected, pathologic T stage (p=0.001), N stage (p=0.002), lymphovascular invasion (p=0.048), and R2 resection (p=0.007) were significantly associated with DFS. However, CAP response category (p=0.053), residual cancer area (p=0.47), and cancer-to-stroma ratio (p=0.25) were not. We analyzed 297 WSIs from 203 patients. Of 31 spatial features evaluated, 5 were associated with DFS (p<0.20). Recursive partitioning using ln(mean cancer shape index [CSI]) <1.775 and ln(SD of stroma shape index [SSI]) >0.651 identified a high-risk group (n=63) with median DFS of 7.23 months (95% CI: 5.19–9.63), compared to 11.57 months in the low-risk group (95% CI: 9.24–17.92) (HR=1.82; 95% CI: 1.31–2.52; p=0.0003). This remained significant after adjusting for T and N stage (HR=1.75; 95% CI: 1.17–2.63; p=0.007). An alternate prognostic index derived via backwards elimination, calculated using 0.2701(mean stromal area) + 0.3905(edge density), also stratified patients. High-risk patients (n=51) had a significantly shorter (p<0.001) DFS (6.2 months) than those in the low-risk category (20.0 months). This significant difference holds in a multivariable analysis controlling for pathologic stage, N stage, and resection margins (HR=1.94, 95% CI: 1.21-3.10, p=0.006). Discussion Current assessment of residual PDAC after TNT is limited by subjective grading and lack of spatial context. Using Tumor Landscape Analysis, we identified high-risk spatial features of the TME that independently predict recurrence. These findings support a novel spatially-informed framework for risk stratification in resected PDAC with residual disease. Citation Format: Miranda Lin, Luis Cisneros, Merih D. Toruner, Andrea Maraone, Paul Dizona, Qian Shi, Martin E. Fernandez-Zapico, Ryan M. Carr. Spatial features of the tumor microenvironment predict recurrence risk in resected pancreatic ductal adenocarcinoma after total neoadjuvant therapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr A051.

Abstract Pancreatic ductal adenocarcinoma (PDAC), the most common histological subtype of pancreatic cancer, is a devastating disease predicted to be the second leading cause of cancer deaths by 2040. Despite extensive molecular characterization, therapeutic targeting of this disease remains largely unsuccessful. Thus, an increased understanding of the mechanisms driving malignant features of PDAC is critical for the development of new therapeutic strategies. Of these, cancer cell survival is a central malignant event in PDAC contributing to disease initiation, progression, and response to therapy. To date, the majority of cell survival mechanisms associated with PDAC biology has highlighted the role of cytoplasmic and extracellular factors, making the role of nuclear elements understudied. Our preliminary data has demonstrated evidence of a novel mechanism regulating nuclear envelope stability, a key process contributing to cell survival. Work from our lab has shown that oncogenic KRAS, the major genetic driver of PDAC and present in ∼40% of cases, is sufficient to reduce the incidence of spontaneous nuclear envelope rupture, a measure of nuclear envelope stability. Using laser-induced nuclear envelope rupture revealed the presence of oncogenic KRAS decreases the extent of ruptures, suggesting an axis downstream of oncogenic KRAS is key for regulation of nuclear stability. Analysis of nuclear lamins, key intermediate filaments providing structure to the nuclear envelope, revealed only A-type lamins, not B-type, are associated with overall PDAC survival and enrich at the nuclear periphery downstream of oncogenic KRAS. Furthermore, BioID protein-protein interaction assays to examine the oncogenic KRAS-induced effects on nuclear repair proteins identified an increase in interaction between Lamin A and Emerin. Knock-down of either protein results in increases in nuclear envelope spontaneous ruptures. Together our findings provide a novel oncogenic KRAS-Lamin A-Emerin axis controlling the nuclear stability in PDAC, which can serve as a new therapeutic avenue to improve PDAC treatment outcomes. Citation Format: Kayla C. LaRue-Nolan, Ashley N. Sigafoos, Luis F. Flores, Kyle J . Roux, Martin E. Fernandez-Zapico. The role of Lamin A in pancreatic cancer nuclear envelope stability [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr A059.

Abstract Pancreatic adenocarcinoma (PDA) has poor response to chemotherapy with a strong likelihood of cancer recurrence. While previous studies have examined patient samples collected before and after chemotherapy, few have analyzed matched samples from the same patients that allow us to deconvolute interpatient heterogeneity, a large limitation to PDA studies. Here, we study the effects of chemotherapy on tumor cells and their surrounding microenvironment using scRNA sequencing of matched pre- and post- treatment tissue biopsies from 5 patients. We utilized the Seurat v4 pipeline to observe transcriptomic differences and corresponding putative cellular interactions in both treatment states. Unsurprisingly, we found insufficient tumor epithelial cells post-treatment due to the intended cytotoxic effects of chemotherapy, leading us to focus on the tumor microenvironment where we had sufficient cells to analyze. We identified that immune cells in the TME are heterogeneously affected by chemotherapy treatment with patient specific differences, but we did identify a unanimous increase in CXCR4 in CD4 and CD8 positive T cells after treatment. Analysis of CAFs revealed that a subset of fibroblasts lose myofibroblastic features and increasingly acquire 'neural'-like features after treatment. This suggests that chemotherapy-altered fibroblasts may contribute to a pro-tumor microenvironment that facilitates recurrence through neuron–CAF–tumor interactions. Through inferred ligand-receptor pairs identified with the CellChat v2 pipeline, we observed that increased CXCL12 in these neural CAFs interacts with the increased CXCR4 on T-cells. We validated the expression of these genes in patients by staining human patient PDAC tissues (both treated and treatment naïve tissues) for neural genes that were highly enriched post-treatment in our single cell sequencing dataset. We have also begun inhibiting these genes of interest in CAFs and are exploring the effects of these ‘neural’-CAFs on patient-derived tumor organoids in culture. Citation Format: Aylin Z. Henstridge, Padma Kadiyala, Ahmed Elhoissiny, Jianhua Liu, Georgina Branch, Nandini Arya, Vaibhav Sahai, Nicole Peterson, Jorge Machicado, Richard Kwon, Allison Schulman, Erik Wamsteker, George Phillips, Martin Fernandez-Zapico, Mark Truty, Timothy Frankel, Fillip Bednar, Marina Pasca di Magliano, Costas Lyssiotis, Eileen S. Carpenter. An increase in neural cancer associated fibroblasts following exposure to chemotherapy in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr B079.

Abstract Pancreatic ductal adenocarcinoma (PDAC), one of the most aggressive forms of pancreatic cancer, is associated with poor survival outcomes and currently ranks as the third leading cause of cancer-related death in the United States. Despite its clinical significance, the mechanisms of PDAC development and progression remain, in part, poorly understood. In this study, we provide evidence of a novel role of sorting nexin 10 (SNX10), a member of the sorting nexin family, in the regulation of KRAS-induced pancreatic carcinogenesis. We demonstrate that SNX10 is downregulated in PDAC, especially in advanced cases. Furthermore, mutational analysis revealed SNX10 genetic alterations in PDAC cases. Functional studies demonstrated that SNX10 overexpression in human PDAC cells inhibited cell proliferation and colony formation. Moreover, SNX10 overexpression induced G1-phase cell-cycle arrest and decreased KRAS signaling activity. Using a novel Snx10 knockout mouse crossed with a Kras-driven PDAC model, we observed reduced survival, increased tumor cell proliferation, enhanced aggression, and heightened inflammation. Collectively, these findings highlight SNX10 as a tumor suppressor candidate in PDAC and underscore its promise as a foundation for new therapeutic approaches. Significance: SNX10 plays a crucial role in reducing pancreatic tumorigenesis. This discovery offers valuable insights into PDAC’s biology and the development of new effective treatments.

For over a century, scientists reported the disruption of normal nuclear shape and size in cancer. These changes have long been used as tools for diagnosis and staging of malignancies. However, to date, the mechanisms underlying these aberrant nuclear phenotypes and their biological significance remain poorly understood. Using a model of pancreatic ductal adenocarcinoma (PDAC), the major histological subtypes of pancreatic cancer, we found that oncogenic mutant KRAS reduces nuclear size. Transcriptomic and protein expression analysis of mutant KRAS–expressing PDAC cells revealed differential levels of several nuclear envelope–associated genes. Further analysis demonstrated the nuclear lamina protein, Emerin (EMD), acted downstream of KRAS to mediate nuclear size reduction in PDAC. Analysis of human PDAC samples showed that increased EMD expression associates with reduced nuclear size. Finally, in vivo genetic depletion of EMD in a mutant KRAS–driven PDAC model resulted in increased nuclear size and a reduced incidence of poorly differentiated PDAC. Thus, our data provide evidence of a potentially novel mechanism underlying nuclear size regulation and its effect in PDAC carcinogenesis.

e14626 Background: Despite advancements in neoadjuvant therapy and surgical techniques, patients with pancreatic ductal adenocarcinoma (PDAC) often experience high recurrence rates after total neoadjuvant therapy (TNT) and resection. Existing tumor response scoring systems, such as the College of American Pathologists (CAP) guidelines, fail to stratify recurrence risk effectively, emphasizing the need for novel, objective approaches. Methods: This study evaluated spatial characteristics of residual cancer and stroma in a multi-site cohort of 203 patients with resected PDAC following TNT, not having achieved a major pathologic response (CAP 2 or 3). Whole slide images (WSI) of hematoxylin and eosin-stained sections were digitized and analyzed using artificial intelligence to perform tissue segmentation. Metrics quantifying spatial morphology and configuration, inspired by principles of landscape ecology, were computed to explore spatial features of the tumor microenvironment (TME). Statistical models (recursive partitioning and regression tree [RPRT] model and Cox model with backwards eliminations) incorporating these features were developed to stratify recurrence risk. Results: Five metrics were used for risk classification model build. Three models successfully classified patients into high- and low-risk groups based on spatial metrics. Models demonstrated moderate discriminatory power (C-statistics: 0.560–0.566) and showed that increased tumor fragmentation, like stromal patch density and cancer patch shape index, were strongly associated with improved outcomes. Conclusions: Integrating spatial metrics of cancer-stroma configuration enhances risk stratification beyond conventional scoring systems. Given increased tumor fragmentation is associated with improved outcomes, these data indirectly suggest ecological mechanisms of treatment resistance. This approach offers a pathway toward personalized post-operative management strategies to improve outcomes in PDAC. Risk classification models. Model Description Event/n Median DFS (95% CI) HR(95% CI) p-value C-statistics 1(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 87 / 101 8.22(5.72 – 10.1) 1.64(1.20 – 2.25) 0.002 0.562 Low risk: log standard deviation of the stroma shape index ≤ 0.651 71 / 102 11.90(9.24 – 25.1) Ref 2(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 & mean cancer shape index ≤ 1.775 58 / 63 7.23(5.19 – 9.63) 1.82(1.31 – 2.52) 0.0003 0.560 Low risk: (log standard deviation of the stroma shape index > 0.651 & mean cancer shape index > 1.775) or log standard deviation of the stroma shape index ≤ 0.651 100 / 140 11.57(9.24 – 17.92) Ref 3(Backwards elimination) High risk: PI * > median 86 / 101 8.02(6.08 – 9.86) 1.73(1.26 – 2.37) 0.0007 0.566 Low risk:PI * ≤ median 72 / 102 15.72(9.97 – 25.05) Ref *PI: (0.2701 * log mean stroma area) + (0.3905 * log edge density).

4155 Background: The tumor microenvironment (TME) that surrounds pancreatic ductal adenocarcinoma (PDAC) is a multi-faceted and dynamic ecosystem in which stromal fibroblasts communicate with cancer cells to mediate tumor growth, metastasis, and chemotherapy resistance. It is well recognized that both cancer-associated fibroblasts (CAFs) and its non-cellular, fibrotic components within the TME can foster a protumorigenic environment for PDAC. However, we still lack a comprehensive understanding of the precise mechanisms in which this dense, fibrotic matrix can help drive malignant behaviors. Here, we reveal a novel mechanism in which the zinc-finger transcription factor GLI2 regulates type 1 collagen expression within CAFs and how the soluble variant of this collagen promotes irinotecan chemoresistance. Methods: We leveraged transcriptomic data from The Cancer Genome Atlas, International Cancer Genome Consortium, and Clinical Proteomic Tumor Analysis Consortium to evaluate GLI2 expression and stromal content of human PDAC tumors through bulk RNA-sequencing deconvolution. Using single-nucleus RNA sequencing of human PDAC tumors, we validated the association of GLI2 expression and stromal matrix constituents in CAFs. Chromatin immunoprecipitation assays in human CAFs confirmed GLI2 binding at the COL1A1 promoter. Through RNAi-based inactivation of GLI2, we determined how loss of GLI2 impacts regulation of type 1 collagen. Additionally, we conducted MTT assays to assess tumor viability in response to irinotecan treatment. Results: Transcriptomic analysis revealed that GLI2 is highly enriched in CAFs and strongly correlated with stromal fibrosis compared to other non-tumor cell constituents within the TME. We have shown that GLI2 directly binds to the promoter of COL1A1, a key component of type 1 collagen, in CAFs and regulates its transcription in a manner dependent on TGFβ1 signaling. Interestingly, PDAC tumors exposed to type 1 collagen show increased expression of pro-tumorigenic pathways involved in inflammation, EGR signaling, cytokine-receptor interactions, and irinotecan resistance. We further validate that human PDAC cells pre-treated with collagen can confer chemoresistance to irinotecan with viability assays. Conclusions: Taken together, our study demonstrates a novel mechanism in which GLI2 regulates the secretion of collagen within CAFs, which in turn can enable PDAC to acquire resistance to standard-of-care treatments. These findings highlight not only the oncogenic functions for CAFs and their fibrotic secretome, but also open new avenues in which therapeutic targeting of the TME may provide clinical benefit for PDAC patients.

Abstract Tumor microenvironments (TMEs) are spatially complex and dynamic systems shaped by evolutionary pressures, tissue architecture, and cellular interactions. To capture this complexity, we developed the Tumor Landscape Analysis (TLA) pipeline, a computational framework applying principles from landscape ecology and spatial statistics to quantitatively characterize tumor spatial heterogeneity. TLA integrates spatially resolved pathology data, including whole-cell, point-based, and region-level formats, and computes multiscale metrics to assess cell distributions, neighborhood relationships, and tissue-level organization. The framework leverages ecological indices such as the Morisita-Horn index, Ripley’s H function, and Shannon diversity to quantify intercellular proximity, spatial clustering, and cellular diversity. It also uses the concept of local microenvironments (LMEs), data-driven ecological niches defined by local cell-type abundance and spatial uniformity, enabling unsupervised and reproducible classification of tumor regions. The use of fragmentation metrics, including patch density, shape complexity, and interspersion, provide further insight into spatial disorganization and emergent tissue architecture. TLA is agnostic to imaging modality and biological context, supporting broad applicability across tumor types and sample formats. By translating complex tissue architectures into interpretable spatial metrics, the pipeline enables integrative analyses that link spatial ecology to clinical and molecular phenotypes. This approach facilitates a deeper understanding of how spatial features contribute to tumor progression, therapeutic resistance, and clinical outcomes, offering new opportunities for precision oncology rooted in spatial systems biology.

Abstract Despite advances in surgery and chemotherapy, patients with resectable pancreatic ductal adenocarcinoma (PDAC) face high recurrence rates (40-60%). Total neoadjuvant therapy (TNT) seeks to enhance margin-negative resections (R0) and address micrometastatic disease, with potential survival benefits. Yet, TNT still results in high recurrence rates, with 1-, 2-, and 3-year disease-free survival (DFS) at 65%, 48%, and 32%, respectively. Residual cancer extent is a key prognostic factor in PDAC after TNT. Tumor response scores show favorable outcomes only for patients achieving near-complete or complete pathologic response. In a cohort of 511 PDAC patients treated with TNT and surgery (2015-2022), improved DFS was only found in those with a complete pathologic response (pCR, 7.8%). This highlights the limited use of current response scoring in stratifying post-TNT patient risk, underscoring the need to better understand disease persistence and relapse. Here we developed a quantitative method to assess residual cancer. Using a digital pathology H&E library from 2180 PDAC cases (2000-2022), an AI platform segmented tissue into cancer epithelium, stroma, and normal regions. For 202 TNT-treated cases without pCR, we calculated a ratio of cancer area to stromal area from representative slides. Modeled after the histologic tumor regression grade (HTRG) system, cases were classified into <5%, 5-50%, or >50% cancer-to-stroma ratios. However, this measure alone showed no difference in DFS, suggesting tumor burden cannot fully explain differences in clinical outcomes. We hypothesized that the spatial organization of the tumor microenvironment (TME) is a determinant of patient outcomes. Drawing from landscape ecology, which studies spatial properties of ecosystems, we applied similar principles to analyze tissue architecture. Using an AI-based two-class segmentation of whole-slide images, we assessed spatial features like patch area, perimeter, density, and Shannon diversity. Python’s ‘pylandstats’ package calculated 21 spatial metrics, reduced via stepwise Cox regression using the Akaike information criterion (AIC). The final model included mean Shannon diversity, mean and standard deviation of stromal patch areas, and stromal patch density. Kaplan-Meier analysis of 202 samples stratified model predictions into quartiles, correlating with high (mean DFS 10.85 months), medium (19.32 months), and low risk (25.92 months) groups. These findings aligned with model expectations, underscoring the potential of spatial TME analysis to predict outcomes. Citation Format: Andrea V. Maraone, Zafar Siddiqui, Luis H. Cisneros, Merih D. Toruner, Mark Truty, Cornelius Thiels, Robert R. McWilliams, Steven R. Alberts, Rondell P. Graham, Carlo Maley, Qian Shi, Martin E. Fernandez-Zapico, Ryan M. Carr. Tumor spatial configuration predicts pancreatic cancer recurrence risk after total neoadjuvant therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5070.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers, primarily due to its complex tumor microenvironment (TME), which drives both disease progression and therapy resistance. Understanding the molecular mechanisms governing TME dynamics is essential for developing new treatment strategies for this devastating disease. In this study, we uncover an oncogenic role for Galectin-1 (Gal1), a glycan-binding protein abundantly expressed by activated pancreatic stellate cells (PSCs), a key component of the PDAC TME that orchestrates tumor progression. Our findings reveal that Gal1 expression is elevated in the nucleus of human PSCs in both tissue samples and cultured cell lines. Using chromatin immunoprecipitation followed by sequencing analysis (ChIP-seq), we identify Gal1 occupancy at the promoters of several cancer-associated genes, including KRAS , a pivotal oncogene involved in PDAC pathogenesis. We demonstrate that Gal1 binds to the KRAS promoter, sustaining KRAS expression in PSCs, which, in turn, maintains PSC activation and promotes the secretion of protumorigenic cytokines. Mechanistically, Gal1 is required to preserve histone H3 lysine 4 monomethylation levels and to recruit the histone methyltransferase MLL1 to target promoters. Collectively, our findings define a nuclear function of Gal1 in modulating the transcriptional landscape of cancer-associated genes in PSCs within the PDAC TME, mediated through an epigenetic mechanism. These insights enhance our understanding of PDAC pathology and open potential avenues for therapeutic interventions targeting intracellular Gal1.