3D histology reveals that immune response to pancreatic precancers is heterogeneous and depends on global pancreas structure.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer for which few effective therapies exist. Immunotherapies specifically are ineffective in pancreatic cancer, in part due to its unique stromal and immune microenvironment. Pancreatic intraepithelial neoplasia, or PanIN, is the main precursor lesion to PDAC. Recently it was discovered that PanINs are remarkably abundant in the grossly normal pancreas, suggesting that the vast majority will never progress to cancer. Here, through construction of 48 samples of cm3-sized human pancreas tissue, we profiled the immune microenvironment of 1,476 PanINs in 3D and at single-cell resolution to better understand the early evolution of the pancreatic tumor microenvironment and to determine how inflammation may play a role in cancer progression. We found that bulk pancreatic inflammation strongly correlates to PanIN cell fraction. We found that the immune response around PanINs is highly heterogeneous, with distinct immune hotspots and cold spots that appear and disappear in a span of tens of microns. Immune hotspots generally mark locations of higher grade of dysplasia or locations near acinar atrophy. The immune composition at these hotspots is dominated by naïve, cytotoxic, and regulatory T cells, cancer associated fibroblasts, and tumor associated macrophages, with little similarity to the immune composition around less-inflamed PanINs. By mapping FOXP3+ cells in 3D, we found that regulatory T cells are present at higher density in larger PanIN lesions compared to smaller PanINs, suggesting that the early initiation of PanINs may not exhibit an immunosuppressive response. This analysis demonstrates that while PanINs are common in the pancreases of most individuals, inflammation may play a pivotal role, both at the bulk and the microscopic scale, in demarcating regions of significance in cancer progression.

PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration.

This study introduces a new imaging, spatial transcriptomics (ST), and single-cell RNA-sequencing integration pipeline to characterize neoplastic cell state transitions during tumorigenesis. We applied a semi-supervised analysis pipeline to examine premalignant pancreatic intraepithelial neoplasias (PanINs) that can develop into pancreatic ductal adenocarcinoma (PDAC). Their strict diagnosis on formalin-fixed and paraffin-embedded (FFPE) samples limited the single-cell characterization of human PanINs within their microenvironment. We leverage whole transcriptome FFPE ST to enable the study of a rare cohort of matched low-grade (LG) and high-grade (HG) PanIN lesions to track progression and map cellular phenotypes relative to single-cell PDAC datasets. We demonstrate that cancer-associated fibroblasts (CAFs), including antigen-presenting CAFs, are located close to PanINs. We further observed a transition from CAF-related inflammatory signaling to cellular proliferation during PanIN progression. We validate these findings with single-cell high-dimensional imaging proteomics and transcriptomics technologies. Altogether, our semi-supervised learning framework for spatial multi-omics has broad applicability across cancer types to decipher the spatiotemporal dynamics of carcinogenesis.

Comprehensive Characterization of Intraductal Oncocytic Papillary Neoplasm of the Pancreas: A Systematic and Critical Review.

Intraductal oncocytic papillary neoplasm (IOPN) of the pancreas is a recently recognized pancreatic tumor. Here, we aimed to determine its most essential features with the systematic review tool. PubMed, Scopus, and Embase were searched for studies reporting data on pancreatic IOPN. The clinicopathologic, immunohistochemical, and molecular data were extracted and summarized. Then, a comparative analysis of the molecular alterations of IOPN with those of pancreatic ductal adenocarcinoma and intraductal papillary mucinous neoplasm from reference cohorts (including The Cancer Genome Atlas) was conducted. The key findings from 414 IOPNs were as follows: 1) The male-to-female ratio was 1.5:1. Pancreatic head was the most common site (131/237; 55.3%), but a diffuse tumor extension involving more than one pancreatic segment was described in about 1 out of 5 cases (49/237; 20.6%). The mean size was 45.5 mm. An associated invasive carcinoma was present in 50% of cases (168/336). In those cases, most tumors were pT1 or pT2 and pN0 (>80%), and vascular invasion was uncommon (20.6%). Regarding survival, more than 90% of patients were alive after surgical resection. 2) Immunohistochemical and molecular features were as follows. The most commonly expressed mucins were MUC5AC (110/112; 98.2%) and MUC6 (78/84; 92.8%). Compared with pancreatic ductal adenocarcinoma and intraductal papillary mucinous neoplasm, the classic pancreatic drivers KRAS, TP53, CDKN2A, SMAD4, and GNAS were less altered in IOPN (P < .01). Moreover, fusions involving PRKACA or PRKACB gene were detected in all of the 68 cases examined, with PRKACB::ATP1B1 being the most common (27/68 cases; 39.7%). These genomic events emerged as an entity-defining molecular alteration of IOPN (P < .01). Thus, such fusions represent a promising biomarker for diagnostic purposes. Recent evidence also suggests their role in influencing the acquisition of oncocytic morphology. IOPN is a distinct pancreatic neoplasm with specific clinicopathologic and molecular features. Considering the clinical or prognostic implications, its recognition is essential for pathologists and, ultimately, patients' management.

Multi-omic profiling of intraductal papillary neoplasms of the pancreas reveals distinct expression patterns and potential markers of progression.

In order to advance our understanding of precancers in the pancreas, 69 pancreatic intraductal papillary neoplasms (IPNs), including 64 intraductal papillary mucinous neoplasms (IPMNs) and 5 intraductal oncocytic papillary neoplasms (IOPNs), 32 pancreatic cyst fluid samples, 104 invasive pancreatic ductal adenocarcinomas (PDACs), 43 normal adjacent tissues (NATs), and 76 macro-dissected normal pancreatic ducts (NDs) were analyzed by mass spectrometry. A total of 10,246 proteins and 22,284 glycopeptides were identified in all tissue samples, and 756 proteins with more than 1.5-fold increase in abundance in IPMNs relative to NDs were identified, 45% of which were also identified in cyst fluids. The over-expression of selected proteins was validated by immunolabeling. Proteins and glycoproteins overexpressed in IPMNs included those involved in glycan biosynthesis and the immune system. In addition, multiomics clustering identified two subtypes of IPMNs. This study provides a foundation for understanding tumor progression and targets for earlier detection and therapies. Significance: This multilevel characterization of intraductal papillary neoplasms of the pancreas provides a foundation for understanding the changes in protein and glycoprotein expression during the progression from normal duct to intraductal papillary neoplasm, and to invasive pancreatic carcinoma, providing a foundation for informed approaches to earlier detection and treatment.

Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic findings.

Pancreatic ductal adenocarcinoma is a rare but lethal cancer. Recent evidence suggests that pancreatic intraepithelial neoplasia (PanIN), a microscopic precursor lesion that gives rise to pancreatic cancer, is larger and more prevalent than previously believed. Better understanding of the growth-law dynamics of PanINs may improve our ability to understand how a miniscule fraction makes the transition to invasive cancer. Here, using three-dimensional tissue mapping, we analyzed >1000 PanINs and found that lesion size is distributed according to a power law. Our data suggest that in bulk, PanIN size can be predicted by general growth behavior without consideration for the heterogeneity of the pancreatic microenvironment or an individual's age, history, or lifestyle. Our models suggest that intraductal spread and fusing of lesions drive our observed size distribution. This analysis lays the groundwork for future mathematical modeling efforts integrating PanIN incidence, morphology, and molecular features to understand tumorigenesis and demonstrates the utility of combining experimental measurement with dynamic modeling in understanding tumorigenesis.

Clinical Relevance of Cancerization of Ducts in Resected Pancreatic Ductal Adenocarcinoma.

OBJECTIVES: Although prevalent in 50%-90% of pancreatic ductal adenocarcinomas, the clinical relevance of "cancerization of ducts" (COD) remains unknown. METHODS: Pathologists retrospectively reviewed slides classifying prevalence of COD. Histopathological parameters, location of first recurrence, recurrence-free survival (RFS), and overall survival (OS) were collected from the institutional pancreatectomy registry. RESULTS: Among 311 pancreatic ductal adenocarcinomas, COD was present in 216 (69.5%) and more prevalent in the cohort that underwent upfront surgery (75.3% vs 63.1%, P = 0.019). Furthermore, COD was associated with female gender (P = 0.040), advanced T stage (P = 0.007), perineural invasion (P = 0.014), lymphovascular invasion (P = 0.025), and R1 margin (P = 0.009), but not N stage (P = 0.401) or tumor differentiation (P = 0.717). In multivariable regression, COD was associated with less liver recurrence (odds ratio, 0.44; P < 0.005). This association was driven by the cohort of patients who had received preoperative treatment (odds ratio, 0.18; P < 0.001). COD was not predictive for RFS or OS. CONCLUSIONS: Cancerization of ducts was not associated with RFS or OS. Currently underrecognized, standardized implementation into histopathological reports may have merit, and further mechanistic scientific experiments need to illuminate its clinical and biologic impact.

PanIN or IPMN? Redefining Lesion Size in 3 Dimensions.

Pancreatic ductal adenocarcinoma (PDAC) develops from 2 known precursor lesions: a majority (∼85%) develops from pancreatic intraepithelial neoplasia (PanIN), and a minority develops from intraductal papillary mucinous neoplasms (IPMNs). Clinical classification of PanIN and IPMN relies on a combination of low-resolution, 3-dimensional (D) imaging (computed tomography, CT), and high-resolution, 2D imaging (histology). The definitions of PanIN and IPMN currently rely heavily on size. IPMNs are defined as macroscopic: generally >1.0 cm and visible in CT, and PanINs are defined as microscopic: generally <0.5 cm and not identifiable in CT. As 2D evaluation fails to take into account 3D structures, we hypothesized that this classification would fail in evaluation of high-resolution, 3D images. To characterize the size and prevalence of PanINs in 3D, 47 thick slabs of pancreas were harvested from grossly normal areas of pancreatic resections, excluding samples from individuals with a diagnosis of an IPMN. All patients but one underwent preoperative CT scans. Through construction of cellular resolution 3D maps, we identified >1400 ductal precursor lesions that met the 2D histologic size criteria of PanINs. We show that, when 3D space is considered, 25 of these lesions can be digitally sectioned to meet the 2D histologic size criterion of IPMN. Re-evaluation of the preoperative CT images of individuals found to possess these large precursor lesions showed that nearly half are visible on imaging. These findings demonstrate that the clinical classification of PanIN and IPMN fails in evaluation of high-resolution, 3D images, emphasizing the need for re-evaluation of classification guidelines that place significant weight on 2D assessment of 3D structures.

3D genomic mapping reveals multifocality of human pancreatic precancers.

Pancreatic intraepithelial neoplasias (PanINs) are the most common precursors of pancreatic cancer, but their small size and inaccessibility in humans make them challenging to study1. Critically, the number, dimensions and connectivity of human PanINs remain largely unknown, precluding important insights into early cancer development. Here, we provide a microanatomical survey of human PanINs by analysing 46 large samples of grossly normal human pancreas with a machine-learning pipeline for quantitative 3D histological reconstruction at single-cell resolution. To elucidate genetic relationships between and within PanINs, we developed a workflow in which 3D modelling guides multi-region microdissection and targeted and whole-exome sequencing. From these samples, we calculated a mean burden of 13 PanINs per cm3 and extrapolated that the normal intact adult pancreas harbours hundreds of PanINs, almost all with oncogenic KRAS hotspot mutations. We found that most PanINs originate as independent clones with distinct somatic mutation profiles. Some spatially continuous PanINs were found to contain multiple KRAS mutations; computational and in situ analyses demonstrated that different KRAS mutations localize to distinct cell subpopulations within these neoplasms, indicating their polyclonal origins. The extensive multifocality and genetic heterogeneity of PanINs raises important questions about mechanisms that drive precancer initiation and confer differential progression risk in the human pancreas. This detailed 3D genomic mapping of molecular alterations in human PanINs provides an empirical foundation for early detection and rational interception of pancreatic cancer.

Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Inflammation in Cancer Cells in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by an immunosuppressive tumor microenvironment enriched with cancer-associated fibroblasts (CAF). This study used a convergence approach to identify tumor cell and CAF interactions through the integration of single-cell data from human tumors with human organoid coculture experiments. Analysis of a comprehensive atlas of PDAC single-cell RNA sequencing data indicated that CAF density is associated with increased inflammation and epithelial-mesenchymal transition (EMT) in epithelial cells. Transfer learning using transcriptional data from patient-derived organoid and CAF cocultures provided in silico validation of CAF induction of inflammatory and EMT epithelial cell states. Further experimental validation in cocultures demonstrated integrin beta 1 (ITGB1) and vascular endothelial factor A (VEGFA) interactions with neuropilin-1 mediating CAF-epithelial cell cross-talk. Together, this study introduces transfer learning from human single-cell data to organoid coculture analyses for experimental validation of discoveries of cell-cell cross-talk and identifies fibroblast-mediated regulation of EMT and inflammation. SIGNIFICANCE: Adaptation of transfer learning to relate human single-cell RNA sequencing data to organoid-CAF cocultures facilitates discovery of human pancreatic cancer intercellular interactions and uncovers cross-talk between CAFs and tumor cells through VEGFA and ITGB1.

Understanding familial risk of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease that is the result of an accumulation of sequential genetic alterations. These genetic alterations can either be inherited, such as pathogenic germline variants that are associated with an increased risk of cancer, or acquired, such as somatic mutations that occur during the lifetime of an individual. Understanding the genetic basis of inherited risk of PDAC is essential to advancing patient care and outcomes through improved clinical surveillance, early detection initiatives, and targeted therapies. In this review we discuss factors associated with an increased risk of PDAC, the prevalence of genetic variants associated with an increased risk in patients with PDAC, estimates of PDAC risk in carriers of pathogenic germline variants in genes associated with an increased risk of PDAC. The role of common variants in pancreatic cancer risk will also be discussed.

International evidence-based Kyoto guidelines for the management of intraductal papillary mucinous neoplasm of the pancreas.

This study group aimed to revise the 2017 international consensus guidelines for the management of intraductal papillary mucinous neoplasm (IPMN) of the pancreas, and mainly focused on five topics; the revision of high-risk stigmata (HRS) and worrisome features (WF), surveillance of non-resected IPMN, surveillance after resection of IPMN, revision of pathological aspects, and investigation of molecular markers in cyst fluid. A new development from the prior guidelines is that systematic reviews were performed for each one of these topics, and published separately to provide evidence-based recommendations. One of the highlights of these new "evidence-based guidelines" is to propose a new management algorithm, and one major revision is to include into the assessment of HRS and WF the imaging findings from endoscopic ultrasound (EUS) and the results of cytological analysis from EUS-guided fine needle aspiration technique, when this is performed. Another key element of the current guidelines is to clarify whether lifetime surveillance for small IPMNs is required, and recommends two options, "stop surveillance" or "continue surveillance for possible development of concomitant pancreatic ductal adenocarcinoma", for small unchanged BD-IPMN after 5 years surveillance. Several other points are also discussed, including identifying high-risk features for recurrence in patients who underwent resection of non-invasive IPMN with negative surgical margin, summaries of the recent observations in the pathology of IPMN. In addition, the emerging role of cyst fluid markers that can aid in distinguishing IPMN from other pancreatic cysts and identify those IPMNs that harbor high-grade dysplasia or invasive carcinoma is discussed.

Three-dimensional assessments are necessary to determine the true, spatially-resolved composition of tissues.

Methods for spatially resolved cellular profiling using thinly cut sections have enabled in-depth quantitative tissue mapping to study inter-sample and intra-sample differences in normal human anatomy and disease onset and progression. These methods often profile extremely limited regions, which may impact the evaluation of heterogeneity due to tissue sub-sampling. Here, we applied CODA, a deep learning-based tissue mapping platform, to reconstruct the three-dimensional (3D) microanatomy of grossly normal and cancer-containing human pancreas biospecimens obtained from individuals who underwent pancreatic resection. To compare inter- and intra-sample heterogeneity, we assessed bulk and spatially resolved tissue composition in a cohort of two-dimensional (2D) whole slide images (WSIs) and a cohort of thick slabs of pancreas tissue that were digitally reconstructed in 3D from serial sections. To demonstrate the marked under sampling of 2D assessments, we simulated the number of WSIs and tissue microarrays (TMAs) necessary to represent the compositional heterogeneity of 3D data within 10% error to reveal that tens of WSIs and hundreds of TMA cores are sometimes needed. We show that spatial correlation of different pancreatic structures decay significantly within a span of microns, demonstrating that 2D histological sections may not be representative of their neighboring tissues. In sum, we demonstrate that 3D assessments are necessary to accurately assess tissue composition in normal and abnormal specimens and in order to accurately determine neoplastic content. These results emphasize the importance of intra-sample heterogeneity in tissue mapping efforts.

Three-dimensional analysis of ductular reactions and their correlation with liver regeneration and fibrosis.

The liver has multiple regeneration modes, including hepatocellular hypertrophy and self-renewal of hepatocytes. When hepatocyte proliferation is impaired, hepatic progenitor cells may proliferate through ductular reaction (DR), differentiate into hepatocytes, and contribute to fibrosis. However, the three-dimensional spatial relationship between DR and regenerating hepatocytes and dynamic changes in DR associated with fibrosis remain poorly understood. Here, we performed three-dimensional (3D) imaging of cleared 42 liver explants with chronic and acute liver diseases and 4 normal livers to visualize DR. In chronic hepatic liver diseases, such as viral hepatitis, steatohepatitis, autoimmune hepatitis, and cryptogenic cirrhosis, the total length and number of branches of DR showed a significant positive correlation. We studied the spatial relationship between DR and GS-expressing cells using glutamine synthetase (GS) and cytokeratin 19 (CK19) as markers of liver regeneration and DR, respectively. The percentage of CK19-positive cells that co-expressed GS was less than 10% in chronic liver diseases. In contrast, nearly one-third of CK19-positive cells co-expressed GS in acute liver diseases, and chronic cholestatic liver diseases, including primary biliary cholangitis and primary sclerosing cholangitis, showed no co-expression. We also found that DR was longer and had more branching in livers with progressive fibrosis compared to those with regressive fibrosis. Our results suggest that DR displays varying degrees of spatial complexity and contribution to liver regeneration. DR may serve as hepatobiliary junctions that maintain continuity between hepatocytes and bile ducts rather than hepatocyte regeneration in chronic liver diseases.

Systematic review of challenging issues in pathology of intraductal papillary mucinous neoplasms.

BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs) are a cystic precursor to pancreatic cancer. IPMNs deemed clinically to be at high-risk for malignant progression are frequently treated with surgical resection, and pathological examination of the pancreatectomy specimen is a key component of the clinical care of IPMN patients. METHODS: Systematic literature reviews were conducted around eight topics of clinical relevance in the examination of pathological specimens in patients undergoing resection of IPMN. RESULTS: This review provides updated perspectives on morphological subtyping of IPMNs, classification of intraductal oncocytic papillary neoplasms, nomenclature for high-grade dysplasia, assessment of T stage, distinction of carcinoma associated or concomitant with IPMN, role of molecular assessment of IPMN tissue, role of intraoperative assessment by frozen section, and preoperative evaluation of cyst fluid cytology. CONCLUSIONS: This analysis provides the foundation for data-driven approaches to several challenging issues in the pathology of IPMNs.

Somatic loss of ATM is a late event in pancreatic tumorigenesis.

Understanding the timing and spectrum of genetic alterations that contribute to the development of pancreatic cancer is essential for effective interventions and treatments. The aim of this study was to characterize somatic ATM alterations in noninvasive pancreatic precursor lesions and invasive pancreatic adenocarcinomas from patients with and without pathogenic germline ATM variants. DNA was isolated and sequenced from the invasive pancreatic ductal adenocarcinomas and precursor lesions of patients with a pathogenic germline ATM variant. Tumor and precursor lesions from these patients as well as colloid carcinoma from patients without a germline ATM variant were immunolabeled to assess ATM expression. Among patients with a pathogenic germline ATM variant, somatic ATM alterations, either mutations and/or loss of protein expression, were identified in 75.0% of invasive pancreatic adenocarcinomas but only 7.1% of pancreatic precursor lesions. Loss of ATM expression was also detected in 31.0% of colloid carcinomas from patients unselected for germline ATM status, significantly higher than in pancreatic precursor lesions [pancreatic intraepithelial neoplasms (p = 0.0013); intraductal papillary mucinous neoplasms, p = 0.0040] and pancreatic ductal adenocarcinoma (p = 0.0076) unselected for germline ATM status. These data are consistent with the second hit to ATM being a late event in pancreatic tumorigenesis. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Predictive ability of pancreatic cyst fluid biomarkers: A systematic review and meta-analysis.

BACKGROUND: Mucinous pancreatic cysts harbor the potential to progress to highly lethal pancreatic ductal adenocarcinoma (PDAC). Since these precursor cysts require cancer surveillance or surgical resection, they need to be reliably distinguished from harmless pancreatic cysts. Current clinical and radiographic assessment is imperfect and the value of cyst fluid analysis for differential diagnosis is unclear. Therefore, we set out to investigate the value of cyst fluid biomarkers in distinguishing pancreatic cysts. METHODS: We performed a systematic review of the current literature to identify articles that evaluated the diagnostic performance of clinically relevant and promising candidate cyst fluid biomarkers, with a particular emphasis on DNA-based biomarkers. Meta-analysis was performed for biomarkers targeted at identifying cyst type and presence of high-grade dysplasia or PDAC. RESULTS: Data from a total of 42 studies was analyzed. Mutations in KRAS and/or GNAS allowed identification of mucinous cysts with a sensitivity of 79% and specificity of 98%. This exceeded the performance of the traditional biomarker carcinoembryonic antigen (CEA; sensitivity 58%, specificity 87%). Mutations in VHL were specific for serous cystadenomas (SCAs; sensitivity 56%, specificity 99%) and help to exclude mucinous cysts. Mutations in CDKN2A, PIK3CA, SMAD4, and TP53 each had high specificities of 97%, 97%, 98%, and 95%, respectively, to identify high-grade dysplasia or PDAC in mucinous cysts. CONCLUSIONS: Cyst fluid analysis can be a valuable tool in the characterization of pancreatic cysts, with relevant clinical implications. Our results support the use of DNA-based cyst fluid biomarkers in the multidisciplinary diagnostic work-up of pancreatic cysts.

Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces.

Recent advances in spatial transcriptomics (STs) enable gene expression measurements from a tissue sample while retaining its spatial context. This technology enables unprecedented in situ resolution of the regulatory pathways that underlie the heterogeneity in the tumor as well as the tumor microenvironment (TME). The direct characterization of cellular co-localization with spatial technologies facilities quantification of the molecular changes resulting from direct cell-cell interaction, as it occurs in tumor-immune interactions. We present SpaceMarkers, a bioinformatics algorithm to infer molecular changes from cell-cell interactions from latent space analysis of ST data. We apply this approach to infer the molecular changes from tumor-immune interactions in Visium spatial transcriptomics data of metastasis, invasive and precursor lesions, and immunotherapy treatment. Further transfer learning in matched scRNA-seq data enabled further quantification of the specific cell types in which SpaceMarkers are enriched. Altogether, SpaceMarkers can identify the location and context-specific molecular interactions within the TME from ST data.

Morphology-guided transcriptomic analysis of human pancreatic cancer organoids reveals microenvironmental signals that enhance invasion.

Pancreatic ductal adenocarcinoma (PDAC) frequently presents with metastasis, but the molecular programs in human PDAC cells that drive invasion are not well understood. Using an experimental pipeline enabling PDAC organoid isolation and collection based on invasive phenotype, we assessed the transcriptomic programs associated with invasion in our organoid model. We identified differentially expressed genes in invasive organoids compared with matched noninvasive organoids from the same patients, and we confirmed that the encoded proteins were enhanced in organoid invasive protrusions. We identified 3 distinct transcriptomic groups in invasive organoids, 2 of which correlated directly with the morphological invasion patterns and were characterized by distinct upregulated pathways. Leveraging publicly available single-cell RNA-sequencing data, we mapped our transcriptomic groups onto human PDAC tissue samples, highlighting differences in the tumor microenvironment between transcriptomic groups and suggesting that non-neoplastic cells in the tumor microenvironment can modulate tumor cell invasion. To further address this possibility, we performed computational ligand-receptor analysis and validated the impact of multiple ligands (TGF-ß1, IL-6, CXCL12, MMP9) on invasion and gene expression in an independent cohort of fresh human PDAC organoids. Our results identify molecular programs driving morphologically defined invasion patterns and highlight the tumor microenvironment as a potential modulator of these programs.