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.

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.

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.

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.

Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer.

Pancreatic cancer is currently the third leading cause of cancer death in the United States. The clinical hallmarks of this disease include abdominal pain that radiates to the back, the presence of a hypoenhancing intrapancreatic lesion on imaging, and widespread liver metastases. Technologies such as tissue clearing and three-dimensional (3D) reconstruction of digitized serially sectioned hematoxylin and eosin-stained slides can be used to visualize large (up to 2- to 3-centimeter cube) tissues at cellular resolution. When applied to human pancreatic cancers, these 3D visualization techniques have provided novel insights into the basis of a number of the clinical characteristics of this disease. Here, we describe the clinical features of pancreatic cancer, review techniques for clearing and the 3D reconstruction of digitized microscope slides, and provide examples that illustrate how 3D visualization of human pancreatic cancer at the microscopic level has revealed features not apparent in 2D microscopy and, in so doing, has closed the gap between bench and bedside. Compared with animal models and 2D microscopy, studies of human tissues in 3D can reveal the difference between what can happen and what does happen in human cancers.

Multifaceted role for p53 in pancreatic cancer suppression.

The vast majority of human pancreatic ductal adenocarcinomas (PDACs) harbor TP53 mutations, underscoring p53's critical role in PDAC suppression. PDAC can arise when pancreatic acinar cells undergo acinar-to-ductal metaplasia (ADM), giving rise to premalignant pancreatic intraepithelial neoplasias (PanINs), which finally progress to PDAC. The occurrence of TP53 mutations in late-stage PanINs has led to the idea that p53 acts to suppress malignant transformation of PanINs to PDAC. However, the cellular basis for p53 action during PDAC development has not been explored in detail. Here, we leverage a hyperactive p53 variant-p5353,54-which we previously showed is a more robust PDAC suppressor than wild-type p53, to elucidate how p53 acts at the cellular level to dampen PDAC development. Using both inflammation-induced and KRASG12D-driven PDAC models, we find that p5353,54 both limits ADM accumulation and suppresses PanIN cell proliferation and does so more effectively than wild-type p53. Moreover, p5353,54 suppresses KRAS signaling in PanINs and limits effects on the extracellular matrix (ECM) remodeling. While p5353,54 has highlighted these functions, we find that pancreata in wild-type p53 mice similarly show less ADM, as well as reduced PanIN cell proliferation, KRAS signaling, and ECM remodeling relative to Trp53-null mice. We find further that p53 enhances chromatin accessibility at sites controlled by acinar cell identity transcription factors. These findings reveal that p53 acts at multiple stages to suppress PDAC, both by limiting metaplastic transformation of acini and by dampening KRAS signaling in PanINs, thus providing key new understanding of p53 function in PDAC.

Frequent Intraluminal Growth of Large Muscular Veins in Surgically Resected Colorectal Cancer Tissues: A 3-Dimensional Pathologic Reconstruction Study.

Although venous invasion (VI) is common in colorectal cancers (CRCs) and is associated with distant metastasis, the 3-dimensional (3D) microscopic features and associated mechanisms of VI are not well elucidated. To characterize the patterns of VI, 103 tissue slabs were harvested from surgically resected CRCs with ≥pT2. They were cleared using the modified immunolabeling-enabled 3D imaging of solvent-cleared organs method, labeled with multicolor fluorescent antibodies, including antibodies against cytokeratin 19, desmin, CD31, and E-cadherin, and visualized by confocal laser scanning microscopy. VI was classified as intravasation, intraluminal growth, and/or extravasation, and 2-dimensional and 3D microscopic features were compared. VI was detected more frequently in 3D (56/103 [54.4%]) than in conventional 2-dimensional hematoxylin and eosin-stained slides (33/103 [32%]; P < .001). When VI was present, it was most commonly in the form of intraluminal growth (51/56), followed by extravasation (13/56) and intravasation (5/56). The mean length of intraluminal growth was 334.0 ± 212.4 µm. Neoplastic cell projections extended from cancer cell clusters in the connective tissue surrounding veins, penetrated the smooth muscle layer, and then grew into and filled the venous lumen. E-cadherin expression changed at each invasion phase; intact E-cadherin expression was observed in the cancer cells in the venous walls, but its expression was lost in small clusters of intraluminal neoplastic cells. In addition, reexpression of E-cadherin was observed when cancer cells formed well-oriented tubular structures and accumulated and grew along the luminal side of the venous wall. In contrast, singly scattered cancer cells and cancer cells with poorly defined tubular structures showed loss of E-cadherin expression. E-cadherin expression was intact in the large cohesive clusters of extravasated cancer cells. However, singly scattered cells and smaller projections of neoplastic cells in the stroma outward of venous wall showed a loss of E-cadherin expression. In conclusion, VI was observed in more than half of the CRCs analyzed by 3D histopathologic image reconstruction. Once inside a vein, neoplastic cells can grow intraluminally. The epithelial-mesenchymal transition is not maintained during VI of CRCs.

Utility of promoter hypermethylation in malignant risk stratification of intraductal papillary mucinous neoplasms.

BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs), a type of cystic pancreatic cancer (PC) precursors, are increasingly identified on cross-sectional imaging and present a significant diagnostic challenge. While surgical resection of IPMN-related advanced neoplasia, i.e., IPMN-related high-grade dysplasia or PC, is an essential early PC detection strategy, resection is not recommended for IPMN-low-grade dysplasia (LGD) due to minimal risk of carcinogenesis, and significant procedural risks. Based on their promising results in prior validation studies targeting early detection of classical PC, DNA hypermethylation-based markers may serve as a biomarker for malignant risk stratification of IPMNs. This study investigates our DNA methylation-based PC biomarker panel (ADAMTS1, BNC1, and CACNA1G genes) in differentiating IPMN-advanced neoplasia from IPMN-LGDs. METHODS: Our previously described genome-wide pharmaco-epigenetic method identified multiple genes as potential targets for PC detection. The combination was further optimized and validated for early detection of classical PC in previous case-control studies. These promising genes were evaluated among micro-dissected IPMN tissue (IPMN-LGD: 35, IPMN-advanced neoplasia: 35) through Methylation-Specific PCR. The discriminant capacity of individual and combination of genes were delineated through Receiver Operating Characteristics curve analysis. RESULTS: As compared to IPMN-LGDs, IPMN-advanced neoplasia had higher hypermethylation frequency of candidate genes: ADAMTS1 (60% vs. 14%), BNC1 (66% vs. 3%), and CACGNA1G (25% vs. 0%). We observed Area Under Curve (AUC) values of 0.73 for ADAMTS1, 0.81 for BNC1, and 0.63 for CACNA1G genes. The combination of the BNC1/ CACNA1G genes resulted in an AUC of 0.84, sensitivity of 71%, and specificity of 97%. Combining the methylation status of the BNC1/CACNA1G genes, blood-based CA19-9, and IPMN lesion size enhanced the AUC to 0.92. CONCLUSION: DNA-methylation based biomarkers have shown a high diagnostic specificity and moderate sensitivity for differentiating IPMN-advanced neoplasia from LGDs. Addition of specific methylation targets can improve the accuracy of the methylation biomarker panel and enable the development of noninvasive IPMN stratification biomarkers.

Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions.

Pancreatic intraepithelial neoplasia (PanIN) is a precursor to pancreatic cancer and represents a critical opportunity for cancer interception. However, the number, size, shape, and connectivity of PanINs in human pancreatic tissue samples are largely unknown. In this study, we quantitatively assessed human PanINs using CODA, a novel machine-learning pipeline for 3D image analysis that generates quantifiable models of large pieces of human pancreas with single-cell resolution. Using a cohort of 38 large slabs of grossly normal human pancreas from surgical resection specimens, we identified striking multifocality of PanINs, with a mean burden of 13 spatially separate PanINs per cm3 of sampled tissue. Extrapolating this burden to the entire pancreas suggested a median of approximately 1000 PanINs in an entire pancreas. In order to better understand the clonal relationships within and between PanINs, we developed a pipeline for CODA-guided multi-region genomic analysis of PanINs, including targeted and whole exome sequencing. Multi-region assessment of 37 PanINs from eight additional human pancreatic tissue slabs revealed that almost all PanINs contained hotspot mutations in the oncogene KRAS, but no gene other than KRAS was altered in more than 20% of the analyzed PanINs. PanINs contained a mean of 13 somatic mutations per region when analyzed by whole exome sequencing. The majority of analyzed PanINs originated from independent clonal events, with distinct somatic mutation profiles between PanINs in the same tissue slab. A subset of the analyzed PanINs contained multiple KRAS mutations, suggesting a polyclonal origin even in PanINs that are contiguous by rigorous 3D assessment. This study leverages a novel 3D genomic mapping approach to describe, for the first time, the spatial and genetic multifocality of human PanINs, providing important insights into the initiation and progression of pancreatic neoplasia.

CODA: quantitative 3D reconstruction of large tissues at cellular resolution.

A central challenge in biology is obtaining high-content, high-resolution information while analyzing tissue samples at volumes relevant to disease progression. We address this here with CODA, a method to reconstruct exceptionally large (up to multicentimeter cubed) tissues at subcellular resolution using serially sectioned hematoxylin and eosin-stained tissue sections. Here we demonstrate CODA's ability to reconstruct three-dimensional (3D) distinct microanatomical structures in pancreas, skin, lung and liver tissues. CODA allows creation of readily quantifiable tissue volumes amenable to biological research. As a testbed, we assess the microanatomy of the human pancreas during tumorigenesis within the branching pancreatic ductal system, labeling ten distinct structures to examine heterogeneity and structural transformation during neoplastic progression. We show that pancreatic precancerous lesions develop into distinct 3D morphological phenotypes and that pancreatic cancer tends to spread far from the bulk tumor along collagen fibers that are highly aligned to the 3D curves of ductal, lobular, vascular and neural structures. Thus, CODA establishes a means to transform broadly the structural study of human diseases through exploration of exhaustively labeled 3D microarchitecture.

Organoids: A Promising Preclinical Model for Pancreatic Cancer Research.

ABSTRACT: Pancreatic cancer is one of the most lethal cancer types, estimated to become the second leading cause of cancer-related deaths in the United States in 2030. The use of 3-dimensional culture systems has greatly expanded over the past few years, providing a valuable tool for the study of pancreatic cancer. In this review, we highlight some of the preclinical in vitro and in vivo models used in pancreatic cancer research, each with its own advantages and disadvantages, and focus on one of the recently used 3-dimensional culture models: organoids. Organoids are multicellular units derived from tissue samples and embedded within extracellular matrix gels after mechanical and enzymatic digestion. We define organoids, differentiate them from other 3-dimensional culture systems such as spheroids, and describe some applications of this model that have recently advanced our understanding of pancreatic cancer and its tumor microenvironment. Organoids have provided valuable insights into pancreatic cancer progression, heterogeneity, and invasion, and they have enabled the creation of biobanks, providing a platform for drug screening. In addition, we discuss some of the future directions and challenges in this model when addressing research questions.