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Introduction: Differentiation of histologically similar structures in the liver, including anatomical structures, benign bile duct lesions, or common types of liver metastases, can be challenging with conventional histological tissue sections alone. Accurate histopathological classification is paramount for the diagnosis and adequate treatment of the disease. Deep learning algorithms have been proposed for objective and consistent assessment of digital histopathological images., Materials and Methods: In the present study, we trained and evaluated deep learning algorithms based on the EfficientNetV2 and ResNetRS architectures to discriminate between different histopathological classes. For the required dataset, specialized surgical pathologists annotated seven different histological classes, including different non-neoplastic anatomical structures, benign bile duct lesions, and liver metastases from colorectal and pancreatic adenocarcinoma in a large patient cohort. Annotation resulted in a total of 204.159 image patches, followed by discrimination analysis using our deep learning models. Model performance was evaluated on validation and test data using confusion matrices., Results: Evaluation of the test set based on tiles and cases revealed overall highly satisfactory prediction capability of our algorithm for the different histological classes, resulting in a tile accuracy of 89% (38 413/43 059) and case accuracy of 94% (198/211). Importantly, the separation of metastasis versus benign lesions was certainly confident on case level, confirming the classification model performed with high diagnostic accuracy. Moreover, the whole curated raw data set is made publically available., Conclusions: Deep learning is a promising approach in surgical liver pathology supporting decision making in personalized medicine., (© 2023 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.)

Several collagen subtypes are involved in pancreatic ductal adenocarcinoma (PDAC) desmoplasia, which constrains therapeutic efficacy. We evaluated collagen type VIII alpha 1 chain (COL8A1), whose function in PDAC is currently unknown. We identified COL8A1 expression in 7 examined PDAC cell lines by microarray analysis, western blotting, and RT‒qPCR. Higher COL8A1 expression occurred in 2 gemcitabine-resistant PDAC cell lines; pancreas tissue (n=15) from LSL-Kras G12D/+ ; p48-Cre mice with advanced PDAC predisposition; and PDAC parenchyma and stroma of a patient tissue microarray (n=82). Bioinformatic analysis confirmed higher COL8A1 expression in PDAC patient tissue available from TCGA (n=183), GTEx (n=167), and GEO (n=261) databases. siRNA or lentiviral sh-mediated COL8A1 inhibition in PDAC cells reduced migration, invasion and gemcitabine resistance and resulted in lower cytidine deaminase and thymidine kinase 2 expression and was rescued by COL8A1-secreting cancer-associated fibroblasts (CAFs). The activation of COL8A1 expression involved cJun/AP-1, as demonstrated by CHIP assay and siRNA inhibition. Downstream of COL8A1, activation of ITGB1 and DDR1 receptors and PI3K/AKT and NF-κB signaling occurred, as detected by expression, adhesion and EMSA binding studies. Orthotopic transplantation of PDAC cells with downregulated COL8A1 expression resulted in reduced tumor xenograft growth and lower gemcitabine resistance but was prevented by cotransplantation of COL8A1-secreting CAFs. Most importantly, COL8A1 expression in PDAC patient tissues from our clinic (n=84) correlated with clinicopathological data, and we confirmed these findings by the use of patient data (n=177) from the TCGA database. These findings highlight COL8A1 expression in tumor and stromal cells as a new biomarker for PDAC progression., Competing Interests: Declaration of Competing Interest The authors declare no potential conflicts of interest., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose: To investigate the safety, clinical efficacy, virus pharmacokinetics, shedding, and immune response after administration of an oncolytic parvovirus (H-1PV, ParvOryx) to patients with metastatic pancreatic ductal adenocarcinoma (PDAC) refractory to first-line therapy., Patients and Methods: This is a noncontrolled, single-arm, open-label, dose-escalating, single-center clinical trial. Seven patients with PDAC and at least one liver metastasis were included. ParvOryx was administered intravenously on 4 consecutive days and as an intralesional injection, 6 to 13 days thereafter. Altogether, three escalating dose levels were investigated. In addition, gemcitabine treatment was initiated on day 28., Results: ParvOryx showed excellent tolerability with no dose-limiting toxicities. One patient had a confirmed partial response and one patient revealed an unconfirmed partial response according to RECIST criteria. Both patients showed remarkably long surivial of 326 and 555 days, respectively. Investigation of pharmacokinetics and virus shedding revealed dose dependency with no excretion of active virus particles in saliva or urine and very limited excretion in feces. H-1PV nucleic acids were detected in tumor samples of four patients. All patients showed T-cell responses to viral proteins. An interesting immunologic pattern developed in tumor tissues and in blood of both patients with partial response suggesting immune activation after administration of ParvOryx., Conclusions: The trial met all primary objectives, revealed no environmental risks, and indicated favorable immune modulation after administration of ParvOryx. It can be considered a good basis for further systematic clinical development alone or in combination with immunomodulatory compounds., (©2021 American Association for Cancer Research.)

Identification of pancreatic ductal adenocarcinoma (PDAC) and precursor lesions in histological tissue slides can be challenging and elaborate, especially due to tumor heterogeneity. Thus, supportive tools for the identification of anatomical and pathological tissue structures are desired. Deep learning methods recently emerged, which classify histological structures into image categories with high accuracy. However, to date, only a limited number of classes and patients have been included in histopathological studies. In this study, scanned histopathological tissue slides from tissue microarrays of PDAC patients ( n = 201, image patches n = 81.165) were extracted and assigned to a training, validation, and test set. With these patches, we implemented a convolutional neuronal network, established quality control measures and a method to interpret the model, and implemented a workflow for whole tissue slides. An optimized EfficientNet algorithm achieved high accuracies that allowed automatically localizing and quantifying tissue categories including pancreatic intraepithelial neoplasia and PDAC in whole tissue slides. SmoothGrad heatmaps allowed explaining image classification results. This is the first study that utilizes deep learning for automatic identification of different anatomical tissue structures and diseases on histopathological images of pancreatic tissue specimens. The proposed approach is a valuable tool to support routine diagnostic review and pancreatic cancer research.

Background/objectives: The aim of this study was to compare intravoxel incoherent motion (IVIM) diffusion weighted (DW) MRI and CT perfusion to assess tumor perfusion of pancreatic ductal adenocarcinoma (PDAC)., Methods: In this prospective study, DW-MRI and CT perfusion were conducted in nineteen patients with PDAC on the day before surgery. IVIM analysis of DW-MRI was performed and the parameters perfusion fraction f, pseudodiffusion coefficient D*, and diffusion coefficient D were extracted for tumors, upstream, and downstream parenchyma. With a deconvolution-based analysis, the CT perfusion parameters blood flow (BF) and blood volume (BV) were estimated for tumors, upstream, and downstream parenchyma. In ten patients, intratumoral microvessel density (MVD tumor ) and microvessel area (MVA tumor ) were analyzed microscopically in resection specimens. Correlation coefficients between IVIM parameters, CT perfusion parameters, and histological microvessel parameters in tumors were calculated. Receiver operating characteristic (ROC) analysis was performed for differentiation of tumors and upstream parenchyma., Results: f tumor significantly positively correlated with BF tumor (r = 0.668, p = 0.002) and BV tumor (r = 0.672, p = 0.002). There were significant positive correlations between f tumor and MVD tumor / MVA tumor (r ≥ 0.770, p ≤ 0.009) as well as between BF tumor and MVD tumor / MVA tumor (r ≥ 0.697, p ≤ 0.025). Correlation coefficients between f tumor and MVD tumor / MVA tumor were not significantly different from correlation coefficients between BF tumor and MVD tumor / MVA tumor (p ≥ 0.400). Moreover, f, BF, BV, and permeability values (PEM) showed excellent performance in distinguishing tumors from upstream parenchyma (area under the ROC curve ≥0.874)., Conclusions: The study shows that IVIM derived f tumor and CT perfusion derived BF tumor similarly reflect vascularity of PDAC and seem to be comparably applicable for the evaluation of tumor perfusion for tumor characterization and as potential quantitative imaging biomarker., Trial Registration: DRKS, DRKS00022227, Registered 26 June 2020, retrospectively registered. https://www.drks.de/drks_web/navigate.do?navigationId=trial . HTML&TRIAL_ID=DRKS00022227.

Objective: To evaluate the impact of clinical and pathological parameters, including resection margin (R) status, on survival in patients undergoing pancreatic surgery after neoadjuvant treatment for initially unresectable pancreatic ductal adenocarcinoma (PDAC)., Background: Prognostic factors are well documented for patients with resectable PDAC, but have not been described in detail for patients with initially unresectable PDAC undergoing resection after neoadjuvant therapy., Methods: Prospectively collected data of consecutive patients with initially unresectable pancreatic cancer treated by neoadjuvant treatment and resection were analyzed. The R status was categorized as R0 (tumor-free margin >1 mm), R1 ≤1 mm (tumor-free margin ≤1 mm), and R1 direct (microscopic tumor infiltration at margin). Clinicopathological characteristics and outcomes were compared among these groups and tested for survival prediction., Results: Between January, 2006 and February, 2017, 280 patients with borderline resectable (n = 18), locally advanced (n = 190), or oligometastatic (n = 72) disease underwent tumor resection after neoadjuvant treatment. Median overall survival from the time of surgery was 25.1 months for R0 (n = 82), 15.3 months for R1 ≤1 mm (n = 99), and 16.1 months for R1 direct (n = 99), with 3-year overall survival rates of 35.0%, 20.7%, and 18.5%, respectively (P = 0.0076). The median duration of the neoadjuvant treatment period was 5.1 months. In multivariable analysis, preoperative CA 19-9 levels, lymph node status, metastasis category, and vascular involvement were all significant prognostic factors for overall survival. The R status was not an independent prognostic factor., Conclusions: In patients undergoing resection after neoadjuvant therapy for initially unresectable PDAC, preoperative CA 19-9 levels, lymph node involvement, metastasis category, and vascular involvement, but not the R status, were independent prognostic factors of overall survival., Competing Interests: All authors declare no financial interests and no conflicts of interest., (Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.)

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by extensive local invasion and systemic spread. In this study, we employed a three-dimensional organoid model of human pancreatic cancer to characterize the molecular alterations critical for invasion. Time-lapse microscopy was used to observe invasion in organoids from 25 surgically resected human PDAC samples in collagen I. Subsequent lentiviral modification and small-molecule inhibitors were used to investigate the molecular programs underlying invasion in PDAC organoids. When cultured in collagen I, PDAC organoids exhibited two distinct, morphologically defined invasive phenotypes, mesenchymal and collective. Each individual PDAC gave rise to organoids with a predominant phenotype, and PDAC that generated organoids with predominantly mesenchymal invasion showed a worse prognosis. Collective invasion predominated in organoids from cancers with somatic mutations in the driver gene SMAD4 (or its signaling partner TGFBR2 ). Reexpression of SMAD4 abrogated the collective invasion phenotype in SMAD4 -mutant PDAC organoids, indicating that SMAD4 loss is required for collective invasion in PDAC organoids. Surprisingly, invasion in passaged SMAD4 -mutant PDAC organoids required exogenous TGFβ, suggesting that invasion in SMAD4 -mutant organoids is mediated through noncanonical TGFβ signaling. The Rho-like GTPases RAC1 and CDC42 acted as potential mediators of TGFβ-stimulated invasion in SMAD4 -mutant PDAC organoids, as inhibition of these GTPases suppressed collective invasion in our model. These data suggest that PDAC utilizes different invasion programs depending on SMAD4 status, with collective invasion uniquely present in PDAC with SMAD4 loss. SIGNIFICANCE: Organoid models of PDAC highlight the importance of SMAD4 loss in invasion, demonstrating that invasion programs in SMAD4 -mutant and SMAD4 wild-type tumors are different in both morphology and molecular mechanism., (©2020 American Association for Cancer Research.)

Epstein-Barr virus positivity (EBV(+)) and high-microsatellite instability (MSI-H) have been identified as molecular subgroups in gastric carcinoma. The aim of our study was to determine the prognostic and predictive relevance of these subgroups in the context of platinum/5-fluorouracil (5-FU) based preoperative chemotherapy (CTx). Additionally, we investigated the clinical relevance of the low-MSI (MSI-L) phenotype. We analysed 760 adenocarcinomas of the stomach or the gastro-oesophageal junction encompassing 143 biopsies before CTx and 617 resected tumours (291 without and 326 after CTx). EBV was determined by PCR and in situ hybridisation for selected cases. MSI was analysed by PCR using five microsatellite markers and classified as MSI-H and MSI-L. Frequencies of EBV(+), MSI-H and MSI-L in the biopsies before CTx were 4.2, 10.5 and 4.9% respectively. EBV(+) or MSI-H did not correlate with response, but MSI-L was associated with better response (p = 0.011). In the resected tumours, frequencies of EBV(+), MSI-H and MSI-L were 3.9, 9.6 and 4.5% respectively. Overall survival (OS) was significantly different in the non-CTx group (p = 0.014). Patients with EBV(+) tumours showed the best OS, followed by MSI-H. MSI-L was significantly associated with worse OS (hazard ratio [HR], 2.21; 95% confidence interval [CI], 1.21-4.04, p = 0.01). In the resected tumours after CTx, MSI-H was also associated with increased OS (HR, 0.54; 95% CI, 0.26-1.09, p = 0.085). In multivariable analysis, molecular classification was an independent prognostic factor in the completely resected (R0) non-CTx group (p = 0.035). In conclusion, MSI-H and EBV(+) are not predictive of response to neoadjuvant platinum/5-FU based CTx, but they are indicative of a good prognosis. In particular, MSI-H indicates a favourable prognosis irrespective of treatment with CTx. MSI-L predicts good response to CTx and its negative prognostic effect for patients treated with surgery alone suggests that MSI-L might help to identify patients with potentially high-benefit from preoperative CTx., (© 2019 The Authors. The Journal of Pathology: Clinical Research published by The Pathological Society of Great Britain and Ireland and John Wiley & Sons Ltd.)

Background: Discriminating between autoimmune pancreatitis (AIP), chronic pancreatitis (CP), and pancreatic ductal adenocarcinoma (PDAC) can be challenging. In this retrospective study, levels of serum and tissue cytokines were analyzed as part of the clinical strategy for the preoperative differentiation between AIP and PDAC. The identification of differential cytokine profiles may help to prevent unnecessary surgical resection and allow optimal treatment of these pathologies., Methods: To compare the cytokine profiles of AIP, CP, and PDAC patients, serum and pancreatic tissue homogenates were subjected to multiplex analysis of 17 inflammatory mediators. In total, serum from 73 patients, composed of 29 AIP (14 AIP-1 and 15 AIP-2), 17 CP, and 27 PDAC, and pancreatic tissue from 36 patients, including 12 AIP (six AIP-1 and six AIP-2), 12 CP, and 12 PDAC, were analyzed., Results: Comparing AIP and PDAC patients' serum, significantly higher concentrations were found in AIP for interleukins IL-1β, IL-7, IL-13, and granulocyte colony-stimulating factor (G-CSF). G-CSF also allowed discrimination of AIP from CP. Furthermore, once AIP was divided into subtypes, significantly higher serum levels for IL-7 and G-CSF were measured in both subtypes of AIP and in AIP-2 for IL-1β when compared to PDAC. G-CSF and TNF-α were also significantly differentially expressed in tissue homogenates between AIP-2 and PDAC., Conclusions: The cytokines IL-1β, IL-7, and G-CSF can be routinely measured in patients' serum, providing an elegant and non-invasive approach for differential diagnosis. G-CSF is a good candidate to supplement the currently known serum markers in predictive tests for AIP and represents a basis for a combined blood test to differentiate AIP and particularly AIP-2 from PDAC, enhancing the possibility of appropriate treatment.

Objectives: Our aim was to establish and characterize a novel pancreatic ductal adenocarcinoma cell line from a patient in whom the origin of the invasive carcinoma could be traced back to the intraductal papillary mucinous neoplasm (IPMN) precursor lesion., Methods: The primary patient-derived tumor was propagated in immunocompromised mice for 2 generations and used to establish a continuous in vitro culture termed ASAN-PaCa. Transplantation to fertilized chicken eggs confirmed the tumorigenic potential in vivo. Molecular analyses included karyotyping, next-generation genomic sequencing, expression analysis of marker proteins, and mucin-profiling., Results: The analysis of marker proteins confirmed the epithelial nature of the established cell line, and revealed that the expression of the mucin MUC1 was higher than that of MUC2 and MUC5AC. ASAN-PaCa cells showed rapid in vitro and in vivo growth and multiple chromosomal aberrations. They harbored mutations in KRAS (Q61H), TP53 (Y220C), and RNF43 (I47V and L418M) but lacked either IPMN-specific GNAS or presumed pancreatic ductal adenocarcinoma-driving mutations in KRAS (codons 12/13), SMAD, and CDKN2A genes., Conclusions: ASAN-PaCa cell line represents a novel preclinical model of pancreatic adenocarcinoma arising in the background of IPMN, and offers an opportunity to study how further introduction of known driver mutations might contribute to pancreatic carcinogenesis.

Galectin-3 influences neoangiogenesis, tumor cell adhesion, and tumor-immune-escape mechanisms. Hence, the expression of galectin-3 in pancreatic ductal adenocarcinoma (PDAC) was evaluated. Galectin-3 expression in PDAC cell lines was proven by the presence of intracellular protein and by release into the supernatant. Furthermore, galectin-3 was found in the majority of human tissue samples. Serum concentrations of galectin-3 in PDAC patients did not differ significantly from healthy donors and did not correlate with established tumor markers. In conclusion, galectin-3 is expressed in PDAC tissues suggesting a role in tumor development; however, no relationship between expression and clinical findings could be established.

Major histocompatibility complex class II antigens (MHC class II) are constitutively expressed by professional antigen presenting cells and present antigenic peptides to specific CD4+ T lymphocytes. MHC class II expression, however, can also be induced on epithelial cells and in a variety of solid tumors. We tested MHC class II expression on tissue samples derived from patients with pancreatic ductal adenocarcinoma (PDAC) and pancreatic endocrine tumors (PET). Immunohistochemistry revealed MHC class II expression in 86 of 112 (76.8%) PDAC samples and in 30 of 43 (70.0%) PET samples. In PDAC and PET, MHC class II expression correlated significantly with severity and activity of intratumoral inflammation, as well as with the infiltration of CD4+ T lymphocytes. High MHC class II expression significantly correlated with a better histological grade of differentiation in PDAC. In vitro MHC class II expression could be induced on PDAC tumor cell lines by interferon-γ. These cells were then able to present the staphylococci enterotoxin B superantigen to T lymphocytes, which resulted in T cell proliferation. Our findings suggest that MHC class II expression on pancreatic tumor cells is induced by the intratumoral inflammatory reaction in pancreatic tumors.

Aims: Undifferentiated (anaplastic) pancreatic cancer and undifferentiated pancreatic carcinoma with osteoclast-like giant cells (giant cell tumour) are rare variants of pancreatic ductal adenocarcinoma. Representing biologically highly aggressive neoplasms, they are frequently diagnosed at an advanced stage. The response to established chemo- or radiochemotherapeutic treatment regimens is poor, and undifferentiated pancreatic cancer generally has a dismal prognosis. As additional therapeutic options have not yet been investigated in undifferentiated pancreatic cancer, the aim was to analyse the expression of putative therapeutic targets that have shown promising results in various other neoplasms., Methods and Results: Fifteen cases of undifferentiated pancreatic cancer (seven containing osteoclast-like giant cells) were investigated clinicopathologically and immunohistochemically for putative therapeutic targets. Whereas L1CAM, cyclooxygenase (COX)-2 and epidermal growth factor receptor (EGFR) were found to be significantly expressed in 80%, 93% and 87% of the investigated tumours, respectively, there was no substantial expression of c-kit (CD117) and there was no detectable expression of Her2/neu., Conclusions: The expression of L1CAM, COX-2 and EGFR in the majority of undifferentiated pancreatic carcinomas suggests that they might represent targets for adjuvant therapy in anaplastic pancreatic cancer. On the other hand, c-kit and Her2/neu seem to have no relevance for the therapy of these tumours.