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.

Inhibitors of calcineurin phosphatase activity (CNIs) such as cyclosporin A (CsA) are widely used to treat tissue transplant rejection and acute graft-versus-host disease (aGVHD), for which inhibition of gene expression dependent on nuclear factor of activated T cells (NFAT) is the mechanistic paradigm. We recently reported that CNIs inhibit TCR-proximal signaling by preventing calcineurin-mediated dephosphorylation of Lck^S59, an inhibitory modification, raising the possibility of another mechanism by which CNIs suppress immune responses. Here we used T cells from mice that express Lck^S59A, which cannot accept a phosphate at residue 59, to initiate aGVHD. Although CsA inhibited NFAT-dependent gene upregulation in allo-aggressive T cells expressing either Lck^WT or Lck^S59A, it was ineffective in treating disease when the T cells expressed Lck^S59A. Two important NFAT-independent T cell functions were found to be CsA-resistant in Lck^S59A T cells: upregulation of the cytolytic protein perforin in tissue-infiltrating CD8⁺ T cells and antigen-specific T/DC adhesion and clustering in lymph nodes. These results demonstrate that effective treatment of aGVHD by CsA requires NFAT-independent inhibition of TCR signaling. Given that NFATs are widely expressed and off-target effects are a major limitation in CNI use, it is possible that targeting TCR-associated calcineurin directly may provide effective therapies with less toxicity.

Background: Brown tumor is a rare skeletal manifestation of secondary hyperparathyroidism. Although diagnosis of the disease is increasingly seen in early stages due to improved screening techniques, some patients still present in a progressed disease stage. The treatment depends on tumor mass and varies from a conservative approach with supportive parathyroidectomy to extensive surgical resection with subsequent reconstruction. Case presentation: We report a case of extensive mandibular brown tumor in a patient with a history of systemic lupus erythematosus, chronic kidney disease, and secondary hyperparathyroidism. Following radical resection of the affected bone, reconstruction could be successfully performed using a free flap. Conclusions: There were no signs of recurrence during five years of close follow-up. Increased awareness and multidisciplinary follow-ups could allow early diagnosis and prevent the need for radical therapeutical approaches.

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-β1, 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.

Extensive desmoplastic stroma is a hallmark of pancreatic ductal adenocarcinoma (PDAC) and contributes to tumor progression and to the relative resistance of tumor cells towards (radio) chemotherapy. Thus, therapies that target the stroma are under intense investigation. To allow the stratification of patients who would profit from such therapies, non-invasive methods assessing the stroma content in relation to tumor mass are required. In the current prospective study, we investigated the usefulness of diffusion-weighted magnetic resonance imaging (DW-MRI), a radiologic method that measures the random motion of water molecules in tissue, in the assessment of PDAC lesions, and more specifically in the desmoplastic tumor stroma. We made use of a sophisticated DW-MRI approach, the so-called diffusion kurtosis imaging (DKI), which possesses potential advantages over conventional and widely used monoexponential diffusion-weighted imaging analysis (cDWI). We found that the diffusion constant D from DKI is highly negatively correlated with the percentage of tumor stroma, the latter determined by histology. D performed significantly better than the widely used apparent diffusion coefficient (ADC) from cDWI in distinguishing stroma-rich (>50% stroma percentage) from stroma-poor tumors (≤50% stroma percentage). Moreover, we could prove the potential of the diffusion constant D as a clinically useful imaging parameter for the differentiation of PDAC-lesions from non-neoplastic pancreatic parenchyma. Therefore, the diffusion constant D from DKI could represent a valuable non-invasive imaging biomarker for assessment of stroma content in PDAC, which is applicable for the clinical diagnostic of PDAC.

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a diagnostic tool that is increasingly used for the detection and characterization of focal masses in the abdomen, among these, pancreatic ductal adenocarcinoma (PDAC). DW-MRI reflects the microarchitecture of the tissue, and changes in diffusion, which are reflected by changes in the apparent diffusion coefficient (ADC), are mainly attributed to variations in cellular density, glandular formation, and fibrosis. When analyzing the T cell infiltrates, we found an association of a tumor-promoting subpopulation, characterized by the expression of interleukin (IL) 21 and IL26, with high ADC values. Moreover, the presence of IL21⁺ and IL26⁺ positive T cells was associated with poor prognosis. Pancreatic cancers—but not healthy pancreatic tissue—expressed receptors for IL21 and IL26, a finding that could be confirmed in pancreatic cell lines. The functionality of these receptors was demonstrated in pancreatic tumor cell lines, which showed phosphorylation of ERK1/2 and STAT3 pathways in response to the respective recombinant interleukins. Moreover, in vitro data showed an increased colony formation of tumor cells. In summary, our data showed an association of IL21⁺ and IL26⁺ immune cell infiltration, increased ADC, and aggressive tumor disease, most likely due to the activation of the key cancer signaling pathways ERK1/2 and STAT3 and formation of tumor colonies.