Microarray technologies enable scientists to identify co-expressed genes at large scale. However, the gene expression analysis does not show functional relationships between co-expressed genes. There is a demand for effective approaches to analyse gene expression data to enable biological discoveries that can lead to identification of markers or therapeutic targets of many diseases. In cancer research, a number of gene expression screens have been carried out to identify genes differentially expressed in cancerous tissue such as Pancreatic Ductal Adenocarcinoma (PDAC). PDAC carries very poor prognosis, it eludes early detection and is characterised by its aggressiveness and resistance to currently available therapies. To identify molecular markers and suitable targets, there exist a research effort that maps differentially expressed genes to protein interactions to gain an understanding at systems level. Such interaction networks have a complex interconnected structure, whose the understanding of which is not a trivial task. Several formal approaches use simulation to support the investigation of such networks. These approaches suffer from the missing knowledge concerning biological systems. Reasoning in the other hand has the advantage of dealing with incomplete and partial information of the network knowledge. The initial approach adopted was to provide an algorithm that utilises a network-centric approach to pancreatic cancer, by re-constructing networks from known interactions and predicting novel protein interactions from structural templates. This method was applied to a data set of co-expressed PDAC genes. To this end, structural domains for the gene products are identified by using threading which is a 3D structure prediction technique. Next, the Protein Structure Interaction Database (SCOPPI), a database that classifies and annotates domain interactions derived from all known protein structures, is used to find templates of structurally interacting domains. Moreover, a network of related biological pathways for the PDAC data was constructed. In order to reason over molecular networks that are affected by dysregulation of gene expression, BioRevise was implemented. It is a belief revision system where the inhibition behaviour of reactions is modelled using extended logic programming. The system computes a minimal set of enzymes whose malfunction explains the abnormal expression levels of observed metabolites or enzymes. As a result of this research, two complementary approaches for the analysis of pancreatic cancer gene expression data are presented. Using the first approach, the pathways found to be largely affected in pancreatic cancer are signal transduction, actin cytoskeleton regulation, cell growth and cell communication. The analysis indicates that the alteration of the calcium pathway plays an important role in pancreas specific tumorigenesis. Furthermore, the structural prediction method reveals ~ 700 potential protein-protein interactions from the PDAC microarray data, among them, 81 novel interactions such as: serine/threonine kinase CDC2L1 interacting with cyclin-dependent kinase inhibitor CDKN3 and the tissue factor pathway inhibitor 2 (TFPI2) interacting with the transmembrane protease serine 4 (TMPRSS4). These resulting genes were further investigated and some were found to be potential therapeutic markers for PDAC. Since TMPRSS4 is involved in metastasis formation, it is hypothesised that the upregulation of TMPRSS4 and the downregulation of its predicted inhibitor TFPI2 plays an important role in this process. The predicted protein-protein network inspired the analysis of the data from two other perspectives. The resulting protein-protein interaction network highlighted the importance of the co-expression of KLK6 and KLK10 as prognostic factors for survival in PDAC as well as the construction of a PDAC specific apoptosis pathway to study different effects of multiple gene silencing in order to reactivate apoptosis in PDAC. Using the second approach, the behaviour of biological interaction networks using computational logic formalism was modelled, reasoning over the networks is enabled and the abnormal behaviour of its components is explained. The usability of the BioRevise system is demonstrated through two examples, a metabolic disorder disease and a deficiency in a pancreatic cancer associated pathway. The system successfully identified the inhibition of the enzyme glucose-6-phosphatase as responsible for the Glycogen storage disease type I, which according to literature is known to be the main reason for this disease. Furthermore, BioRevise was used to model reaction inhibition in the Glycolysis pathway which is known to be affected by Pancreatic cancer.

Das Mikromilieu solider Tumor (tumor mircoenvironment, TME) weist verschiedene Besonderheiten auf, von denen bekannt ist, dass sie zu Chemotherapieresistenz und Tumorprogression beitragen können. Neben der Extrazellulären Matrix (ECM), den cancer associated cells (CAC) und diversen Entzündungszellen tragen auch chemische und physikalische Besonderheiten (Hypoxie, Azidose, erhöhter Gewebedruck, oxidativer Stress und Nährstoffmangel) zu Tumorprogression und Chemotherapieresistenz bei. Zudem wissen wir, dass Hitzeschock-Proteine (HSPs), Toll-like Rezeptoren (TLRs) und ABC-Transporter mit erhöhter Chemotherapieresistenz und Tumorprogression im Pankreas- und Kolonkarzinom einhergehen. Hier wurde untersucht, ob ein in vitro induzierter Nährstoffmangel im HT29 Kolonkarzinom, im Panc-1 Pankreaskarzinom und im MIA PaCa-2 Pankreaskarzinom zu einer gesteigerten Expression von HSP70, HSP90, MDR1, ABCB5 und TLR1 bis TLR10 auf mRNA und Proteinebene führt. Zudem wurde unter allen Versuchsbedingungen die Stoffwechselaktivität über einen MTS-Test gemessen. Der Nährstoffmangel wurde über die Kultivierung in einem Hybridomamedium, welches als proteinfreies Medium gilt und über die Kultivierung in einem serumfreien Medium induziert. Es zeigte sich, dass insbesondere die entdifferenzierte Panc-1 Pankreaskarzinomzelllinie eine erhöhte Resistenz gegenüber dem induzierten Nährstoffmangel aufwies. Auf mRNA-Ebene zeigten sich bei allen drei Tumorzelllinien deutliche Expressionssteigerungen. Diese waren insbesondere im Hybridomamedium nachweisbar und traten beim HT29-Kolonkarzinom nach 48h und im Panc-1 Pankreaskarzinom bereits nach 24h auf. Besonders intensive Expressionssteigerungen konnten im HT29 Kolonkarzinom bei ABCB5, TLR7 und TLR9 nachgewiesen werden. Die Expression von MDR1 war insbesondere im MIA PaCa-2 Pankreaskarzinom gesteigert. Auf Proteinebene konnte im HT29 Kolonkarzinom eine Expressionssteigerung bei HSP90 und TLR6 nachgewiesen werden. Die Ergebnisse lassen zwei Interpretationen zu. Zum einen könnte über den Nährstoffmangel eine aggressivere Subpopulation selektioniert worden sein. In diesem Zusammenhang konnten die Expressionsdaten des Tumorstammzellmarkers CD133 leider nicht ausgewertet werden. Alternativ kann angenommen werden, dass die untersuchten Tumorzelllinien ihren aggressiven Phänotyp erst unter Nährstoffmangelbedingungen, wie wir sie regelmäßig in soliden Tumoren finden, zur Expression bringen. / The tumor microenvironment (TME) in solid tumors is low on nutrients and favors tumor progression and resistance to chemotherapies in different ways. In this study we cultured HT29 colorectal carcinoma cells, Panc-1 pancreatic carcinoma cells and MIA PaCa-2 pancreatic carcinoma cells in nutrient deprived conditions (NDC) and performed rtPCR expression analysis, SDS-PAGE and immunohistochemical staining after 24, 48 and 72 hours. Gene expression of ABC transporters (ABCB5, MDR1), heat-shock proteins (HSP70, HSP90) and Toll-like receptors (TLR1 – TLR10) in the NDC compared to normal condition was analyzed. We performed MTS tetrazolium assays to monitor the activity of the respiratory chain in any condition. We showed that the examined cell lines, and in particular Panc-1 pancreatic carcinoma, are very resistant to the NDC. The gens of interest showed increase expression after 48 hours (HT29) and 24 hours (Panc-1). The results suggest that culturing in NDC either selects a very aggressive and resistant subpopulation or NDC induces gene expression changes and shows us how cancer cells really perform in the nutrient deprived tumor environment. Unfortunately, we were not able to use the gene expression analysis of the stem cell marker CD133.

Objective: The aim of this study was to develop an immunomagnetic/real-time reverse transcriptase polymerase chain reaction (RT-PCR) assay and assess its clinical value for the molecular detection of circulating tumor cells (CTCs) in peripheral blood of pancreatic cancer patients. Methods: The presence of CTCs was evaluated in 34 pancreatic cancer patients before systemic therapy and in 40 healthy controls, through immunomagnetic enrichment, using the antibodies BM7 and VU1D9 [targeting mucin 1 and epithelial cell adhesion molecule (EpCAM), respectively], followed by real-time RT-PCR analysis of the genes KRT19, MUC1, EPCAM, CEACAM5 and BIRC5. Results: The developed assay showed high specificity, as none of the healthy controls were found to be positive for the multimarker gene panel. CTCs were detected in 47.1% of the pancreatic cancer patients before the beginning of systemic treatment. Shorter median progression-free survival (PFS) was observed for patients who had at least one detectable tumor-associated transcript, compared with patients who were CTC negative. Median PFS time was 66.0 days [95% confidence interval (CI) 44.8–87.2] for patients with baseline CTC positivity and 138.0 days (95% CI 124.1–151.9) for CTC-negative patients (p = 0.01, log-rank test). Conclusion: Our results suggest that in addition to the current prognostic methods, CTC analysis represents a potential complementary tool for prediction of outcome in pancreatic cancer patients. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Since its introduction, contrast-enhanced ultrasonography (CEUS) has significantly extended the value of ultrasonography (US). CEUS can be used to more accurately determine pancreatic lesions compared to conventional US or to characterize lesions already detectable by US. Thus, CEUS can aid in the differential diagnosis of pancreatic tumors. Using US contrast media, it is possible to visually detect microvessels in the majority of pancreatic ductal adenocarcinomas. Thus, the use of quantitatively evaluated transabdominal CEUS can help in the differentiation of patients with mass-forming pancreatitis from patients with pancreatic adenocarcinomas. In neuroendocrine pancreatic tumors, different enhancement patterns can be observed in relation to the tumor mass: larger ones show a rapid early enhancement sometimes combined with necrotic central structures, and smaller ones disclose a capillary-blush enhancement. Pseudocysts, the most widespread cystic lesions of the pancreas, are not vascularized. They do not show any signal in CEUS and remain entirely anechoic in all phases, while true cystic pancreatic tumors usually have vascularized septa and parietal nodules. In summary, CEUS is effective for differentiating solid pancreatic tumors in most cases. CEUS is safe and cost effective and can better discriminate solid from cystic pancreatic lesions, thereby directing further imaging modalities. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Background Pancreatic heterotopia (PH) is defined as ectopic pancreatic tissue outside the normal pancreas and its vasculature and duct system. Most frequently, PH is detected incidentally by histopathological examination. The aim of the present study was to analyze a large single-center series of duodenal PH with respect to the clinical presentation. Methods A prospective pancreatic database was retrospectively analyzed for cases of PH of the duodenum. All pancreatic and duodenal resections performed between January 2000 and October 2015 were included and screened for histopathologically proven duodenal PH. PH was classified according to Heinrich’s classification (Type I acini, ducts, and islet cells; Type II acini and ducts; Type III only ducts). Results A total of 1274 pancreatic and duodenal resections were performed within the study period, and 67 cases of PH (5.3%) were identified. The respective patients were predominantly male (72%) and either underwent pancreatoduodenectomy (n = 60); a limited pancreas resection with partial duodenal resection (n = 4); distal pancreatectomy with partial duodenal resection (n = 1); total pancreatectomy (n = 1); or enucleation (n = 1). Whereas 65 patients (83.5%) were asymptomatic, 11 patients (18.4%) presented with symptoms related to PH (most frequently with abdominal pain [72%] and duodenal obstruction [55%]). Of those, seven patients (63.6%) had chronic pancreatitis in the heterotopic pancreas. The risk of malignant transformation into adenocarcinoma was 2.9%. Conclusions PH is found in approximately 5% of pancreatic or duodenal resections and is generally asymptomatic. Chronic pancreatitis is not uncommon in heterotopic pancreatic tissue, and even there is a risk of malignant transformation. PH should be considered for the differential diagnosis of duodenal lesions and surgery should be considered, especially in symptomatic cases.

Background Pancreatic heterotopia (PH) is defined as ectopic pancreatic tissue outside the normal pancreas and its vasculature and duct system. Most frequently, PH is detected incidentally by histopathological examination. The aim of the present study was to analyze a large single-center series of duodenal PH with respect to the clinical presentation. Methods A prospective pancreatic database was retrospectively analyzed for cases of PH of the duodenum. All pancreatic and duodenal resections performed between January 2000 and October 2015 were included and screened for histopathologically proven duodenal PH. PH was classified according to Heinrich’s classification (Type I acini, ducts, and islet cells; Type II acini and ducts; Type III only ducts). Results A total of 1274 pancreatic and duodenal resections were performed within the study period, and 67 cases of PH (5.3%) were identified. The respective patients were predominantly male (72%) and either underwent pancreatoduodenectomy (n = 60); a limited pancreas resection with partial duodenal resection (n = 4); distal pancreatectomy with partial duodenal resection (n = 1); total pancreatectomy (n = 1); or enucleation (n = 1). Whereas 65 patients (83.5%) were asymptomatic, 11 patients (18.4%) presented with symptoms related to PH (most frequently with abdominal pain [72%] and duodenal obstruction [55%]). Of those, seven patients (63.6%) had chronic pancreatitis in the heterotopic pancreas. The risk of malignant transformation into adenocarcinoma was 2.9%. Conclusions PH is found in approximately 5% of pancreatic or duodenal resections and is generally asymptomatic. Chronic pancreatitis is not uncommon in heterotopic pancreatic tissue, and even there is a risk of malignant transformation. PH should be considered for the differential diagnosis of duodenal lesions and surgery should be considered, especially in symptomatic cases.

Since its introduction, contrast-enhanced ultrasonography (CEUS) has significantly extended the value of ultrasonography (US). CEUS can be used to more accurately determine pancreatic lesions compared to conventional US or to characterize lesions already detectable by US. Thus, CEUS can aid in the differential diagnosis of pancreatic tumors. Using US contrast media, it is possible to visually detect microvessels in the majority of pancreatic ductal adenocarcinomas. Thus, the use of quantitatively evaluated transabdominal CEUS can help in the differentiation of patients with mass-forming pancreatitis from patients with pancreatic adenocarcinomas. In neuroendocrine pancreatic tumors, different enhancement patterns can be observed in relation to the tumor mass: larger ones show a rapid early enhancement sometimes combined with necrotic central structures, and smaller ones disclose a capillary-blush enhancement. Pseudocysts, the most widespread cystic lesions of the pancreas, are not vascularized. They do not show any signal in CEUS and remain entirely anechoic in all phases, while true cystic pancreatic tumors usually have vascularized septa and parietal nodules. In summary, CEUS is effective for differentiating solid pancreatic tumors in most cases. CEUS is safe and cost effective and can better discriminate solid from cystic pancreatic lesions, thereby directing further imaging modalities. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Microarray technologies enable scientists to identify co-expressed genes at large scale. However, the gene expression analysis does not show functional relationships between co-expressed genes. There is a demand for effective approaches to analyse gene expression data to enable biological discoveries that can lead to identification of markers or therapeutic targets of many diseases. In cancer research, a number of gene expression screens have been carried out to identify genes differentially expressed in cancerous tissue such as Pancreatic Ductal Adenocarcinoma (PDAC). PDAC carries very poor prognosis, it eludes early detection and is characterised by its aggressiveness and resistance to currently available therapies. To identify molecular markers and suitable targets, there exist a research effort that maps differentially expressed genes to protein interactions to gain an understanding at systems level. Such interaction networks have a complex interconnected structure, whose the understanding of which is not a trivial task. Several formal approaches use simulation to support the investigation of such networks. These approaches suffer from the missing knowledge concerning biological systems. Reasoning in the other hand has the advantage of dealing with incomplete and partial information of the network knowledge. The initial approach adopted was to provide an algorithm that utilises a network-centric approach to pancreatic cancer, by re-constructing networks from known interactions and predicting novel protein interactions from structural templates. This method was applied to a data set of co-expressed PDAC genes. To this end, structural domains for the gene products are identified by using threading which is a 3D structure prediction technique. Next, the Protein Structure Interaction Database (SCOPPI), a database that classifies and annotates domain interactions derived from all known protein structures, is used to find templates of structurally interacting domains. Moreover, a network of related biological pathways for the PDAC data was constructed. In order to reason over molecular networks that are affected by dysregulation of gene expression, BioRevise was implemented. It is a belief revision system where the inhibition behaviour of reactions is modelled using extended logic programming. The system computes a minimal set of enzymes whose malfunction explains the abnormal expression levels of observed metabolites or enzymes. As a result of this research, two complementary approaches for the analysis of pancreatic cancer gene expression data are presented. Using the first approach, the pathways found to be largely affected in pancreatic cancer are signal transduction, actin cytoskeleton regulation, cell growth and cell communication. The analysis indicates that the alteration of the calcium pathway plays an important role in pancreas specific tumorigenesis. Furthermore, the structural prediction method reveals ~ 700 potential protein-protein interactions from the PDAC microarray data, among them, 81 novel interactions such as: serine/threonine kinase CDC2L1 interacting with cyclin-dependent kinase inhibitor CDKN3 and the tissue factor pathway inhibitor 2 (TFPI2) interacting with the transmembrane protease serine 4 (TMPRSS4). These resulting genes were further investigated and some were found to be potential therapeutic markers for PDAC. Since TMPRSS4 is involved in metastasis formation, it is hypothesised that the upregulation of TMPRSS4 and the downregulation of its predicted inhibitor TFPI2 plays an important role in this process. The predicted protein-protein network inspired the analysis of the data from two other perspectives. The resulting protein-protein interaction network highlighted the importance of the co-expression of KLK6 and KLK10 as prognostic factors for survival in PDAC as well as the construction of a PDAC specific apoptosis pathway to study different effects of multiple gene silencing in order to reactivate apoptosis in PDAC. Using the second approach, the behaviour of biological interaction networks using computational logic formalism was modelled, reasoning over the networks is enabled and the abnormal behaviour of its components is explained. The usability of the BioRevise system is demonstrated through two examples, a metabolic disorder disease and a deficiency in a pancreatic cancer associated pathway. The system successfully identified the inhibition of the enzyme glucose-6-phosphatase as responsible for the Glycogen storage disease type I, which according to literature is known to be the main reason for this disease. Furthermore, BioRevise was used to model reaction inhibition in the Glycolysis pathway which is known to be affected by Pancreatic cancer.

Pancreatic stellate cells (PSCs) constitute important cells of the pancreatic microenvironment and their close interaction with cancer cells is important in pancreatic cancer. It is currently not known whether PSCs accumulate genetic alterations that contribute to tumor biology. Our aim was to analyze genetic alterations in cancer associated PSCs. PSC DNA was matched to DNA isolated from pancreatic cancer patients’ blood (n = 5) and analyzed by Next-Generation Sequencing (NGS). Bioinformatic analysis was performed using the GATK software and pathogenicity prediction scores. Sanger sequencing was carried out to verify specific genetic alterations in a larger panel of PSCs (n = 50). NGS and GATK analysis identified on average 26 single nucleotide variants in PSC DNA as compared to the matched blood DNA that could be visualized with the Integrative Genomics Viewer. The absence of PDAC driver mutations (KRAS, p53, p16/INK4a, SMAD4) confirmed that PSC isolations were not contaminated with cancer cells. After filtering the variants, using different pathogenicity scores, ten genes were identified (SERPINB2, CNTNAP4, DENND4B, DPP4, FGFBP2, MIGA2, POLE, SNRNP40, TOP2B, and ZDHHC18) in single samples and confirmed by Sanger sequencing. As a proof of concept, functional analysis using control and SERPINB2 knock-out fibroblasts revealed functional effects on growth, migration, and collagen contraction. In conclusion, PSC DNA exhibit a substantial amount of single nucleotide variants that might have functional effects potentially contributing to tumor aggressiveness.

Background Treatment of cancer patients in certified cancer centers, that meet specific quality standards in term of structures and procedures of medical care, is a national treatment goal in Germany. However, convincing evidence that treatment in certified cancer centers is associated with better outcomes in patients with pancreatic cancer is still missing. Methods We used patient-specific information (demographic characteristics, diagnoses, treatments) from German statutory health insurance data covering the period 2009–2017 and hospital characteristics from the German Standardized Quality Reports. We investigated differences in survival between patients treated in hospitals with and without pancreatic cancer center certification by the German Cancer Society (GCS) using the Kaplan–Meier estimator and Cox regression with shared frailty. Results The final sample included 45,318 patients with pancreatic cancer treated in 1,051 hospitals (96 GCS-certified, 955 not GCS-certified). 5,426 (12.0%) of the patients were treated in GCS-certified pancreatic cancer centers. Patients treated in certified and non-certified hospitals had similar distributions of age, sex, and comorbidities. Median survival was 8.0 months in GCS-certified pancreatic cancer centers and 4.4 months in non-certified hospitals. Cox regression adjusting for multiple patient and hospital characteristics yielded a significantly lower hazard of long-term, all-cause mortality in patients treated in GCS-certified pancreatic centers (Hazard ratio = 0.89; 95%-CI = 0.85–0.93). This result remained robust in multiple sensitivity analyses, including stratified estimations for subgroups of patients and hospitals. Conclusion This robust observational evidence suggests that patients with pancreatic cancer benefit from treatment in a certified cancer center in terms of survival. Therefore, the certification of hospitals appears to be a powerful strategy to improve patient outcomes in pancreatic cancer care.