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Pancreatic Neoplasms: HELP
Articles by Alexander Muckenhuber
Based on 10 articles published since 2010
(Why 10 articles?)
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Between 2010 and 2020, Alexander Muckenhuber wrote the following 10 articles about Pancreatic Neoplasms.
 
+ Citations + Abstracts
1 Article Image-Based Molecular Phenotyping of Pancreatic Ductal Adenocarcinoma. 2020

Kaissis, Georgios A / Ziegelmayer, Sebastian / Lohöfer, Fabian K / Harder, Felix N / Jungmann, Friederike / Sasse, Daniel / Muckenhuber, Alexander / Yen, Hsi-Yu / Steiger, Katja / Siveke, Jens / Friess, Helmut / Schmid, Roland / Weichert, Wilko / Makowski, Marcus R / Braren, Rickmer F. ·Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Radiology, 81675 Munich, Germany. · Imperial College of Science, Technology and Medicine, Faculty of Engineering, Department of Computing, SW7 2AZ London, UK. · Technical University of Munich, School of Medicine, Institute for Pathology, 81675 Munich, Germany. · Institute of Developmental Cancer Therapeutics, West German Cancer Center, University Hospital Essen, 45147 Essen, Germany. · Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, parter site Essen, Germany) and German Cancer Research Center, DKFZ, 69120 Heidelberg, Germany. · Technical University of Munich, School of Medicine, Surgical Clinic and Policlinic, 81675 Munich, Germany. · Technical University of Munich, School of Medicine, Department of Internal Medicine II, 81675 Munich, Germany. ·J Clin Med · Pubmed #32155990.

ABSTRACT: To bridge the translational gap between recent discoveries of distinct molecular phenotypes of pancreatic cancer and tangible improvements in patient outcome, there is an urgent need to develop strategies and tools informing and improving the clinical decision process. Radiomics and machine learning approaches can offer non-invasive whole tumor analytics for clinical imaging data-based classification. The retrospective study assessed baseline computed tomography (CT) from 207 patients with proven pancreatic ductal adenocarcinoma (PDAC). Following expert level manual annotation, Pyradiomics was used for the extraction of 1474 radiomic features. The molecular tumor subtype was defined by immunohistochemical staining for KRT81 and HNF1a as quasi-mesenchymal (QM) vs. non-quasi-mesenchymal (non-QM). A Random Forest machine learning algorithm was developed to predict the molecular subtype from the radiomic features. The algorithm was then applied to an independent cohort of histopathologically unclassifiable tumors with distinct clinical outcomes. The classification algorithm achieved a sensitivity, specificity and ROC-AUC (area under the receiver operating characteristic curve) of 0.84 ± 0.05, 0.92 ± 0.01 and 0.93 ± 0.01, respectively. The median overall survival for predicted QM and non-QM tumors was 16.1 and 20.9 months, respectively, log-rank-test

2 Article SUMO pathway inhibition targets an aggressive pancreatic cancer subtype. 2020

Biederstädt, Alexander / Hassan, Zonera / Schneeweis, Christian / Schick, Markus / Schneider, Lara / Muckenhuber, Alexander / Hong, Yingfen / Siegers, Gerrit / Nilsson, Lisa / Wirth, Matthias / Dantes, Zahra / Steiger, Katja / Schunck, Kathrin / Langston, Steve / Lenhof, H-P / Coluccio, Andrea / Orben, Felix / Slawska, Jolanta / Scherger, Anna / Saur, Dieter / Müller, Stefan / Rad, Roland / Weichert, Wilko / Nilsson, Jonas / Reichert, Maximilian / Schneider, Günter / Keller, Ulrich. ·Medical Clinic and Policlinic III, Klinikum rechts der Isar, Technical University Munich, München, Germany. · Medical Clinic and Polyclinic II, Klinikum rechts der Isar, Technical University Munich, München, Germany. · Department of Hematology, Oncology and Tumor Immunology, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany. · Center for Bioinformatics, Saarland Informatics Campus, Saarland University, Saarbrücken, Germany. · Saarbrücken Graduate School of Computer Science, Saarland Informatics Campus, Saarland University, Saarbrücken, Germany. · Institute of Pathology, Technical University Munich, München, Germany. · Department of Surgery, Sahlgrenska Cancer Center, Gothenburg University, Gothenburg, Sweden. · German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany. · Goethe University, Medical School, Institute of Biochemistry II, Frankfurt, Germany. · Oncology Drug Discovery Unit, Takeda Pharmaceuticals International Co, Cambridge, Massachusetts, USA. · Institute for Translational Cancer Research and Experimental Cancer Therapy, Technical University Munich, München, Germany. · Institute of Molecular Oncology and Functional Genomics, Technical University Munich, München, Germany. · Medical Clinic and Polyclinic II, Klinikum rechts der Isar, Technical University Munich, München, Germany guenter.schneider@tum.de ulrich.keller@charite.de. · Department of Hematology, Oncology and Tumor Immunology, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany guenter.schneider@tum.de ulrich.keller@charite.de. ·Gut · Pubmed #32001555.

ABSTRACT: OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) still carries a dismal prognosis with an overall 5-year survival rate of 9%. Conventional combination chemotherapies are a clear advance in the treatment of PDAC; however, subtypes of the disease exist, which exhibit extensive resistance to such therapies. Genomic MYC amplifications represent a distinct subset of PDAC with an aggressive tumour biology. It is clear that hyperactivation of MYC generates dependencies that can be exploited therapeutically. The aim of the study was to find and to target MYC-associated dependencies. DESIGN: We analysed human PDAC gene expression datasets. Results were corroborated by the analysis of the small ubiquitin-like modifier (SUMO) pathway in a large PDAC cohort using immunohistochemistry. A SUMO inhibitor was used and characterised using human and murine two-dimensional, organoid and in vivo models of PDAC. RESULTS: We observed that MYC is connected to the SUMOylation machinery in PDAC. Components of the SUMO pathway characterise a PDAC subtype with a dismal prognosis and we provide evidence that hyperactivation of MYC is connected to an increased sensitivity to pharmacological SUMO inhibition. CONCLUSION: SUMO inhibitor-based therapies should be further developed for an aggressive PDAC subtype.

3 Article A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy. 2019

Kaissis, Georgios / Ziegelmayer, Sebastian / Lohöfer, Fabian / Steiger, Katja / Algül, Hana / Muckenhuber, Alexander / Yen, Hsi-Yu / Rummeny, Ernst / Friess, Helmut / Schmid, Roland / Weichert, Wilko / Siveke, Jens T / Braren, Rickmer. ·Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany. · Department of Pathology, School of Medicine, Technical University of Munich, Munich, Germany. · Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany. · Department of Surgery, School of Medicine, Technical University of Munich, Munich, Germany. · Division of Solid Tumor Translational Oncology, West German Cancer Center, University Hospital Essen, Essen, Germany. · German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany. ·PLoS One · Pubmed #31577805.

ABSTRACT: PURPOSE: Development of a supervised machine-learning model capable of predicting clinically relevant molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) from diffusion-weighted-imaging-derived radiomic features. METHODS: The retrospective observational study assessed 55 surgical PDAC patients. Molecular subtypes were defined by immunohistochemical staining of KRT81. Tumors were manually segmented and 1606 radiomic features were extracted with PyRadiomics. A gradient-boosted-tree algorithm was trained on 70% of the patients (N = 28) and tested on 30% (N = 17) to predict KRT81+ vs. KRT81- tumor subtypes. A gradient-boosted survival regression model was fit to the disease-free and overall survival data. Chemotherapy response and survival were assessed stratified by subtype and radiomic signature. Radiomic feature importance was ranked. RESULTS: The mean±STDEV sensitivity, specificity and ROC-AUC were 0.90±0.07, 0.92±0.11, and 0.93±0.07, respectively. The mean±STDEV concordance indices between the disease-free and overall survival predicted by the model based on the radiomic parameters and actual patient survival were 0.76±0.05 and 0.71±0.06, respectively. Patients with a KRT81+ subtype experienced significantly diminished median overall survival compared to KRT81- patients (7.0 vs. 22.6 months, HR 4.03, log-rank-test P = <0.001) and a significantly improved response to gemcitabine-based chemotherapy over FOLFIRINOX (10.14 vs. 3.8 months median overall survival, HR 2.33, P = 0.037) compared to KRT81- patients, who responded significantly better to FOLFIRINOX over gemcitabine-based treatment (30.8 vs. 13.4 months median overall survival, HR 2.41, P = 0.027). Entropy was ranked as the most important radiomic feature. CONCLUSIONS: The machine-learning based analysis of radiomic features enables the prediction of subtypes of PDAC, which are highly relevant for disease-free and overall patient survival and response to chemotherapy.

4 Article Pancreatic Ductal Adenocarcinoma Subtyping Using the Biomarkers Hepatocyte Nuclear Factor-1A and Cytokeratin-81 Correlates with Outcome and Treatment Response. 2018

Muckenhuber, Alexander / Berger, Anne Katrin / Schlitter, Anna Melissa / Steiger, Katja / Konukiewitz, Björn / Trumpp, Andreas / Eils, Roland / Werner, Jens / Friess, Helmut / Esposito, Irene / Klöppel, Günter / Ceyhan, Güralp O / Jesinghaus, Moritz / Denkert, Carsten / Bahra, Marcus / Stenzinger, Albrecht / Sprick, Martin R / Jäger, Dirk / Springfeld, Christoph / Weichert, Wilko. ·Institute of Pathology, Technical University Munich and German Cancer Consortium (DKTK; partner site Munich), Munich, Germany. · Department of Medical Oncology, Heidelberg University Hospital and National Center for Tumor Diseases, Heidelberg, Germany. · Division of Stem Cells and Cancer, German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, Heidelberg, Germany. · Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM GmbH, Heidelberg, Germany. · German Cancer Consortium (DKTK), Heidelberg, Germany. · Division of Theoretical Bioinformatics and Heidelberg Center for Personalised Oncology (DKFZ-HIPO), German Cancer Research Center (DKFZ), Heidelberg, Germany. · Department for Bioinformatics and Functional Genomics, Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, Heidelberg University, Heidelberg, Germany. · Department of Surgery, University Hospital of the Ludwig-Maximilian University, Munich, Germany. · Department of Surgery, University Hospital of the Technical University Munich, Munich, Germany. · Institute of Pathology, University Hospital Düsseldorf, Düsseldorf, Germany. · Institute of Pathology, Charité University Medicine Berlin and German Cancer Consortium (DKTK; partner site Berlin), Berlin, Germany. · Department of Surgery, Charité University Medicine Berlin, Berlin, Germany. · Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany. · Institute of Pathology, Technical University Munich and German Cancer Consortium (DKTK; partner site Munich), Munich, Germany. wilko.weichert@tum.de. ·Clin Cancer Res · Pubmed #29101303.

ABSTRACT:

5 Article pT but not pN stage of the 8th TNM classification significantly improves prognostication in pancreatic ductal adenocarcinoma. 2017

Schlitter, Anna Melissa / Jesinghaus, Moritz / Jäger, Carsten / Konukiewitz, Björn / Muckenhuber, Alexander / Demir, Ihsan Ekin / Bahra, Marcus / Denkert, Carsten / Friess, Helmut / Kloeppel, Günter / Ceyhan, Güralp O / Weichert, Wilko. ·Institute of Pathology, Technical University Munich, Munich, Germany. Electronic address: melissa.schlitter@tum.de. · Institute of Pathology, Technical University Munich, Munich, Germany; German Cancer Consortium (DKTK), Partner Site Munich, Germany. · Department of Surgery, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany. · Institute of Pathology, Technical University Munich, Munich, Germany. · Department of Surgery, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany; German Cancer Consortium (DKTK), Partner Site Munich, Germany. · Department of Surgery, Charité University Hospital, Berlin, Germany. · Institute of Pathology, Charité University Hospital, Berlin, Germany; German Cancer Consortium (DKTK), Partner Site Berlin, Germany. ·Eur J Cancer · Pubmed #28802189.

ABSTRACT: The UICC TNM (tumour-node-metastasis) staging system for pancreatic ductal adenocarcinoma (PDAC) has been a matter of debate over decades because survival prediction based on T stages was weak and unreliable. To improve staging, the recently published 8th TNM edition (2016) introduced a conceptually completely changed strictly size-based T staging system and a refined N stage for PDAC. To investigate the clinical value of the novel TNM classification, we compared the prognostic impact of pT and pN stage between the 7th and 8th edition in two well-characterised independent German PDAC cohorts from different decades, including a total number of 523 patients. Former UICC T staging (7th edition 2009) resulted in a clustering of pT3 cases (72% and 85% of cases per cohort, respectively) and failed to show significant prognostic differences between the four stages in one of the investigated cohorts (p = 0.074). Application of the novel size-based T stage system resulted in a more equal distribution of cases between the four T categories with a predominance of pT2 tumours (65% and 60% of cases). The novel pT staging algorithm showed greatly improved discriminative power with highly significant overall differences between the four pT stages in both investigated cohorts in univariate and multivariate analyses (p < 0.001, each). In contrast, no prognostic differences were observed between the recently introduced pN1 and pN2 categories in both cohorts (p = 0.970 and p = 0.061). pT stage of resected PDAC patients according to the novel UICC staging protocol (8th edition) significantly improves patient stratification, whereas introduction of an extended N stage protocol does not demonstrate high clinical relevance in our cohorts.

6 Article High prevalence of incidental and symptomatic venous thromboembolic events in patients with advanced pancreatic cancer under palliative chemotherapy: A retrospective cohort study. 2017

Berger, Anne Katrin / Singh, Hans Martin / Werft, Wiebke / Muckenhuber, Alexander / Sprick, Martin R / Trumpp, Andreas / Weichert, Wilko / Jäger, Dirk / Springfeld, Christoph. ·National Center for Tumor Diseases (NCT), Department of Medical Oncology, University Hospital Heidelberg, Heidelberg, Germany. Electronic address: anne.berger@med.uni-heidelberg.de. · National Center for Tumor Diseases (NCT), Department of Medical Oncology, University Hospital Heidelberg, Heidelberg, Germany. · Hochschule Mannheim, University of Applied Sciences, Mannheim, Germany. · Institute of Pathology, Technische Universität München (TUM), München, Germany. · Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM), Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany. ·Pancreatology · Pubmed #28462862.

ABSTRACT: OBJECTIVES: Pancreatic cancer patients are at high risk for venous thromboembolic events (VTEs), and chemotherapy is a known additional risk factor. In this context, there is a controversial discussion whether prophylactic anticoagulation should be offered to all outpatients receiving chemotherapy. METHODS: In this retrospective study, we analyzed incidental and symptomatic VTEs in 150 pancreatic cancer patients receiving either gemcitabine-based chemotherapy or chemotherapy according to the FOLFIRINOX protocol. RESULTS: VTEs were identified in 25% of patients, but were not associated with an adverse survival. There was no significant difference in VTE incidence between patients treated with gemcitabine-based chemotherapy or the more intensive FOLFIRINOX protocol. A commonly used risk score to predict VTEs in cancer patients did not predict the occurrence of VTEs in our patients. The occurrence of VTEs was not associated with one of the recently described pancreatic cancer subtypes. CONCLUSION: One quarter of pancreatic cancer patients treated with palliative chemotherapy develops symptomatic or incidental VTEs that cannot be predicted by type of chemotherapy, subtype of pancreatic cancer or a commonly used risk score. Further studies are necessary to identify patients at risk, and to better define which patients at risk should be treated with prophylactic anticoagulation.

7 Article CYP3A5 mediates basal and acquired therapy resistance in different subtypes of pancreatic ductal adenocarcinoma. 2016

Noll, Elisa M / Eisen, Christian / Stenzinger, Albrecht / Espinet, Elisa / Muckenhuber, Alexander / Klein, Corinna / Vogel, Vanessa / Klaus, Bernd / Nadler, Wiebke / Rösli, Christoph / Lutz, Christian / Kulke, Michael / Engelhardt, Jan / Zickgraf, Franziska M / Espinosa, Octavio / Schlesner, Matthias / Jiang, Xiaoqi / Kopp-Schneider, Annette / Neuhaus, Peter / Bahra, Marcus / Sinn, Bruno V / Eils, Roland / Giese, Nathalia A / Hackert, Thilo / Strobel, Oliver / Werner, Jens / Büchler, Markus W / Weichert, Wilko / Trumpp, Andreas / Sprick, Martin R. ·Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM), Heidelberg, Germany. · Divison of Stem Cells and Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany. · Department of Pathology, University of Heidelberg, Heidelberg, Germany. · National Center for Tumor Diseases (NCT), Heidelberg, Germany. · Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany. · Heidelberg Pharma GmbH, Ladenburg, Germany. · Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany. · Division of Biostatistics, German Cancer Research Center, Heidelberg, Germany. · Department of General, Visceral and Transplantation Surgery, Charité-Universitätsmedizin Berlin, Berlin, Germany. · Institute of Pathology, Charité-Universitätsmedizin Berlin, Berlin, Germany. · Institute of Pharmacy and Molecular Biotechnology, Bioquant, University of Heidelberg, Heidelberg, Germany. · Heidelberg Center for Personalized Oncology (DKFZ-HIPO), German Cancer Research Center, Heidelberg, Germany. · Department of General and Visceral Surgery, University Hospital Heidelberg, Heidelberg, Germany. · German Cancer Consortium (DKTK), Heidelberg, Germany. ·Nat Med · Pubmed #26855150.

ABSTRACT: Although subtypes of pancreatic ductal adenocarcinoma (PDAC) have been described, this malignancy is clinically still treated as a single disease. Here we present patient-derived models representing the full spectrum of previously identified quasi-mesenchymal (QM-PDA), classical and exocrine-like PDAC subtypes, and identify two markers--HNF1A and KRT81--that enable stratification of tumors into different subtypes by using immunohistochemistry. Individuals with tumors of these subtypes showed substantial differences in overall survival, and their tumors differed in drug sensitivity, with the exocrine-like subtype being resistant to tyrosine kinase inhibitors and paclitaxel. Cytochrome P450 3A5 (CYP3A5) metabolizes these compounds in tumors of the exocrine-like subtype, and pharmacological or short hairpin RNA (shRNA)-mediated CYP3A5 inhibition sensitizes tumor cells to these drugs. Whereas hepatocyte nuclear factor 4, alpha (HNF4A) controls basal expression of CYP3A5, drug-induced CYP3A5 upregulation is mediated by the nuclear receptor NR1I2. CYP3A5 also contributes to acquired drug resistance in QM-PDA and classical PDAC, and it is highly expressed in several additional malignancies. These findings designate CYP3A5 as a predictor of therapy response and as a tumor cell-autonomous detoxification mechanism that must be overcome to prevent drug resistance.

8 Article Profiling of cMET and HER Family Receptor Expression in Pancreatic Ductal Adenocarcinomas and Corresponding Lymph Node Metastasis to Assess Relevant Pathways for Targeted Therapies: Looking at the Soil Before Planting the Seed. 2016

Muckenhuber, Alexander / Babitzki, Galina / Thomas, Marlene / Hölzlwimmer, Gabriele / Zajac, Magdalena / Jesinghaus, Moritz / Bergmann, Frank / Werner, Jens / Stenzinger, Albrecht / Weichert, Wilko. ·From the *Institute of Pathology, University Hospital Heidelberg, Ruprecht-Karls Universität, Heidelberg; †Roche Pharma Research and Early Development, Roche Innovation Center, Penzberg, Germany; ‡AstraZeneca, Personalized Healthcare and Biomarkers, Innovative Medicines and Early Development, Cambridge, United Kingdom; §Department of Surgery, University Hospital Grosshadern, Ludwig-Maximilians-Universität, München, Germany; ∥National Center for Tumor Diseases, Heidelberg; and ¶German Cancer Consortium (DKTK), Dresden, Germany. ·Pancreas · Pubmed #26825865.

ABSTRACT: OBJECTIVES: Comprehensive assessment of cMET and HER family receptor tyrosine kinases expression, changes of expression during metastatic progression, amplification status of the MET gene, and correlations with patient characteristics in pancreatic ductal adenocarcinoma (PDAC) was conducted. METHODS: We investigated 56 PDACs and corresponding lymph node metastases for HER1 to HER4 and cMET expression by immunohistochemistry, as well as cMET gene copy numbers by chromogenic in situ hybridization. RESULTS: Of all receptor tyrosine kinases evaluated, cMET expression was highest with 46.5% of tumors showing moderate or strong expression and a weak correlation with gene copy number status (P = 0.04; Spearman ρ = 0.28). cMET expression was increased in metastases. In contrast, expression levels of HER family receptors were generally low both in primaries and metastases. A weak yet significant correlation of HER1 and cMET expression levels was observed (P < 0.001; Spearman ρ = 0.44) and HER1 was often present in poorly differentiated tumors (G3, P = 0.049). CONCLUSIONS: Our data suggest that cMET might constitute an interesting molecule for combining targeted and chemotherapeutic approaches in PDAC, because expression is frequent and increased during metastatic progression. In PDAC, cMET protein expression might be a more useful stratification biomarker than cMET gene amplification, which does not seem to be its primary regulator.

9 Article Ataxia-telangiectasia-mutated protein kinase levels stratify patients with pancreatic adenocarcinoma into prognostic subgroups with loss being a strong indicator of poor survival. 2015

Kamphues, Carsten / Bova, Roberta / Bahra, Marcus / Klauschen, Frederick / Muckenhuber, Alexander / Sinn, Bruno V / Warth, Arne / Goeppert, Benjamin / Endris, Volker / Neuhaus, Peter / Weichert, Wilko / Stenzinger, Albrecht. ·From the *Department of General, Visceral and Transplantation Surgery, and †Institute of Pathology, Charité University Hospital, Berlin; ‡Institute of Pathology, University Hospital Heidelberg; and §National Center for Tumor Diseases, Heidelberg, Germany. ·Pancreas · Pubmed #25423555.

ABSTRACT: OBJECTIVES: Recently, aberrations in the gene encoding for ataxia-telangiectasia-mutated (ATM) protein kinase have been reported for pancreatic ductal adenocarcinomas (PDAC). These findings argue that ATM deficiency may play a role during carcinogenesis. Therefore, in this study, we investigated the clinical relevance of ATM expression and ATM activation in PDAC. METHODS: Both ATM expression and nuclear phosphoSer1981-ATM levels were assessed by immunohistochemistry in a cohort of 133 PDAC and correlated with clinicopathological parameters. RESULTS: We found stratification in prognostic subgroups. Complete loss of Ser1981-ATM was indicative of the worst prognosis (median survival, 10.8 vs 14.3 months [low expression] vs 31.1 months [high expression], P < 0.001). Similarly, analysis of ATM expression demonstrated absent expression levels of ATM to be associated with dismal prognosis (median survival, 9.6 months), whereas expression of ATM in general was associated with increased survival (17.7 months, P = 0.001). CONCLUSIONS: Our analysis shows that both ATM expression and activated ATM are prognostic markers in PDAC with respect to standard clinicopathological parameters. These results suggest that ATM should be further explored as prognostic as well as predictive factor with respect to conventional chemotherapies and for putative synthetic lethal approaches.

10 Article High SIRT1 expression is a negative prognosticator in pancreatic ductal adenocarcinoma. 2013

Stenzinger, Albrecht / Endris, Volker / Klauschen, Frederick / Sinn, Bruno / Lorenz, Katja / Warth, Arne / Goeppert, Benjamin / Ehemann, Volker / Muckenhuber, Alexander / Kamphues, Carsten / Bahra, Marcus / Neuhaus, Peter / Weichert, Wilko. ·Institute of Pathology, and National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany. albrecht.stenzinger@med.uni-heidelberg.de. ·BMC Cancer · Pubmed #24088390.

ABSTRACT: BACKGROUND: Several lines of evidence indicate that Sirt1, a class III histone deacetylase (HDAC) is implicated in the initiation and progression of malignancies and thus gained attraction as druggable target. Since data on the role of Sirt1 in pancreatic ductal adenocarcinoma (PDAC) are sparse, we investigated the expression profile and prognostic significance of Sirt1 in vivo as well as cellular effects of Sirt1 inhibition in vitro. METHODS: Sirt1 expression was analyzed by immunohistochemistry in a large cohort of PDACs and correlated with clinicopathological and survival data. Furthermore, we investigated the impact of overexpression and small molecule inhibition on Sirt1 in pancreatic cancer cell culture models including combinatorial treatment with chemotherapy and EGFR-inhibition. Cellular events were measured quantitatively in real time and corroborated by conventional readouts including FACS analysis and MTT assays. RESULTS: We detected nuclear Sirt1 expression in 36 (27.9%) of 129 PDACs. SIRT1 expression was significantly higher in poorly differentiated carcinomas. Strong SIRT1 expression was a significant predictor of poor survival both in univariate (p = 0.002) and multivariate (HR 1.65, p = 0.045) analysis. Accordingly, overexpression of Sirt1 led to increased cell viability, while small molecule inhibition led to a growth arrest in pancreatic cancer cells and impaired cell survival. This effect was even more pronounced in combinatorial regimens with gefitinib, but not in combination with gemcitabine. CONCLUSIONS: Sirt1 is an independent prognosticator in PDACs and plays an important role in pancreatic cancer cell growth, which can be levered out by small molecule inhibition. Our data warrant further studies on SIRT1 as a novel chemotherapeutic target in PDAC.