• Deutsch
Login

Open Access

  • Home
  • Search
  • Browse
  • Publish/report a document
  • Help

Refine

Has Fulltext

  • yes (3)
  • no (2)

Author

  • Röcken, Christoph (3)
  • Ebert, Matthias (2)
  • Fischbach, Wolfgang (2)
  • Gockel, Ines (2)
  • Grenacher, Lars (2)
  • Grosser, Bianca (2)
  • Jäger, Dirk (2)
  • Kather, Jakob Nikolas (2)
  • Lordick, Florian (2)
  • Messmann, Helmut (2)
+ more

Year of publication

  • 2023 (2)
  • 2021 (1)
  • 2019 (1)
  • 2014 (1)

Document Type

  • Article (5)

Language

  • English (4)
  • German (1)

Keywords

  • Cancer Research (2)
  • Gastroenterology (2)
  • Oncology (2)
  • Biochemistry (1)
  • Decision Sciences (miscellaneous) (1)
  • Endocrinology (1)
  • General Medicine (1)
  • Health Informatics (1)
  • Health Information Management (1)
  • Medicine (miscellaneous) (1)
+ more

Institute

  • Medizinische Fakultät (5)
  • Universitätsklinikum (4)
  • Lehrstuhl für Allgemeine und Spezielle Pathologie (2)
  • Lehrstuhl für Innere Medizin mit Schwerpunkt Gastroenterologie (2)
  • Nachhaltigkeitsziele (2)
  • Ziel 3 - Gesundheit und Wohlergehen (2)
  • Lehrstuhl für Physiologie (1)

5 search hits

  • 1 to 5
  • 10
  • 20
  • 50
  • 100

Sort by

  • Year
  • Year
  • Title
  • Title
  • Author
  • Author
Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study (2021)
Muti, Hannah Sophie ; Heij, Lara Rosaline ; Keller, Gisela ; Kohlruss, Meike ; Langer, Rupert ; Dislich, Bastian ; Cheong, Jae-Ho ; Kim, Young-Woo ; Kim, Hyunki ; Kook, Myeong-Cherl ; Cunningham, David ; Allum, William H ; Langley, Ruth E ; Nankivell, Matthew G ; Quirke, Philip ; Hayden, Jeremy D ; West, Nicholas P ; Irvine, Andrew J ; Yoshikawa, Takaki ; Oshima, Takashi ; Huss, Ralf ; Grosser, Bianca ; Roviello, Franco ; d'Ignazio, Alessia ; Quaas, Alexander ; Alakus, Hakan ; Tan, Xiuxiang ; Pearson, Alexander T ; Luedde, Tom ; Ebert, Matthias P ; Jäger, Dirk ; Trautwein, Christian ; Gaisa, Nadine Therese ; Grabsch, Heike I ; Kather, Jakob Nikolas
S3-Leitlinie Magenkarzinom – Diagnostik und Therapie der Adenokarzinome des Magens und des ösophagogastralen Übergangs – Langversion 2.0 – August 2019. AWMF-Registernummer: 032/009OL (2019)
Moehler, Markus ; Al-Batran, Salah-Edin ; Andus, Tilo ; Arends, Jann ; Arnold, Dirk ; Baretton, Gustavo ; Bornschein, Jan ; Budach, Wilfried ; Daum, Severin ; Dietrich, Christoph ; Ebert, Matthias ; Fischbach, Wolfgang ; Flentje, Michael ; Gockel, Ines ; Grenacher, Lars ; Haier, Jörg ; Höcht, Stefan ; Jakobs, Rolf ; Jenssen, Christian ; Kade, Barbara ; Kanzler, Stefan ; Langhorst, Jost ; Link, Hartmut ; Lordick, Florian ; Lorenz, Dietmar ; Lorenzen, Sylvie ; Lutz, Manfred ; Messmann, Helmut ; Meyer, Hans-Joachim ; Mönig, Stefan ; Ott, Katja ; Quante, Michael ; Röcken, Christoph ; Schlattmann, Peter ; Schmiegel, Wolff-H. ; Schreyer, Andreas ; Tannapfel, Andrea ; Thuss-Patience, Peter ; Weimann, Arved ; Unverzagt, Susanne
International comparison of the German evidence-based S3-guidelines on the diagnosis and multimodal treatment of early and locally advanced gastric cancer, including adenocarcinoma of the lower esophagus (2014)
Moehler, Markus ; Baltin, Christoph T. H. ; Ebert, Matthias ; Fischbach, Wolfgang ; Gockel, Ines ; Grenacher, Lars ; Hölscher, Arnulf H. ; Lordick, Florian ; Malfertheiner, Peter ; Messmann, Helmut ; Meyer, Hans-Joachim ; Palmqvist, Anne ; Röcken, Christoph ; Schuhmacher, Christoph ; Stahl, Michael ; Stuschke, Martin ; Vieth, Michael ; Wittekind, Christian ; Wagner, Dorothea ; Mönig, Stefan P.
Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study (2023)
Muti, Hannah Sophie ; Röcken, Christoph ; Behrens, Hans-Michael ; Loeffler, Chiara Maria Lavinia ; Reitsam, Nic Gabriel ; Grosser, Bianca ; Märkl, Bruno ; Stange, Daniel E. ; Jiang, Xiaofeng ; Veldhuizen, Gregory Patrick ; Truhn, Daniel ; Ebert, Matthias P. ; Grabsch, Heike Irmgard ; Kather, Jakob Nikolas
Aim Gastric cancer (GC) is a tumor entity with highly variant outcomes. Lymph node metastasis is a prognostically adverse biomarker. We hypothesized that GC primary tissue contains information that is predictive of lymph node status and patient prognosis and that this information can be extracted using Deep Learning (DL). Methods Using three patient cohorts comprising 1146 patients, we trained and validated a DL system to predict lymph node status directly from hematoxylin-and-eosin stained GC tissue sections. We investigated the concordance between the DL-based prediction from the primary tumor slides (aiN score) and the histopathological lymph node status (pN). Furthermore, we assessed the prognostic value of the aiN score alone and when combined with the pN status. Results The aiN score predicted the pN status reaching Area Under the Receiver Operating Characteristic curves (AUROCs) of 0.71 in the training cohort and 0.69 and 0.65 in the two test cohorts. In a multivariate Cox analysis, the aiN score was an independent predictor of patient survival with Hazard Ratios (HR) of 1.5 in the training cohort and of 1.3 and 2.2 in the two test cohorts. A combination of the aiN score and the pN status prognostically stratified patients by survival with p-values <0.05 in log-rank tests. Conclusion GC primary tumor tissue contains additional prognostic information that is accessible using the aiN score. In combination with the pN status, this can be used for personalized management of gastric cancer patients after prospective validation.
Intestinal BMP-9 locally upregulates FGF19 and is down-regulated in obese patients with diabetes (2023)
Drexler, Stephan ; Cai, Chen ; Hartmann, Anna-Lena ; Moch, Denise ; Gaitantzi, Haristi ; Ney, Theresa ; Kraemer, Malin ; Chu, Yuan ; Zheng, Yuwei ; Rahbari, Mohammad ; Treffs, Annalena ; Reiser, Alena ; Lenoir, Bénédicte ; Valous, Nektarios A. ; Jäger, Dirk ; Birgin, Emrullah ; Sawant, Tejas A. ; Li, Qi ; Xu, Keshu ; Dong, Lingyue ; Otto, Mirko ; Itzel, Timo ; Teufel, Andreas ; Gretz, Norbert ; Hawinkels, Lukas J. A. C. ; Sánchez, Aránzazu ; Herrera, Blanca ; Schubert, Rudolf ; Moshage, Han ; Reissfelder, Christoph ; Ebert, Matthias P. A. ; Rahbari, Nuh N. ; Breitkopf-Heinlein, Katja
believed to be mainly produced in the liver. The serum levels of BMP-9 were reported to be reduced in newly diagnosed diabetic patients and BMP-9 overexpression ameliorated steatosis in the high fat diet-induced obesity mouse model. Furthermore, injection of BMP-9 in mice enhanced expression of fibroblast growth factor (FGF)21. However, whether BMP-9 also regulates the expression of the related FGF19 is not clear. Because both FGF21 and 19 were described to protect the liver from steatosis, we have further investigated the role of BMP-9 in this context. We first analyzed BMP-9 levels in the serum of streptozotocin (STZ)-induced diabetic rats (a model of type I diabetes) and confirmed that BMP-9 serum levels decrease during diabetes. Microarray analyses of RNA samples from hepatic and intestinal tissue from BMP-9 KO- and wild-type mice (C57/Bl6 background) pointed to basal expression of BMP-9 in both organs and revealed a down-regulation of hepatic Fgf21 and intestinal Fgf19 in the KO mice. Next, we analyzed BMP-9 levels in a cohort of obese patients with or without diabetes. Serum BMP-9 levels did not correlate with diabetes, but hepatic BMP-9 mRNA expression negatively correlated with steatosis in those patients that did not yet develop diabetes. Likewise, hepatic BMP-9 expression also negatively correlated with serum LPS levels. In situ hybridization analyses confirmed intestinal BMP-9 expression. Intestinal (but not hepatic) BMP-9 mRNA levels were decreased with diabetes and positively correlated with intestinal E-Cadherin expression. In vitro studies using organoids demonstrated that BMP-9 directly induces FGF19 in gut but not hepatocyte organoids, whereas no evidence of a direct induction of hepatic FGF21 by BMP-9 was found. Consistent with the in vitro data, a correlation between intestinal BMP-9 and FGF19 mRNA expression was seen in the patients’ samples. In summary, our data confirm that BMP-9 is involved in diabetes development in humans and in the control of the FGF-axis. More importantly, our data imply that not only hepatic but also intestinal BMP-9 associates with diabetes and steatosis development and controls FGF19 expression. The data support the conclusion that increased levels of BMP-9 would most likely be beneficial under pre-steatotic conditions, making supplementation of BMP-9 an interesting new approach for future therapies aiming at prevention of the development of a metabolic syndrome and liver steatosis.
  • 1 to 5

OPUS4 Logo

  • Contact
  • Imprint
  • Sitelinks