Daniel Seehofer

Forschungsnetzwerk zur Früherkennung und Prävention- LiSyM-Krebs

Ein Netzwerk von Klinikern, Wissenschaftlern und Datenmanagern hat sich zur Aufgabe gemacht, Methoden zu entwickeln, um Patienten mit einem hohen Risiko für ein Leberkarzinom frühzeitig, in Vorstadien der Tumorentwicklung, identifizieren zu können. Gemeinsam bilden sie das „Systemmedizinische Forschungsnetzwerk zur Früherkennung und Prävention von Leberkrebs“, LiSym-Krebs, das vom Bundesministerium für Bildung und Forschung ...

SMART-NAFLD : A Systems Medicine Approach to Early Detection and Prevention of Hepatocellular Carcinoma in Non-Alcoholic Fatty Liver Disease

The massive increase in obesity is leading to an alarming rise in non-alcoholic liver disease (NAFLD). This development will lead to a dramatic increase in liver diseases such as hepatocellular carcinoma (HCC). A particular challenge is that NAFLD-associated HCCs, for reasons still unknown, not only occur in association with advanced liver fibrosis/cirrhosis, ...

DEEP-HCC - Detailed Analysis of the Spatial Organization of the Development of Hepatocellular Carcinoma

This generic project is intended to be a forum for all LiSyM partner and external stakeholders interested in participating in the BMBF initiative LiSyM-Krebs.

To investigate the underlying molecular principles of metabolic and morphogenic zonation of the human liver lobule, we generated an integrated epigenetic map across three zones (pericentral, intermediate and periportal) by methylation and transcriptomic analysis of hepatocytes captured by laser micro-dissection. We observe a deep link between epigenetic zonation of human liver and a zonated expression of metabolic and morphogenic pathways: Key transcriptionally zonated enzymes in xenobiotic and ...

ODE model describes dynamics of IFNalpha-induced signaling in Huh7.5 cells for a time scale up to 32 hours after stimulation with IFNalpha. The model consists of an IFN receptor model, formation/degradation and cytoplasmic/nuclear shuttling of STAT1-homodimers, STAT1-STAT2-heterodimers and STAT1-STAT2-IRF9 (ISGF3) complexes. On top, formation of feedback proteins STAT1, STAT2, IRF9, USP18, SOCS1, SOCS3 and IRF2 and corresponding influences on IFNalpha signaling dynamics was incorporated. The model ...