Our Work

Clinical Bantel Berg Schafmayer Modelling Steuer Hoehme Brusch Technology Brosch Schulze Hengstler SMART-NAFLD Klingmüller Timmer Berg Seehofer Michalski/Mehrabi/Billmann Glanemann/Lammert Berg Vondran Kauczor/Sedlaczek Denecke Hoehme Steuer Timmer Klingmüller Denecke Kauczor Schulze Seehofer/Damm Berg/Matz-Soja C-TIP-HCC Dooley Bantel Drasdo Glanemann/Lammert Bode Bantel Canbay/Best Cramer/Vondran/Olde-Damink Drasdo Timmer Hoehme Saez-Rodriguez Dooley Hengstler Klingmüller Cramer Bantel Bode DEEP-HCC Hampe Zerial Brusch Demir/Tacke Seehofer Schafmayer Trebicka Berg Berndt Brusch Zechner Brors Hampe Zerial Shevchenko Huch Kopka/Pietzsch Simons Geyer/Mann Chavakis/Coskun Data and Program Management Müllhaupt Müller Müller Müller Müller

Synergizing Clinical, Technological, and Modeling Endeavors

To achieve our goals, the LiSyM-Cancer network requires the integration of activities in a matrix structure.

In addition to the coordination of the three consortia and data management, it includes a combination of clinical, technological, and modeling activities across the individual projects as overarching topics.

LiSyM-Cancer Projects


SMART-NAFLD focuses on alterations in metabolism and signal transduction that favor disease progression to liver cancer. The project aims to identify alarm signatures in the blood of patients with fatty liver diseases without cirrhosis. This will facilitate to develop model-based trajectories for individual patients to evaluate the closeness to the tipping point towards liver cancer (tipping point 1).



C-TIP-HCC employs multiscale modeling to address structural and compositional changes in the extracellular matrix, and differences in cellular phenotypes in cirrhotic nodules. This facilitates the discrimination of the tissue in compensated cirrhosis across a tipping point towards liver cancer formation (tipping point 2). Aim of the modeling is to predict strategies to prevent or slow down disease progression from cirrhosis to liver cancer.



DEEP-HCC focuses on early liver cancer and provides an unprecedented deep multi-dimensional functional and spatial characterization, with tissue-to-single cell precision. A comprehensive data set will be generated consisting of 3D digital tissue reconstruction, spatial transcriptomics, epigenetics, lipidomics, pseudotime-ordered somatic mutations and personalized complex liver cancer organoids. This unique convergence of datasets will be integrated within a comprehensive metabolic/signaling-, spatio-temporal- and stochastic modelling workflow, to reveal emergent multimodal liver cancer signatures.



The essential goal of the Program Directorate and Management is to enable and support network collaborations across the projects. Synergies between the consortia are mediated to ensure achievement of the working plans. The Project and Communications Management Team works closely with the Program Director, SAB, and Network Coordinators to facilitate the successful implementation of the program and the publication and usability of the results. The data management team ensures the flow of data, data exchange and data backup within the consortia and across the network according to the FAIR criteria.