LiSyM-Cancer comprises three subprojects - SMART-NAFLD, C-TIP-HCC and DEEP-HCC and the Programme and Data Management. These projects use an integrative systems medicine approach in which liver cell communication, metabolism and signal transduction as well as the dynamics of the different liver cell populations and the composition of the extracellular matrix are examined. High-standard multi- and spatial-OMICS and imaging methods are applied. Based on quantitative data, mathematicians and bioinformaticians develop models to enable the early detection of alterations (tipping points) facilitating liver cancer development. Although most liver cancers develop based on cirrhosis (tipping point 2), due to the rapid increase of overweight and obese patients with NAFLD, the first tipping point is becoming increasingly important.

The three projects in LiSyM-Cancer: SMART-NAFLD characterises the transition from NAFLD directly to HCC (tipping point 1), C-TIP-HCC investigates the transition from liver cirrhosis to HCC (tipping point 2) and DEEP-HCC provides an multi-dimensional characterisation of early HCC.

LiSyM-Cancer furthermore addresses the following questions:

1. What are the similarities and differences of the HCCs arising in patients with fatty liver disease in the absence of cirrhosis versus those that develop in patients with liver cirrhosis?
2. Which factors or mechanisms explain that men are significantly more likely to develop liver cancer than women?
3. Which components in the blood reflect a crossing of the tipping points for liver cancer development and could be used as biomarkers for early detection?
4. Which parameters of tipping point exceedance could serve as target structures that prevent or significantly delay the development of HCC?

The essential goal of the Programme Directorate and Management is to enable and support cross-network consortial cooperation and to mediate synergies between the consortia so that the milestones of the individual projects and the entire network can be successfully achieved. A trustworthy exchange of data is indispensable and includes compliance with data protection regulations which is facilitated and organised by a central, super-ordinate data management system. For optimal collaboration the programme management and data management are combined.

The data architecture uses the following systems: FAIRDOM SEEK for sharing scientific data and publications, the open source NextCloud for fast sharing of semi-structured big data, OMERO for sharing image data, openBIS for near-lab sharing of data and metadata and REDCap for patient data.