The central role of MEC/MES is to act as a versatile partner for the clinical surgery team to develop and implement modern patient care for our patients. With a focus on visceral and hepatobiliary oncology, our goal is provide the right treatment, at the right time to the individual disease background of each patient. We use a variety of cellular and molecular technologies to identify and investigate mechanisms of biomarkers allowing personalization and optimization of therapy and therapy surveillance. Moreover, by implementing labelfree and labeling-based approaches, alongside cooperation campaigns with experts from electrical engineering, we use this platform to develop next stage functional cancer imaging strategies that support the intro-operative surgical guidance. We focus on human-based disease modeling and standardization plus digitalization of lab procedures and documentation, thus allowing repeatable and open science meanwhile supporting the 3R movement in biomedical research. We believe our research is in line with current science policy and of current technology level.
Expertise:

• Patient-derived cancer stem cell research: primary organoid technology for pancreas, colon, rectum, hepatic and cholangiocarcinoma and its patient-matching, organ-equivalent non-cancer tissue, from resection and biopsy material
• Human induced pluripotent stem cells (hiPSC): generation new hiPSC lines from donor-derived somatic cells, differentiation of hiPSC into hepatic and intestinal lineage
• Biobanking system for body fluids and tissue sample
• Neuro biology: in vitro brain tumor models: stem cell models for transcriptional and DNA methylation subtypes of glioblastoma, low grade glioma models, pediatric brain tumor models featuring MYC-medulloblastomas and glioma, differentiation of hiPSC into neural stem cells and neural crest cells,  terminal differentiation into sensory neurons, sphere size quantification
• Genetic engineering: gene/microRNA expression modulation via interference or overexpression using transient and stable transformation of target matrix, single nucleotide editing (mono and bi allelic)
• Generation of therapy resistance in vitro models using stress or biomarker-driven approaches
• Co-culture assays tumor cells with components of the tumor microenvironment
• Biomarker analytics: qPCR, protein assays such as Western blot, FACS, ELISA, CRISPR-Cas13 diagnostics, immune histo and immune fluorescence cytochemistry
• Functional assays: quantification of cellular survival, growth, apoptosis, necrosis, ferroptosis, motility, invasiveness, uptake of intervention/reporter dye, stemness, clonogenicity, chemo- and radio therapy resistance,
• Cell metabolomics (glutaminolysis and ATP consumption)
• Electronic lab notebook management system (ElabFTW)
• Systematic review of scientific literature and meta-analysis