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Research
The PhD projects in Cologne and Seoul will be conducted in trans-national synergistic topics and hence we expect to benefit massively from our combined expertise.
Research Project
1. Genomic instability driven by p53 deficiency.
Roland Ullrich studies resistance under therapies using ALK-v1,2,3 mice crossed to TP53-wt and mutant alleles.
Julie George studies genomic trajectories in models and patients with different modes of p53 deficiency.
Yoon-La Choi studies heterogeneity resulting from p53 mutation by spatial transcriptomics.
Sabine Merkelbach-Bruse and Ka-Won Noh provide single cell WGS and RNAseq for monitoring lung cancer patients by CTCs in peripheral blood.
Young-Kee Shin providing novel technology efficient enough to study multiple tumor genomes and transcriptomes in peripheral blood (i.e. Cichlid device, which has been successfully transferred to Cologne).
2. Instability in tumor genomes and effects on microenvironment driven by metabolic shift.
Axel Hillmer studies effects in KEAP1-deficient tumors and hypoxia-driven transcriptomes.
Se-Hoon Lee studies therapy resistance mediated by adaptation in the TME.
Ka-Won Noh and Reinhard Buettner study features in tumor cells and TME by snRNA-Seq and spatial transcriptomics.
Han-Na Kim comprehensively analyzes the microbial communities within tumor tissues and host genomic landscapes.
3. Heterogeneity in different KRAS-driven tumors & tumors with germline variants for lung cancer risk
Silvia von Karstedt studies early genomic trajectories in tumors arising from various KRAS mutations and co-mutations.
Hong-Hee Won studies germ-line lung cancer risk variants in never smokers and compares Korean and German variants (German variants provided by the nNGM network).
Ka-Won Noh and Reinhard Buettner study features in tumor cells and TME by snRNA-Seq and spatial transcriptomics.
Matthias Scheffler and Juergen Wolf investigate consequences of molecular heterogeneity in KRAS tumors with different patterns of co-mutations and provide expertise in clinical translation.
4. In silico technologies.
Martin Peifer reconstructs evolutionary trajectories in stable vs instable lung cancer genomes
Katarzyna Bozek uses Federated Learning on lung cancer images for predictive modeling of therapy effects.
Kyu-Hwan Jung uses Machine Learning and AI to measure subclonality and heterogeneity in NSCLC.
For more information about specific projects, please visit the individual pages listed here
University of Cologne
Sungkyunkwan University
Core Facilitators
Federated learning for improved clinical outcome prediction in lung cancer
Katarzyna Bozek
Genomic instability influenced by metabolic switch after NRF2 activation in LUAD.
Axel Hillmer
Single cell DNA/RNAseq from CTCs.
Sabine Merkelbach-Bruse and Ka-Won Noh
Effect of ecological niches on KRAS mutations in early tumor expansion.
Silvia von Karstedt
Genomic trajectories with different modes of p53 deficiency in SCLC models and patients.
Julie George
Modelling genomic evolution in stable and instable lung cancer genomes.
Martin Peifer
Therapeutic consequences of molecular heterogeneity in KRAS-mutated NSCLC.
Matthias Scheffler and Juergen Wolf
Deciphering the impact of evolutionary genetic heterogeneity during ALK targeted treatment in EML4-ALK mutated NSCLC.
Roland Ullrich
Comparing tumor heterogeneity and genomic instability between different models of LUAD (p53mut, KEAP1, KRAS/p53) by snRNA-Seq and spatial transcriptomics.
Ka-Won Noh and Reinhard Buettner
Untwining the heterogeneity of lung cancer derived from fusion gene using spatially resolved transcriptomics.
Yoon-La Choi
Deep learning-omics-clinical hybrid research projects.
Kyu-Hwan Jung
Unraveling the Multifaceted Interplay of Microbiome and Multi-Omics in Lung Cancer Immunotherapy.
Han-Na Kim
Cancer Genomics for Precision Immunotherapy.
Se-Hoon Lee
Identifying causal therapeutic targets and understanding the molecular basis of lung cancer using genome-wide association and multi-omics analyses.
Hong-Hee Won
Advancing Virtual Pathology and AI-Based Image Analysis
Yuri Tolkach
Core Facility for Circulating Tumor Cell Analysis.
Young Kee Shin
