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- Inflammatory Stress in Stem Cells
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- Helmholtz Professorship Cell Biology
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Division of Molecular Genetics
Prof. Dr. Peter Lichter
Our laboratory applies oncogenomic approaches for the elucidation of pathomechanisms of tumor etiology and progression as a basis for novel treatment strategies, and for the identification of prognostic and predictive genes and gene signatures. To this aim, we perform large screens using comprehensive molecular profiling technologies revealing tumor cell alterations at the level of the genome, transcriptome, methylome and chromatin. Integration of such data sets with clinical data allows us to identify candidate genes, which we subsequently test for their i) possible role in tumor pathophysiology, ii) potential as targets for novel therapy-strategies, iii) prognostic value to stratify patient subgroups for risk-adapted therapy regimens and iv) potential to predict therapy response or resistance in cancer patients. Within the last 5 years, we have greatly contributed to novel tumor sub-classification schemes that allow for stratification of cancer patients for different therapy regimens on the basis of molecular tumor profiles. By unravelling pathogenically relevant genes, we have identified candidate targets for the development of novel therapies, in particular in leukemia and glioma. Through the functional characterization of candidate genes we also developed pre-clinical models for the testing of novel therapies.
In the department we work on the following research topics:
Brain tumors
- Pathophysiology of childhood and adult brain tumors
- Tumor metabolism
- Preclinical models
- Tumor-stromal interaction
- Immune-escape mechanisms
- Immune-therapeutic targets
- Preclinical models
- Development of prognostic and predictive markers and gene signatures for clinical use
- Personalized oncology in gynecological tumors within DKFZ-HIPO (Heidelberg Center for Personalized Oncology)
- Role of DNA repair defects in chromothripsis
- Mechanistic basis of catastrophic genomic events
- In vitro and in vivo modeling of one-off complex genomic rearrangements