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​My project aims to understand how specific pathway inhibitors in routine clinical use in B-cell lymphoma and leukemia patients affect signaling activity of primary tumor cell populations exposed to drugs on transcriptional level. We hypothesize that the response of tumors exposed to a panel of drugs will vary quantitatively and qualitatively as a function of drug sensitivity and pathway activity (wiring) of individual tumors. We aim to use the drug response patterns generated upon ex-vivo drug exposure to make predictions on activated signaling cascades for individual tumors, diseases and disease categories. By comparing the dense matrix of the transcriptional landscape derived from perturbation of 100 individual tumors with their known clonal structure and genotypes across a panel of 10 ex-vivo treatment conditions, we will be able to functionally tie gene expression to causal molecular properties and pathways as we use specific and well-annotated inhibitors. The use of inhibitors with targets including the BCR (BTK, PI3K) and essential downstream nodes (mTOR, MEK) will allow us to understand the response to single drugs and to precisely compare the transcriptional downstream landscape and thereby understand how inhibitors and tumors differ.

The emerging molecular network build on ~1000 transcriptomes of drug-induced primary leukemia and lymphoma samples will allow us to use lymphoma as a model to understand how the fingerprint of targeted drugs can be used to derive “connectivity maps” of tumors, classify disease and develop

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