Talk Title: Cell-Specific Analysis of Tumour-Stroma Signalling
Dr Claus Jorgensen is a Group Leader at the Cancer Research UK Manchester Institute, University of Manchester. He obtained his PhD at the University of Southern Denmark in 2005 after which he moved to Toronto, Canada for his postdoctoral training with Dr Tony Pawson at the Samuel Lunenfeld Research Institute. In 2010 Dr Jorgensen established his independent career at The Institute of Cancer research, London UK and relocated to CRUK Manchester Institute in 2014.
My main research goal is to understand how aberrantly regulated cellular signalling networks drive tumour progression. Specifically I am focussed on determining how a multicellular microenvironment composed of both tumour and host cells synergise to drive progression and resistance to therapy in pancreatic ductal adenocarcinoma.
Tumours are complex organs that, in addition to the transformed cancer cells, contain infiltrating host cells. It is widely accepted that infiltrating cells such as fibroblasts and immune cells influence the malignant behaviour of cancer cells. However, the mechanisms whereby stromal cells support cancer cells are currently not clearly defined. Specifically, our understanding of the reciprocal signals that are exchanged between tumour and stromal cells and their interdependencies is not fully appreciated. To address this we have combined cell-specific labelling by isotopomeric amino acids in long-term co-cultures (CTAP, Gauthier et al Nat Methods 2013 and Tape et al MCP 2014) with global proteomics analysis to discern cell signalling at cell-specific resolution in direct co-culture models. Using this approach we have delineated an oncogene-driven signalling axis, whereby cancer cells co-opt stromal cells to elicit reciprocal signals, which engage new signalling pathways in the cancer cells (Tape et al Cell 2016). Importantly, specific tumour cell phenotypes are only observed in co-culture models, suggesting that our biochemical appreciation of cell signalling in complex model systems needs further investigation.