Systems Oncology

We are particularly interested in the chemical messages that are sent between cells as pancreatic cancer develops.  We aim to identify the key signals that drive tumour growth and help the cancer cells to spread around the body, and ultimately find new ways to block these signals – reducing tumour growth and metastatic spread.  Survival from pancreatic cancer has changed little over the years; the average five-year survival rate is just 12%, thus identifying new ways to treat this disease is a real priority for the 10,000 people diagnosed each year in the UK.       

Pancreatic Ductal Adenocarcinoma is the most common form of Pancreatic Cancer. Its commonly detected all too late and most patients are presenting with metastatic disease. Local disease e.g., tumour that has not escaped the pancreas, may be removed by surgery and treated by chemotherapy whereas metastatic disease is only treated by chemotherapy. Pancreatic Cancer is characterised by an extensive desmoplastic reaction where most of the tumour is made up by host ‘normal’ cells and extracellular matrix (scar tissue) with tumour cells only occupying ~15% of the tumour volume on average. Host cells such as fibroblasts and various immune cell populations are co-opted by tumour cells to enable tumour development, resist treatment and avoid recognition by tumour cell killing immune cells. The remodelled extracellular matrix increases tissue stiffness and interstitial pressure, decreasing therapeutic efficiency, and altering cell growth.  Our long-term goals are to understand how specific signals are processed to promote tumour progression and how blocking these signals can enhance therapeutic response. 

We focus on identifying and delineating the regulatory mechanisms whereby tumour cells co-opt stromal cells and how the ‘activated’ stromal cells affect tumour cell behaviour (malignant progression, drug sensitivity and metastasis). To establish the specificities of signalling networks and how they impinge on specific cellular processes, we are using Mass Cytometry (CyTOF), CRISPR editing/screening, sequencing and quantitative mass spectrometry to systematically measure signalling on a global level. Through data-integrative approaches, we aim to describe how signals are processed in a cell-specific manner, which requires single cell methodologies to separate the activities of all the cell types in the tumour.   We are also creating new models of pancreatic cancer in the laboratory, using synthetic scaffolds to artificially alter the stiffness of the tumour, mixing in fibroblasts and immune cells, and experimentally determining the effect of each component on the tumour growth.   

Reducing the stiffness of the PDAC organoid environment results in cells creating ductal-like structures as they develop from original more firm area into the softer area.