Predicting Patient Outcomes in Pancreatic Cancer via Multiomic Analysis of the Tumour Microenvironment

Dr. Aidan O’Dowling

Dr. Aidan O’Dowling has been awarded the Research Ireland’s Enterprise Partnership Scheme in partnership with Breakthrough Cancer Research.  Aidan is working under the supervision of Dr. Stephen Thorpe at the School of Medicine at University College Dublin.

About 600 people in Ireland will be diagnosed with pancreatic cancer this year. Based on current practice, less than 1-in-10 of these will survive 5 years beyond diagnosis. While outcomes for most cancers are improving, this is not the case for pancreatic cancer. It is predicted to become the second leading cause of cancer death by 2030.

A unique characteristic of pancreatic cancer is the dense tissue, called stroma, that forms around the tumour. The stroma in pancreatic cancer is more extensive and physically stiffer than that of any other tumour. This stiffness encourages cancer growth and spread, and also acts as a barrier to prevent drugs from reaching cancer cells, which contributes to treatment resistance.

Surgery is the only potential cure for pancreatic cancer. As the symptoms of pancreatic cancer are non-specific, patients are typically diagnosed with advanced cancer and only 1-in-5 patients present with tumours which are suitable for surgery. To increase the number of patients who can access surgical treatment, chemotherapy can be provided with the aim of shrinking the tumour. This is called neoadjuvant therapy.

This study aims to:

• Characterise both the biomechanical response of pancreatic tissue to tumour growth (i.e. the stiffness of both the tumour and the adjacent normal tissue) and its response to chemotherapy.
• Correlate these results to routine diagnostic computed tomography (CT) scans via artificial intelligence.
• Develop lab-based models using patient tumours to observe drug responses.

Biopsy and surgically resected tissue will be collected from consenting patients who undergo these procedures as part of their normal treatment. In addition to routine diagnostic analysis, we will assess tissue composition, structure, and stiffness. Cells from the obtained tissue will be used to test responses to several different drug treatments. We will compare our laboratory results to patient Computed Tomography (CT) scans.

This study will help us better understand how the tumour responds to drug treatment and provide a foundation for personalised approaches to chemotherapy use and survival.