Poster Presentation 35th Lorne Cancer Conference 2023

Spatially resolved proteomics to identify cellular communication networks in pancreatic cancer (#211)

Clara Kosasih 1 , Claire Marceaux 1 , Belinda Lee 1 , Ka Yee Fung 1 , Adele Preaudet 1 , Michael Griffin 2 , Peter Gibbs 1 , Sean Grimmond 3 , Marie-Liesse Asselin-Labat 1 , Tracy Putoczki 1
  1. Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
  2. Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Melbourne, VIC, Australia
  3. Centre for Cancer Research, University of Melbourne, Melbourne, VIC, Australia

The incidence of pancreatic cancer is increasing in Australia. This is alarming, as pancreatic cancer continues to be recalcitrant to therapeutic interventions, reflected in a 5-year survival rate of less than 12%. The development of successful new therapies has been fundamentally limited by the inadequate understanding of the complex interactions that occur between pancreatic cancer cells and their environment.

Pancreatic cancer is associated with chronic inflammation resulting from dysregulated activation of the innate and adaptive arms of the immune system in the pancreas, which invariably leads to an immunosuppressive environment allowing for tumour immune escape. Adaptive immune checkpoint inhibitors have proven ineffective in pancreatic cancer, despite these immunotherapies providing unprecedented survival benefits in other cancers.

We aim to generate a detailed phenotypic and spatial analysis of the communication networks within the stromal microenvironment of pancreatic cancer using the MIBIscope multiplexed tissue imaging platform. We will determine prognostic associations by extracting details on the patient treatment response from our unique PURPLE translational registry, with a focus on comparison of differences in the tumour microenvironment between chemotherapy resistant patients and responsive patients. Our results will be integrated with additional bulk and single-cell multi-omics data-sets on matched tissue samples. Our objective is to enable the discovery and development of molecular-targeted biomarkers and treatment strategies.