Seeking improved outcomes in pancreatic cancer: Applying multi-omic data analysis approaches to explore the biology underpinning pancreatic cancer-rel

Background

At the time of cancer diagnosis, over 45% of pancreatic cancer patients have diabetes. Typically, diabetes is of new-onset, and is considered to be a 'symptom' of pancreatic cancer, known as type 3c diabetes.

Single-cell gene expression analysis from pancreatic tumours, stratified by diabetes, and parallel analysis of blood protein profiles to identify genes and pathways dysregulated in pancreatic cancer-related diabetes is ongoing. Objectives

1) Perform state-of-the-art bioinformatic analysis of single cell gene expression and blood-based proteomic data, selecting candidate markers that exemplify differences between diabetogenic versus non-diabetogenic pancreatic cancer 2) Undertake pathway analysis to investigate novel mechanisms involved in pancreatic cancer-related diabetes

3) Undertake laboratory validation of molecular findings

Understanding how pancreatic cancer causes diabetes and its associated molecular consequences will significantly advance the field.