Analysis of dynamics of body composition using computerised tomography scans and their association to molecular taxonomy in pancreatic cancer (Glasgow

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The above title ends in (Glasgow lead).Studentship strategic priority area: Basic & Clinical ResearchKeywords: Pancreatic cancer, molecular subtypes, precision medicine, tumour-host-interaction, medical imagingAbstract: This project will primarily involve computational and AI methods including bioinformatics (algorithm development) to first carry out analysis of pancreatic tumour profiles in correlation with CT scan image analysis (to examine body composition) and systemic inflammation markers to define genetic characteristics and genomic aberrations, based on this multi-omic patient cohort dataset analysis. Gene pathways of importance will also be assess using multiplex IF staining so that spatial proteomics can be analysed using a digital pathology approach. This is to characterise potential molecular patterns that may contribute to clinical phenotypes, and subsequently define key biological pathways underpinning each phenotype identified. These relationships will then be ranked based on prognosis, and findings will be further validated in patient cohort data to confirm clinical relevance, in order to try and predict patient outcome. CT scan image analysis will be carried out on trusted research environment developed by the iCASE industrial partner Collective Mind Radiology.