Quantitative proteomic analysis of pancreatic cyst fluid for early detection of cancer using University of Hull HPC Viper

Project Description

The timely diagnosis of pancreatic ductal adenocarcinoma (PDAC) is challenging due to a lack of disease-specific symptoms, resulting in the majority of patients presenting with advanced disease and poor prognosis. Detection of PDAC, ideally at a premalignant or early invasive stage when surgery could be more effective, would greatly increase survival rates, thus meeting a substantial unmet need. PDAC currently stands as the 10th most common cancer and 6th leading cause of cancer deaths in the UK. While a marked improvement in survival over time has been observed with other cancer types, e.g. melanoma, the five-year survival rate for PDAC has increased from 3-4% to only 7% in recent years.
About 10% of PDAC cases arise from a pancreatic cystic lesion, e.g. intraductal papillary mucinous neoplasms (IPMN), which can be up to 30% of a typical pancreatic resective workload. Current international consensus (Fukuoka guidelines) on management of IPMNs cannot accurately predict association with carcinoma based on imaging. Pancreatic cystic fluid (PCyF) collected via endoscopic ultrasound guided fine needle aspiration (EUS-FNA) has been explored for more accurate molecular diagnosis. Biochemical tests (amylase, carcinoembryonic antigen and mucin) can yield inaccurate or uncertain (false positive or negative) results and insufficiently discriminate the pre-malignant pancreatic cysts from others. The ideal molecular diagnostic test would be capable of accurately detecting pancreatic cancer at early stages to avoid unnecessary morbid surgery or initiation of inappropriate surveillance. In this study, we aim to analyse molecular changes, or ‘signatures’, associated with early stages of pancreatic carcinogenesis by using quantitative proteomics (QP) technology. Highly innovative and based on exciting pilot data (obtained in 2021 through collaboration with Dr Holger Kramer, MRC Laboratory of Molecular Biology, Cambridge) approach of performing PCyF analysis at whole proteome resolution levels as a diagnostic test would be key for a complete, unbiased characterisation of highest possible number of proteomic events and changes associated with early stages of pancreatic cancer.

The research assistant (RA) would have a short term contract to work specifically on this project. The RA would be responsible for the platform technologies (bioinformatic analysis of proteomics data using University of Hull (UoH) High Performance Computer (HPC) VIPER), to analyse generated in 2021 pilot data as well as the scientific drive and the dissemination and publishing of the data. Mr Dimitrios Manolis is an early career researcher and has expertise in using label-free quantitative proteomics approaches and the UoH HPC VIPER , acquired during his Wellcome Trust funded summer scholarship in 2019, graduate internship in 2020 and self-funded MSc study in 2020-2022 (all - under supervision of Dr Leonid Nikitenko, and last one - also under co-supervision of Dr Holger Kramer).