Title: Application of deep proteomics using an aptamer-based technology to advance early detection of pancreatic cancer
Funder: Cancer Research UK

Abstract: Background Currently 85% of individuals with pancreatic ductal adenocarcinoma (PDAC) are ineligible for potentially curative surgery due to late diagnosis. Early detection would improve survival. However, PDAC is relatively rare and screening the general population with current modalities is not feasible, due to the large potential for misdiagnosis. Screening only those at high-risk would improve the accuracy of future screening programmes. Approximately 65% of PDAC patients have diabetes mellitus (DM), with DM onset occurring, on average, 13 months prior to PDAC diagnosis. Evidence now shows that ~10% of adults diagnosed with type 2 DM (T2DM) actually have the lesser-known type 3c form of the disease (T3cDM), which includes PDAC-associated DM (PDAC-DM). Thus, individuals with new-onset DM (NOD) are the largest high-risk group for PDAC as the onset of DM in these individuals could be an early symptom of PDAC. For this reason, CRUK have awarded our group a programme grant to recruit and follow individuals with NOD for research into early detection of PDAC. The success of this programme requires novel approaches to biomarker discovery. Aim To identify protein biomarkers that distinguish type 3c diabetes (which includes PDAC-associated) from type 2 diabetes, paving the way for the development of diagnostic tools capable of selecting individuals for PDAC screening at the point of diagnosis of diabetes. Methods We will undertake the deepest interrogation of the human plasma proteome for biomarkers of PDAC to-date. Using a state-of-the-art aptamer-based platform (SOMAscan) we will measure ~5,000 proteins in individual plasma samples from disease groups selected to address early diagnosis of PDAC in NOD. SOMAscan’s deep-multiplexing will reveal differentially expressed proteins and enable pathway analysis which will inform candidate selection. We will validate the three best-performing candidates in an independent cohort, providing proof of concept of the process and generating the requisite data for future application of candidates and/or the SOMAscan platform to the CRUK funded cohort of NOD individuals. Outcome As the broadest characterisation of the proteome in PDAC to-date, it will provide novel validated biomarkers for early detection of PDAC in NOD. These markers will be ready for optimisation and clinical trials. The project will demonstrate the utility of SOMAscan for future applications and mining of the data-set will provide insight into the biology underpinning PDAC-associated T3cDM. This award will pave the way for a funding application to apply SOMAScan to pre-diagnostic PDAC samples collected through CRUK-funded and NIH-funded Early Detection Programmes.

Lay abstract: Background Currently 85% of individuals with pancreatic ductal adenocarcinoma (PDAC) are ineligible for potentially curative surgery due to late diagnosis. Early detection would improve survival. However, PDAC is relatively rare and screening the general population with current modalities is not feasible, due to the large potential for misdiagnosis. Screening only those at high-risk would improve the accuracy of future screening programmes. Approximately 65% of PDAC patients have diabetes mellitus (DM), with DM onset occurring, on average, 13 months prior to PDAC diagnosis. Evidence now shows that ~10% of adults diagnosed with type 2 DM (T2DM) actually have the lesser-known type 3c form of the disease (T3cDM), which includes PDAC-associated DM (PDAC-DM). Thus, individuals with new-onset DM (NOD) are the largest high-risk group for PDAC as the onset of DM in these individuals could be an early symptom of PDAC. For this reason, CRUK have awarded our group a programme grant to recruit and follow individuals with NOD for research into early detection of PDAC. The success of this programme requires novel approaches to biomarker discovery. Aim To identify protein biomarkers that distinguish type 3c diabetes (which includes PDAC-associated) from type 2 diabetes, paving the way for the development of diagnostic tools capable of selecting individuals for PDAC screening at the point of diagnosis of diabetes. Methods We will undertake the deepest interrogation of the human plasma proteome for biomarkers of PDAC to-date. Using a state-of-the-art aptamer-based platform (SOMAscan) we will measure ~5,000 proteins in individual plasma samples from disease groups selected to address early diagnosis of PDAC in NOD. SOMAscan’s deep-multiplexing will reveal differentially expressed proteins and enable pathway analysis which will inform candidate selection. We will validate the three best-performing candidates in an independent cohort, providing proof of concept of the process and generating the requisite data for future application of candidates and/or the SOMAscan platform to the CRUK funded cohort of NOD individuals. Outcome As the broadest characterisation of the proteome in PDAC to-date, it will provide novel validated biomarkers for early detection of PDAC in NOD. These markers will be ready for optimisation and clinical trials. The project will demonstrate the utility of SOMAscan for future applications and mining of the data-set will provide insight into the biology underpinning PDAC-associated T3cDM. This award will pave the way for a funding application to apply SOMAScan to pre-diagnostic PDAC samples collected through CRUK-funded and NIH-funded Early Detection Programmes.

Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES;4.5 RESOURCES AND INFRASTRUCTURE (DETECTION)
Health categories: CANCER AND NEOPLASMS