Mass Spectrometry-Based Protein Biomarker Discovery in Pancreatic Cancer

Sammanfattning: Background: Pancreatic cancer has the lowest survival rate among all the major cancer types. Although recent decades have seen advances in diagnostic imaging, surgical techniques, perioperative care and oncological treatment, this has not been translated into major improvements in clinical outcome. The 5-year survival rate remains less than 10% for all stages. One important unmet clinical need is biomarkers of clinical utility that can be used for early detection, prognostication and guidance of treatment.Aim: The aim of this thesis was to develop and validate protein biomarkers for diagnosis, prognosis and prediction of treatment response in pancreatic cancer.Methods: Mass spectrometry (MS)-based proteomic profiling of fresh frozen tissue specimens from pancreatic cancer patients and control subjects was conducted to identify potential protein biomarkers. These were subsequently verified by targeted proteomics (parallel reaction monitoring (PRM)) and bioinformatic analysis. Selected biomarker candidates were further validated in larger patient cohorts by tissue microarray-based immunohistochemistry studies, serum immunoassay measurements and in vitro experiments.Results/conclusions:(I) A proteolytic digestion protocol was optimised for MS-based proteomics studies. Urea in-solution digestion at room temperature (24 ± 2 °C) was found to be superior to traditional proteolysis at 37 °C, presenting several advantages such as fewer experimentally-induced post-translational modifications (carbamylation and pyroglutamic acid modifications), increased identification of peptides and proteins, and improved protein quantification by reducing coefficients of variations.(II) Some 165 potential protein biomarkers were identified in pancreatic cancer tissues and a panel of 45 biomarker candidates was verified by targeted MS. The novel protein BASP1 was significantly associated with favourable survival and positive response to adjuvant chemotherapy in pancreatic cancer patients. Bioinformatic analysis indicated that BASP1 interacts with Wilms tumour protein WT1. Patients with negative BASP1 and high WT1 expression had the poorest outcomes.(III) Prognostic analysis of YAP1 demonstrated a significant correlation with lower survival, at both mRNA expression levels (TCGA cohort) and protein expression levels (Lund cohort). Inhibiting the YAP1/TEAD interaction interfered with the expression of AREG, CTGF, CYR61 and MSLN in pancreatic cancer cells, which suggests that YAP1 transcriptional activity may affect the evolution and persistence of a fibrotic tumour microenvironment.(IV) Expression of AGP1 in pancreatic cancer tissues is significantly correlated with poor survival. Circulating levels of AGP1 and CA 19-9 yielded a high diagnostic accuracy (AUC 0.963) for discrimination of resectable pancreatic cancer patients against healthy controls.