Abstract 5647: Multivariant analysis to decipher the human pancreatic cancer proteome to identify novel biomarkers and therapeutic targets
Authors: Law Henry Chun Hin , Lagundzin Dragana , Wagner Zachary S. , Woods Nicholas 
Published: August 2018

Abstract
The microenvironment of a tumor plays a vital role in its development and progression. We hypothesized that the pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment could elucidate proteins associated with patient survival. This project utilized a quantitative proteomics approach designed to: 1) Identify differentially expressed proteins in the tumor microenvironment of PDAC liver metastases that exhibited different levels of cancer cell differentiation; 2) Distinguish proteins associated with PDAC patient survival to build a predictive model for prognosis; and 3) Identify potential therapeutic targets to promote patient survival. A cohort of PDAC liver metastases from 60 patients was collected from the Pancreatic SPORE Rapid Autopsy Program at the University of Nebraska Medical Center. The tissue samples were preserved within 1-3 hours to avoid post-mortem protein degradation. The tissues were divided into 7 batches and were lysed, digested and differentially labeled with isobaric Tandem Mass Tags. The tagged peptides were mixed, fractionated with C18 spin columns and analyzed by an Orbitrap Fusion Lumos LC-MS/MS system. 30811 peptides and 3960 proteins were identified from the analysis. 1842 of them were quantified and 917 proteins were submitted for principal component analysis. Tissue samples with similar protein expressions were grouped into 4 major clusters. Samples exhibit a tendency to cluster depending on similar histological features and tumor cell differentiation. Gene ontology enrichment analysis of the corresponding protein clusters suggests samples group according to tumor cellularity, the degree of differentiation and stroma involvement. The proteome data was then correlated to the survival days post diagnosis with partial least square analysis to identify PDAC prognostic markers. Thymidine phosphorylase (TYMP) was one of the highest scoring proteins in the model. This protein converts 5'-deoxy-5-fluorouridine into 5-fluorouracil and is a known predictive marker for capecitabine treatment. Current data suggests patients with higher TYMP expressions tend to have longer survival after the diagnosis. One of the high scoring proteins identified in the model is endoplasmic reticulum aminopeptidase 1 (ERAP1). ERAP1 is an enzyme which trims precursor peptides in the endoplasmic reticulum. Antigenic peptides from the cancer cells might be altered in the process. With further validation, the biomarkers identified with this methodology could provide insight into the design of personalized cancer treatment for PDAC patients.
Citation Format: Henry Chun Hin Law, Dragana Lagundzin, Zachary S. Wagner, Nicholas Woods. Multivariant analysis to decipher the human pancreatic cancer proteome to identify novel biomarkers and therapeutic targets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5647.