IDENTIFICATION OF NOVEL PROTEINS IN THE PANCREATIC CANCER MICROENVIRONMENT.

Abstract

Background: Pancreatic cancer is an extremely aggressive malignancy that is characterised by an intense desmoplastic response, the role of which remains unknown. Proteomic studies allow the analysis of the protein content of a cell or tissue and offer a more functional perspective than traditional gene based studies. Recent work has suggested that the surrounding stromal tissue actively participates in tumour progression and invasion and this may be detectable by critical changes in protein expression. We aim to characterize the protein expression in the pancreatic cancer microenvironment using a proteomic-based approach. Methods: Pancreatectomy specimens obtained following surgery were sectioned, stained and specific cell populations obtained using laser capture microdissection (LCM). We obtained malignant ductal cells and stromal cells both immediately adjacent to tumour (juxtatumoral stroma) and distant to the tumour (panstroma). Proteins from these cell populations were subsequently separated using two-dimensional gel electrophoresis (2DE) and visualized using silver staining. Spot profiles from each were compared to identify differentially expressed spots and mass spectrometry used to identify proteins from these spots of interest. Results: Four groups of protein samples have been acquired, each gel displaying in excess of 700 spots. Comparison of the spot patterns revealed nine consistent differences between ductal cells and stromal cells. Five of these differences were limited to the juxtatumoral stromal cells, and appear to represent novel proteins previously unreported in pancreatic stromal cells. Conclusions: By employing proteomic-based technologies, we have demonstrated differential protein expression between pancreatic stromal cells and malignant ductal epithelium. Furthermore, we have shown that some of these proteins are limited to those stromal cells lying immediately adjacent to the malignant ducts. Such proteins may represent future novel biomarkers or therapeutic targets.