Modelling the micro- and macro- environment of pancreatic cancer: from patients to pre-clinical models and back.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with very low survival rates. Over the past 50 years, improvements in PDAC survival have significantly lagged behind the progress made in other cancers. PDAC's dismal prognosis is due to typical late-stage diagnosis combined with lack of effective treatments and complex mechanisms of disease. We propose that improvements in survival are partly hindered by the current focus on largely modelling and targeting PDAC as one disease, despite it being heterogeneous. Implementing new disease-representative pre-clinical mouse models that capture this complexity could enable the development of transformative therapies. Specifically, these models should recapitulate human PDAC late-stage biology, heterogeneous genetics, extensive non-malignant stroma, and associated risk factors and comorbidities. In this Perspective, we focus on how pre-clinical mouse models could be improved to exemplify key features of PDAC micro- and macro- environments, which would drive clinically relevant patient stratification, tailored treatments and improved survival.