Developing novel 3D bioprinting techniques to create pancreatic cancer models

Abstract

Cancer is a leading cause of death worldwide, with pancreatic ductal adenocarcinoma (PDAC) having the lowest survival rates among all cancers, which have not improved in the past 50 years. PDAC tumours are characterised by a stiff, fibrotic stroma, which contributes to the cancer’s aggressiveness and chemoresistance. Over the past decade, 3D bioprinting techniques have gained popularity for their potential to create complex, biomimetic 3D in vitro models, which recapitulate native tissue responses. However, developing 3D bioprinting techniques requires addressing several challenges, primarily bioink biocompatibility and printability, as well as long-term cell survival and behaviour. In this present study, a novel 3D bioprinting method was developed using droplet-based bioprinting technologies. Optimisation studies of bioprinting parameters demonstrated that using an electromagnetic droplet (EMD) printhead, droplets of cell-laden GelMA bioinks can be extruded with accuracy and precision. Additionally, two different support materials were explored to deposit the droplets into: a gellan gum granular gel suspension medium and pure Matrigel. Both methods showed that by adjusting the printing conditions, such as bath temperature or extrusion pressure, the size and definition of the hydrogel droplets can be controlled. Furthermore, this method enabled multilineage cell patterning, the Matrigel-based constructs demonstrating enhanced cell viability, proliferation and functional activity. Lastly, Matrigel was combined with a low-temperature gelation GelMA formulation to increase its mechanical properties and offer a more robust microenvironment without losing its inherent biocompatibility and support for cellular functions. Despite some remaining limitations, such as achieving high resolution printing and scalability, this novel method offers a unique tool for creating Matrigel rich 3D bioprinted cancer models. Its customisation and reliability make it an appealing approach, which can be adapted to a variety of tissues and pathophysiological conditions. Further development of this method could transform it into a powerful tool in the 3D bioprinting field.