Tomographic volumetric bioprinting of 3D pancreatic cancer models

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is the most frequent type of pancreatic cancer, one of the leading causes of cancer-related deaths worldwide. PDAC is marked by a dense, fibrous tumor microenvironment, in which stromal fibroblasts surround the cancerous ductal epithelial cells. The cross-talk between pancreatic cells and the surrounding fibroblasts leads to inflammation and stiffening of the surrounding tissue, which is believed to hinder anti-cancer drugs’ uptake and effectiveness. In vitro, fully human models of the pancreatic cancer microenvironment are needed to foster the development of new, more effective therapies; but it is still challenging to make these models anatomically and functionally relevant. Here, we use tomographic volumetric bioprinting, a novel method to fabricate cell-laden multi-mm viable constructs within less than a minute, to produce anatomically relevant fibroblast-laden gelatine methacrylate-based pancreatic duct models, including a duct and an acinus. We then seeded human pancreatic ductal epithelial (HPDE) cells, wild type or cancerous, into these models and evaluated the progression of the constructs for several days after printing. We show that the 3D pancreatic duct models remain viable for up to 14 days after bioprinting. We used immunofluorescence to evaluate the surrounding fibroblasts' activation by quantifying the relative expressions of alpha smooth muscle actin (𝛂SMA) vs. actin in the fibroblasts. 𝛂SMA is known to be overespressed in inflammated tumor-associated fibroblasts, and to lead to tissue stiffening. We show that 𝛂SMA expression is significantly higher in fibroblasts co-cultured with cancerous than with wild-type HPDE cells, that this expression increases with time, and that it is higher in fibroblasts that lay closer to HPDE cells than in those deeper into the model. These models could potentially be used in drug development or to shed light on the early progression of the disease.

Contents

This repository contains the raw data, materials list, protocols, and code necessary to reproduce the work in the namesake preprint.