A 3D Bio-Printed-Based Model for Pancreatic Ductal Adenocarcinoma

Author:

Godier Claire1,Baka Zakaria1,Lamy Laureline23,Gribova Varvara45ORCID,Marchal Philippe6,Lavalle Philippe45,Gaffet Eric1ORCID,Bezdetnaya Lina23,Alem Halima17ORCID

Affiliation:

1. IJL, CNRS, Université de Lorraine, 54000 Nancy, France

2. CRAN, CNRS, Université de Lorraine, 54506 Vandœuvre-lès-Nancy, France

3. Département Recherche, Institut de Cancérologie de Lorraine (ICL), 6 Avenue de Bourgogne, 54519 Vandœuvre-lès-Nancy, France

4. Institut National de la Santé et de la Recherche Médicale (INSERM) U1121, Biomaterials and Bioengineering, 1 rue Eugène Boeckel, 67100 Strasbourg, France

5. Faculté de Chirurgie Dentaire, Université de Strasbourg, 8 rue Sainte Elisabeth, 67000 Strasbourg, France

6. LRGP, CNRS, Université de Lorraine, 54000 Nancy, France

7. Institut Universitaire de France, 75000 Paris, France

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a disease with a very poor prognosis, characterized by incidence rates very close to death rates. Despite the efforts of the scientific community, preclinical models that faithfully recreate the PDAC tumor microenvironment remain limited. Currently, the use of 3D bio-printing is an emerging and promising method for the development of cancer tumor models with reproducible heterogeneity and a precisely controlled structure. This study presents the development of a model using the extrusion 3D bio-printing technique. Initially, a model combining pancreatic cancer cells (Panc-1) and cancer-associated fibroblasts (CAFs) encapsulated in a sodium alginate and gelatin-based hydrogel to mimic the metastatic stage of PDAC was developed and comprehensively characterized. Subsequently, efforts were made to vascularize this model. This study demonstrates that the resulting tumors can maintain viability and proliferate, with cells self-organizing into aggregates with a heterogeneous composition. The utilization of 3D bio-printing in creating this tumor model opens avenues for reproducing tumor complexity in the future, offering a versatile platform for improving anti-cancer therapy models.

Funder

Ministry of Higher Education, Innovation, and Research

French PIA project “Lorraine Université d’Excellence”

Publisher

MDPI AG

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