AUTHOR=Sbirkov Yordan , Molander Diana , Milet Clement , Bodurov Ilia , Atanasov Boyko , Penkov Radoslav , Belev Nikolay , Forraz Nico , McGuckin Colin , Sarafian Victoria TITLE=A Colorectal Cancer 3D Bioprinting Workflow as a Platform for Disease Modeling and Chemotherapeutic Screening JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=9 YEAR=2021 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2021.755563 DOI=10.3389/fbioe.2021.755563 ISSN=2296-4185 ABSTRACT=

Colorectal cancer (CRC) is the third most common malignancy and has recently moved up to the second leading cause of death among carcinomas. Prognosis, especially for advanced diseases or certain molecular subtypes of CRC, remains poor, which highlights the urgent need for better therapeutic strategies. However, currently, as little as 0.1% of all drugs make it from bench to bedside because of the inherently high false-positive and false-negative rates of current preclinical and clinical drug testing data. Therefore, the success of developing novel treatment agents lies in the introduction of improved preclinical disease models which resemble in vivo carcinomas closer, possess higher predictive properties, and offer opportunities for individualized therapies. Aiming to address these needs, we have established an affordable, flexible, and highly reproducible 3D bioprinted CRC model. The histological assessment of Caco-2 cells in 3D bioprints revealed the formation of glandular-like structures which show greater pathomorphological resemblance to tumors than monolayer cultures do. RNA expression profiles in 3D bioprinted cells were marked by upregulation of genes involved in cell adhesion, hypoxia, EGFR/KRAS signaling, and downregulation of cell cycle programs. Testing this 3D experimental platform with three of the most commonly used chemotherapeutics in CRC (5-fluoruracil, oxaliplatin, and irinotecan) revealed overall increased resistance compared to 2D cell cultures. Last, we demonstrate that our workflow can be successfully extended to primary CRC samples. Thereby, we describe a novel accessible platform for disease modeling and drug testing, which may present an innovative opportunity for personalized therapeutic screening.