AUTHOR=Sztankovics Dániel , Moldvai Dorottya , Petővári Gábor , Gelencsér Rebeka , Krencz Ildikó , Raffay Regina , Dankó Titanilla , Sebestyén Anna TITLE=3D bioprinting and the revolution in experimental cancer model systems—A review of developing new models and experiences with in vitro 3D bioprinted breast cancer tissue-mimetic structures JOURNAL=Pathology and Oncology Research VOLUME=29 YEAR=2023 URL=https://www.por-journal.com/journals/pathology-and-oncology-research/articles/10.3389/pore.2023.1610996 DOI=10.3389/pore.2023.1610996 ISSN=1532-2807 ABSTRACT=

Growing evidence propagates those alternative technologies (relevant human cell-based—e.g., organ-on-chips or biofabricated models—or artificial intelligence-combined technologies) that could help in vitro test and predict human response and toxicity in medical research more accurately. In vitro disease model developments have great efforts to create and serve the need of reducing and replacing animal experiments and establishing human cell-based in vitro test systems for research use, innovations, and drug tests. We need human cell-based test systems for disease models and experimental cancer research; therefore, in vitro three-dimensional (3D) models have a renaissance, and the rediscovery and development of these technologies are growing ever faster. This recent paper summarises the early history of cell biology/cellular pathology, cell-, tissue culturing, and cancer research models. In addition, we highlight the results of the increasing use of 3D model systems and the 3D bioprinted/biofabricated model developments. Moreover, we present our newly established 3D bioprinted luminal B type breast cancer model system, and the advantages of in vitro 3D models, especially the bioprinted ones. Based on our results and the reviewed developments of in vitro breast cancer models, the heterogeneity and the real in vivo situation of cancer tissues can be represented better by using 3D bioprinted, biofabricated models. However, standardising the 3D bioprinting methods is necessary for future applications in different high-throughput drug tests and patient-derived tumour models. Applying these standardised new models can lead to the point that cancer drug developments will be more successful, efficient, and consequently cost-effective in the near future.