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      An in-silico study of cancer cell survival and spatial distribution within a 3D microenvironment

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          Abstract

          3D cell cultures are in-vitro models representing a significant improvement with respect to traditional monolayers. Their diffusion and applicability, however, are hampered by the complexity of 3D systems, that add new physical variables for experimental analyses. In order to account for these additional features and improve the study of 3D cultures, we here present SALSA (ScAffoLd SimulAtor), a general purpose computational tool that can simulate the behavior of a population of cells cultured in a 3D scaffold. This software allows for the complete customization of both the polymeric template structure and the cell population behavior and characteristics. In the following the technical description of SALSA will be presented, together with its validation and an example of how it could be used to optimize the experimental analysis of two breast cancer cell lines cultured in collagen scaffolds. This work contributes to the growing field of integrated in-silico/in-vitro analysis of biological systems, which have great potential for the study of complex cell population behaviours and could lead to improve and facilitate the effectiveness and diffusion of 3D cell culture models.

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          Engineering tumors with 3D scaffolds.

          Microenvironmental conditions control tumorigenesis and biomimetic culture systems that allow for in vitro and in vivo tumor modeling may greatly aid studies of cancer cells' dependency on these conditions. We engineered three-dimensional (3D) human tumor models using carcinoma cells in polymeric scaffolds that recreated microenvironmental characteristics representative of tumors in vivo. Strikingly, the angiogenic characteristics of tumor cells were dramatically altered upon 3D culture within this system, and corresponded much more closely to tumors formed in vivo. Cells in this model were also less sensitive to chemotherapy and yielded tumors with enhanced malignant potential. We assessed the broad relevance of these findings with 3D culture of other tumor cell lines in this same model, comparison with standard 3D Matrigel culture and in vivo experiments. This new biomimetic model may provide a broadly applicable 3D culture system to study the effect of microenvironmental conditions on tumor malignancy in vitro and in vivo.
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            Hypersensitivity to contact inhibition provides a clue to cancer resistance of naked mole-rat.

            The naked mole-rat is the longest living rodent with a maximum lifespan exceeding 28 years. In addition to its longevity, naked mole-rats have an extraordinary resistance to cancer as tumors have never been observed in these rodents. Furthermore, we show that a combination of activated Ras and SV40 LT fails to induce robust anchorage-independent growth in naked mole-rat cells, while it readily transforms mouse fibroblasts. The mechanisms responsible for the cancer resistance of naked mole-rats were unknown. Here we show that naked mole-rat fibroblasts display hypersensitivity to contact inhibition, a phenomenon we termed "early contact inhibition." Contact inhibition is a key anticancer mechanism that arrests cell division when cells reach a high density. In cell culture, naked mole-rat fibroblasts arrest at a much lower density than those from a mouse. We demonstrate that early contact inhibition requires the activity of p53 and pRb tumor suppressor pathways. Inactivation of both p53 and pRb attenuates early contact inhibition. Contact inhibition in human and mouse is triggered by the induction of p27(Kip1). In contrast, early contact inhibition in naked mole-rat is associated with the induction of p16(Ink4a). Furthermore, we show that the roles of p16(Ink4a) and p27(Kip1) in the control of contact inhibition became temporally separated in this species: the early contact inhibition is controlled by p16(Ink4a), and regular contact inhibition is controlled by p27(Kip1). We propose that the additional layer of protection conferred by two-tiered contact inhibition contributes to the remarkable tumor resistance of the naked mole-rat.
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              3D bioprinting of functional tissue models for personalized drug screening and in vitro disease modeling

              3D bioprinting is emerging as a promising technology for fabricating complex tissue constructs with tailored biological components and mechanical properties. Recent advances have enabled scientists to precisely position materials and cells to build functional tissue models for in vit ro drug screening and disease modeling. This review presents state-of-the-art 3D bioprinting techniques and discusses the choice of cell source and biomaterials for building functional tissue models that can be used for personalized drug screening and disease modeling. In particular, we focus on 3D-bioprinted liver models, cardiac tissues, vascularized constructs, and cancer models for their promising applications in medical research, drug discovery, toxicology, and other pre-clinical studies. Schematic diagram showing the use of 3D bioprinting to build in vitro constructs that can be used for drug testing and disease modeling.
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                Author and article information

                Contributors
                marilisa.cortesi2@unibo.it
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                31 July 2020
                31 July 2020
                2020
                : 10
                : 12976
                Affiliations
                [1 ]ISNI 0000 0004 1757 1758, GRID grid.6292.f, Department of Electrical, Electronic and Information Engineering “G. Marconi”, , University of Bologna, ; Cesena, FC Italy
                [2 ]ISNI 0000 0004 1755 9177, GRID grid.419563.c, Osteoncology and Rare Tumors Center, , Istituto Scientifico Romagnolo Per Lo Studio E La Cura Dei Tumori (IRST) IRCCS, ; Meldola, FC Italy
                [3 ]ISNI 0000 0004 1757 1758, GRID grid.6292.f, Advanced Research Center On Electronic Systems (ARCES), , University of Bologna, ; Bologna, BO Italy
                [4 ]ISNI 0000 0004 1757 1758, GRID grid.6292.f, BioEngLab, Health Science and Technology, Interdepartmental Center for Industrial Research (HST-CIRI), , University of Bologna, ; Ozzano Emilia, BO Italy
                Article
                69862
                10.1038/s41598-020-69862-7
                7395763
                32737377
                2deff9c4-60d3-4588-998f-d5b9e3e08fcb
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 24 January 2020
                : 21 July 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100009879, Regione Emilia-Romagna;
                Award ID: PG/2018/632022
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                computational models,biomedical engineering
                Uncategorized
                computational models, biomedical engineering

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