Supporting data for "3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments"
2020-05-29
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2017-01-01
2018-12-01
2018-12-01
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2019-01-21
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Title
Supporting data for "3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments"
Published Date
2020-05-29
Author Contact
McAlpine, Michael C
mcalpine@umn.edu
mcalpine@umn.edu
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Dataset
Experimental Data
Programming Software Code
Experimental Data
Programming Software Code
Abstract
The data set includes the experimental data and the corresponding code files for " 3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments", Fanben Meng, Carolyn M Meyer, Daeha Joung, Daniel A Vallera, Michael C McAlpine, Angela PanoskaltsisāMortari, Adv. Mater. 2019, 31 (10), 1806899. The development of 3D in vitro models capable of recapitulating native tumor microenvironments could improve the translatability of potential anticancer drugs and treatments. Here, 3D bioprinting techniques are used to build tumor constructs via precise placement of living cells, functional biomaterials, and programmable release capsules. This enables the spatiotemporal control of signaling molecular gradients, thereby dynamically modulating cellular behaviors at a local level. Vascularized tumor models are created to mimic key steps of cancer dissemination (invasion, intravasation, and angiogenesis), based on guided migration of tumor cells and endothelial cells in the context of stromal cells and growth factors. The utility of the metastatic models for drug screening is demonstrated by evaluating the anticancer efficacy of immunotoxins. These 3D vascularized tumor tissues provide a proof-of-concept platform to i) fundamentally explore the molecular mechanisms of tumor progression and metastasis, and ii) preclinically identify therapeutic agents and screen anticancer drugs.
Description
A full description of the data set is included in the file "Readme_Meng_Tumor_Model.txt".
Referenced by
Meng, F., Meyer, C., Joung, D., Vallera, D., McAlpine, M., & PanoskaltsisāMortari, A. (2019). 3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments. Advanced Materials, 31(10),
https://doi.org/10.1002/adma.201806899
https://doi.org/10.1002/adma.201806899
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Funding information
National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (Award No. 1R21EB022830)
A seed grant from the UMN Institute for Engineering in Medicine
A Pilot Project award from the UMN Prostate and Urologic Cancer Translational Workgroup
National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (Award No. 1DP2EB020537)
Cancer Bioengineering Fellowship, UMN Physical Sciences in Oncology Center (PSOC)
A seed grant from the UMN Institute for Engineering in Medicine
A Pilot Project award from the UMN Prostate and Urologic Cancer Translational Workgroup
National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (Award No. 1DP2EB020537)
Cancer Bioengineering Fellowship, UMN Physical Sciences in Oncology Center (PSOC)
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Suggested citation
Meng, Fanben; Meyer, Carolyn M; Joung, Daeha; Vallera, Daniel A; McAlpine, Michael C; Panoskaltsis-Mortari, Angela. (2020). Supporting data for "3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments". Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/xxnh-v194.
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Data 1_Supporting Data for Growth Factor Release.zip
Data 1_Supporting Data for Growth Factor Release
(50.09 KB)
Data 2_Supporting Data for Guided Tumor Cell Migration.zip
Data 2_Supporting Data for Guided Tumor Cell Migration
(179.36 KB)
Data 3_Supporting Data for Cell Viability.zip
Data 3_Supporting Data for Cell Viability
(23.71 KB)
Data 4_Supporting Data for qPCR.zip
Data 4_Supporting Data for qPCR
(57.32 KB)
Data 5_Supporting Data for Drug Tests.zip
Data 5_Supporting Data for Drug Tests
(83.36 KB)
Data 6_Printing Code & Chamber Design - Fisnar.zip
Printing Code & Chamber Design
(113.03 KB)
Readme_Meng_Tumor_Model.txt
Description of data
(10.17 KB)
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