Cellular characterization dataset aimed to quantify cancer cell extravasation in a 3D hydrogel-based microfluidic model
The cell characterization dataset contains quantitative measurements designed to assess and compare the extravasation behavior of different colorectal cancer cell lines (HT29 and SW620) within hydrogel-based 3D microfluidic models using OrganoPlate platform. The purpose of this dataset is to quantif...
| Autores: | , , |
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| Tipo de recurso: | conjunto de datos |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consorci de Serveis Universitaris de Catalunya (CSUC) |
| Repositorio: | CORA.Repositori de Dades de Recerca |
| OAI Identifier: | oai:dnet:cora.rdr____::743f68dad6f17c2d78773dbd2af90478 |
| Acceso en línea: | https://doi.org/10.34810/DATA2658 |
| Access Level: | acceso abierto |
| Palabra clave: | Medicine, Health and Life Sciences Cell Line Authentication Colorectal Neoplasms Microphysiological Systems |
| Sumario: | The cell characterization dataset contains quantitative measurements designed to assess and compare the extravasation behavior of different colorectal cancer cell lines (HT29 and SW620) within hydrogel-based 3D microfluidic models using OrganoPlate platform. The purpose of this dataset is to quantify how efficiently and to what extent cancer cells migrate across an endothelial barrier into the surrounding extracellular matrix over time, thereby modeling key steps of the metastatic process in vitro. The data capture multiple experimental time points (24, 48, and 72 hours) for each cell line and include numerical outputs such as total and migrated cell counts, migration percentages, and average migration distances. These measurements are complemented by image-based parameters reflecting cell distribution across the top, ECM, and bottom channels, providing spatial context to migration dynamics. The dataset’s nature is quantitative and image-derived, reflecting systematic microscopic analyses used to calculate cellular migration ratios and distances in standardized multi-lane microfluidic environments. In scope, the data encompass comparative assessments between cancer cell lines with different metastatic potentials, across multiple time points and replicates, enabling temporal and phenotypic characterization of extravasation process. Overall, the dataset serves as a quantitative resource for evaluating cancer cell invasion and barrier traversal in a biomimetic, hydrogel-based 3D flow model, supporting translational studies in tumor biology, metastasis, and microphysiological system optimization. |
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