Patient-Derived Osteosarcoma Organoid Invasion and Treatment Response in Tuneable Matrices

Luke Hipwood's research data from figshare, last updated June 2026, investigates osteosarcoma organoid behavior. The dataset likely contains measurements from organoids embedded in photocrosslinkable matrices with tuneable stiffness and composition, such as GelMA and LungMA. It includes image-based segmentation results for core and invasive compartments under chemotherapy treatment.

Use Cases

• Modeling the effect of matrix stiffness on cancer cell invasion based on the described soft (1 kPa) and stiff (4 kPa) conditions.
• Comparing chemoresistance in different extracellular matrix environments based on the described response to doxorubicin in GelMA versus LungMA.
• Analyzing the divergence between metabolic viability and functional invasion using the described image-based segmentation of core and invasive compartments.

Strengths

• Data is derived from patient-specific osteosarcoma cells, providing a patient-derived model.
• Matrices have independently tuneable stiffness (approximately 1 kPa and 4 kPa) and composition (collagen-rich GelMA and basement membrane protein-enriched LungMA).
• Released under a permissive CC-BY-4.0 license, allowing for broad reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The primary data file is a 513.6 KB DOCX document, which is a very small and non-standard format for structured data.

Provenance

Source

figshare, author Luke Hipwood.

Collection Method

Experimental data from assembling patient-derived osteosarcoma cells into organoids embedded in photocrosslinkable extracellular matrices.

Freshness

Last updated 2026-06-02 05:39:46; freshness should be verified.