AI Article Synopsis

  • Researchers are exploring 3D tumor models made with an elastic polymer to evaluate cancer drugs, aiming to reduce reliance on rodent models in drug discovery.
  • A 3D scaffold was created using patient-derived cells from low-grade serous ovarian cancer and subjected to long-term drug testing, showing similar drug responses to those seen in mouse models.
  • The study concludes that these 3D models can effectively replicate tumor behavior, making them a promising alternative for long-term drug evaluations in cancer research.

Article Abstract

Background: Long-term drug evaluation heavily relies upon rodent models. Drug discovery methods to reduce animal models in oncology may include three-dimensional (3D) cellular systems that take into account tumor microenvironment (TME) cell types and biomechanical properties.

Methods: In this study we reconstructed a 3D tumor using an elastic polymer (acrylate-endcapped urethane-based poly(ethylene glycol) (AUPPEG)) with clinical relevant stiffness. Single cell suspensions from low-grade serous ovarian cancer (LGSOC) patient-derived early passage cultures of cancer cells and cancer-associated fibroblasts (CAF) embedded in a collagen gel were introduced to the AUPPEG scaffold. After self-organization in to a 3D tumor, this model was evaluated by a long-term (> 40 days) exposure to a drug combination of MEK and HSP90 inhibitors. The drug-response results from this long-term in vitro model are compared with drug responses in an orthotopic LGSOC xenograft mouse model.

Results: The in vitro 3D scaffold LGSOC model mimics the growth ratio and spatial organization of the LGSOC. The AUPPEG scaffold approach allows to test new targeted treatments and monitor long-term drug responses. The results correlate with those of the orthotopic LGSOC xenograft mouse model.

Conclusions: The mechanically-tunable scaffolds colonized by a three-dimensional LGSOC allow long-term drug evaluation and can be considered as a valid alternative to reduce, replace and refine animal models in drug discovery.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583378PMC
http://dx.doi.org/10.1186/s40824-023-00441-3DOI Listing

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