Methods to Evaluate Cell Growth, Viability, and Response to Treatment in a Tissue Engineered Breast Cancer Model. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Goliwas, Kayla; Richter, Jillian; Pruitt, Hawley; Araysi, Lita; Anderson, Nicholas; Samant, Rajeev; Lobo-Ruppert, Susan; Berry, Joel; Frost, Andra
• Is Part Of: Scientific reports. Volume 7:Issue 1(2017)
• Page Start: 1
• Page End: 14
• Publication Date: 2017-12
• Subjects: Natural history -- Research -- Periodicals; Biology -- Research -- Periodicals; Physical sciences -- Research -- Periodicals; Earth sciences -- Research -- Periodicals; Environmental sciences -- Research -- Periodicals; 502.85
• DOI: 10.1038/s41598-017-14326-8
• Languages: English
• ISSNs: 2045-2322

Abstract

Abstract The use ofin vitro, engineered surrogates in the field of cancer research is of interest for studies involving mechanisms of growth and metastasis, and response to therapeutic intervention. While biomimetic surrogates better model human disease, their complex composition and dimensionality make them challenging to evaluate in a real-time manner. This feature has hindered the broad implementation of these models, particularly in drug discovery. Herein, several methods and approaches for the real-time, non-invasive analysis of cell growth and response to treatment in tissue-engineered, three-dimensional models of breast cancer are presented. The tissue-engineered surrogates used to demonstrate these methods consist of breast cancer epithelial cells and fibroblasts within a three dimensional volume of extracellular matrix and are continuously perfused with nutrients via a bioreactor system. Growth of the surrogates over time was measured using opticalin vivo (IVIS) imaging. Morphologic changes in specific cell populations were evaluated by multi-photon confocal microscopy. Response of the surrogates to treatment with paclitaxel was measured by optical imaging and by analysis of lactate dehydrogenase and caspase-cleaved cytokeratin 18 in the perfused medium. Each method described can be repeatedly performed during culture, allowing for real-time, longitudinal analysis of cell populations within engineered tumor models.