High-Throughput Platform for Patient-Derived, Small Cell Number, Three-Dimensional Ovarian Cancer Spheroids
Abstract
Ovarian cancer metastasis involves growth of ovarian cancer cells shed from primary tumor as multicellular spheroidal aggregates within ascites fluid. Multicellular tumor spheroids are physiologically significant 3D in vitro models for preclinical drug screens. Conventional hanging drop spheroid cultures utilize high number of starting cells, and are tedious for long-term maintenance. The objective of our study was two fold: A) to generate stable, uniform multicellular spheroids using very small number of ovarian cancer cells in a novel 384-well hanging drop platform and to B) establish a high throughput 3D platform for preclinical studies. Methods: We used non-serous and serous ovarian cancer cells as well as patient ascites to demonstrate stable incorporation of as few as 10 cells into a single spheroid. Spheroids had uniform geometry, and their projected spheroid areas varied as a function of initial cell seeding density. Cell-cell interaction was detected using cytoskeletal actin staining. Nuclei counterstaining indicated compaction of cells forming tightly packed spheroids, with demarcated boundaries. Cells within spheroids demonstrated high viability of greater than 85%. Spheroids remained 80% viable in response to 50 micrometers cisplatin, whereas 2D monolayer cultures were only 30% viable, suggesting multicellular ovarian cancer spheroids are inherently chemoresistant. Conclusions: Ovarian cancer spheroids can be generated from limited cell numbers in high throughput hanging drops with high viability. 3D spheroids demonstrate therapeutic resistance relative to cells in 2D culture. Stable incorporation of low cell numbers is advantageous when translating this research to rare populations of cancer stem-like cells isolated from patient samples. Our platform is applicable to understanding ovarian cancer biology and for carrying out preclinical drug sensitivity assays.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2014
- Accession Number
- ADA619723
Entities
People
- Geeta Mehta
Organizations
- University of Michigan