Ovarian Cancer Patient-Derived Organoid Models for Pre-Clinical Drug Testing

Abstract

Ovarian cancer is a fatal gynecologic cancer and the fifth leading cause of cancer death among women in the United States. Developing new drug treatments is crucial to advancing healthcare and improving patient outcomes. Organoids are in-vitro three-dimensional multicellular miniature organs. Patient-derived organoid (PDO) models of ovarian cancer may be optimal for drug screening because they more accurately recapitulate tissues of interest than two-dimensional cell culture models and are inexpensive compared to patient-derived xenografts. In addition, ovarian cancer PDOs mimic the variable tumor microenvironment and genetic background typically observed in ovarian cancer. Here, a method is described that can be used to test conventional and novel drugs on PDOs derived from ovarian cancer tissue and ascites. A luminescence-based adenosine triphosphate (ATP) assay is used to measure viability, growth rate, and drug sensitivity. Drug screens in PDOs can be completed in 7-10 days, depending on the rate of organoid formation and drug treatments.

Figure 1:. Patient-derived organoids before drug screening.

(A) Experimental outline for PDO drug screen. Given the doubling time of the PDO line and the drug exposure time, the experimental plan may need to be adjusted. (B) Representative brightfield images (40x) of two ovarian cancer PDO lines (#1 and #2). Scale bar = 50 μm. Abbreviations: PDO = patient-derived organoids.

Figure 2:. Representative results of ovarian cancer PDO following carboplatin treatment.

(A) Two PDO lines were treated with increasing concentrations of carboplatin for seven days. The X-axis shows carboplatin concentration; the Y-axis displays the % of live cells normalized to control organoids (no carboplatin). Assays were completed in triplicate with two biological replicates. The error bars denote the standard deviation. (B) GR-value graph representing the logarithmic carboplatin concentration (x-Axis) and the GR value (Y-Axis). These values were generated in the online GR calculator. The error bars indicate the standard deviation.