Protocol for high throughput 3D drug screening of patient derived melanoma and renal cell carcinoma

Abstract

High Throughput Screening (HTS) with 3D cell models is possible thanks to the recent progress and development in 3D cell culture technologies. Results from multiple studies have demonstrated different drug responses between 2D and 3D cell culture. It is now widely accepted that 3D cell models more accurately represent the physiologic conditions of tumors over 2D cell models. However, there is still a need for more accurate tests that are scalable and better imitate the complex conditions in living tissues. Here, we describe ultrahigh throughput 3D methods of drug response profiling in patient derived primary tumors including melanoma as well as renal cell carcinoma that were tested against the NCI oncologic set of FDA approved drugs. We also tested their autologous patient derived cancer associated fibroblasts, varied the in-vitro conditions using matrix vs matrix free methods and completed this in both 3D vs 2D rendered cancer cells. The result indicates a heterologous response to the drugs based on their genetic background, but not on their maintenance condition. Here, we present the methods and supporting results of the HTS efforts using these 3D of organoids derived from patients. This demonstrated the possibility of using patient derived 3D cells for HTS and expands on our screening capabilities for testing other types of cancer using clinically approved anti-cancer agents to find drugs for potential off label use.

Keywords: 3D cell models; HTS; Melanoma; Organoid; Patient derived organoids; Phenotypic; RCC; Renal carcinoma; Renal cell carcinoma; Scaffold free.

Figure 1.. Brightfield images of PDOrg cells in 2D and 3D format.

(A) PDOrg Melanoma and (B) RCC were grown initially in the presence of Cultrex gel to form organoids and then were adapted to 2D cell culture for cell scaling. Scale bars shown in red as 100 microns.

Figure 2.. 3D Cell Density Linearity Test.

(A) The correct cell number to be used for the assays was determined to be in the linear range of the assay. Z’ values were calculated with the different cell number tested following addition of the CellTiter-Glo® (B) Across all the assay conditions tested, the Z’ values ranged from 0.42 for the lowest cell number tested and about 0.8 for the highest cell number tested. (C) The confirmation of 3D spheroid was done by Z-stack analysis for each of the cell lines used for this study. Nuclei of cells were stained with Hoechst and mages were taken using 2-micron image slices.

Figure 3.. Concentration Response of the Pharmacological Controls.

Concentration response curve for the positive controls used for the assay. Each curve represents the mean and the standard deviation of 16 replicates. The Cells + DMSO value is plotted as a single point to demonstrate what the raw baseline value is for each tumor of CAF. Error bars are included and shown in SD.

Figure 4.. NCI Oncology Pilot Screening Data Results.

(A) The correlation plots demonstrate the activity of all the compounds in the assays. (B) Correlation plots with compounds with an % response of 25 percent or more.

Figure 5.. Concentration Response of Selective and Active Drugs vs Melanoma.

Concentration response curve for each drug is shown in pink (melanoma) or blue (CAF) and green (PDC). IC50 is shown in micromolar concentration. Each curve represents the mean and the standard deviation of 3 replicates. Error bars are included and shown in SD.

Figure 6.. Concentration Response of Selective and Active Drugs vs RCC.

Concentration response curve for each drug is shown in pink (RCC) or blue (CAF). IC50 is shown in micromolar concentration. Each curve represents the mean and the standard deviation of 3 replicates. Error bars are included and shown in SD.