Abstract P5-02-02: Development of automated 3D high-throughput drug screening platform for patient-derived breast cancer organoids
Authors: Kim Jungeun , Kim Hoe Suk , Kim Ga Yeon , Park Kyung hyeun , Ryu Seung yeon , Lee Sangeun , Lee Dong Woo , Ku Bosung , Lee Han-Byoel , Han Wonshik 
Published: March 2022

Abstract
Background Patient-derived cancer organoids, which reliably conserve original features of tumors, are emerging as an excellent model for predicting therapy response and drug screening. Developing optimized 3D high-throughput drug screening platform to establish patient-derived cancer organoids and simultaneously perform drug screening is essential for personalized medicine. Methods We established normal breast organoids (n=4) and breast cancer organoids (n=10) from 20 fresh surgical specimen (normal 7, tumor 13 cases). A number (500-2000) of normal and cancer cells were automatically dispensed with the ASFA™ Spotter ST and organoids were generated by hydrogel hanging-drop culture on Cellvitro™ Pillar platform (Medical & Bio Decision, South Korea). Organoids were subjected to drug screening for 17 anticancer drugs including chemoreagents and targeted drugs in the 3D HTS system. Drug sensitivity was tested in triplicate in different concentration ranges for 5 days. Drug cytotoxic effect was assessed by calcein AM staining. Acquisition and analysis of high-content 3D organoid images were peformed using ASFA™ SCANNER (Medical & Bio Decision, South Korea). The IC50 for each drug was calculated by a sigmoidal dose-response curve, using the GraphPad Prism 9 program. We analyzed a drug response index (DRI) using a prediction alogorithm to evalute drug sensitivity (DRI&lt;-0.5) and resistance (DRI&gt;0.5). Results We summarized the DRI value of patient-derived breast organoids of 7 drugs (Table 1). 6 tumor organoids (2T, 6T, 8T, 10T, 13T, 15T) showed high sensitivity to Docetaxel, Doxorubicin, Paclitaxel, and Gemcitabin while 4 tumor organoids (1T, 9T, 14T, 16T) were less sensitive and resistant. 2 tumor organoids (10T, 16T) were sensitive to Tamoxifen and 2 tumor organoids (6T, 8T) show high sensitivity to palbociclib and erlotinib. Normal organoids show less sensitivity and resistance to chemotherapeutic drugs.
Drug response index &gt;0.5 : resistancy top 30%, Drug response index &lt;-0.5 : sensitivity top 30%. Conclusions Herein, we developed the hydrogel hanging-drop culture on Cellvitro™ Pillar platform for easily and rapidly high-throughput drug screening in patient-derived organoids using a small number of cells by testing clinically actionable drugs at different concentrations. There were different drug response indeces for each individual organoids to chemoreagents and targeted drugs. We anticipate that 3D high-throughput drug screenings platform based on patient-derived organoids can provide the information to predict drug response and allow for finding more appropriate therapy for individual patients.
Table 1.DRI values of patient-derived breast organoids of 7 drugs.Patient No.Tumor/NormalDocetaxelPaclitaxelDoxorubicinTamoxifenGemcitabinePalbociclibErlotinib1TTumor1.051.261.080.060.590.26-2TTumor-0.64-0.72-0.60-0.08-0.79--6TTumor-0.98-0.99-2.330.00-1.44-2.31-1.608TTumor-0.32-0.50-0.250.64-1.07-1.47-0.669TTumor1.050.980.610.870.430.610.4410TTumor-0.84-0.77-0.78-1.680.790.610.0913TTumor-0.87-0.430.560.70-0.510.611.1714TTumor0.861.261.180.481.81--15TTumor-1.59-1.45-1.41--0.71-0.13-16TTumor1.051.261.18-1.70-1.22-2NNormal1.051.260.650.741.810.610.7810NNormal1.05-0.910.810.870.880.610.084NNormal-0.31-0.25-0.530.25-0.190.61-1.575NNormal1.051.130.380.75-0.630.610.10
Citation Format: Jungeun Kim, Hoe Suk Kim, Ga Yeon Kim, Kyung hyeun Park, Seung yeon Ryu, Sangeun Lee, Dong Woo Lee, Bosung Ku, Han-Byoel Lee, Wonshik Han. Development of automated 3D high-throughput drug screening platform for patient-derived breast cancer organoids [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-02-02.