Systematic Evaluation of Gastric Tumor Cell Index and Two-Drug Combination Therapy via 3-Dimensional High-Throughput Drug Screening - Lim, Sung Hee; Sa, Jason K.; Lee, Dong Woo; Kim, Jusun; Kim, Seung Tae; Park, Se Hoon; Ku, Bosung; Park, Joon Oh; Park, Young Suk; Lim, Hoyeong; Kang, Won Ki; Nam, Do-Hyun; et al. (Frontiers in Oncology, 2019)
Tumor heterogeneity greatly limits personalised treatment of cancer. Patient-derived tumor cell (PDC) models precisely recapitulate the molecular properties and biology of the disease, making them effective preclinical tools for assessing anti-cancer drug activities. Accurately estimating tumor purity is essential for performing high-throughput drug screening (HTS). In the current study, we measured and predicted the tumor population index in PDC models for two-drug combinational strategies using an HTS system. Gastric cancer cell-lines and PDCs were subjected to multi-colour immunofluorescence analysis against EpCAM and vimentin to evaluate the tumor cell index based on EpCAM expression levels. We generated a tumor purity prediction model using five different gastric cancer cell-lines (AGS, KATO-III, MKN-45, NCI-N87, SNU-216) with fluorescence intensity-based techniques. These stage IV gastric cancer PDC models were evaluated using a micropillar/microwell chip-based HTS system. HER2/CCNE1-amplified PDCs were considerably resistant to an HER2 inhibitor, while combinational treatment consisting of an HER2 inhibitor with anti-WEE1 compound substantially suppressed tumor cell growth. Moreover, PDCs with BRCA1/2 mutations were synergistically sensitive to HER2 and PARP inhibition therapy. Finally, somatic mutations in TP53 and CDKN2A with MYC amplification rendered PDCs susceptible to the drug combination of WEE1 and HER2. Collectively, our systematic method of high-throughput drug sensitivity screening is an integral pre-clinical platform for evaluating potential two-drug combinational approaches for personalised treatment of cancer.