Abstract
Tumor heterogeneity greatly limits personalized 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. Accurate estimation of tumor purity is essential for performing high-throughput drug screening (HTS). In the present study, we measured and predicted the tumor population index in PDC models for two-drug combinational strategies using HTS system. Gastric cancer cell-lines and PDCs were subjected to multi-color 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. Afterwards, 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 cellular 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 personalized treatment of cancer.
Highlights
Conventional pre-clinical tools for evaluating pharmacological drug responses primarily rely on twodimensional cultured cancer cell-lines or patient-derived xenograft (PDX) models
To establish a systematic high-throughput drug screening (HTS) platform for evaluating the tumor cell index and two-drug combinational strategy in gastric cancer, we generated a library of Patient-derived tumor cell (PDC) derived from surgically resected gastric tumor specimens or ascites-derived tumor cells (Figure 1A)
Fluorescence intensity analysis showed that all five gastric cancer cell lines were marked by global expression levels of EpCAM, while normal fibroblasts exhibited upregulation of vimentin expression (Figure 1B)
Summary
Conventional pre-clinical tools for evaluating pharmacological drug responses primarily rely on twodimensional cultured cancer cell-lines or patient-derived xenograft (PDX) models. While both models have been used widely and extensively for translational cancer research, several challenges limit their direct clinical utility. Traditional cancer cell-lines may not recapitulate the unique genetic background of each patient. While PDX systems retain the genomic characteristics of the parental tumors in situ, generation of PDX models is often resource- and timeconsuming [12]. Patient-derived tumor cell (PDC) models provide unique opportunities for prospective preclinical research. We previously demonstrated that PDCs exhibit high degrees of genetic similarity compared to the parental tumors both molecularly and phenotypically [13, 14]
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