Abstract 1917: High-throughput evaluation of treatment response in patient-derived glioma stem cell models

Abstract

Abstract Although significant progresses in molecular oncology are being made using conventional cell lines, most therapies still fail in phase III clinical trials. Patient-derived models are being used more frequently as they are more faithfully representing the genomic features of primary tumors. However, one by one test of each model from large biobanks is extremely economy and time consuming. In this study, each of a panel of patient-derived glioblastoma stem cell (GSC) models was uniquely tagged by a lentiviral Cas9D10A and paired-gRNA targetable unique reporter (CAPTURE) barcoding system. Barcoded GSCs were then pooled evenly and following by radiation treatment (RT) in vitro. Amplicon sequencing was employed to count the barcodes distribution, which represent the relative cell number. The results showed that this approach faithfully identified the RT resistant GSCs from a mixing pool when comparing to the results from canonical clonogenic assay. In addition, a fluorescence marker will be switched by delivery of corresponding barcodes targeting CRISPR so that we can re-isolate interested cell models from the treated pool for investigating the treatment sensitivity and resistance mechanism. This study will provide a robust approach for therapeutic discovery take advantage of patient-derived models from large biobanks. Citation Format: Ze-yan Zhang, Yingwen Ding, Ravesanker Ezhilarasan, Jie Yang, Lihong Long, Lawrence Bronk, Qianghu Wang, Erik P. Sulman. High-throughput evaluation of treatment response in patient-derived glioma stem cell models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1917.