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A Clinical Genomics-Guided Prioritizing Strategy Enables Selecting Proper Cancer Cell Lines for Biomedical Research
Xin Shao1, Yi Wang1, Xiaoyan Lu1
1Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Abstract:
Selecting appropriate cell lines to represent a disease is crucial for the success of biomedical research, because the usage of less relevant cell lines could deliver misleading results. However, systematic guidance on cell line selection is unavailable. Here we developed a clinical Genomics-guided Prioritizing Strategy for Cancer Cell Lines (CCL-cGPS) and help to guide this process. Statistical analyses revealed CCL-cGPS selected cell lines were among the most appropriate models. Moreover, we observed a linear correlation between the drug response and CCL-cGPS score of cell lines for breast and thyroid cancers. Using RT4 cells selected by CCL-GPS, we identified mebendazole and digitoxin as candidate drugs against bladder cancer and validate their promising anticancer effect through in vitro and in vivo experiments. Additionally, a web tool was developed. In conclusion, CCL-cGPS bridges the gap between tumors and cell lines, presenting a helpful guide to select the most suitable cell line models.
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