Functional drug testing of pediatric acute lymphocytic leukemia cells by single-cell transcriptome sequencing for mapping cellular drug response
Functional precision medicine (FPM) aims to match the right patients to the right drugs by using specific features of the individual's cancer cells. Recently, FPM has been propelled by technologies that enable high throughput ex vivo drug profiling to tailor treatments for individual patients. Here, we present a proof of concept study for an integrated experimental system that incorporates ex vivo treatment response with a single-cell gene expression output that enables barcoding of several drug conditions in one single-cell sequencing experiment. We perform functional annotation of drug resistance using the glucocorticoid-resistant E/R+ REH cells as a cellular model and evaluate three different approaches for single-cell transcriptome sequencing (scRNA-seq). Using this integrated system, we show that all scRNA-seq methods accurately reflected gene expression changes in the system, with high cell recovery and accurate tagging of the different drug conditions. Furthermore, we identified a substantial single-cell transcriptional response to fludarabine, a drug of particular interest for treatment of high-risk ALL. Overall design: We perform functional annotation of drug resistance using the glucocorticoid-resistant E/R+ REH cells as a cellular model and evaluate three different approaches for single-cell transcriptome sequencing (scRNA-seq). Five conditions were chosen based on dose response curves measured by FMCA. Single-cell sequencing of the treated cells was carried out using three different approaches, Parse Evercode WTK, MULTI-seq and 10x Chromium Fixed RNA Profiling. We investigated whether specific drug conditions influenced the gene expression profiles of the single cells recovered.