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. 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.

功能型精准医学（Functional Precision Medicine, FPM）旨在通过利用个体癌细胞的特定特征，为适宜患者匹配精准的治疗药物。近年来，支持高通量体外药物筛选以实现个体化治疗定制的技术，推动了FPM领域的发展。本研究针对一套整合式实验系统开展了概念验证研究，该系统将离体药物处理响应与单细胞基因表达检测结果相结合，可在单次单细胞测序实验中实现多种药物处理条件的条形码标记。我们以糖皮质激素耐药的E/R+ REH细胞系作为细胞模型，开展了药物耐药性的功能注释研究，并评估了三种不同的单细胞转录组测序（Single-Cell RNA Sequencing, scRNA-seq）方法。借助该整合式实验系统，我们证实所有scRNA-seq方法均可准确反映体系内的基因表达变化，且细胞回收率高、不同药物处理条件的标记精准。此外，我们还发现氟达拉滨（fludarabine）可引发显著的单细胞转录响应——氟达拉滨是治疗高危急性淋巴细胞白血病（Acute Lymphoblastic Leukemia, ALL）的重点关注药物。我们再次以糖皮质激素耐药的E/R+ REH细胞系作为细胞模型，开展药物耐药性的功能注释研究，并对三种单细胞转录组测序方法进行评估。本研究基于FMCA检测得到的剂量反应曲线选取了五种处理条件，采用Parse Evercode WTK、MULTI-seq以及10x Chromium Fixed RNA Profiling三种不同方法对经药物处理的细胞进行单细胞测序。我们探究了特定药物处理条件是否会对回收的单细胞的基因表达谱产生影响。