The gene-regulatory dynamics governing drug responses in cancer are yet to be fully understood. Here, we report a pipeline capable of producing high-throughput pharmacotranscriptomic profiling through live-cell barcoding using antibody–oligonucleotide conjugates. This pipeline combines drug screening with 96-plex single-cell RNA sequencing. We show the potential of this approach by exploring the heterogeneous transcriptional landscape of primary high-grade serous ovarian cancer (HGSOC) cells after treatment with 45 drugs, with 13 distinct classes of mechanisms of action. A subset of phosphatidylinositol 3-OH kinase (PI3K), protein kinase B (AKT) and mammalian target of rapamycin (mTOR) inhibitors induced the activation of receptor tyrosine kinases, such as the epithelial growth factor receptor (EGFR), and this was mediated by the upregulation of caveolin 1 (CAV1). This drug resistance feedback loop could be mitigated by the synergistic action of agents targeting PI3K–AKT–mTOR and EGFR for HGSOC with CAV1 and EGFR expression. Using this workflow could enable the personalized testing of patient-derived tumor samples at single-cell resolution.

控制癌症药物反应的基因调控动力学尚不完全清楚。在这里，我们报道了一种能够通过使用抗体-寡核苷酸偶联物的活细胞条形码产生高通量药物转录组学分析的管道。该流程将药物筛选与 96 重单细胞 RNA 测序相结合。我们通过探索用 45 种药物治疗后原代高级别浆液性卵巢癌 （HGSOC） 细胞的异质性转录景观来展示这种方法的潜力，具有 13 种不同的作用机制。磷脂酰肌醇 3-OH 激酶 （PI3K）、蛋白激酶 B （AKT） 和哺乳动物雷帕霉素靶标 （mTOR） 抑制剂的一个亚群诱导受体酪氨酸激酶的激活，例如上皮生长因子受体 （EGFR），这是由小窝蛋白 1 （CAV1） 的上调介导的。这种耐药反馈回路可以通过靶向 PI3K-AKT-mTOR 和 EGFR 的药物对具有 CAV1 和 EGFR 表达的 HGSOC 的协同作用来缓解。使用该工作流程可以实现以单细胞分辨率对患者来源的肿瘤样本进行个性化检测。