Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA.
Department of Radiology, Stanford University, Stanford, CA 94305, USA.
Sci Adv. 2022 Sep 16;8(37):eabn6550. doi: 10.1126/sciadv.abn6550.
Assessing the efficacy of cancer therapeutics in mouse models is a critical step in treatment development. However, low-resolution measurement tools and small sample sizes make determining drug efficacy in vivo a difficult and time-intensive task. Here, we present a commercially scalable wearable electronic strain sensor that automates the in vivo testing of cancer therapeutics by continuously monitoring the micrometer-scale progression or regression of subcutaneously implanted tumors at the minute time scale. In two in vivo cancer mouse models, our sensor discerned differences in tumor volume dynamics between drug- and vehicle-treated tumors within 5 hours following therapy initiation. These short-term regression measurements were validated through histology, and caliper and bioluminescence measurements taken over weeklong treatment periods demonstrated the correlation with longer-term treatment response. We anticipate that real-time tumor regression datasets could help expedite and automate the process of screening cancer therapies in vivo.
评估癌症治疗药物在小鼠模型中的疗效是治疗开发的关键步骤。然而，低分辨率的测量工具和小样本量使得在体内确定药物疗效成为一项困难且耗时的任务。在这里，我们提出了一种商业上可扩展的可穿戴电子应变传感器，通过连续监测皮下植入肿瘤的微米级进展或消退，可以自动进行癌症治疗药物的体内测试，时间分辨率达到分钟级。在两种体内癌症小鼠模型中，我们的传感器在治疗开始后 5 小时内就能区分药物治疗和载体治疗肿瘤的肿瘤体积动力学差异。通过组织学和卡尺以及生物发光测量对长达一周的治疗期间进行验证，证明了与长期治疗反应的相关性。我们预计，实时肿瘤消退数据集可以帮助加快和自动化体内癌症治疗药物的筛选过程。
