Izmir Biomedicine and Genome Center, Balcova, 35330 Izmir, Turkey.
Department of Analytical Chemistry, Faculty of Pharmacy, Izmir Katip Celebi University, Cigli, 35620 Izmir, Turkey.
ACS Sens. 2023 Jul 28;8(7):2543-2555. doi: 10.1021/acssensors.3c00208. Epub 2023 Jun 20.
Functional assay platforms could identify the biophysical properties of cells and their therapeutic response to drug treatments. Despite their strong ability to assess cellular pathways, functional assays require large tissue samples, long-term cell culture, and bulk measurements. Even though such a drawback is still valid, these limitations did not hinder the interest in these platforms for their capacity to reveal drug susceptibility. Some of the limitations could be overcome with single-cell functional assays by identifying subpopulations using small sample volumes. Along this direction, in this article, we developed a high-throughput plasmonic functional assay platform to identify the growth profile of cells and their therapeutic profile under therapies using mass and growth rate statistics of individual cells. Our technology could determine populations' growth profiles using the growth rate data of multiple single cells of the same population. Evaluating spectral variations based on the plasmonic diffraction field intensity images in real time, we could simultaneously monitor the mass change for the cells within the field of view of a camera with the capacity of > ∼500 cells/h scanning rate. Our technology could determine the therapeutic profile of cells under cancer drugs within few hours, while the classical techniques require days to show reduction in viability due to antitumor effects. The platform could reveal the heterogeneity within the therapeutic profile of populations and determine subpopulations showing resistance to drug therapies. As a proof-of-principle demonstration, we studied the growth profile of MCF-7 cells and their therapeutic behavior to standard-of-care drugs that have antitumor effects as shown in the literature, including difluoromethylornithine (DFMO), 5-fluorouracil (5-FU), paclitaxel (PTX), and doxorubicin (Dox). We successfully demonstrated the resistant behavior of an MCF-7 variant that could survive in the presence of DFMO. More importantly, we could precisely identify synergic and antagonistic effects of drug combinations based on the order of use in cancer therapy. Rapidly assessing the therapeutic profile of cancer cells, our plasmonic functional assay platform could be used to reveal personalized drug therapies for cancer patients.
功能测定平台可以鉴定细胞的生物物理特性及其对药物治疗的反应。尽管它们具有评估细胞通路的强大能力，但功能测定需要大量的组织样本、长期的细胞培养和批量测量。尽管存在这样的缺点，但这些局限性并没有阻碍人们对这些平台的兴趣，因为它们能够揭示药物敏感性。通过使用单细胞功能测定来鉴定小样本量的亚群，可以克服一些局限性。沿着这个方向，在本文中，我们开发了一种高通量的等离子体功能测定平台，通过个体细胞的质量和生长速率统计数据来鉴定细胞的生长曲线和治疗曲线。我们的技术可以通过同一群体中多个单细胞的生长速率数据来确定群体的生长曲线。通过实时评估基于等离子体衍射场强度图像的光谱变化，我们可以同时监测相机视场内细胞的质量变化，其扫描速率> ∼500 个细胞/小时。我们的技术可以在几个小时内确定细胞在癌症药物下的治疗曲线，而传统技术需要几天时间才能显示由于抗肿瘤作用导致的存活率降低。该平台可以揭示群体治疗曲线的异质性，并确定对药物治疗有抗性的亚群。作为原理验证演示，我们研究了 MCF-7 细胞的生长曲线及其对标准治疗药物的治疗行为，这些药物具有抗肿瘤作用，如文献中所述，包括二氟甲基鸟氨酸 (DFMO)、5-氟尿嘧啶 (5-FU)、紫杉醇 (PTX) 和阿霉素 (Dox)。我们成功地证明了能够在 DFMO 存在下存活的 MCF-7 变体的耐药行为。更重要的是，我们可以根据癌症治疗中的使用顺序，精确地确定药物组合的协同和拮抗作用。快速评估癌细胞的治疗曲线，我们的等离子体功能测定平台可以用于揭示癌症患者的个性化药物治疗。
