Plasmonic functional assay platform determines the therapeutic profile of cancer cells

Abstract

Functional assay platforms could identify the biophysicalpropertiesof cells and their therapeutic response to drug treatments. Despitetheir strong ability to assess cellular pathways, functional assaysrequire large tissue samples, long-term cell culture, and bulk measurements.Even though such a drawback is still valid, these limitations didnot hinder the interest in these platforms for their capacity to revealdrug susceptibility. Some of the limitations could be overcome withsingle-cell functional assays by identifying subpopulations usingsmall sample volumes. Along this direction, in this article, we developeda high-throughput plasmonic functional assay platform to identifythe growth profile of cells and their therapeutic profile under therapiesusing mass and growth rate statistics of individual cells. Our technologycould determine populations' growth profiles using the growthrate data of multiple single cells of the same population. Evaluatingspectral variations based on the plasmonic diffraction field intensityimages in real time, we could simultaneously monitor the mass changefor the cells within the field of view of a camera with the capacityof > & SIM;500 cells/h scanning rate. Our technology could determinethe therapeutic profile of cells under cancer drugs within few hours,while the classical techniques require days to show reduction in viabilitydue to antitumor effects. The platform could reveal the heterogeneitywithin the therapeutic profile of populations and determine subpopulationsshowing resistance to drug therapies. As a proof-of-principle demonstration,we studied the growth profile of MCF-7 cells and their therapeuticbehavior to standard-of-care drugs that have antitumor effects asshown in the literature, including difluoromethylornithine (DFMO),5-fluorouracil (5-FU), paclitaxel (PTX), and doxorubicin (Dox). Wesuccessfully demonstrated the resistant behavior of an MCF-7 variantthat could survive in the presence of DFMO. More importantly, we couldprecisely identify synergic and antagonistic effects of drug combinationsbased on the order of use in cancer therapy. Rapidly assessing thetherapeutic profile of cancer cells, our plasmonic functional assayplatform could be used to reveal personalized drug therapies for cancerpatients.