Single-Cell Codetection of Metabolic Activity, Intracellular Functional Proteins, and Genetic Mutations from Rare Circulating Tumor Cells

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• 作者：Yu Zhang ; Yin Tang ; Shuai Sun ; Zhihua Wang ; Wenjun Wu ; Xiaodong Zhao ; Daniel M. Czajkowsky ; Yan Li ; Jianhui Tian ; Ling Xu ; Wei Wei ; Yuliang Deng ; Qihui Shi
• 刊名：Analytical Chemistry
• 出版年：2015
• 出版时间：October 6, 2015
• 年：2015
• 卷：87
• 期：19
• 页码：9761-9768
• 全文大小：427K
• ISSN：1520-6882

文摘

The high glucose uptake and activation of oncogenic signaling pathways in cancer cells has long made these features, together with the mutational spectrum, prime diagnostic targets of circulating tumor cells (CTCs). Further, an ability to characterize these properties at a single cell resolution is widely believed to be essential, as the known extensive heterogeneity in CTCs can obscure important correlations in data obtained from cell population-based methods. However, to date, it has not been possible to quantitatively measure metabolic, proteomic, and genetic data from a single CTC. Here we report a microchip-based approach that allows for the codetection of glucose uptake, intracellular functional proteins, and genetic mutations at the single-cell level from rare tumor cells. The microchip contains thousands of nanoliter grooves (nanowells) that isolate individual CTCs and allow for the assessment of their glucose uptake via imaging of a fluorescent glucose analog, quantification of a panel of intracellular signaling proteins using a miniaturized antibody barcode microarray, and retrieval of the individual cell nuclei for subsequent off-chip genome amplification and sequencing. This approach integrates molecular-scale information on the metabolic, proteomic, and genetic status of single cells and permits the inference of associations between genetic signatures, energy consumption, and phosphoproteins oncogenic signaling activities in CTCs isolated from blood samples of patients. Importantly, this microchip chip-based approach achieves this multidimensional molecular analysis with minimal cell loss (<20%), which is the bottleneck of the rare cell analysis.