Quantitative profiling of integrin αvβ3 on single cells with quantum dot labeling to reveal the phenotypic heterogeneity of glioblastoma. Issue 39 (27th September 2019)

• Record Type: Journal Article
• Authors: Wang, Tingting; Li, Guang; Wang, Dianbing; Li, Feng; Men, Dong; Hu, Tao; Xi, Yan; Zhang, Xian-En
• Is Part Of: Nanoscale. Volume 11:Issue 39(2019)
• Page Start: 18224
• Page End: 18231
• Publication Date: 2019-09-27
• Subjects: Nanoscience -- Periodicals; Nanotechnology -- Periodicals; 620.505
• DOI: 10.1039/c9nr01105f
• Languages: English
• ISSNs: 2040-3364

Abstract

Abstract : The distribution, localization and density of individual molecules ( e.g. drug-specific receptors) on single cells can offer profound information about cell phenotypes. Abstract : The distribution, localization and density of individual molecules ( e.g. drug-specific receptors) on single cells can offer profound information about cell phenotypes. Profiling this information is a new research direction within the field of single cell biology, but it remains technically challenging. Through the combined use of quantum dot labeling, structured illumination microscopy (SIM) and computer-aided local surface reconstruction, we acquired a 3D imaging map of a drug target molecule, integrin αvβ3, on glioblastoma cells at the single cell level. The results revealed that integrin αvβ3 exhibits discrete distribution on the surface of glioblastoma cells, with its density differing significantly among cell lines. The density is illustrated as the approximate number of target molecules per μm 2 on the irregular cell surface, ranging from 0 to 1.6. Functional studies revealed that the sensitivity of glioblastoma cells to inhibitor molecules depends on the density of the target molecules. After inhibitor treatment, the viability and invasion ability of different glioblastoma cells were highly correlated with the density of integrin αvβ3 on their surfaces. This study not only provides a novel protocol for the quantitative analysis of surface proteins from irregular single cells, but also offers a clue for understanding the heterogeneity of tumor cells on the basis of molecular phenotypes. Thus, this work has potential significance in guiding targeted therapies for cancers.