Literature DB >> 28932842

Microfluidic isolation of platelet-covered circulating tumor cells.

Xiaocheng Jiang1, Keith H K Wong, Aimal H Khankhel, Mahnaz Zeinali, Eduardo Reategui, Matthew J Phillips, Xi Luo, Nicola Aceto, Fabio Fachin, Anh N Hoang, Wooseok Kim, Annie E Jensen, Lecia V Sequist, Shyamala Maheswaran, Daniel A Haber, Shannon L Stott, Mehmet Toner.   

Abstract

The interplay between platelets and tumor cells is known to play important roles in metastasis by enhancing tumor cell survival, tumor-vascular interactions, and escape from immune surveillance. However, platelet-covered circulating tumor cells (CTC) are extremely difficult to isolate due to masking or downregulation of surface epitopes. Here we describe a microfluidic platform that takes advantage of the satellite platelets on the surface of these "stealth" CTCs as a ubiquitous surface marker for isolation. Compared to conventional CTC enrichment techniques which rely on known surface markers expressed by tumor cells, platelet-targeted isolation is generally applicable to CTCs of both epithelial and mesenchymal phenotypes. Our approach first depletes unbound, free platelets by means of hydrodynamic size-based sorting, followed by immunoaffinity-based capture of platelet-covered CTCs using a herringbone micromixing device. This method enabled the reliable isolation of CTCs from 66% of lung and 60% of breast cancer (both epithelial) patient samples, as well as in 83% of melanoma (mesenchymal) samples. Interestingly, we observed special populations of CTCs that were extensively covered by platelets, as well as CTC-leukocyte clusters. Because these cloaked CTCs often escape conventional positive and negative isolation mechanisms, further characterization of these cells may uncover important yet overlooked biological information in blood-borne metastasis and cancer immunology.

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Year:  2017        PMID: 28932842      PMCID: PMC5690580          DOI: 10.1039/c7lc00654c

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  36 in total

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