产品号 #19657
直接从全血中通过免疫磁珠分选循环肿瘤细胞
概述
使用 EasySep™ Direct 人CTC富集试剂盒，可通过免疫磁珠负选，简便高效地从人全血样本中直接分选出高纯度的人循环肿瘤细胞（CTCs）。EasySep™ 技术结合了单克隆抗体的特异性和无柱磁选系统的简便性，在过去 20 多年中被广泛应用于发表的科学研究中。
在此 EasySep™ 负选过程中，非目标细胞会被抗体复合物和称为 EasySep™ Direct
RapidSpheres™ 的磁珠标记。表达以下标志物的非目标细胞将被去除：CD2、CD14、CD16、CD19、CD45、CD61 和 CD66b。通过EasySep™磁极将被磁性标记的细胞与未被标记的目的细胞CTCs中分离出来，只需简单地将目的细胞倾倒或吸取至新的管中即可。完成磁珠细胞分选后，目标CTCs即可用于流式细胞术、细胞培养或DNA/RNA提取等下游应用。了解更多关于 EasySep™ 免疫磁性技术的工作原理。探索更多可优化您的实验流程的相关产品，包括细胞鉴定、冻存及其他产品。
MAGNET COMPATIBILITY
• EasySep™ Magnet (Catalog #18000)
• “The Big Easy” EasySep™ Magnet (Catalog #18001)
• Easy 50 EasySep™ Magnet (Catalog #18002)
• EasyEights™ EasySep™ Magnet (Catalog #18103)
SUBTYPE
Cell Isolation Kits
CELL TYPE
Cancer Cells and Cell Lines
SPECIES
Human
SAMPLE SOURCE
Whole Blood
SELECTION METHOD
Negative
APPLICATION
Cell Isolation
BRAND
EasySep
AREA OF INTEREST
Cancer, Immunology
实验数据
产品说明书及文档
Find supporting information and directions for use in the Product Information Sheet or explore additional protocols below.
Resources and Publications
Educational Materials (11)
Frequently Asked Questions
Publications (2)
Facile, rapid and efficient isolation of circulating tumor cells using aptamer-targeted magnetic nanoparticles integrated with a microfluidic device. RSC advances 2022 nov
Abstract
Facile and sensitive detection and isolation of circulating tumor cells (CTCs) was achieved using the aptamer-targeted magnetic nanoparticles (Apt-MNPs) in conjugation with a microfluidic device. Apt-MNPs were developed by the covalent attachment of anti-MUC1 aptamer to the silica-coated magnetic nanoparticles via the glutaraldehyde linkers. Apt-MNPs displayed high stability and functionality after 6 months of storage at 4 °C. The specific microfluidic device consisting of mixing, sorting and separation modules was fabricated through conventional photo- and soft-lithography by using polydimethylsiloxane. The capture efficiency of Apt-MNPs was first studied in vitro on MCF-7 and MDA-MB-231 cancer cell lines in the bulk and microfluidic platforms. The cell capture yields of more than 91% were obtained at the optimum condition after 60 minutes of exposure to 50 $\mu$g mL-1 Apt-MNPs with 10 to 106 cancer cells in different media. CTCs were also isolated efficiently from the blood samples of breast cancer patients and successfully propagated in vitro. The isolated CTCs were further characterized using immunofluorescence staining. The overall results indicated the high potential of the present method for the detection and capture of CTCs.
Label-free detection of rare circulating tumor cells by image analysis and machine learning. Scientific reports 2020
Abstract
Detection and characterization of rare circulating tumor cells (CTCs) in patients' blood is important for the diagnosis and monitoring of cancer. The traditional way of counting CTCs via fluorescent images requires a series of tedious experimental procedures and often impacts the viability of cells. Here we present a method for label-free detection of CTCs from patient blood samples, by taking advantage of data analysis of bright field microscopy images. The approach uses the convolutional neural network, a powerful image classification and machine learning algorithm to perform label-free classification of cells detected in microscopic images of patient blood samples containing white blood cells and CTCs. It requires minimal data pre-processing and has an easy experimental setup. Through our experiments, we show that our method can achieve high accuracy on the identification of rare CTCs without the need for advanced devices or expert users, thus providing a faster and simpler way for counting and identifying CTCs. With more data becoming available in the future, the machine learning model can be further improved and can serve as an accurate and easy-to-use tool for CTC analysis.
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