An integrated flow cytometry-based platform for isolation and molecular characterization of circulating tumor single cells and clusters.
An integrated flow cytometry-based platform for isolation and molecular characterization of circulating tumor single cells and clusters.
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DOI：
10.1038/s41598-018-23217-5
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发表时间：
2018-03-22
影响因子：
4.6
通讯作者：
Carpenter EL
中科院分区：
文献类型：
--
作者：
Bhagwat N;Dulmage K;Pletcher CH Jr;Wang L;DeMuth W;Sen M;Balli D;Yee SS;Sa S;Tong F;Yu L;Moore JS;Stanger BZ;Dixon EP;Carpenter EL
罕见的循环肿瘤细胞(CTCs)和细胞团的全面分子分析经常受到产量和纯度低以及细胞丢失的阻碍。为了解决这个问题，我们开发了一个完全集成的平台，用于从血液中分离基于流式细胞术的CTCs和簇，该平台可以与整个转录组分析或靶向RNA转录定量相结合。下游分子特征可以通过指数排序与细胞表型相关联。这一新开发的平台利用基于在线磁粉的白细胞去除，以及声波细胞聚焦和洗涤，实现了血细胞和非细胞碎片减少98%，以及尖峰肿瘤细胞的对数倍浓缩。我们还可以在4/7重复的100万个WBC中检测到1个掺入的肿瘤细胞。重要的是，使用200μm的大喷嘴和较低的鞘压力(3.5 psi)最大限度地减少了剪切力，从而保持了细胞的活力和完整性，同时允许从血液中同时回收单个细胞和簇。作为原则的证明，我们从基因工程的胰腺癌小鼠模型(n = 12小鼠)中分离并转录鉴定了63个单个CTC，并使用指数排序，能够基于关联的单细胞蛋白和基因表达识别不同的上皮亚群和间充质亚群。
Comprehensive molecular analysis of rare circulating tumor cells (CTCs) and cell clusters is often hampered by low throughput and purity, as well as cell loss. To address this, we developed a fully integrated platform for flow cytometry-based isolation of CTCs and clusters from blood that can be combined with whole transcriptome analysis or targeted RNA transcript quantification. Downstream molecular signature can be linked to cell phenotype through index sorting. This newly developed platform utilizes in-line magnetic particle-based leukocyte depletion, and acoustic cell focusing and washing to achieve >98% reduction of blood cells and non-cellular debris, along with >1.5 log-fold enrichment of spiked tumor cells. We could also detect 1 spiked-in tumor cell in 1 million WBCs in 4/7 replicates. Importantly, the use of a large 200μm nozzle and low sheath pressure (3.5 psi) minimized shear forces, thereby maintaining cell viability and integrity while allowing for simultaneous recovery of single cells and clusters from blood. As proof of principle, we isolated and transcriptionally characterized 63 single CTCs from a genetically engineered pancreatic cancer mouse model (n = 12 mice) and, using index sorting, were able to identify distinct epithelial and mesenchymal sub-populations based on linked single cell protein and gene expression.
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影响因子：
4.7
作者：
Carpenter EL;Rader J;Ruden J;Rappaport EF;Hunter KN;Hallberg PL;Krytska K;O'Dwyer PJ;Mosse YP
通讯作者：
Mosse YP
影响因子：
158.5
作者：
Cristofanilli, M;Budd, GT;Hayes, DF
通讯作者：
Hayes, DF
影响因子：
7.4
作者：
Fu, Glenn K.;Wilhelmy, Julie;Stern, David;Fan, H. Christina;Fodor, Stephen P. A.
通讯作者：
Fodor, Stephen P. A.
影响因子：
4.6
作者：
Fachin F;Spuhler P;Martel-Foley JM;Edd JF;Barber TA;Walsh J;Karabacak M;Pai V;Yu M;Smith K;Hwang H;Yang J;Shah S;Yarmush R;Sequist LV;Stott SL;Maheswaran S;Haber DA;Kapur R;Toner M
通讯作者：
Toner M
影响因子：
2.3
作者：
Divella, Rosa;Daniele, Antonella;Mazzocca, Antonio
通讯作者：
Mazzocca, Antonio