Shah Pavak K, Herrera-Loeza Silvia Gabriela, Sims Christopher E, Yeh Jen Jen, Allbritton Nancy L
Department of Biomedical Engineering, University of North Carolina, Chapel Hill, North Carolina 27599 and North Carolina State University, Raleigh, North Carolina, 27695.
Cytometry A. 2014 Jul;85(7):642-9. doi: 10.1002/cyto.a.22480. Epub 2014 Jun 17.
Primary patient samples are the gold standard for molecular investigations of tumor biology yet are difficult to acquire, heterogeneous in nature and variable in size. Patient-derived xenografts (PDXs) comprised of primary tumor tissue cultured in host organisms such as nude mice permit the propagation of human tumor samples in an in vivo environment and closely mimic the phenotype and gene expression profile of the primary tumor. Although PDX models reduce the cost and complexity of acquiring sample tissue and permit repeated sampling of the primary tumor, these samples are typically contaminated by immune, blood, and vascular tissues from the host organism while also being limited in size. For very small tissue samples (on the order of 10(3) cells) purification by fluorescence-activated cell sorting (FACS) is not feasible while magnetic activated cell sorting (MACS) of small samples results in very low purity, low yield, and poor viability. We developed a platform for imaging cytometry integrated with micropallet array technology to perform automated cell sorting on very small samples obtained from PDX models of pancreatic and colorectal cancer using antibody staining of EpCAM (CD326) as a selection criteria. These data demonstrate the ability to automate and efficiently separate samples with very low number of cells.
原发性患者样本是肿瘤生物学分子研究的金标准,但难以获取,本质上具有异质性且大小不一。由在裸鼠等宿主生物体中培养的原发性肿瘤组织组成的患者来源异种移植瘤(PDX),能使人类肿瘤样本在体内环境中增殖,并紧密模拟原发性肿瘤的表型和基因表达谱。尽管PDX模型降低了获取样本组织的成本和复杂性,并允许对原发性肿瘤进行重复采样,但这些样本通常会被宿主生物体的免疫、血液和血管组织污染,而且大小也有限。对于非常小的组织样本(约10³个细胞),通过荧光激活细胞分选(FACS)进行纯化不可行,而对小样本进行磁性激活细胞分选(MACS)会导致纯度极低、产量低和活力差。我们开发了一个集成微板阵列技术的成像细胞术平台,以EpCAM(CD326)抗体染色作为选择标准,对从胰腺癌和结直肠癌的PDX模型中获得的非常小的样本进行自动细胞分选。这些数据证明了对细胞数量极少的样本进行自动化和高效分离的能力。