Department of Physiology, University of Manitoba, Winnipeg, Canada.
Cytometry A. 2011 Feb;79(2):159-66. doi: 10.1002/cyto.a.21012. Epub 2010 Dec 30.
Telomeres, the end of chromosomes, are organized in a nonoverlapping fashion and form microterritories in nuclei of normal cells. Previous studies have shown that normal and tumor cell nuclei differ in their 3D telomeric organization. The differences include a change in the spatial organization of the telomeres, in telomere numbers and sizes and in the presence of telomeric aggregates. Previous attempts to identify the above parameters of 3D telomere organization were semi-automated. Here we describe the automation of 3D scanning for telomere signatures in interphase nuclei based on three-dimensional fluorescent in situ hybridization (3D-FISH) and, for the first time, define its sensitivity in tumor cell detection. The data were acquired with a high-throughput scanning/acquisition system that allows to measure cells and acquire 3D images of nuclei at high resolution with 40 × or 60 × oil and at a speed of 10,000-15,000 cells h(-1) , depending on the cell density on the slides. The automated scanning, TeloScan, is suitable for large series of samples and sample sizes. We define the sensitivity of this automation for tumor cell detection. The data output includes 3D telomere positions, numbers of telomeric aggregates, telomere numbers, and telomere signal intensities. We were able to detect one aberrant cell in 1,000 normal cells. In conclusions, we are able to detect tumor cells based on 3D architectural profiles of the genome. This new tool could, in the future, assist in patient diagnosis, in the detection of minimal residual disease, in the analysis of treatment response and in treatment decisions.
端粒是染色体的末端,以非重叠的方式组织,并在正常细胞的核中形成微区。先前的研究表明,正常和肿瘤细胞核在其 3D 端粒结构上存在差异。这些差异包括端粒空间组织、端粒数量和大小以及端粒聚集物的存在的改变。先前尝试识别 3D 端粒结构的上述参数都是半自动的。在这里,我们描述了基于三维荧光原位杂交(3D-FISH)的间期核中端粒特征的 3D 扫描自动化,并首次定义了其在肿瘤细胞检测中的灵敏度。这些数据是使用高通量扫描/采集系统获得的,该系统允许以 40×或 60×油的高分辨率测量细胞并获取核的 3D 图像,速度为 10,000-15,000 个细胞/小时,具体取决于载玻片上细胞的密度。自动化扫描 TeloScan 适用于大量样本和样本大小。我们定义了这种自动化肿瘤细胞检测的灵敏度。数据输出包括 3D 端粒位置、端粒聚集物数量、端粒数量和端粒信号强度。我们能够在 1000 个正常细胞中检测到一个异常细胞。总之,我们能够基于基因组的 3D 结构特征来检测肿瘤细胞。这个新工具未来可能有助于患者诊断、微小残留病检测、治疗反应分析和治疗决策。