Novel automated three-dimensional genome scanning based on the nuclear architecture of telomeres

Abstract

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.