Circulating Tumor Cell Enrichment and Single-Cell Isolation Combining the CellSearch® and DEPArray™ Systems.

The analysis of circulating tumor cells (CTCs) has shown potential for detection of cancer spread, prognosis, therapeutic target selection, and monitoring of treatment response. CTCs can be obtained repeatedly by simple blood draws as so-called "liquid biopsy." Thus, they can serve as a surrogate material for primary or metastatic tissue biopsies. In addition, isolation of CTCs provides the possibility to investigate those cells which may hold the (molecular) traits responsible for metastatic progression and ultimately patient death. As such, CTCs represent a target of utmost importance in cancer research and therapy. In this chapter, we describe a workflow for the enrichment of CTCs with the FDA-cleared CellSearch® system followed by the isolation of single CTCs using the DEPArray™ technology enabling further molecular single-cell analyses.

Array-Based Comparative Genomic Hybridization for the Detection of Copy Number Alterations in Single Cells.

Comprehensive genome-wide analyses of single cells represent an important tool for clinical applications, such as pre-implantation diagnostic and prenatal diagnosis, as well as for cancer research purpose. For the latter, studies of tumor heterogeneity, circulating tumor cells (CTCs), and disseminated cancer cells (DCCs) require the analysis of single-cell genomes. Here we describe a reliable and robust array-based comparative genomic hybridization (aCGH) protocol based on Ampli 1™ whole genome amplification that allows the detection of copy number alterations (CNAs) in single cancer cells as small as 100 kb.

Isolation and Genomic Analysis of Circulating Tumor Cell Clusters in Cancer Patients.

The role of circulating tumor cell (CTC) clusters in the metastatic dissemination process is gaining increased attention. Besides homotypic clusters, heterotypic clusters that contain tumor cells admixed with normal cells are frequently observed in patients with solid tumors. Current methods used for cluster detection and enumeration do not allow an accurate estimation of the relative fractions of tumor cells. Here we describe a method for estimating tumor fraction of clusters including isolation and collection of single clusters, assessment of copy number alterations of single clusters by low-pass whole genome sequencing, and bioinformatic analysis of sequencing data.