INTRODUCTION

Recent advances in single cell isolation techniques and next generation sequencing (NGS) have paved the way for the genome-wide molecular analysis of individual circulating tumour cells (CTCs) in patients with metastatic carcinomas. Here we present the results of a pilot study evaluating the feasibility and reliability of NGS of single CTC from whole blood samples.

MATERIALS & METHODS

Single cells of the human breast cancer cell line HCC38 were harvested from spiked blood samples in a semi-automated workflow consisting of immunomagnetic enrichment using the CellSearch system and dielectrophoretic cell sorting using the DEPArray system. DNA was isolated and amplified using the Ampli1 whole genome amplification (WGA) kit and subjected to low-coverage genome-wide paired-end sequencing for copy number variation (CNV) analysis and targeted re-sequencing of 200 cancer-related genes for somatic mutation analysis.

RESULTS

Single-cell WGA products of four HCC38 cells were subjected to whole genome sequencing for CNV analysis. Average coverage depth was 0,68x. At a binning window of 50 kb, detection results of CNVs in single-cell samples were highly consistent (>81% copy number concordance per bin genome wide) with CNV profiles from non-amplified multi-cell samples of the same cell line. We could demonstrate that part of the discordance was due to the acquisition of novel DNA-rearrangements in the single cells. Three of the single-cell WGA products were additionally subjected to targeted re-sequencing for mutation analysis of 200 selected genes, of which the analysis is currently ongoing.

DISCUSSION

Our study demonstrates the feasibility of a comprehensive genome-wide CNV analysis and targeted mutation analysis using NGS of single tumour cells isolated from whole blood samples in a highly automated isolation workflow. This approach provides a robust framework for the study of intercellular heterogeneity within the CTC population in blood samples of patients with (metastatic) breast cancer. In addition, our results document the extent of WGA-induced bias of a recently commercialized PCR-based WGA kit.

These authors contributed equally to the data presented in this abstract.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P1-04-03.