Sensitive and High-throughput Detection, Separation and Analysis of Circulating Tumor Cells

Abstract

This dissertation describes novel methods to detect, separate and analyze circulating tumor cells (CTCs) from peripheral blood, with a high sensitivity and throughput. The ensemble-decision aliquot ranking (eDAR) platform is a new method for isolating CTCs from cancer patients with a recovery ratio of 93% and a zero false positive rate. We have validated this method by analyzing the samples from breast, pancreatic and lung cancer patients. The capability to perform downstream analyses on the isolated CTCs were also tested and integrated into the eDAR platform. We developed a method that can monitor eight protein markers, using a sequential staining and photobleaching procedure. Single-cell isolation and culture of the trapped CTCs were also tested. Based on these, we re-designed the eDAR platform by applying a new active cell sorting scheme and a new further purification method. Because many applications in the CTC area are focused on the enumeration, we also developed an automated method for counting tumor cells in whole blood samples. This enumeration method was validated by a side-by-side comparison with CellSearch, the only FDA approved method at present, in 90 metastatic breast cancer patient samples. These tools facilitate fundamental investigation of rare cells, as well as developing non-invasive biopsy to improve the clinical treatment.