Isolation of rare circulating tumour cells in cancer patients by microchip technology

Abstract

Viable tumour-derived epithelial cells (circulating tumour cells or CTCs) have been identified in peripheral blood from cancer patients and are probably the origin of intractable metastatic disease. Although extremely rare, CTCs represent a potential alternative to invasive biopsies as a source of tumour tissue for the detection, characterization and monitoring of non-haematologic cancers. The ability to identify, isolate, propagate and molecularly characterize CTC subpopulations could further the discovery of cancer stem cell biomarkers and expand the understanding of the biology of metastasis. Current strategies for isolating CTCs are limited to complex analytic approaches that generate very low yield and purity. Here we describe the development of a unique microfluidic platform (the 'CTC-chip') capable of efficient and selective separation of viable CTCs from peripheral whole blood samples, mediated by the interaction of target CTCs with antibody (EpCAM)-coated microposts under precisely controlled laminar flow conditions, and without requisite pre-labelling or processing of samples. The CTC-chip successfully identified CTCs in the peripheral blood of patients with metastatic lung, prostate, pancreatic, breast and colon cancer in 115 of 116 (99%) samples, with a range of 5-1,281 CTCs per ml and approximately 50% purity. In addition, CTCs were isolated in 7/7 patients with early-stage prostate cancer. Given the high sensitivity and specificity of the CTC-chip, we tested its potential utility in monitoring response to anti-cancer therapy. In a small cohort of patients with metastatic cancer undergoing systemic treatment, temporal changes in CTC numbers correlated reasonably well with the clinical course of disease as measured by standard radiographic methods. Thus, the CTC-chip provides a new and effective tool for accurate identification and measurement of CTCs in patients with cancer. It has broad implications in advancing both cancer biology research and clinical cancer management, including the detection, diagnosis and monitoring of cancer.

Figure 1. Isolation of CTCs from whole blood using a microfluidic device

a, The workstation setup for CTC separation. The sample is continually mixed on a rocker, and pumped through the chip using a pneumatic-pressure-regulated pump. b, The CTC-chip with microposts etched in silicon. c, Whole blood flowing through the microfluidic device. d, Scanning electron microscope image of a captured NCI-H1650 lung cancer cell spiked into blood (pseudo coloured red). The inset shows a high magnification view of the cell.

Figure 2. CTC capture and enumeration

a, Capture yield as a function of flow rate. Data shown represent measurements averaged over three devices, and each error bar represents the standard error of the mean. b, Capture yields from buffer spiked with 100 cells per ml of four different cell lines: prostate (PC3-9), breast (SkBr-3), bladder (T-24), and NSCLC (NCI-H1650). Each data point was repeated in at least 3 devices. The error bars represent standard deviations of measurements within each experiment. c, Regression analysis of capture efficiency for various target cell concentrations, comparing whole blood to lysed blood samples. The plot represents number of cells spiked versus number of cells recovered. d–k, Higher magnification (20×) images of captured CTCs and haematologic cells from NSCLC patients, stained with DAPI, and for cytokeratin and CD45. Merged images identify CTCs in panels d–g and haematologic cells in panels h–k.

Figure 3. Enumeration of CTCs from cancer patients

a, Summary of samples and CTC counts per 1 ml of blood in patients with various advanced cancers and localized prostate cancer. b, Frequency of CTCs per 1 ml of blood, by diagnosis. The box plot presents the median, lower and upper quartiles (25th, 75th percentiles). Data points that lie outside the 10th and 90th percentiles are shown as outliers. c, Purity of captured CTCs (ratio of CTCs to total nucleated cells), by diagnosis. d–i, Serial CTC assessment. CTC quantity (red), and tumour size (blue) measured as the unidimensional sum of all significant tumour sites on a CT scan, are well correlated over the course of anti-cancer treatment for nine patients. Six of them are shown here, for whom diagnoses and specific therapies were: NSCLC, 1st-line carboplatin, paclitaxel (d); NSCLC, 2nd-line pemetrexed (e); colorectal, 1st-line 5FU, irinotecan (f); pancreatic, 1st-line gemcitabine, bevacizumab (g); pancreatic, 1st-line gemcitabine (h); pancreatic, 1st-line gemcitabine, erlotinib (i). Baseline CT scans were before therapy initiation and CTC measurements began at or shortly after the first treatment.

Figure 4. Characterization of CTCs with tumour-specific molecular markers

a, b, CTCs from a prostate cancer patient stained positive for DAPI and PSA expression. c, RT–PCR amplification of PSA transcript is seen in two patients with prostate cancer (PCa), but not in two patients with lung cancer (LuCa), and only in blood fractions enriched for CTCs as opposed to non-enriched fractions (non-CTC). d, e, CTCs from an NSCLC patient stained for DAPI and TTF-1. f, RT–PCR shows expression of TTF-1 in two patients with lung cancer (LuCa), which is absent in two patients with prostate cancer (PCa), and only when RNA was eluted from blood fractions enriched for CTCs as opposed to non-enriched fractions (non-CTC).