Design and Clinical Application of an Integrated Microfluidic Device for Circulating Tumor Cells Isolation and Single-Cell Analysis

Abstract

Circulating tumor cells (CTCs) have been considered as an alternative to tissue biopsy for providing both germline-specific and tumor-derived genetic variations. Single-cell analysis of CTCs enables in-depth investigation of tumor heterogeneity and individualized clinical assessment. However, common CTC enrichment techniques generally have limitations of low throughput and cell damage. Herein, based on micropore-arrayed filtration membrane and microfluidic chip, we established an integrated CTC isolation platform with high-throughput, high-efficiency, and less cell damage. We observed a capture rate of around 85% and a purity of 60.4% by spiking tumor cells (PC-9) into healthy blood samples. Detection of CTCs from lung cancer patients demonstrated a positive detectable rate of 87.5%. Additionally, single CTCs, ctDNA and liver biopsy tissue of a representative advanced lung cancer patient were collected and sequenced, which revealed comprehensive genetic information of CTCs while reflected the differences in genetic profiles between different biological samples. This work provides a promising tool for CTCs isolation and further analysis at single-cell resolution with potential clinical value.

Keywords: CTC-isolation; high-throughput sequencing; lung cancer; microfluidics; single-cell analysis.

Figure 1

Schematic illustration of the integrated microfluidic circulating tumor cells (CTC) isolation platform. Taking lung cancer as an example, 2 mL blood sample was loaded into the device. All red blood cells (RBCs), platelets and most WBCs were filtered, while CTCs and some WBCs of large size were captured. Then CTCs and residual WBCs were washed off the membrane and transferred into the purifying chip, where WBCs would be further removed by CD45 dynabeads. Finally, the supernatant with CTCs and free WBCs was collected for identification and single-cell isolation. This work is licensed under a Creative Commons Attribution 3.0 Unported License. It is attributed to Mingxin Xu.

Figure 2

Capture of PC9-GFP cells by the integrated device. (a,b) Representative merged fluorescent field and bright images of PC9-GFP cells, white blood cells (WBCs) and CD45 dynabeads (as indicated by the arrows) after processing by the novel device (a) (magnification, ×200), (b) (magnification, ×400). (c) Capture rate of the integrated device at different concentrations of PC9-GFP cells. Data were expressed as mean ± standard error of mean (SEM).

Figure 3

Analysis of captured CTCs from blood samples of patients. (a) Representative fluorescent staining images of CTC detected in a blood sample of a lung cancer patient. The blue color referred to nuclear staining (DAPI), the green color referred to CD45, and the red color demonstrated CK expression. Magnification, ×200. (b) The average number of CTCs in lung cancer patients (n = 16) and non-tumor patients (n = 4). (c) The average number of CTCs in lung cancer patients of different stages (Stage I, n = 1; Stage II, n = 1; Stage III, n = 2; Stage IV, n = 11).

Figure 4

Schematic illustration of the diagnosis, treatment and sample collection of a representative advanced lung cancer patient (patient #1).

Figure 5

The genetic variations of liver biopsy tissue, ctDNA and single CTC samples. (a) The distribution of SNVs on the genome. (b) The distribution of InDels on the genome. (c) The proportion of different base mutation types. (d) The top 10 somatic mutations among 4 samples.

Figure 6

Common SNVs, InDels and mutated genes in liver biopsy tissue, ctDNA and single CTC samples. (a,b) Common mutation sites and related genes in ctDNA and liver biopsy tissue samples before treatment (S124 and S145). (c) Common gene mutation in single CTC and ctDNA sample after treatment (S094 and S063). SNP: single nucleotide polymorphism; DEL: deletion.