Detection of Single Cancer Cell Multidrug Resistance With Single Cell Bioanalyzer

Abstract

Objectives: Despite the development of various cancer treatment methods, chemotherapy remains the most common approach for treating cancer. The risk of tumors acquiring resistance to chemotherapy remains a significant hurdle to the successful treatment of various types of cancer. Therefore, overcoming or predicting multidrug resistance in clinical treatment is essential. The detection of circulating tumor cells (CTCs) is an important component of liquid biopsy and the diagnosis of cancer. This study aims to test the feasibility of single-cell bioanalyzer (SCB) and microfluidic chip technology in identifying patients with cancer resistant to chemotherapy and propose new methods to provide clinicians with new choices. Methods: In this study, we used rapidly isolated viable CTCs from the patient blood samples method combined with SCB technology and a novel microfluidic chip, to predict whether patients with cancer are resistant to chemotherapy. SCB and microfluidic chip were used to select single CTCs, and the accumulation of chemotherapy drug was fluorescently measured in real time on these cells in the absence and presence of permeability-glycoprotein inhibitors. Results: Initially, we successfully isolated viable CTCs from the blood samples of patients. Additionally, the present study accurately predicted the response of 4 lung cancer patients to chemotherapeutic drugs. In addition, the CTCs of 17 patients with breast cancer diagnosed at Zhuhai Hospital of Traditional Chinese and Western Medicine were assessed. The results indicated that 9 patients were sensitive to chemotherapeutic drugs, 8 patients were resistant to a certain degree, and only 1 was completely resistant to chemotherapy. Conclusion: The present study indicated that the SCB technology could be used as a prognostic assay to evaluate the CTCs response to available drugs and guide physicians to treatment options that are most likely to be effective.

Keywords: cancer circulating tumor cell; microfluidic chip; single-cell bioanalyzer.

Figure 1.

The microfluidic chip allows the isolation and treatment of single cells in the single-cell bioanalyzer (SCB). (A) Images of the microchip. (B) The layout of the microfluidic device indicates that reservoirs 3 and 4 were used for drug delivery, whereas reservoirs 1 and 2 served as the cell inlet and waste, respectively. The “S” corresponds to the cell retention structure. (C) Schematic diagrams displaying the sorting of a single cancer cell and its retention near the cell retention structure. (D) The cancer cell retained within the cell retention structure is shown.

Figure 2.

Investigation of the PTX-sensitive and resistant lung cancer cells. (A and B) A549 and A549T cells were treated with 2.0 μg/mL PTX for 15 min. The fluorescence intensity was measured by the SCB assay. (A) Images of the fluorescent chemotherapy-treated A549 cells. (B) Images of the fluorescent chemotherapy-treated A549T cells. (C) Drug accumulation was measured on a single A549 cell. The fluorescence signal value was significantly increased by ∼2.5-fold (P < .001), reaching a maximum of 0.124 in ∼2100 s. (D) Drug accumulation was measured on a single A549T cell. The retention of A549T cells and their treatment with PTX, the fluorescence signal value did not significantly increase (P > .05). The statistical analysis of data was performed by the t-test (n = 3).

Figure 3.

The effect of the P-gp inhibitor in A549/A549T cells. Following treatment of A549 and A549T cells with 2.0 μg/mL PTX and 80 μmol/mL tariquidar, the SCB was used to detect the drug accumulation of the 2 cells. (A) The drug accumulation was measured on a single A549 cell. (B) The drug accumulation was measured on a single A549T cell. The fluorescence value of A549T cells was significantly increased by ∼2.8-fold (P < .001) in response to tariquidar compared with that noted in A549 cells. The statistical analysis of data was performed by the t-test (n = 3).

Figure 4.

Cancer cells can be isolated from “mimic” blood by SCB analysis. (A) Images of mixing cancer cells with PBMCs (this image was obtained with an SCB; therefore, the background was red). (B) Tumor cells were incubated with antibodies and imaged using a fluorescent microscope.

Figure 5.

The SCB can be used to predict the patient's response to chemotherapy. (A) CTCs were retained in the microfluidic channel. (B) CTCs were extracted from whole blood. The intracellular fluorescence intensity was significantly increased (P < .01), which indicated that they were sensitive to chemotherapy (Patient No. 2). (C) CTCs were extracted from whole blood, whereas the fluorescence intensity was not accumulated only if the P-gp inhibitor was provided and the case was determined as MDR (Patient No. 1). (D) CTCs were captured from peripheral blood and imaged under a fluorescent microscope. (E) CTCs were extracted from pleural effusion and the intracellular fluorescence intensity was significantly increased (P < .01), which indicated that they were sensitive to chemotherapy (Patient No. 6). (F) CTCs were extracted from pleural effusion and the fluorescence intensity was not accumulated only if the P-gp inhibitor was provided and the case was determined as MDR (Patient No. 4).

Figure 6.

Prediction platform for the sensitivity to chemotherapy of patients with breast cancer (n = 17). (A) CTCs (n = 8) from patients with breast cancer were sensitive to chemotherapy (PTX), and the P-gp inhibitor could not increase the accumulation of PTX in cancer cells. (B) The fluorescent intensity of these 9 CTC samples was significantly increased (P < .05), suggesting that the patients with breast cancer may be sensitive to chemotherapeutic drugs. The statistical analysis of data was performed by the t-test.

Figure 7.

Schematic representation of a proposed workflow for the diagnosis and treatment using the single-cell bioanalyzer (SCB).