Detection of circulating tumor cells in blood by shell-isolated nanoparticle - enhanced Raman spectroscopy (SHINERS) in microfluidic device

Abstract

Isolation and detection of circulating tumor cells (CTCs) from human blood plays an important role in non- invasive screening of cancer evolution and in predictive therapeutic treatment. Here, we present the novel tool utilizing: (i) the microfluidic device with (ii) incorporated photovoltaic (PV) based SERS-active platform, and (iii) shell-isolated nanoparticles (SHINs) for simultaneous separation and label-free analysis of circulating tumour cells CTCs in the blood specimens with high specificity and sensitivity. The proposed microfluidic chip enables the efficient size - based inertial separation of circulating cancer cells from the whole blood samples. The SERS-active platform incorporated into the microfluidic device permits the label-free detection and identification of isolated cells through the insight into their molecular and biochemical structure. Additionally, the silver nanoparticles coated with an ultrathin shell of silica (Ag@SiO₂) was used to improve the detection accuracy and sensitivity of analysed tumor cells via taking advantages of shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS). The empirical analysis of SHINERS spectra revealed that there are some differences among studied (HeLa), renal cell carcinoma (Caki-1), and blood cells. Unique SHINERS features and differences in bands intensities between healthy and cancer cells might be associated with the variations in the quantity and quality of molecules such as lipid, protein, and DNA or their structure during the metastasis cancer formation. To demonstrate the statistical efficiency of the developed method and improve the differentiation for circulating tumors cells detection the principal component analysis (PCA) has been performed for all SHINERS data. PCA method has been applied to recognize the most significant differences in SHINERS data among the three analyzed cells: Caki-1, HeLa, and blood cells. The proposed approach challenges the current multi-steps CTCs detection methods in the terms of simplicity, sensitivity, invasiveness, destructivity, time and cost of analysis, and also prevents the defragmentation/damage of tumor cells and thus leads to improving the accuracy of analysis. The results of this research work show the potential of developed SERS based tool for the separation of tumor cells from whole blood samples in a simple and minimally invasive manner, their detection and molecular characterization using one single technology.

Figure 1

Scheme of the preparation of SERS substrate, microfluidic system, analyte and measurement. Main steps involve cleaning (a), drying (b), sputtering of thin layer of silver (c), the process of preparing microfluidic system (d), analyte and buffer preparation followed by the separation of tumor cells (e) and finally the measurement takes place (f).

Figure 2

(A) Setup used for CTCs separation from whole blood, (B) top view of microfluidic device, (C) cross-sectional view of microchannel (dimensions in the figure are given in millimeters), and (D) SEM image of SERS-active platform incorporated into the detection area chambers (DA) of microfluidic device.

Figure 3

SEM (A,B) and AFM (C,D) images at different magnifications of Ag/PV SERS-active platforms sputtered with 8 nm layer of silver via PVD technique. (E) presents the histograms of the size of the silver objects on the surface of the PV based substrates.

Figure 4

TEM micrographs of Ag@SiO₂ nanostructures.

Figure 5

Schematic view of cancer cell isolation from whole blood.

Figure 6

Averaged and normalized SHINERS spectra of (A) blood cells, (B) Caki-1, and (C) HeLa cells recorded on Ag/PV SERS platform in microfluidic device with SHINs (shell-isolated nanoparticles).

Figure 7

Averaged and normalized SERS spectra of (A) HeLa and (B) Caki-1, cells recorded on Ag/PV SERS platform in microfluidic device without SHINs (shell-isolated nanoparticles).

Figure 8

(A) The plots of PC-1 versus PC-2 scores component calculated for blood cells, HeLa and Caki-1 cells and corresponding PC-1 loading data (B).