Tumour cell identification by means of Raman spectroscopy in combination with optical traps and microfluidic environments

Abstract

Raman spectroscopy has been recognized to be a powerful tool for label-free discrimination of cells. Sampling methods are under development to utilize the unique capabilities to identify cells in body fluids such as saliva, urine or blood. The current study applied optical traps in combination with Raman spectroscopy to acquire spectra of single cells in microfluidic glass channels. Optical traps were realized by two 1070 nm single mode fibre lasers. Microflows were controlled by a syringe pump system. A novel microfluidic glass chip was designed to inject single cells, modify the flow speed, accommodate the laser fibres and sort cells after Raman based identification. Whereas the integrated microchip setup used 514 nm for excitation of Raman spectra, a quartz capillary setup excited spectra with 785 nm laser wavelength. Classification models were trained using linear discriminant analysis to differentiate erythrocytes, leukocytes, acute myeloid leukaemia cells (OCI-AML3), and breast tumour cells BT-20 and MCF-7 with accuracies that are comparable with previous Raman experiments of dried cells and fixed cells in a Petri dish. Implementation into microfluidic environments enables a high degree of automation that is required to improve the throughput of the approach for Raman activated cell sorting.

Methods and Applications of Raman Microspectroscopy to Single-Cell Analysis

“…Already, pioneer studies have demonstrated the potential of Raman spectroscopy for in vivo cancer demarcation that can guide surgical procedures or for cell sorting without contaminating antibodies or fluorophores. 78 We believe that combi-nations of current technology, e.g., microfluidic sample delivery, liquid chromatography, or super-resolved optical approaches will soon be combined with Raman spectroscopy to enable even faster sample analysis or the localization of chemical products at subwavelengthlength scales. Raman spectroscopy has evolved from an exotic technique that only a handful of select research groups were able to perform to an entire research area by itself, enriching and complementing other analytical approaches.…”

“…In a recent demonstration of this potential, Duchow et al 78 combined optical trapping with cell sorting in microfluidic channels to discriminate between erythrocytes, leukocytes, acute myeloid leukemia cells, and two types of breast tumor cells, with an overall accuracy of 92.2% by using 785 nm wavelength excitation and a specificity of 94.9%, after switching to the excitation of Raman scattering at 514 nm.…”

Molecular pathology via IR and Raman spectral imaging

“…Preliminary results from a number of laboratories worldwide [15] have indicated that these novel spectral methods can distinguish between normal tissue types, disease types and stages, and even identify the primary tumors from spectral patterns observed in metastatic cells. Furthermore, these techniques can analyze single, unstained and unlabeled cells, and therefore, can be used in the detection of circulating tumor cells [16,17].…”

“…This method is more labor intensive, but yields in relatively short time hundreds of spectra of selected cellular features that show enormous sensitivity toward many biochemical processes, such as the metabolic activity in live yeast cells [38,39]. For example, this approach has been used very successfully to follow stem cell differentiation [40][41][42], photochemical changes in melanosomes [43] or for the detection of circulating tumor cells in flow cytometry [16,17]. Finally, due to the very high spatial resolution of Ra-SCP, spectral information from individual bacterial cells can be collected [44,45].…”

Single-cell discrimination based on optical tweezers Raman spectroscopy

“…Recently, some single-cell identification studies have reported the discrimination of different types of cells. For example, in combination with statistical methods, Raman microscopy has been successfully applied to distinguish between benign and malignant cells [18][19][20], and healthy cells and dying or stressed cells [21]; it has also been used to discriminate between cell types [22][23][24][25], even for highly similar cancer cell lines. However, most previous studies focused on distinguishing between different types of cells such as cancer cells and healthy cells, or different states of the same cells.…”