Spectral Fiber Sensors for Cancer Diagnostics

Globally, one of the leading causes of mortality and morbidity is cancer. Hence, efforts are focused to detect cancer at an early stage, and optical spectroscopy is largely being used for early cancer diagnostics.

Healthy and malignant tissue can be distinguished with the help of molecular or fluorescence spectroscopy methods such as IR-absorption or diffuse reflection, Raman scattering. Raman spectroscopy has already been effectively applied for the detection of skin cancer. Moreover, the performance power of NIR, MIR, and fluorescence spectroscopy has also been successful in detecting cervical and breast cancer. However, integrating MIR and Raman spectroscopy into one single instrument is innovative and very promising since those are complementary methods.

Sample Preparation

Matched pairs of tumor and adjacent non-tumor renal cortex tissues were taken from kidneys of patients who underwent radical nephrectomy in the Klinik für Urologie, Charité—Universitätsmedizin Berlin.

MIR

The Matrix MF (Bruker) with MCT detector and the iS5 (Thermo Fisher Scientific) with DTGS detector FTIR spectrometers were used to carry out mid-Infrared measurements. The spectra were recorded in contact using two distinctive ATR probes. Spectra in the region from 2600 to 3600 cm−1 was obtained using a probe containing chalcogenide Infrared (CIR) fibers with zirconium dioxide tip (art photonics GmbH). Spectra recorded in the fingerprint region were obtained using a MIR-ATR probe with a silica tip (art photonics GmbH) and polycrystalline Infrared (PIR) fibers.

Raman

All Raman experiments were carried out using a Ventana spectrometer (Ocean Optics) coupled to fiber optic probes. One single fiber was used as the excitation channel and the detection channel simultaneously for spectra obtained in the high-wavenumber region of 2600–3600 cm−1. The laser working with 690 nm excitation (CNI Optoelectronics) was coupled into the 400 μm core fiber with homemade coupler permitting delivery of laser light into the fiber and back to the spectrometer. A 785-nm laser for excitation (Ocean Optics) was used to record measurements in the fingerprint region (600–1800 cm−1).

NIR

The NIR measurements were performed with the help of the portable fiber-optic NIRQuest InGaAs spectrometer (Ocean Optics) operating in reflectance mode and in the spectral range from 900 to 1700 nm. The spectrometer was connected with the light source and probe via optical fibers and to a computer using the USB port.

Setup for NIR measurements. (1)-NIR probe R (1+7) from art photonics GmbH, (2)-Tissue slice in petri dish, (3)- NIRQuest spectrometer, (4)- halogen lamp, (5)- PC with software for spectra collection.

Figure 1. Setup for NIR measurements. (1)-NIR probe R (1+7) from art photonics GmbH, (2)-Tissue slice in petri dish, (3)- NIRQuest spectrometer, (4)- halogen lamp, (5)- PC with software for spectra collection.

Results and Discussion

MIR spectra recorded from cancer and non-cancer tissue demonstrate contributions from proteins, lipids, and other carbohydrates. Figure 2 illustrates averaged spectra obtained from kidney samples. Signal intensities in the range of 1300–1800 cm−1 are analogous. The signals at 1740, 1460, and 1378 cm-1 can be assigned to lipids. They are caused by C=O stretching, CH3 asymmetric, and CH3 symmetric bending vibrations, respectively. The Amide bands can be observed at 1650, 1560, and 1300cm-1. Typical bands due to the phosphate group of phospholipids can be seen at 1085 and 1240 cm−1. The so-called phosphate group refers to the phosphor-diester-linkage found in phospholipids. Moreover, collagen and polysaccharides contribute to characteristic signals within this wavenumber range. The prominent band around 1040 cm−1 is most probably due to sugar molecules which can also be present in DNA.

Preprocessed spectra showing clear differences between cancerous and non-cancer samples

Figure 2. Preprocessed spectra showing clear differences between cancerous and non-cancer samples

MIR spectra mentioned above were obtained in the fingerprint region from 900 to 1800 cm−1. The signals detected in this region of the spectrum are derived from C=O and C=C stretching vibrations and also from bending and skeletal vibrations.

NIR spectrum is composed of various spectral signatures of components such as proteins, lipids, phosphate, and carbohydrates. It has specific spectral regions, which display higher variation of composition between tumor and normal tissue. In order to highlight these regions, mathematical preprocessing was used. The goal of signal pretreatment is to enhance data quality before modeling and eliminate physical information from the spectra which can be considerably impacted upon by nonlinearities introduced by light scattering. The cancer mean spectrum was subtracted to emphasize differences between cancer and normal spectra.

The largest spectral differences between cancer and normal tissues were seen in the interval characteristic for the first overtones and combination vibrations of CH, NH, and OH bonds. It is well known that in normal tissues, carbohydrate level and phosphate content are higher than in cancer tissues. Results signify that the first and second overtones of the C-H vibrations and also the combination bands of CH, NH, and OH can serve as diagnostic markers for kidney cancer.

Furthermore, the differentiation between non-cancer and cancer samples appeared to be very straightforward based on Raman spectroscopy. Cancer samples did not exhibit fluorescence, while the non-cancer samples exhibited a very strong fluorescence that covered nearly all Raman signals.

Figure 3 shows a spectrum obtained from kidney cancer. The signals in the lower wavenumber range display low intensities. Typical signals observed in this range are because of skeletal vibrations of amino acids. For instance, the C-S stretching mode of cysteine is observed around 660 cm−1. Raman bands with higher intensities are located at 1300, 1441, and 1660 cm−1. Those vibrations can be assigned to CH2CH3 twisting, CH2 bending, and C=O stretching modes, respectively. The first signal is obtained from collagen or lipid, whereas the last signal is due to proteins and the remaining signal can be produced by both biomolecules.

Raman spectra obtained from one patient showing the differences between cancer and non-cancer samples for measurements in fingerprint and high wavenumber region. Signals can be detected more clearly after the subtraction of the fluorescence background (shown below).

Figure 3. Raman spectra obtained from one patient showing the differences between cancer and non-cancer samples for measurements in fingerprint and high wavenumber region. Signals can be detected more clearly after the subtraction of the fluorescence background (shown below).

A 690-nm laser was used to excite the Raman spectra in the high-wavenumber region. A similar behavior was observed for the spectra obtained with 785 nm; the fluorescence was greater for the non-cancer samples than the cancer samples. Within this region, some signals can be assigned to vibrational modes of proteins, lipids, and water. Lipids exhibit distinct peaks at 2920 and 2850 cm−1corresponding to the anti-symmetric and symmetric CH2 stretching vibrations. Proteins result in peaks at 2956 and 2870 cm−1 in correlation with the stretching vibrations of the CH3 group. The characteristic broad band for water is located at 3400 cm−1.

Conclusions

Molecular spectroscopy can be used to distinguish between cancerous tissues from non-cancerous ones, and the investigated methods complement each other. This can be considered as a beginning point for the advancement of a multimodal instrument for the detection of cancer.

This information has been sourced, reviewed and adapted from materials provided by art photonics GmbH.

For more information on this source, please visit art photonics GmbH.

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