Raman spectroscopic techniques to detect ovarian cancer biomarkers in blood plasma

Abstract

Robust diagnosis of ovarian cancer is crucial to improve patient outcomes. The lack of a single and accurate diagnostic approach necessitates the advent of novel methods in the field. In the present study, two spectroscopic techniques, Raman and surface-enhanced Raman spectroscopy (SERS) using silver nanoparticles, have been employed to identify signatures linked to cancer in blood. Blood plasma samples were collected from 27 patients with ovarian cancer and 28 with benign gynecological conditions, the majority of which had a prolapse. Early ovarian cancer cases were also included in the cohort (n = 17). The derived information was processed to account for differences between cancerous and healthy individuals and a support vector machine (SVM) algorithm was applied for classification. A subgroup analysis using CA-125 levels was also conducted to rule out that the observed segregation was due to CA-125 differences between patients and controls. Both techniques provided satisfactory diagnostic accuracy for the detection of ovarian cancer, with spontaneous Raman achieving 94% sensitivity and 96% specificity and SERS 87% sensitivity and 89% specificity. For early ovarian cancer, Raman achieved sensitivity and specificity of 93% and 97%, respectively, while SERS had 80% sensitivity and 94% specificity. Five spectral biomarkers were detected by both techniques and could be utilised as a panel of markers indicating carcinogenesis. CA-125 levels did not seem to undermine the high classification accuracies. This minimally invasive test may provide an alternative diagnostic and screening tool for ovarian cancer that is superior to other established blood-based biomarkers.

Multi-biomarker panel signature as the key to diagnosis of ovarian cancer

“…The presence of very low level of serum biomarkers in the early stage of the disease may be challenging in processing for clinical studies. Recently, for the first time, Raman spectroscopy has been used to assay the blood samples for diagnosis of early and late stage ovarian cancer (Paraskevaidi et al., 2018; Peng et al., 2014). Raman Spectroscopy is based on the phenomenon of inelastic light scattering caused when light interact with matter.…”

“…In addition, to differentiate between healthy and ovarian cancer cases, the method was assessed in different levels of CA125 to rule out that the detection accuracy was due to CA125 level, and both techniques provided satisfactory results. Both techniques detected five spectral biomarkers, which are promising as multi-biomarker panel in diagnosing ovarian cancer (Paraskevaidi et al., 2018). These studies highlight the promising role of Raman spectroscopy in the biomarker studies and its adoption in multibiomarker studies will be prospective breakthrough in the field of biomarker research.…”

Label‐free serum detection based on Raman spectroscopy for the diagnosis and classification of glioma

“…These changes indicated that the contents of proteins, lipids, and other biological macromolecules in the serum of patients were significantly reduced, which may be related to the active growth and metabolism of malignant tumor cells and the rapid increase in the consumption of proteins, amino acids, and lipids, as similar results had been reported in literature on the detection of tumor serum by Raman spectroscopy. [8,[32][33][34] The peak intensities at 505 cm −1 (S S and proteins), 535 cm −1 (S S and proteins), 703 cm −1 (C S stretching and proteins), 1,032 cm −1 (CH 2 and CH 3 bending and phenylalanine), 1,313 cm −1 (CH 2 deformation and in-plane vibrations, tryptophan, α-helix, and phospholipids), and 1,342 cm −1 (CH 2 /CH 3 wagging, twisting and/or bending, α-helix proteins, and phospholipids) were higher in the LGG group and lower in the HGG group than in the control group, and the reasons for these results need to be investigated further. PCA-LDA has been performed in the classification of Raman spectroscopy in cancer diagnosis and has exhibited highly accurate prediction results.…”

A comparative analysis of different biofluids towards ovarian cancer diagnosis using Raman microspectroscopy

“…Raman is a powerful technique for biological materials analysis, with applications ranging from cell imaging to cancer diagnosis [10][11][12]. Regarding ovarian cancer, Raman spectroscopy of tissue [13,14] as well as blood plasma and serum [15][16][17][18] has been reported. The main advantages of using biofluids rely in that sample preparation is not needed; hence, no reagents are required, and the liquid biopsies processing is less invasive than traditional tissue ones.…”