New Insights into the Multivariate Analysis of SER Spectra Collected on Blood Samples for Prostate Cancer Detection: Towards a Better Understanding of the Role Played by Different Biomolecules on Cancer Screening: A Preliminary Study

Abstract

It is possible to obtain diagnostically relevant data on the changes in biochemical elements brought on by cancer via the use of multivariate analysis of vibrational spectra recorded on biological fluids. Prostate cancer and control groups included in this research generated almost similar SERS spectra, which means that the values of peak intensities present in SERS spectra can only give unspecific and limited information for distinguishing between the two groups. Our diagnostic algorithm for prostate cancer (PCa) differentiation was built using principal component analysis and linear discriminant analysis (PCA-LDA) analysis of spectral data, which has been widely used in spectral data management in many studies and has shown promising results so far. In order to fully utilize the entire SERS spectrum and automatically determine the most meaningful spectral features that can be used to differentiate PCa from healthy patients, we perform a multivariate analysis on both the entire and specific spectral intervals. Using the PCA-LDA model, the prostate cancer and control groups are clearly distinguished in our investigation. The separability of the following two data sets is also evaluated using two alternative discrimination techniques: principal least squares discriminant analysis (PLS-DA) and principal component analysis—support vector machine (PCA-SVM).

High-Accuracy Renal Cell Carcinoma Discrimination through Label-Free SERS of Blood Serum and Multivariate Analysis

“…Collagen [34,36], phospholipids [34,36], hypoxanthine [33,38], δ(CH2/CH3) [20,22,35,38] ergothioneine [32] 1575 1576-1585 δ(C=C) of phenylalanine [28,30,33,34,36], acetoacetate [34,36,38], riboflavin [30,34,35], DNA/RNA bases [29], uric acid [20], amide II [20] hypoxanthine [22] ergothioneine [32] Amide II 1657 1640-1680 ν(C=O) of amide I with the α-helix conformation [20,28,29,[34][35][36]39] or collagen [30,31] Amid I α helix 2107 2108 Thiocyanate [40] Thiocyanate ν-stretching, δ-bending, τ-twisting.…”

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

“…SVM in combination with SERS has been used for the early detection of oral cancer among patients using serum and saliva samples and achieved an accuracy of 80% [ 227 ]. Prostate cancer has been extensively studied and successfully identified using different techniques, such as serum analysis combined with PCA-SVM [ 228 ]; detection of prostate specific antigens [ 229 , 230 , 231 , 232 ]; EVs combined with CNN [ 230 ]; miRNAs [ 233 ]; different multivariate techniques, e.g., PCA-LDA and PCA-SVM [ 234 ]; and urine profiling [ 235 ].…”

Developing New Diagnostic Tools Based on SERS Analysis of Filtered Salivary Samples for Oral Cancer Detection

“…SERS substrate consisted of plasmonic silver nanoparticles synthesized according to a method developed by Leopold and Lendl [22], which was widely explored by our group in various studies [20,[23][24][25][26][27]. The synthesis procedure refers to the reduction in silver nitrate ions to silver nanoparticles in the presence of hydroxylamine molecules.…”

“…After 30 min, the samples were ready to be measured. All the samples were prepared using the same batch of silver colloids, and interand intrabatch reproducibility was assessed for several other biological fluids [8,20,24,27].…”