Discrimination of serum Raman spectroscopy between normal and colorectal cancer using selected parameters and regression-discriminant analysis

Abstract

Raman spectroscopy of tissues has been widely studied for the diagnosis of various cancers, but biofluids were seldom chosen as the analyte because of the low concentration. Herein, serum of 30 normal people, 46 colon cancer, and 44 rectum cancer patients were measured using Raman spectra and analyzed. The information of Raman peaks (intensity and width) and that of the fluorescence background (baseline function coefficients) were selected as parameters for statistical analysis. Principal component regression (PCR) and partial least square regression (PLSR) were used on the selected parameters separately to see the diagnosing performance of the parameters. PCR performed better than PLSR in our spectral data. Then linear discriminant analysis (LDA) was used on the principal components (PCs) of the two regression methods on the selected parameters, and the diagnostic accuracy were 88% and 83%. The conclusion is that the selected parameters can maintain the information of the original spectra well and Raman spectroscopy of serum has the potential for the diagnosis of colorectal cancer.

Characterization and Visualization of Vesicles in the Endo-Lysosomal Pathway with Surface-Enhanced Raman Spectroscopy and Chemometrics

“…These challenges have been addressed by applying various chemometric methods, such as principal component (PCA) 10,[14][15][16][17][18] and linear discriminant analysis (LDA), 14,19,20 least square regression 14,21,22 as well as cluster analysis, 17,23,24 which mostly aim at the extraction of representative spectral features for the characterization and/or classification of the sample. 7,14,17,25,26 Furthermore, traditional SERS analysis, including that in the SERS reporter approach, relies on the comparison of spectra from an unknown sample to either: (i) one or more known reference spectral features from a Raman library/literature or (ii) pure samples of expected components.…”

Emerging targets in lipid-based therapy

“…Algorithms that organize the comprehensive Raman spectrum, and that sort malignant and normal profiles through assignment by discriminant function analyses, already exist and have been applied, for example, to the analysis of human ductal carcinoma cells in a mouse model of human pancreatic cancer [251]. In addition to tissue analyses, biofluids such as serum appear to have potential spectral reporters of carcinoma as well with this methodology [252–254]. The technique was appreciated for its potential in medical applications more than a decade ago and has been steadily proving its value since then [255–257].…”

Role of Raman spectroscopy and surface enhanced Raman spectroscopy in colorectal cancer

“…Raman spectroscopy offers the possibility of determining the presence of malignancy by detecting differences in Raman spectral features between normal and malignant tissue. Previously, Raman spectroscopy has been applied to in vivo probes that have the ability to discriminate multiple tissue types [35,36] , biofluid analysis [37] and also analysis of cancerous cell lines for both discrimination and characterization [38,39] . The motivation behind using Raman used in vivo is to aid rapid diagnosis and help to identify possible areas of tissue for biopsy that might otherwise be missed.…”

“…Using Raman spectroscopy and LDA analysis alone the study found this technique to have approximately 65% specificity and sensitivity for the discrimination of cancer in peripheral blood samples. The use of non-enhanced Raman spectroscopy for the discrimination of blood serum between normal and CRC was first reported by Li et al [37] (2012). Li et al [37] presents a study using clinical samples from 44 colon, 46 rectum and 30 healthy controls.…”

“…The use of non-enhanced Raman spectroscopy for the discrimination of blood serum between normal and CRC was first reported by Li et al [37] (2012). Li et al [37] presents a study using clinical samples from 44 colon, 46 rectum and 30 healthy controls. Raman peak parameters and fluorescence background were used along with multivariate analysis techniques such as PCR and PLSR for the dimension deduction of spectral data.…”