Optical Screening of Female Breast Cancer from Whole Blood Using Raman Spectroscopy

Abstract

This study is intended to develop a screening method for female breast cancer (BRC) from whole blood using Raman spectroscopy. A multivariate partial least squares (PLS) regression model is developed which is based upon Raman spectra of BRC-positive and healthy participants. It yields coefficients of regression at the corresponding Raman shifts. These coefficients represent the changes in molecular structures which are associated with the progress of disease. The present study pointed out some specific molecules which differentiated BRC-positive and healthy groups. In the BRC-positive group, a rising trend of calcium oxalate, calcium hydroxyapatite, phosphatidylserine and qunoid ring, and a lowering trend of tryptophan, tyrosine, and proline were observed in PLS-based coefficients of regression. The R-square value of the model was found to be 0.987, which is accepted clinically. The model was tested for the prediction of 50 randomly collected samples at a cutoff value of 0.5 with the gray region defined in the range of 0.4-0.6. Goodness of fit was estimated using accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curve, and area under ROC curve. All of these parameters were found to be very promising.

Microcalcifications in breast cancer: From pathophysiology to diagnosis and prognosis

“…This raises the possibility of utilising Raman analysis as a non-invasive, clinical imaging technique to identify calcifications likely to be representative of a malignancy. A recent study even found that Raman analysis of whole blood samples could detect Raman shifts characteristic of calcium oxalate and hydroxyapatite, which were elevated in blood from breast cancer patients (42).…”

<p>SERS-based differential diagnosis between multiple solid malignancies: breast, colorectal, lung, ovarian and oral cancer</p>

“…Several reports have shown that spontaneous Raman or SERS analysis of liquid or dried blood serum/plasma can efficiently discriminate between control and several types of cancer such as breast,21–23 lung,24 ovarian,25 colorectal,26–28 or head and neck cancer 29. In spite of that, the results of these preliminary studies cannot be compared directly, because of significant differences in the experimental setup employed for acquiring the SERS spectra of serum.…”

Raman spectroscopy of blood plasma samples from breast cancer patients at different stages

“…Notably, all the patients of the stage 4 are found very much distinct from each other, indicated by the clustering pattern of the Raman spectral data of this stage in the PCA scatter plots (Figure 5 a and Figure 6a) which may be due to the increase in the degree of the severity of the breast cancer, and the diversity of routes towards metastasis. This study advances previously published work related to the use of Raman spectroscopy for the characterization/diagnosis of breast cancer by using blood plasma/serum samples from clinically diagnosed patients, as the spectral markers of689 (Nucleotide conformation), 788 (phosphodiester bands in DNA), 828 (tyrosine/protein), 848 (most probably due to single bond stretching vibrations for amino acids and polysaccharides) and 1663 cm -1 (DNA) have not previously been identified.In these reports, Bilal et al applied Partial least squares(PLS) regression analysis to the Raman spectral data acquired from blood serum of breast cancer and healthy individuals and coefficients of regression were determinedwith sensitivity of 90% and specificity 75% which are associated with the changes at the bio-molecular level[23], while in the current study sensitivity and specificity have been found to be as high as 100% in the comparison of control and breast cancer samples. In another study, Pichardo-Molina et al applied Raman spectroscopy along with principal components analysis (PCA) and PCA-Linear Discriminate Analysis (LDA) to breast cancer and control blood samples, identifying specific bands which distinguish breast cancer blood serum samples from the healthy ones[24].…”

“…applied Partial least squares(PLS) regression analysis to the Raman spectral data acquired from blood serum of breast cancer and healthy individuals and coefficients of regression were determined which are associated with the changes at the bio-molecular level, hence indicating the development of the disease [23]. In another study, Pichardo-Molina et al applied Raman spectroscopy along with principal components analysis (PCA) and PCA-Linear Discriminate Analysis (LDA) to breast cancer and control blood samples, identifying specific bands which distinguish breast cancer blood serum samples from the healthy ones [24].…”