Discrimination of leukemias and non-leukemic cancers in blood serum samples of children and adolescents using a Raman spectral model.

This study aimed to identify the differences presented in the Raman spectrum of blood serum from normal subjects compared to leukemic and non-leukemic subjects and the differences between the leukemics and non-leukemics, correlating the spectral differences with the biomolecules. Serum samples from children and adolescents were subjected to Raman spectroscopy (830 nm, laser power 350 mW; n = 566 spectra, being 72 controls, 269 leukemics, and 225 non-leukemics). Exploratory analysis based on principal component analysis (PCA) of the serum sample's spectra was performed. Classification models based on partial least squares discriminant analysis (PLS-DA) were developed to classify the spectra into normal, leukemic, and non-leukemic, as well as to discriminate spectra of leukemic from non-leukemic. The exploratory analysis showed principal components with peaks related to amino acids, proteins, lipids, and carotenoids. The spectral differences between normal, leukemic, and non-leukemic showed features assigned to proteins (serum features), amino acids, and carotenoids. The PLS-DA model classified the spectra of the normal group versus leukemic and non-leukemic groups with accuracy of 66%, sensitivity of 99%, and specificity of 57%. The PLS-DA discriminated the spectra of the leukemic and non-leukemic groups with accuracy of 67%, sensitivity of 72%, and specificity of 60%. The study showed that Raman spectroscopy is a technique that may be used for the biochemical differentiation of leukemias and other types of cancer in serum samples of children and adolescents. Nevertheless, building an extensive data library of Raman spectra from serum samples of controls, leukemics, and non-leukemics of different age groups is necessary to understand the findings better.