Identification of blood cell changes in pediatric oncological patients through Raman spectroscopy

Abstract

This study aimed to use the Raman spectroscopy technique to identify biochemical changes in blood cell samples of healthy, leukemic, and non‐leukemic subjects by principal component analysis (PCA) and to discriminate the groups by partial least squares discriminant analysis (PLS‐DA). For the study, 121 blood samples were collected from healthy children and adolescents among those with leukemia and other types of cancer (non‐leukemics). A volume of 80 μl of blood cells was placed in an aluminum sample holder and submitted to dispersive Raman spectroscopy (laser: 830 nm and 250 mW), with an exposure time of 30 s. A total of 308 Raman spectra were analyzed and indicated significant differences in the bands referred to nucleic acids (671 and 756 cm−1), amino acids (671, 1,215, and 1,544 cm−1), proteins (756, 1,215, 1,430, 1,531, and 1,548 cm−1), β‐carotene (1,531 cm−1), and cytochrome c (756 and 1,371 cm−1), showing higher intensity in normal samples. The analysis of the PCA variables (PCs) showed that there was a higher concentration of cytochrome c (633, 749, 855, 1,004, 1,127, 1,212, 1,370, 1,433, 1,531, and 1,614 cm−1), in the normal samples, and a higher concentration of phenylalanine (1,004 cm−1) was observed in the leukemic samples with statistically significant (ANOVA, p < 0.05). Discriminant analysis by PLS‐DA model classified the spectra into the groups normal (healthy), leukemic, and non‐leukemic with accuracy of 67.5%; when considering normal versus cancer, the accuracy increased to 98.3%, with sensitivity of 100% and specificity of 87.8%. Results demonstrated the applicability of Raman spectroscopy for analyzing biochemical compounds in blood cells, thus identifying the spectral differences between the groups normal, leukemic, and non‐leukemic (with other types of cancer). However, it presented a low accuracy due to classification errors when discriminating between the groups leukemic and non‐leukemic.