Acute leukemias are oncohematological diseases that compromise the bone marrow and have a complex diagnostic definition, leading to a high mortality when diagnosed late. This study proposed to determine the spectral differences between whole blood and plasma samples of healthy and leukemic subjects based on Raman spectroscopy (RS), correlating these differences with their resulting biochemical alterations and performing discriminant analysis of the samples (n ¼ 38 whole blood and n ¼ 40 plasma samples). Raman spectra were obtained using a dispersive Raman spectrometer (830-nm wavelength, 280-mW laser power, 30-s exposure time) with a Raman probe. The exploratory analysis based on principal component analysis (PCA) of the blood and plasma sample's spectra showed loading vectors with peaks related to amino acids, proteins, carbohydrates, lipids, and carotenoids, being the spectral differences related to amino acids and proteins for whole blood samples, and mainly carotenoids for plasma samples. Discriminant models based on partial least squares (PLS) and PCA were developed and classified the spectra as healthy or leukemic, with sensitivity of 91.9% (PLS) and 83.9% (PCA), specificity of 100% (both PLS and PCA), and overall accuracy of 96.5% (PLS) and 93.0% (PCA) for the whole blood spectra. In plasma, the sensitivity was 95.7% (PLS) and 11.6% (PCA), specificity of 98% (PLS) and 100% (PCA), and overall accuracy of 97.1% (PLS) and 64.1% (PCA). The study demonstrated that RS is a technique with potential to be applied in the diagnosis of acute leukemias in whole blood samples.

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.

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.

Background Wilm’s Tumor (WT) is the most common pediatric kidney cancer. Whereas most WTs are isolated, approximately 5% are associated with syndromes such as Denys-Drash (DDS), characterized by early onset nephropathy, disorders of sex development and predisposition to WT. Case presentation A 46,XY patient presenting with bilateral WT and genital ambiguity without nephropathy was heterozygous for the novel c.851_854dup variant in WT1 gene sequence. This variant affects the protein generating the frameshift p.(Ser285Argfs*14) that disrupts a nuclear localization signal (NLS) region. Conclusions This molecular finding is compatible with the severe scenario regarding the Wilm’s tumor presented by the patient even though nephropathy was absent.