Raman spectroscopy can recognize the KMT2A rearrangement as a distinct subtype of leukemia.

Acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) are the two most common hematologic malignancies, challenging to treat and associated with high recurrence and mortality rates. This work aims to identify specific Raman biomarkers of ALL cells with the KMT2A gene rearrangement (KMT2A-r), representing a highly aggressive subtype of childhood leukemia with a poor prognosis. The proposed approach combines the sensitivity and specificity of Raman spectroscopy with machine learning and allows us to distinguish not only myelo- and lymphoblasts but also discriminate B-cell precursor (BCP) ALL with KMT2A-r from other blasts of BCP-ALL. We have found that KMT2A-r ALL cells fixed with 0.5% glutaraldehyde exhibit a unique spectroscopic profile that enables us to identify this subtype from other leukemias and normal cells. Therefore, a rapid and label-free method was developed to identify ALL blasts with KMT2A-r based on the ratio of the two Raman bands assigned to phenylalanine - 1040 and 1008 cm-1. This is the first time that a particular group of leukemic cells has been identified in a label-free way. The identified biomarker can be used as a screening method in diagnostic laboratories or non-reference medical centers.

Automatic subtyping of Diffuse Large B-cell Lymphomas (DLBCL): Raman-based genetic and metabolic classification.

Diffuse large B-cell lymphoma (DLBCL), the most common non-Hodgkin's lymphoma in adults, is a genetically and metabolically heterogeneous group of aggressive malignancies. The complexity of their molecular composition and the variability in clinical presentation make clinical diagnosis and treatment selection a serious challenge. The challenge is therefore to quickly and correctly classify DLBCL cells. In this work, we show that Raman imaging is a tool with high diagnostic potential, providing unique information about the biochemical components of tumor cells and their metabolism. We present models of classification of lymphoma cells based on their Raman spectra. The models automatically and efficiently identify DLBCL cells and assign them to a given cell-of-origin (COO) subtype (activated B cell-like (ABC) or germinal center B cell-like (GCB)) or, respectively, to a comprehensive cluster classification (CCC) subtype (OxPhos/non-OxPhos). In addition, we describe each lymphoma subtype by its unique spectral profile, linking it to biochemical, genetic, or metabolic features.

Raman classification of selected subtypes of acute lymphoblastic leukemia (ALL).

B-cell precursor acute lymphoblastic leukemia (BCP-ALL) with chromosome translocations like KMT2A gene rearrangement (KMT2A-r) and BCR-ABL1 fusion gene have been recognized as crucial drivers in both BCP-ALL leukemogenesis and treatment management. Standard diagnostic protocols for proliferative diseases of the hematopoietic system, like KMT2A-r-ALL, are genetically based and strongly molecularly oriented. Therefore, an efficient diagnostic procedure requires not only experienced and multidisciplinary laboratory staff but also considerable instrumentation and material costs. In recent years, a Raman spectroscopy method has been increasingly used to detect subtle chemical changes in individual cells resulting from stress or disease. Therefore, the objective of this study was to identify Raman signatures for the molecular subtypes and to develop a classification method based on the unique spectroscopic profile of in vitro models that represent specific aberrations aimed at KMT2A-r (RS4;11, and SEM) and the BCR-ABL1 fusion gene (SUP-B15, BV-173, and SD-1). Data analysis was based on chemometric methods, i.e. principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and support vector machine (SVM). The PCA-based multivariate model was used for pattern recognition of each investigated group of cells while PLS-DA and SVM were used to build models for the discrimination of spectra from the studied BCP-ALL molecular subtypes. The results showed that the studied molecular subtypes of ALL have characteristic spectroscopic profiles reflecting their peculiar biochemical state. The content of lipids (1600 cm-1), nucleic acids (789 cm-1), and haemoproteins (754, 1130, and 1315 cm-1), which are crucial in cell metabolism, was indicated as the main source of differentiation between subtypes. Identification of spectroscopic markers of cells with BCR-ABL1 or KMT2A-r may be useful in pharmacological studies to monitor the effectiveness of chemotherapy and further to understand differences in molecular responses between leukemia primary cells and cell lines.