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.

We analyzed the pattern of whole-genome copy number alterations (CNAs) and their association with the kinetics of blast clearance during the induction treatment among 195 pediatric patients with B-cell precursor acute lymphoblastic leukemia (BCP-ALL) who displayed intermediate or high levels of minimal residual disease (MRD). Using unsupervised hierarchical clustering of CNAs > 5 Mbp, we dissected three clusters of leukemic samples with distinct kinetics of blast clearance [A – early slow responders (n=105), B – patients with persistent leukemia (n=24), C – fast responders with the low but detectable disease at the end of induction (n=66)] that corresponded with the patients’ clinical features, the microdeletion profile,the presence of gene fusions and patients survival. Low incidence of large CNAs and chromosomal numerical aberrations occurred in cluster A which included ALL samples showing recurrent microdeletions within the genes encoding transcription factors (i.e., IKZF1, PAX5, ETV6, and ERG), DNA repair genes (XRCC3 and TOX), or harboring chromothriptic pattern of CNAs. Low hyperdiploid karyotype with trisomy 8 or hypodiploidy was predominantly observed in cluster B. Whereas cluster C included almost exclusively high-hyperdiploid ALL samples with concomitant mutations in RAS pathway genes. The pattern of CNAs influences the kinetics of leukemic cell clearance and selected aberrations affecting DNA repair genes may contribute to BCP-ALL chemoresistance.