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The KMT2A (MLL) gene rearrangements (KMT2A-r) are associated with a diverse spectrum of acute leukemias. Although most KMT2A-r are restricted to nine partner genes, we have recently revealed that KMT2A-USP2 fusions are often missed during FISH screening of these genetic alterations. Therefore, complementary methods are important for appropriate detection of any KMT2A-r. Here we use a machine learning model to unravel the most appropriate markers for prediction of KMT2A-r in various types of acute leukemia. A Random Forest and LightGBM classifier was trained to predict KMT2A-r in patients with acute leukemia. Our results revealed a set of 20 genes capable of accurately estimating KMT2A-r. The SKIDA1 (AUC: 0.839; CI: 0.799–0.879) and LAMP5 (AUC: 0.746; CI: 0.685–0.806) overexpression were the better markers associated with KMT2A-r compared to CSPG4 (also named NG2; AUC: 0.722; CI: 0.659–0.784), regardless of the type of acute leukemia. Of importance, high expression levels of LAMP5 estimated the occurrence of all KMT2A-USP2 fusions. Also, we performed drug sensitivity analysis using IC50 data from 345 drugs available in the GDSC database to identify which ones could be used to treat KMT2A-r leukemia. We observed that KMT2A-r cell lines were more sensitive to 5-Fluorouracil (5FU), Gemcitabine (both antimetabolite chemotherapy drugs), WHI-P97 (JAK-3 inhibitor), Foretinib (MET/VEGFR inhibitor), SNX-2112 (Hsp90 inhibitor), AZD6482 (PI3Kβ inhibitor), KU-60019 (ATM kinase inhibitor), and Pevonedistat (NEDD8-activating enzyme (NAE) inhibitor). Moreover, IC50 data from analyses of ex-vivo drug sensitivity to small-molecule inhibitors reveals that Foretinib is a promising drug option for AML patients carrying FLT3 activating mutations. Thus, we provide novel and accurate options for the diagnostic screening and therapy of KMT2A-r leukemia, regardless of leukemia subtype.
Background: Acute leukemia in early age (EAL) is characterized by acquired genetic alterations such as MLL rearrangements (MLL-r). The aim of this case-controlled study was to investigate whether single nucleotide polymorphisms (SNPs) of IKZF1, ARID5B, and CEBPE could be related to the onset of EAL cases (<24 months-old at diagnosis).
Methods: The SNPs (IKZF1 rs11978267, ARID5B rs10821936 and rs10994982, CEBPE rs2239633) were genotyped in 265 cases [169 acute lymphoblastic leukemia (ALL) and 96 acute myeloid leukaemia (AML)] and 505 controls by Taqman allelic discrimination assay. Logistic regression was used to evaluate the association between SNPs of cases and controls, adjusted on skin color and/or age. The risk was determined by calculating odds ratios (ORs) with 95% confidence interval (CI).
Results: Children with the IKZF1 SNP had an increased risk of developing MLL-germline ALL in white children. The heterozygous/mutant genotype in ARID5B rs10994982 significantly increased the risk for MLL-germline leukemia in white and non-white children (OR 2.60, 95% CI: 1.09-6.18 and OR 3.55, 95% CI: 1.57-8.68, respectively). The heterozygous genotype in ARID5B rs10821936 increased the risk for MLL-r leukemia in both white and non-white (OR 2.06, 95% CI: 1.12-3.79 and OR 2.36, 95% CI: 1.09-5.10, respectively). Furthermore, ARID5B rs10821936 conferred increased risk for MLL-MLLT3 positive cases (OR 7.10, 95% CI:1.54-32.68). Our data do not show evidence that CEBPE rs2239633 confers increased genetic susceptibility to EAL.
Conclusions: IKZF1 and CEBPE variants seem to play a minor role in genetic susceptibility to EAL, while ARID5B rs10821936 increased the risk of MLL-MLLT3. This result shows that genetic susceptibility could be associated with the differences regarding MLL breakpoints and partner genes.