The nucleoside analog azacitidine (AZA) is used in the treatment of myelodysplastic syndromes (MDS), but 30–40% of patients fail to respond or relapse after treatment. Hence, to identify new molecular alterations that allow for identification of patients unlikely to respond to AZA could impact the utility of this therapy. We determined the expression levels of genes involved in AZA metabolism: UCK1, UCK2, DCK, hENT1, RRM1 and RRM2 using quantitative PCR in samples from 57 patients with MDS who received AZA. Lower expression of UCK1 was seen in patients without a response to AZA (median 0.2 vs 0.49 for patients with response to AZA, P=0.07). This difference in UCK1 expression was not influenced by aberrant methylation of the UCK1 promoter. In addition, the seven polymorphic loci found in the coding sequence were not associated with UCK1 gene expression nor AZA response. Silencing of UCK1 by siRNA leads to blunted response to AZA in vitro. The univariate analysis revealed that patients expressing lower than median levels of UCK1 had a shorter overall survival (P=0.049). Our results suggest that expression level of UCK1 is correlated with clinical outcome and may influence the clinical response to AZA treatment in patients with MDS.

The immunophenotype is a key element to classify B-cell Non-Hodgkin Lymphomas (B-NHL); while it is routinely obtained through immunohistochemistry, the use of flow cytometry (FC) could bear several advantages. However, few FC laboratories can rely on a long-standing practical experience, and the literature in support is still limited; as a result, the use of FC is generally restricted to the analysis of lymphomas with bone marrow or peripheral blood involvement. In this work, we applied machine learning to our database of 1465 B-NHL samples from different sources, building four artificial predictive systems which could classify B-NHL in up to nine of the most common clinico-pathological entities. Our best model shows an overall accuracy of 92.68%, a mean sensitivity of 88.54% and a mean specificity of 98.77%. Beyond the clinical applicability, our models demonstrate (i) the strong discriminatory power of MIB1 and Bcl2, whose integration in the predictive model significantly increased the performance of the algorithm; (ii) the potential usefulness of some non-canonical markers in categorizing B-NHL; and (iii) that FC markers should not be described as strictly positive or negative according to fixed thresholds, but they rather correlate with different B-NHL depending on their level of expression.

The connection with acute myelogenous leukemia (AML) of dihydroorotate dehydrogenase (hDHODH), a key enzyme in pyrimidine biosynthesis, has attracted significant interest from pharma as a possible AML therapeutic target. We recently discovered compound 1, a potent hDHODH inhibitor (IC₅₀ = 1.2 nM), able to induce myeloid differentiation in AML cell lines (THP1) in the low nM range (EC₅₀ = 32.8 nM) superior to brequinar’s phase I/II clinical trial (EC₅₀ = 265 nM). Herein, we investigate the 1 drug-like properties observing good metabolic stability and no toxic profile when administered at doses of 10 and 25 mg/kg every 3 days for 5 weeks (Balb/c mice). Moreover, in order to identify a backup compound, we investigate the SAR of this class of compounds. Inside the series, 17 is characterized by higher potency in inducing myeloid differentiation (EC₅₀ = 17.3 nM), strong proapoptotic properties (EC₅₀ = 20.2 nM), and low cytotoxicity toward non-AML cells (EC₃₀(Jurkat) > 100 μM).

Dihydroorotate Dehydrogenase (DHODH) is a key enzyme of the de novo pyrimidine biosynthesis, whose inhibition can induce differentiation and apoptosis in acute myeloid leukemia (AML). DHODH inhibitors had shown promising in vitro and in vivo activity on solid tumors, but their effectiveness was not confirmed in clinical trials, probably because cancer cells exploited the pyrimidine salvage pathway to survive. Here, we investigated the antileukemic activity of MEDS433, the DHODH inhibitor developed by our group, against AML. Learning from previous failures, we mimicked human conditions (performing experiments in the presence of physiological uridine plasma levels) and looked for synergic combinations to boost apoptosis, including classical antileukemic drugs and dipyridamole, a blocker of the pyrimidine salvage pathway. MEDS433 induced apoptosis in multiple AML cell lines, not only as a consequence of differentiation, but also directly. Its combination with antileukemic agents further increased the apoptotic rate, but when experiments were performed in the presence of physiological uridine concentrations, results were less impressive. Conversely, the combination of MEDS433 with dipyridamole induced metabolic lethality and differentiation in all AML cell lines; this extraordinary synergism was confirmed on AML primary cells with different genetic backgrounds and was unaffected by physiological uridine concentrations, predicting in human activity.