Biological versus Clinical Risk Factors in Acute Myeloid Leukemia: Is There a Winner?

We present a case of a patient with a three-month history of peripheral blood cytopenia without a confirmed diagnosis of myelodysplastic syndrome, who developed a favourable-risk acute myeloid leukemia (AML), according to the European Leukemia Net (ELN) criteria. The patient achieved a complete remission with incomplete platelet recovery (CRi) after induction. The patient achieved the morphological CR after the first consolidation and completed the first-line treatment with a syngeneic stem cell transplantation (SCT). A disease relapse occurred after one year of CR (blast cell count in the bone marrow 15%), and the patient was offered a haplo-SCT, which he refused due to personal reasons. In this paper, we discuss the interplay between clinical and biological risk factors in non-high-risk AML patients and speculate that some old clinical risk factors (e.g., age of the patient, achievement of CR after induction, and previous history of myelodysplastic syndrome) may still impact on the treatment decision algorithm of some of these patients.

Identification of Novel Components of Target-of-Rapamycin Signaling Pathway by Network-Based Multi-Omics Integrative Analysis.

Target of rapamycin (TOR) is a major signaling pathway and regulator of cell growth. TOR serves as a hub of many signaling routes, and is implicated in the pathophysiology of numerous human diseases, including cancer, diabetes, and neurodegeneration. Therefore, elucidation of unknown components of TOR signaling that could serve as potential biomarkers and drug targets has a great clinical importance. In this study, our aim is to integrate transcriptomics, interactomics, and regulomics data in Saccharomyces cerevisiae using a network-based multiomics approach to enlighten previously unidentified, potential components of TOR signaling. We constructed the TOR-signaling protein interaction network, which was used as a template to search for TOR-mediated rapamycin and caffeine signaling paths. We scored the paths passing from at least one component of TOR Complex 1 or 2 (TORC1/TORC2) using the co-expression levels of the genes in the transcriptome data of the cells grown in the presence of rapamycin or caffeine. The resultant network revealed seven hitherto unannotated proteins, namely, Atg14p, Rim20p, Ret2p, Spt21p, Ylr257wp, Ymr295cp, and Ygr017wp, as potential components of TOR-mediated rapamycin and caffeine signaling in yeast. Among these proteins, we suggest further deciphering of the role of Ylr257wp will be particularly informative in the future because it was the only protein whose removal from the constructed network hindered the signal transduction to the TORC1 effector kinase Npr1p. In conclusion, this study underlines the value of network-based multiomics integrative data analysis in discovering previously unidentified components of the signaling networks by revealing potential components of TOR signaling for future experimental validation.

Digital PCR improves the quantitation of DMR and the selection of CML candidates to TKIs discontinuation.

Treatment-free remission (TFR) by tyrosine kinase inhibitors (TKI) discontinuation in patients with deep molecular response (DMR) is a paramount goal in the current chronic myeloid leukemia (CML) therapeutic strategy. The best DMR level by real-time quantitative PCR (RT-qPCR) for TKI discontinuation is still a matter of debate. To compare the accuracy of digital PCR (dPCR) and RT-qPCR for BCR-ABL1 transcript levels detection, 142 CML patients were monitored for a median time of 24 months. Digital PCR detected BCR-ABL1 transcripts in the RT-qPCR undetectable cases. The dPCR analysis of the samples, grouped by the MR classes, revealed a significant difference between MR4.0 and MR4.5 (P = 0.0104) or MR5.0 (P = 0.0032). The clinical and hematological characteristics of the patients grouped according to DMR classes (MR4.0 vs MR4.5-5.0 ) were superimposable. Conversely, patients with dPCR values <0.468 BCR-ABL1 copies/µL (as we previously described) showed a longer DMR duration (P = 0.0220) and mainly belonged to MR4.5-5.0 (P = 0.0442) classes compared to patients with higher dPCR values. Among the 142 patients, 111 (78%) discontinued the TKI treatment; among the 111 patients, 24 (22%) lost the MR3.0 or MR4.0 . RT-qPCR was not able to discriminate patients with higher risk of MR loss after discontinuation (P = 0.8100). On the contrary, according to dPCR, 12/25 (48%) patients with BCR-ABL1 values ≥0.468 and 12/86 (14%) patients with BCR-ABL1 values <0.468 lost DMR in this cohort, respectively (P = 0.0003). Treatment-free remission of patients who discontinued TKI with a dPCR <0.468 was significantly higher compared to patients with dPCR ≥ 0.468 (TFR at 2 years 83% vs 52% P = 0.0017, respectively). In conclusion, dPCR resulted in an improved recognition of stable DMR and of candidates to TKI discontinuation.

Saccharomyces cerevisiae adapted to grow in the presence of low-dose rapamycin exhibit altered amino acid metabolism.

BACKGROUND: Rapamycin is a potent inhibitor of the highly conserved TOR kinase, the nutrient-sensitive controller of growth and aging. It has been utilised as a chemotherapeutic agent due to its anti-proliferative properties and as an immunosuppressive drug, and is also known to extend lifespan in a range of eukaryotes from yeast to mammals. However, the mechanisms through which eukaryotic cells adapt to sustained exposure to rapamycin have not yet been thoroughly investigated. METHODS: Here, S. cerevisiae response to long-term rapamycin exposure was investigated by identifying the physiological, transcriptomic and metabolic differences observed for yeast populations inoculated into low-dose rapamycin-containing environment. The effect of oxygen availability and acidity of extracellular environment on this response was further deliberated by controlling or monitoring the dissolved oxygen level and pH of the culture. RESULTS: Yeast populations grown in the presence of rapamycin reached higher cell densities complemented by an increase in their chronological lifespan, and these physiological adaptations were associated with a rewiring of the amino acid metabolism, particularly that of arginine. The ability to synthesise amino acids emerges as the key factor leading to the major mechanistic differences between mammalian and microbial TOR signalling pathways in relation to nutrient recognition. CONCLUSION: Oxygen levels and extracellular acidity of the culture were observed to conjointly affect yeast populations, virtually acting as coupled physiological effectors; cells were best adapted when maximal oxygenation of the culture was maintained in slightly acidic pH, any deviation necessitated more extensive readjustment to additional stress factors.