Prediction of Response to FDA-Approved Targeted Therapy and Immunotherapy in Acute Lymphoblastic Leukemia (ALL).

OPINION STATEMENT: Acute lymphoblastic leukemia (ALL) represents the predominant cancer in pediatric populations, though its occurrence in adults is relatively rare. Pre-treatment risk stratification is crucial for predicting prognosis. Important factors for assessment include patient age, white blood cell (WBC) count at diagnosis, extramedullary involvement, immunophenotype, and cytogenetic aberrations. Minimal residual disease (MRD), primarily assessed by flow cytometry following remission, plays a substantial role in guiding management plans. Over the past decade, significant advancements in ALL outcomes have been witnessed. Conventional chemotherapy has remarkably reduced mortality rates; however, its intensive nature raises safety concerns and has led to the emergence of treatment-resistant cases with recurrence of relapses. Consequently, The U.S. Food and Drug Administration (FDA) has approved several novel treatments for relapsed/refractory ALL due to their demonstrated efficacy, as indicated by improved complete remission and survival rates. These treatments include tyrosine kinase inhibitors (TKIs), the anti-CD19 monoclonal antibody blinatumomab, anti-CD22 inotuzumab ozogamicin, anti-CD20 rituximab, and chimeric antigen receptor (CAR) T-cell therapy. Identifying the variables that influence treatment decisions is a pressing necessity for tailoring therapy based on heterogeneous patient characteristics. Key predictive factors identified in various observational studies and clinical trials include prelymphodepletion disease burden, complex genetic abnormalities, and MRD. Furthermore, the development of serious adverse events following treatment could be anticipated through predictive models, allowing for appropriate prophylactic measures to be considered. The ultimate aim is to incorporate the concept of precision medicine in the field of ALL through valid prediction platform to facilitate the selection of the most suitable treatment approach.

Prognostic significance of early platelet count decline in preterm newborns.

OBJECTIVES: Decline of platelets with or without thrombocytopenia is observed in critically ill preterm newborns. Prognostic significance of platelets count in Neonatal Intensive Care Unit focused on outcome after thrombocytopenia. We aimed to estimate the changes in platelets count within the first 7 days of life in preterm newborns and its relation to final outcomes. METHODS: Retrospectively, the platelets count during the first 7 days of life, and its association with mortality, length of stay among survivors (LOS), and later severe morbidities were determined. Appropriate regression analyses were used to examine possible relations between studied variables. RESULTS AND DISCUSSION: Platelets drop that did not reach thrombocytopenia level in the first 7 days of life happened in 61.7%. Platelets count drop in the first 7 days of life was a predictor of mortality, LOS, and major morbidities such as intraventricular hemorrhage and necrotizing enterocolitis. CONCLUSIONS: Platelets count drop within the first 7 days of life independent of thrombocytopenia can be used to predict increased mortality, LOS, and the development of later severe morbidities in critically ill preterm neonates.

Synergisitic and Antagonistic AML Cell Type-specific Responses to 5-Aza-2-deoxycitidine and 1-h-D-Arabinofuranoside.

BACKGROUND: The search for synergistic drug combinations is critical to the treatment of drug-resistant cancer, such as acute myeloid leukemia (AML). Characterizing RNA expression associated with 5-aza-2'-deoxycytidine (DAC) and 1-h-D-arabinofuranosylcytosine (Ara-C) is a critical step to increase the efficacy of their combinatorial therapies. MATERIALS AND METHODS: After 72 h of single-dose treatments of AML cells with DAC or Ara-C, the half-maximal effective concentration of DAC and Ara-C and the drug combination index were assessed. RESULTS: Pre-treatment with DAC restores cellular sensitivity in Ara-C-resistant AML cells. In contrast, DAC/Ara-C combinations are antagonistic in other Ara-C-sensitive AML cells. CONCLUSION: Our results provide an alternative approach for predicting what combinations, dosing and scheduling of drug delivery should be used to better individualize therapy of AML.