Background: In the randomized, phase 3 QUAZAR AML-001 trial, oral azacitidine (Oral-AZA) significantly prolonged overall survival (OS) compared with placebo (PBO) (median OS 24.7 vs 14.8 months [mo], respectively) in older patients (pts) with AML in first remission after intensive chemotherapy (IC). At an updated data cutoff performed in Sep 2020, 34.9% of pts in the Oral-AZA arm and 24.4% of pts in the PBO arm remained alive at ≥3 y from randomization. Aims: Assess clinical and biological variables associated with long-term survival (LTS) in QUAZAR AML-001. Methods: In all, 472 pts were randomized 1:1 to receive Oral-AZA 300 mg or PBO QD ×14d/28d within 4 mo of achieving first complete remission (CR) or CR with incomplete blood count recovery (CRi) after IC. The primary endpoint was OS, time from randomization until death, withdrawal of consent, or loss to follow-up. The LTS cohort comprised pts who were alive ≥3 y from randomization as of Sep 2020 and the non-LTS cohort included pts who died or were censored before 3 y. Variables assessed for association with LTS were diagnostic (Dx [pre-IC]) features (AML subtype, cytogenetic risk, NPM1 and FLT3 mutations [mut]); pre-study treatment (Tx) variables (response to IC [CR/CRi], receipt of consolidation, number of consolidation cycles); baseline (BL) demographic and disease characteristics, hematologic parameters (red blood cells [RBCs], hemoglobin, platelets, and leukocyte subsets), and measurable residual disease (MRD) status; and post-BL variables (MRD response [conversion from MRD+ at BL to MRD– on study], timing of MRD– [MRD– response on-study vs BL MRD–], and receipt of transplant after Tx discontinuation [D/C]). Associations of LTS with bone marrow immune parameters (CD3, CD4, and CD8 T-cell counts, and expression of PD-1/TIM-3 T-cell exhaustion markers) were investigated in a subset of pts (n=108). Variables were compared within Tx arms (LTS vs non-LTS) in univariate analyses with P values corrected for multiple testing. A logistic multivariable regression analysis of the effects of prognostic BL covariates on LTS was performed. Results: The LTS cohort included 83/238 pts (34.9%) in the Oral-AZA arm and 57/234 pts (24.4%) in the PBO arm. Within both arms, factors significantly associated with LTS were intermediate (Int)-risk cytogenetics and NPM1mut at Dx, and MRD response (MRD+ to MRD–) on study (Figure). MRD response rate was 2-fold higher with Oral-AZA vs PBO (37% vs 19%, respectively), and while early attrition was more common in the PBO arm, most MRD responses occurred within 6 mo. Factors significantly associated with LTS only in the PBO arm were BL (post-IC) MRD– status and receipt of transplant after Tx D/C. No significant associations were observed between BL hematological or immune parameters and LTS. The multivariable analysis (MVA) confirmed Oral-AZA Tx as independently significantly predictive of LTS vs PBO. Other covariates significantly associated with LTS in MVA were Int-risk cytogenetics and NPM1mut at Dx, and MRD– status at BL. Image:Summary/Conclusion: Oral-AZA Tx was significantly associated with LTS vs PBO. In univariate analysis, Int-risk cytogenetics and NPM1mut at Dx, and MRD response on-study, were significantly prognostic of LTS in both arms, whereas MRD– status at BL (post-IC) was associated with LTS only in the PBO arm.

Motivation: Patient and sample diversity is one of the main challenges when dealing with clinical cohorts in biomedical genomics studies. During last decade, several methods have been developed to identify biomarkers assigned to specific individuals or subtypes of samples. However, current methods still fail to discover markers in complex scenarios where heterogeneity or hidden phenotypical factors are present. Here, we propose a method to analyze and understand heterogeneous data avoiding classical normalization approaches of reducing or removing variation. Results: DEcomposing heterogeneous Cohorts using Omic data profiling (DECO) is a method to find significant association among biological features (biomarkers) and samples (individuals) analyzing large-scale omic data. The method identifies and categorizes biomarkers of specific phenotypic conditions based on a recurrent differential analysis integrated with a non-symmetrical correspondence analysis. DECO integrates both omic data dispersion and predictor-response relationship from non-symmetrical correspondence analysis in a unique statistic (called h-statistic), allowing the identification of closely related sample categories within complex cohorts. The performance is demonstrated using simulated data and five experimental transcriptomic datasets, and comparing to seven other methods. We show DECO greatly enhances the discovery and subtle identification of biomarkers, making it especially suited for deep and accurate patient stratification.

Background:The β‐thalassemias are a group of inherited disorders characterized by absent or reduced production of the β‐globin chains of hemoglobin (Hb), leading to ineffective erythropoiesis, chronic anemia, and multiple morbidities, and often require lifelong RBC transfusions. Increasing HbF is a therapeutic approach to rescuing the defect imposed by reduced/absent β‐globin in β‐thalassemias. Luspatercept is a first‐in‐class erythroid maturation agent that binds to select TGF‐β superfamily ligands and enhances late‐stage erythropoiesis by a mechanism that is still not fully understood. The phase 3, randomized, double‐blind, placebo‐controlled BELIEVE study evaluated the efficacy and safety of luspatercept in adult β‐thalassemia patients requiring regular RBC transfusions. In the BELIEVE study, treatment with luspatercept resulted in significant reductions in RBC transfusion burden compared with placebo.Aims:To explore the effects of luspatercept treatment on HbF levels in patients with RBC transfusion‐dependent (TD) β‐thalassemia, and to explore the relationship of HbF changes with transfusion burden reduction.Methods:In the BELIEVE study, 336 adults with TD β‐thalassemia were randomized to receive either luspatercept or placebo, administered subcutaneously every 21 days for 48 weeks, plus best supportive care. Hb variants were analyzed by HPLC and HbF was reported as a percentage of total Hb from whole blood samples collected at baseline and throughout the treatment period. P values were derived by 2‐tailed t‐test (parametric method) and Wilcoxon test (non‐parametric method). Differences in HbF changes during treatment were compared between responders and non‐responders (as defined by transfusion burden decrease of ≥33% over any 12 weeks), patients with baseline HbF≤1% and HbF>1%, and luspatercept‐ and placebo‐treated patients.Results:HbF levels increased by a mean 1.2‐fold in luspatercept‐treated patients beginning at Dose2 Day1, increasing to 2.5‐fold by the end of the evaluation period (Dose16 Day1). Mean change in HbF levels remained relatively unchanged in placebo‐treated patients through Dose16 Day1, ranging from 0.9‐ to 1.2‐fold of baseline levels.Among luspatercept‐treated patients starting at Dose5 until Dose16 Day1, HbF fold increase was greater in responders vs non‐responders (Dose5 Day1: 2.1 vs 1.8 mean fold increase, P < 0.024, Dose16 Day1: 2.7 vs 2.1 mean fold increase, P = 0.012). To determine whether changes in HbF were secondary to RBC transfusion reduction or a direct effect of luspatercept, a subgroup analysis was performed in patients with normal HbF (HbF≤1%) at baseline. In luspatercept‐treated patients with normal HbF at baseline, HbF increased by a mean 1.4‐fold in responders and 1.5‐fold in non‐responders, beginning at Dose2 Day1, and continued to increase to 3.8‐fold in responders and 2.9‐fold in non‐responders by Dose16 Day1, with no statistically significant difference between HbF changes in responders and non‐responders (Figure). HbF levels were not modulated in placebo‐treated patients. In luspatercept‐treated patients with elevated (>1%) levels of HbF at baseline, HbF levels increased more in responders compared with non‐responders (2.8 vs 2.0 mean fold increase, P = 0.009).Summary/Conclusion:Luspatercept treatment was associated with increased HbF in patients with RBC TD β‐thalassemia. This luspatercept treatment effect on increasing HbF levels was observed in both responders and non‐responders. Luspatercept‐mediated increases in HbF were observed early and maintained throughout the treatment period.image

Patients with lower-risk myelodysplastic syndromes (MDS) are affected primarily by symptoms of chronic anemia and fatigue rather than progression to acute myeloid leukemia. Severe thrombocytopenia, although less common in lower-risk MDS, is associated with increased risk of bleeding. For anemic patients, the principal aim of treatment is to improve anemia and decrease red blood cell transfusions. For transfusion-dependent patients with lower-risk MDS without chromosome 5q deletion [non-del(5q) MDS], there are limited effective treatments. Erythropoiesis-stimulating agents (ESAs) are generally first-line therapy, yielding frequent responses with a median duration of 18–24 months. Immunosuppressive therapy or allogeneic stem cell transplantation are restricted to select patients. New strategies for ESA-refractory or relapsed patients include lenalidomide, alone or in combination with ESAs; oral azacitidine; and new molecules such as the activin receptor type II ligand traps luspatercept and sotatercept. In thrombocytopenic patients, thrombopoietin receptor agonists are under evaluation. While trials to evaluate these treatment strategies are underway, efforts are needed to optimize therapies through better patient selection and response prediction as well as integrating molecular and genetic data into clinical practice. We provide an overview of current treatment approaches for lower-risk non-del(5q) MDS and explore promising directions for future research.

The presence of genetic changes is a hallmark of chronic lymphocytic leukemia (CLL). The most common cytogenetic abnormalities with independent prognostic significance in CLL are 13q14, ATM and TP53 deletions and trisomy 12. However, CLL displays a great genetic and biological heterogeneity. The aim of this study was to analyze the genomic imbalances in CLL cytogenetic subsets from both genomic and gene expression perspectives to identify new recurrent alterations.The genomic imbalances and expression levels of 67 patients were analyzed. The novel recurrent abnormalities detected with bacterial artificial chromosome array were confirmed by FISH and oligonucleotide microarrays. In all cases, gene expression profiling was assessed.Copy number alterations were identified in 75% of cases. Overall, the results confirmed FISH studies for the regions frequently involved in CLL and also defined a new recurrent gain on chromosome 20q13.12, in 19% (13/67) of the CLL patients. Oligonucleotide expression correlated with the regions of loss or gain of genomic material, suggesting that the changes in gene expression are related to alterations in copy number.Our study demonstrates the presence of a recurrent gain in 20q13.12 associated with overexpression of the genes located in this region, in CLL cytogenetic subgroups.

Specific microRNA (miRNA) signatures have been associated with different cytogenetic subtypes in acute leukemias. This finding prompted us to investigate potential associations between genetic abnormalities in multiple myeloma (MM) and singular miRNA expression profiles. Moreover, global gene expression profiling was also analyzed to find correlated miRNA gene expression and select miRNA target genes that show such correlation. For this purpose, we analyzed the expression level of 365 miRNAs and the gene expression profiling in 60 newly diagnosed MM patients, selected to represent the most relevant recurrent genetic abnormalities. Supervised analysis showed significantly deregulated miRNAs in the different cytogenetic subtypes as compared with normal PC. It is interesting to note that miR-1 and miR-133a clustered on the same chromosomal loci, were specifically overexpressed in the cases with t(14;16). The analysis of the relationship between miRNA expression and their respective target genes showed a conserved inverse correlation between several miRNAs deregulated in MM cells and CCND2 expression level. These results illustrate, for the first time, that miRNA expression pattern in MM is associated with genetic abnormalities, and that the correlation of the expression profile of miRNA and their putative mRNA targets is useful to find statistically significant protein-coding genes in MM pathogenesis associated with changes in specific miRNAs.