Relationship between comorbidities, mutational profile, and outcome after intensive chemotherapy in patients older than 60 years with acute myeloid leukemia: Assessment of different risk scores.

The aim of this study was to evaluate how comorbidities and molecular landscape relate to outcome in patients with acute myeloid leukemia (AML) aged 60 years or older who received intensive induction therapy. In 91 patients, 323 mutations were identified in 77 genes by next-generation sequencing, with a median of four mutations per patient, with NPM1, FLT3, TET2, and DNMT3A being the most frequently mutated genes. A multistate model identified FLT3, IDH2, RUNX1, and TET2 mutations as associated with a higher likelihood of achieving complete remission while STAG2 mutations were associated with primary refractory disease, and DNMT3A, FLT3, IDH2, and TP53 mutations with mortality after relapse. Ferrara unfitness criteria and performance status were the best predictors of short-term outcome (area under the curve = 82 for 2-month survival for both parameters), whereas genomic classifications better predicted long-term outcome, with the Patel risk stratification performing the best over the 5-year follow-up period (C-index = 0.63 for event-free and overall survival). We show that most genomic prognostic classifications, mainly used in younger patients, are useful for classifying older patients, but to a lesser extent, because of different mutational profiles. Specific prognostic classifications, incorporating performance status, comorbidities, and cytogenetic/molecular data, should be specifically designed for patients over 60 years.

Intergenic ORFs as elementary structural modules of de novo gene birth and protein evolution.

The noncoding genome plays an important role in de novo gene birth and in the emergence of genetic novelty. Nevertheless, how noncoding sequences' properties could promote the birth of novel genes and shape the evolution and the structural diversity of proteins remains unclear. Therefore, by combining different bioinformatic approaches, we characterized the fold potential diversity of the amino acid sequences encoded by all intergenic open reading frames (ORFs) of S. cerevisiae with the aim of (1) exploring whether the structural states' diversity of proteomes is already present in noncoding sequences, and (2) estimating the potential of the noncoding genome to produce novel protein bricks that could either give rise to novel genes or be integrated into pre-existing proteins, thus participating in protein structure diversity and evolution. We showed that amino acid sequences encoded by most yeast intergenic ORFs contain the elementary building blocks of protein structures. Moreover, they encompass the large structural state diversity of canonical proteins, with the majority predicted as foldable. Then, we investigated the early stages of de novo gene birth by reconstructing the ancestral sequences of 70 yeast de novo genes and characterized the sequence and structural properties of intergenic ORFs with a strong translation signal. This enabled us to highlight sequence and structural factors determining de novo gene emergence. Finally, we showed a strong correlation between the fold potential of de novo proteins and one of their ancestral amino acid sequences, reflecting the relationship between the noncoding genome and the protein structure universe.

Genomic analysis of primary and secondary myelofibrosis redefines the prognostic impact of ASXL1 mutations: a FIM study.

We aimed to study the prognostic impact of the mutational landscape in primary and secondary myelofibrosis. The study included 479 patients with myelofibrosis recruited from 24 French Intergroup of Myeloproliferative Neoplasms (FIM) centers. The molecular landscape was studied by high-throughput sequencing of 77 genes. A Bayesian network allowed the identification of genomic groups whose prognostic impact was studied in a multistate model considering transitions from the 3 conditions: myelofibrosis, acute leukemia, and death. Results were validated using an independent, previously published cohort (n = 276). Four genomic groups were identified: patients with TP53 mutation; patients with ≥1 mutation in EZH2, CBL, U2AF1, SRSF2, IDH1, IDH2, NRAS, or KRAS (high-risk group); patients with ASXL1-only mutation (ie, no associated mutation in TP53 or high-risk genes); and other patients. A multistate model found that both TP53 and high-risk groups were associated with leukemic transformation (hazard ratios [HRs] [95% confidence interval], 8.68 [3.32-22.73] and 3.24 [1.58-6.64], respectively) and death from myelofibrosis (HRs, 3.03 [1.66-5.56] and 1.77 [1.18-2.67], respectively). ASXL1-only mutations had no prognostic value that was confirmed in the validation cohort. However, ASXL1 mutations conferred a worse prognosis when associated with a mutation in TP53 or high-risk genes. This study provides a new definition of adverse mutations in myelofibrosis with the addition of TP53, CBL, NRAS, KRAS, and U2AF1 to previously described genes. Furthermore, our results argue that ASXL1 mutations alone cannot be considered detrimental.

Leukemic evolution of polycythemia vera and essential thrombocythemia: genomic profiles predict time to transformation.

Among myeloproliferative neoplasms, polycythemia vera (PV) and essential thrombocythemia (ET) are the 2 entities associated with the most chronic disease course. Leukemic evolution occurs rarely but has a grim prognosis. The interval between diagnosis and leukemic evolution is highly variable, from a few years to >20 years. We performed a molecular evaluation of 49 leukemic transformations of PV and ET by targeted next-generation sequencing. Using a hierarchical classification, we identified 3 molecular groups associated with a distinct time to leukemic transformation. Short-term transformations were mostly characterized by a complex molecular landscape and mutations in IDH1/2, RUNX1, and U2AF1 genes, whereas long-term transformations were associated with mutations in TP53, NRAS, and BCORL1 genes. Studying paired samples from chronic phase and transformation, we detected some mutations already present during the chronic phase, either with a significant allele burden (short-term transformation) or with a very low allele burden (especially TP53 mutations). However, other mutations were not detected even 1 year before leukemic transformation. Our results suggest that the leukemic transformation of PV and ET may be driven by distinct time-dependent molecular mechanisms.

Sequential mutational evaluation of CALR -mutated myeloproliferative neoplasms with thrombocytosis reveals an association between CALR allele burden evolution and disease progression.

In myeloproliferative neoplasms (MPN), JAK2V617F allele burden measurement has an impact on prognosis that helps in patient monitoring. Less is known about its usefulness in CALR-mutated cases. Additional mutations found by next-generation sequencing have also shown an impact on prognosis that may drive therapeutic choices, especially in myelofibrosis, but few studies focused on CALR-mutated patients. We performed a molecular evaluation combining next-generation sequencing with a myeloid panel and CALR allele burden measurement at diagnosis and during follow-up in a cohort of 45 patients with CALR-mutated essential thrombocythaemia. The bone marrow histology was also blindly reviewed in order to apply the WHO2016 classification. The most frequently mutated gene was TET2 (11/21 mutations). CALR type 1-like patients appear to have a more complex molecular landscape. We found an association between disease progression and CALR allele burden increase during follow-up, independently of additional mutations and WHO2016-reviewed diagnosis. Patients with disease progression at the time of follow-up showed a significant increase in CALR allele burden (+16·7%, P = 0·005) whereas patients without disease progression had a stable allele burden (+3·7%, P = 0·194). This result argues for clinical interest in CALR allele burden monitoring.

An electrostatic switching mechanism to control the lipid transfer activity of Osh6p.

A central assumption is that lipid transfer proteins (LTPs) bind transiently to organelle membranes to distribute lipids in the eukaryotic cell. Osh6p and Osh7p are yeast LTPs that transfer phosphatidylserine (PS) from the endoplasmic reticulum (ER) to the plasma membrane (PM) via PS/phosphatidylinositol-4-phosphate (PI4P) exchange cycles. It is unknown how, at each cycle, they escape from the electrostatic attraction of the PM, highly anionic, to return to the ER. Using cellular and in vitro approaches, we show that Osh6p reduces its avidity for anionic membranes once it captures PS or PI4P, due to a molecular lid closing its lipid-binding pocket. Thus, Osh6p maintains its transport activity between ER- and PM-like membranes. Further investigations reveal that the lid governs the membrane docking and activity of Osh6p because it is anionic. Our study unveils how an LTP self-limits its residency time on membranes, via an electrostatic switching mechanism, to transfer lipids efficiently.