Fast Multigrid Solution Method for Nested Edge-Based Finite Element Meshes

In this paper a fast multigrid solution method for edge-based finite element magnetostatic field computation with nested meshes in introduced and its efficiency is investigated. Special prolongation and restriction matrices were constructed according to the nature of the edge based field approximation

Improving prognostication and treatment choices for patients with AML

The treatment landscape of the aggressive haematological malignancy acute myeloid leukaemia (AML) has expanded but the prognosis is still unsatisfactory poor. Here, we aimed at improving prognostication and treatment choices in AML by addressing current clinical obstacles to successful AML treatment. Acute promyelocytic leukaemia (APL) is an AML subset characterised by a high rate of early death (ED). In Paper I, we developed a novel risk score for ED in APL. We identified three risk groups for ED based on regression analyses on first a training cohort from the population-based Swedish AML Registry (n=301) and later an external validation cohort from a hospital-based registry (n=129). The presented risk score included age, platelets and white blood cell (WBC) count. Importantly, already sub-normal to normal WBC counts conferred higher risks of ED. Molecular studies of elderly AML patients are sparse. In Paper II, we focused on patients ≥65 years to investigate the prognostic effect of molecular markers and to propose an algorithm for response to intensive chemotherapy (IC) in this patient group. We combined clinical data with targeted DNA- and RNA-sequencing of 182 patients. Notably, we identified and externally validated three risk categories for complete remission achievement after IC based on mutational status of TP53 and gene expression levels of ZBTB7A and EEPD1. Hypomethylating agents (HMAs) constitute a backbone for AML patients ineligible for IC. There are limited studies on their effectiveness in the real-world setting. In Paper III, we compared the utility of HMAs against IC and palliative care in all AML patients ≥60 years in Sweden (n=3135) during 2008-2018. Propensity score matching in this population-based cohort showed that HMAs are as effective as IC upfront when patient characteristics were balanced. Additionally, predictive factors for overall survival in HMA treated patients were different to IC treated patients. The HMA azacitidine combined with venetoclax is the current frontline option to AML patients unfit for IC. Few studies have addressed how this synergism arises. In Paper IV, we characterised the epigenetic and transcriptomic effects of azacitidine-venetoclax in vitro and elucidated potential survival/resistance mechanisms in AML blasts including the serine synthesis pathway and NTRK signaling. Furthermore, we utilised obtained RNA-seq data and in silico predictions to propose add-ons to azacitidine-venetoclax to further strengthen the synergy. In summary, the research presented herein contributes to improved personalised medicine in AML via real-world data, risk stratification algorithms and insights into potential novel therapeutic approaches

Improving prognostication and treatment choices for patients with AML

The treatment landscape of the aggressive haematological malignancy acute myeloid leukaemia (AML) has expanded but the prognosis is still unsatisfactory poor. Here, we aimed at improving prognostication and treatment choices in AML by addressing current clinical obstacles to successful AML treatment. Acute promyelocytic leukaemia (APL) is an AML subset characterised by a high rate of early death (ED). In Paper I, we developed a novel risk score for ED in APL. We identified three risk groups for ED based on regression analyses on first a training cohort from the population-based Swedish AML Registry (n=301) and later an external validation cohort from a hospital-based registry (n=129). The presented risk score included age, platelets and white blood cell (WBC) count. Importantly, already sub-normal to normal WBC counts conferred higher risks of ED. Molecular studies of elderly AML patients are sparse. In Paper II, we focused on patients ≥65 years to investigate the prognostic effect of molecular markers and to propose an algorithm for response to intensive chemotherapy (IC) in this patient group. We combined clinical data with targeted DNA- and RNA-sequencing of 182 patients. Notably, we identified and externally validated three risk categories for complete remission achievement after IC based on mutational status of TP53 and gene expression levels of ZBTB7A and EEPD1. Hypomethylating agents (HMAs) constitute a backbone for AML patients ineligible for IC. There are limited studies on their effectiveness in the real-world setting. In Paper III, we compared the utility of HMAs against IC and palliative care in all AML patients ≥60 years in Sweden (n=3135) during 2008-2018. Propensity score matching in this population-based cohort showed that HMAs are as effective as IC upfront when patient characteristics were balanced. Additionally, predictive factors for overall survival in HMA treated patients were different to IC treated patients. The HMA azacitidine combined with venetoclax is the current frontline option to AML patients unfit for IC. Few studies have addressed how this synergism arises. In Paper IV, we characterised the epigenetic and transcriptomic effects of azacitidine-venetoclax in vitro and elucidated potential survival/resistance mechanisms in AML blasts including the serine synthesis pathway and NTRK signaling. Furthermore, we utilised obtained RNA-seq data and in silico predictions to propose add-ons to azacitidine-venetoclax to further strengthen the synergy. In summary, the research presented herein contributes to improved personalised medicine in AML via real-world data, risk stratification algorithms and insights into potential novel therapeutic approaches

Integrated transcriptomic and genomic analysis improves prediction of complete remission and survival in elderly patients with acute myeloid leukemia

Relevant molecular tools for treatment stratification of patients >= 65 years with acute myeloid leukemia (AML) are lacking. We combined clinical data with targeted DNA- and full RNA-sequencing of 182 intensively and palliatively treated patients to predict complete remission (CR) and survival in AML patients >= 65 years. Intensively treated patients withNPM1andIDH2(R172)mutations had longer overall survival (OS), whereas mutatedTP53conferred lower CR rates and shorter OS.FLT3-ITDandTP53mutations predicted worse OS in palliatively treated patients. Gene expression levels most predictive of CR were combined with somatic mutations for an integrated risk stratification that we externally validated using the beatAML cohort. We defined a high-risk group with a CR rate of 20% in patients with mutatedTP53, compared to 97% CR in low-risk patients defined by high expression ofZBTB7AandEEPD1withoutTP53mutations. Patients without these criteria had a CR rate of 54% (intermediate risk). The difference in CR rates translated into significant OS differences that outperformed ELN stratification for OS prediction. The results suggest that an integrated molecular risk stratification can improve prediction of CR and OS and could be used to guide treatment in elderly AML patients

Drug screen in patient cells suggests quinacrine to be repositioned for treatment of acute myeloid leukemia

To find drugs suitable for repositioning for use against leukemia, samples from patients with chronic lymphocytic, acute myeloid and lymphocytic leukemias as well as peripheral blood mononuclear cells (PBMC) were tested in response to 1266 compounds from the LOPAC1280 library (Sigma). Twenty-five compounds were defined as hits with activity in all leukemia subgroups (<50% cell survival compared with control) at 10 mu M drug concentration. Only one of these compounds, quinacrine, showed low activity in normal PBMCs and was therefore selected for further preclinical evaluation. Mining the NCI-60 and the NextBio databases demonstrated leukemia sensitivity and the ability of quinacrine to reverse myeloid leukemia gene expression. Mechanistic exploration was performed using the NextBio bioinformatic software using gene expression analysis of drug exposed acute myeloid leukemia cultures (HL-60) in the database. Analysis of gene enrichment and drug correlations revealed strong connections to ribosomal biogenesis nucleoli and translation initiation. The highest drug-drug correlation was to ellipticine, a known RNA polymerase I inhibitor. These results were validated by additional gene expression analysis performed in-house. Quinacrine induced early inhibition of protein synthesis supporting these predictions. The results suggest that quinacrine have repositioning potential for treatment of acute myeloid leukemia by targeting of ribosomal biogenesis

A risk score based on real-world data to predict early death in acute promyelocytic leukemia

With increasingly effective treatments, early death (ED) has become the predominant reason for therapeutic failure in patients with acute promyelocytic leukemia (APL). To better prevent ED, patients with high-risk of ED must be identified. Our aim was to develop a score that predicts the risk of ED in a real-life setting. We used APL patients in the population based Swedish AML Registry (n=301) and a Portuguese hospital-based registry (n=129) as training and validation cohorts, respectively. The cohorts were comparable with respect to age (median, 54 and 53 years) and ED rate (19.6% and 18.6%). The score was developed by logistic regression analyses, risk-per-quantile assessment and scoring based on ridge regression coefficients from multivariable penalized logistic regression analysis. White blood cell count, platelet count and age were selected by this approach as the most significant variables for predicting ED. The score identified low-, high-and very high-risk patients with ED risks of 4.8%, 20.2% and 50.9% respectively in the training cohort and with 6.7%, 25.0% and 36.0% as corresponding values for the validation cohort. The score identified an increased risk of ED already at sub-normal and normal white blood cell counts and, consequently, it was better at predicting ED risk than the Sanz score (AUROC 0.77 vs. 0.64). In summary, we here present an externally validated and population-based risk score to predict ED risk in a real-world setting, identifying patients with the most urgent need of aggressive ED prevention. The results also suggest that increased vigilance for ED is already necessary at sub-normal/normal white blood cell counts