Integrative nucleophosmin mutation-associated microRNA and gene expression pattern analysis identifies novel microRNA - target gene interactions in acute myeloid leukemia.

BACKGROUND: MicroRNAs are regulators of gene expression, which act mainly by decreasing mRNA levels of their multiple targets. Deregulated microRNA expression has been shown for acute myeloid leukemia, a disease also characterized by altered gene expression associated with distinct genomic aberrations such as nucleophosmin (NPM1) mutations. To shed further light on the role of deregulated microRNA and gene expression in cytogenetically normal acute myeloid leukemia with NPM1 mutation we performed an integrative analysis of microRNA and mRNA expression data sets. DESIGN AND METHODS: Both microRNA and gene expression profiles were investigated in samples from a cohort of adult cytogenetically normal acute myeloid leukemia patients (n=43; median age 46 years, range 23-60 years) with known NPM1 mutation status (n=23 mutated, n=20 wild-type) and the data were integratively analyzed. Putative microRNA-mRNA interactions were validated by quantitative reverse transcriptase polymerase chain reaction, western blotting and luciferase reporter assays. For selected microRNAs, sensitivity of microRNA-overexpressing cells to cytarabine treatment was tested by FACS viability and cell proliferation assays. RESULTS: Our integrative approach of analyzing both microRNA- and gene expression profiles in parallel resulted in a refined list of putative target genes affected by NPM1 mutation-associated microRNA deregulation. Of 177 putative microRNA - target mRNA interactions we identified and validated 77 novel candidates with known or potential involvement in leukemogenesis, such as IRF2-miR-20a, KIT-miR-20a and MN1-miR-15a. Furthermore, our data showed that deregulated expression of tumor suppressor microRNAs, such as miR-29a and miR-30c, might contribute to sensitivity to cytarabine, which is observed in NPM1 mutated acute myeloid leukemia. CONCLUSIONS: Overall, our observations highlight that integrative data analysis approaches can improve insights into leukemia biology, and lead to the identification of novel microRNA - target gene interactions of potential relevance for acute myeloid leukemia treatment.

Core outcome set measurement for future clinical trials in acute myeloid leukemia: the HARMONY study protocol using a multi-stakeholder consensus-based Delphi process and a final consensus meeting.

BACKGROUND: Acute myeloid leukemia (AML) is the most common acute leukemia in adults and has an unacceptably low cure rate. In recent years, a number of new treatment strategies and compounds were developed for the treatment of AML. There were several randomized controlled clinical trials with the objective to improve patients' management and patients' outcome in AML. Unfortunately, these trials are not always directly comparable since they do not measure the same outcomes, and currently there are no core outcome sets that can be used to guide outcome selection and harmonization in this disease area. The HARMONY (Healthcare Alliance for Resourceful Medicine Offensive against Neoplasms in Hematology) Alliance is a public-private European network established in 2017 and currently includes 53 partners and 32 associated members from 22 countries. Amongst many other goals of the HARMONY Alliance, Work Package 2 focuses on defining outcomes that are relevant to each hematological malignancy. Accordingly, this pilot study will be performed to define a core outcome set in AML. METHODS: The pilot study will use a three-round Delphi survey and a final consensus meeting to define a core outcome set. Participants will be recruited from different stakeholder groups, including patients, clinicians, regulators and members of the European Federation of Pharmaceutical Industries and Associations. At the pre-Delphi stage, a literature research was conducted followed by several semi-structured interviews of clinical public and private key opinion leaders. Subsequently, the preliminary outcome list was discussed in several multi-stakeholder face-to-face meetings. The Delphi survey will reduce the preliminary outcome list to essential core outcomes. After completion of the last Delphi round, a final face-to-face meeting is planned to achieve consensus about the core outcome set in AML. DISCUSSION: As part of the HARMONY Alliance, the pilot Delphi aims to define a core outcome set in AML on the basis of a multi-stakeholder consensus. Such a core outcome set will help to allow consistent comparison of future clinical trials and real-world evidence research and ensures that appropriate outcomes valued by a range of stakeholders are measured within future trials.

Orientation of monoclonal antibodies in ion-exchange chromatography: A predictive quantitative structure-activity relationship modeling approach.

Chromatographic separation of biopharmaceuticals in general and monoclonal antibodies (mAbs) specifically is the bottleneck in terms of cost and throughput in preparative purification. Still, generalized platform processes are used, neglecting molecule specific characteristics, defining protein-resin interaction terms. Currently used in silico modeling approaches do not consider the orientation of the molecule towards the chromatographic resins as a result of the structural features on an atomic level. This paper describes a quantitative structure-activity relationship (QSAR) approach to model the orientation of mAbs on ion exchange chromatographic matrices as a function of property distribution and mobile phase characteristics. 6 mAbs were used to build a predictive QSAR model and to investigate the preferred binding orientations and resulting surface shielding on resins. Thereby different dominating orientations, caused by composition of Fab fragments of the mAbs, could be identified. The presented methodology is suitable to gain extended insight in molecule orientation on chromatographic resins and to tailor purification strategies based on molecule structure.

An orientation sensitive approach in biomolecule interaction quantitative structure-activity relationship modeling and its application in ion-exchange chromatography.

Quantitative structure-activity relationship (QSAR) modeling for prediction of biomolecule parameters has become an established technique in chromatographic purification process design. Unfortunately available descriptor sets fail to describe the orientation of biomolecules and the effects of ionic strength in the mobile phase on the interaction with the stationary phase. The literature describes several special descriptors used for chromatographic retention modeling, all of these do not describe the screening of electrostatic potential by the mobile phase in use. In this work we introduce two new approaches of descriptor calculations, namely surface patches and plane projection, which capture an oriented binding to charged surfaces and steric hindrance of the interaction with chromatographic ligands with regard to electrostatic potential screening by mobile phase ions. We present the use of the developed descriptor sets for predictive modeling of Langmuir isotherms for proteins at different pH values between pH 5 and 10 and varying ionic strength in the range of 10-100mM. The resulting model has a high correlation of calculated descriptors and experimental results, with a coefficient of determination of 0.82 and a predictive coefficient of determination of 0.92 for unknown molecular structures and conditions. The agreement of calculated molecular interaction orientations with both, experimental results as well as molecular dynamic simulations from literature is shown. The developed descriptors provide the means for improved QSAR models of chromatographic processes, as they reflect the complex interactions of biomolecules with chromatographic phases.

Molecular dissection of valproic acid effects in acute myeloid leukemia identifies predictive networks.

Histone deacetylase inhibitors (HDACIs) like valproic acid (VPA) display activity in leukemia models and induce tumor-selective cytotoxicity against acute myeloid leukemia (AML) blasts. As there are limited data on HDACIs effects, we aimed to dissect VPA effects in vitro using myeloid cell lines with the idea to integrate findings with in vivo data from AML patients treated with VPA additionally to intensive chemotherapy (n = 12). By gene expression profiling we identified an in vitro VPA response signature enriched for genes/pathways known to be implicated in cell cycle arrest, apoptosis, and DNA repair. Following VPA treatment in vivo, gene expression changes in AML patients showed concordant results with the in vitro VPA response despite concomitant intensive chemotherapy. Comparative miRNA profiling revealed VPA-associated miRNA expression changes likely contributing to a VPA-induced reversion of deregulated gene expression. In addition, we were able to define markers predicting VPA response in vivo such as CXCR4 and LBH. These could be validated in an independent cohort of VPA and intensive chemotherapy treated AML patients (n = 114) in which they were inversely correlated with relapse-free survival. In summary, our data provide new insights into the molecular mechanisms of VPA in myeloid blasts, which might be useful in further advancing HDAC inhibition based treatment approaches in AML.

A comprehensive molecular dynamics approach to protein retention modeling in ion exchange chromatography.

In downstream processing, the underlying adsorption mechanism of biomolecules to adsorbent material are still subject of extensive research. One approach to more mechanistic understanding is simulating this adsorption process and hereby the possibility to identify the parameters with strongest impact. So far this method was applied with all-atom molecular dynamics simulations of two model proteins on one cation exchanger. In this work we developed a molecular dynamics tool to simulate protein-adsorber interaction for various proteins on an anion exchanger and ran gradient elution experiments to relate the simulation results to experimental data. We were able to show that simulation results yield similar results as experimental data regarding retention behavior as well as binding orientation. We could identify arginines in case of cation exchangers and aspartic acids in case of anion exchangers as major contributors to binding.

Custom-tailored adsorbers: A molecular dynamics study on optimal design of ion exchange chromatography material.

The performance of functionalized materials, e.g., ion exchange resins, depends on multiple resin characteristics, such as type of ligand, ligand density, the pore accessibility for a molecule, and backbone characteristics. Therefore, the screening and identification process for optimal resin characteristics for separation is very time and material consuming. Previous studies on the influence of resin characteristics have focused on an experimental approach and to a lesser extent on the mechanistic understanding of the adsorption mechanism. In this in silico study, a previously developed molecular dynamics (MD) tool is used, which simulates any given biomolecule on resins with varying ligand densities. We describe a set of simulations and experiments with four proteins and six resins varying in ligand density, and show that simulations and experiments correlate well in a wide range of ligand density. With this new approach simulations can be used as pre-experimental screening for optimal adsorber characteristics, reducing the actual number of screening experiments, which results in a faster and more knowledge-based development of custom-tailored adsorbers.