Novel aldo-keto reductase 1C3 inhibitor affects androgen metabolism but not ovarian function in healthy women: a phase 1 study.

OBJECTIVE: Aldo-keto reductase 1C3 (AKR1C3) has been postulated to be involved in androgen, progesterone, and estrogen metabolism. Aldo-keto reductase 1C3 inhibition has been proposed for treatment of endometriosis and polycystic ovary syndrome. Clinical biomarkers of target engagement, which can greatly facilitate drug development, have not yet been described for AKR1C3 inhibitors. Here, we analyzed pharmacodynamic data from a phase 1 study with a new selective AKR1C3 inhibitor, BAY1128688, to identify response biomarkers and assess effects on ovarian function. DESIGN: In a multiple-ascending-dose placebo-controlled study, 33 postmenopausal women received BAY1128688 (3, 30, or 90 mg once daily or 60 mg twice daily) or placebo for 14 days. Eighteen premenopausal women received 60 mg BAY1128688 once or twice daily for 28 days. METHODS: We measured 17 serum steroids by liquid chromatography-tandem mass spectrometry, alongside analysis of pharmacokinetics, menstrual cyclicity, and safety parameters. RESULTS: In both study populations, we observed substantial, dose-dependent increases in circulating concentrations of the inactive androgen metabolite androsterone and minor increases in circulating etiocholanolone and dihydrotestosterone concentrations. In premenopausal women, androsterone concentrations increased 2.95-fold on average (95% confidence interval: 0.35-3.55) during once- or twice-daily treatment. Note, no concomitant changes in serum 17ß-estradiol and progesterone were observed, and menstrual cyclicity and ovarian function were not altered by the treatment. CONCLUSIONS: Serum androsterone was identified as a robust response biomarker for AKR1C3 inhibitor treatment in women. Aldo-keto reductase 1C3 inhibitor administration for 4 weeks did not affect ovarian function.ClinicalTrials.gov Identifier: NCT02434640; EudraCT Number: 2014-005298-36.

Walking-related digital mobility outcomes as clinical trial endpoint measures: protocol for a scoping review.

INTRODUCTION: Advances in wearable sensor technology now enable frequent, objective monitoring of real-world walking. Walking-related digital mobility outcomes (DMOs), such as real-world walking speed, have the potential to be more sensitive to mobility changes than traditional clinical assessments. However, it is not yet clear which DMOs are most suitable for formal validation. In this review, we will explore the evidence on discriminant ability, construct validity, prognostic value and responsiveness of walking-related DMOs in four disease areas: Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease and proximal femoral fracture. METHODS AND ANALYSIS: Arksey and O'Malley's methodological framework for scoping reviews will guide study conduct. We will search seven databases (Medline, CINAHL, Scopus, Web of Science, EMBASE, IEEE Digital Library and Cochrane Library) and grey literature for studies which (1) measure differences in DMOs between healthy and pathological walking, (2) assess relationships between DMOs and traditional clinical measures, (3) assess the prognostic value of DMOs and (4) use DMOs as endpoints in interventional clinical trials. Two reviewers will screen each abstract and full-text manuscript according to predefined eligibility criteria. We will then chart extracted data, map the literature, perform a narrative synthesis and identify gaps. ETHICS AND DISSEMINATION: As this review is limited to publicly available materials, it does not require ethical approval. This work is part of Mobilise-D, an Innovative Medicines Initiative Joint Undertaking which aims to deliver, validate and obtain regulatory approval for DMOs. Results will be shared with the scientific community and general public in cooperation with the Mobilise-D communication team. REGISTRATION: Study materials and updates will be made available through the Center for Open Science's OSFRegistry (https://osf.io/k7395).

Single-agent activity of phosphatidylinositol 3-kinase inhibition with copanlisib in patients with molecularly defined relapsed or refractory diffuse large B-cell lymphoma.

Patients with relapsed/refractory diffuse large B-cell lymphoma (DLBCL) have adverse outcomes. We evaluated the efficacy and safety of the phosphatidylinositol 3-kinase inhibitor copanlisib in patients with relapsed/refractory DLBCL and assessed the relationship between efficacy and DLBCL cell of origin (COO; activated B-cell like [ABC] and germinal center B-cell like [GCB]) and other biomarkers. The primary endpoint was objective response rate (ORR) in DLBCL COO subgroups (ABC, GCB, and unclassifiable) and by CD79B mutational status (NCT02391116). Sixty-seven patients received copanlisib (ABC DLBCL, n = 19; GCB DLBCL, n = 30; unclassifiable, n = 3; missing, n = 15). The ORR was 19.4%; 31.6% and 13.3% in ABC and GCB DLBCL patients, respectively. ORR was 22.2%/20.0% for patients with/without CD79B mutations (wild type, n = 45; mutant, n = 9; missing, n = 13). Overall median progression-free survival and duration of response were 1.8 and 4.3 months, respectively. Adverse events included hypertension (40.3%), diarrhea (37.3%), and hyperglycemia (32.8%). Aberrations were detected in 338 genes, including BCL2 (53.7%) and MLL2 (53.7%). A 16-gene signature separating responders from nonresponders was identified. Copanlisib treatment demonstrated a manageable safety profile in patients with relapsed/refractory DLBCL and a numerically higher response rate in ABC vs. GCB DLBCL patients.

mTORC1 Inhibition Corrects Neurodevelopmental and Synaptic Alterations in a Human Stem Cell Model of Tuberous Sclerosis.

Hyperfunction of the mTORC1 pathway has been associated with idiopathic and syndromic forms of autism spectrum disorder (ASD), including tuberous sclerosis, caused by loss of either TSC1 or TSC2. It remains largely unknown how developmental processes and biochemical signaling affected by mTORC1 dysregulation contribute to human neuronal dysfunction. Here, we have characterized multiple stages of neurogenesis and synapse formation in human neurons derived from TSC2-deleted pluripotent stem cells. Homozygous TSC2 deletion causes severe developmental abnormalities that recapitulate pathological hallmarks of cortical malformations in patients. Both TSC2(+/-) and TSC2(-/-) neurons display altered synaptic transmission paralleled by molecular changes in pathways associated with autism, suggesting the convergence of pathological mechanisms in ASD. Pharmacological inhibition of mTORC1 corrects developmental abnormalities and synaptic dysfunction during independent developmental stages. Our results uncouple stage-specific roles of mTORC1 in human neuronal development and contribute to a better understanding of the onset of neuronal pathophysiology in tuberous sclerosis.

Automated sample preparation platform for mass spectrometry-based plasma proteomics and biomarker discovery.

The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of proteins within plasma, as well as the inherent variability in composition from patient to patient. In addition, it is widely accepted that most soluble plasma biomarkers for diseases such as cancer will be represented by tissue leakage products, circulating in plasma at low levels. It is therefore necessary to find approaches with the prerequisite level of sensitivity in such a complex biological matrix. Strategies for fractionating the plasma proteome have been suggested, but improvements in sensitivity are often negated by the resultant process variability. Here we describe an approach using multidimensional chromatography and on-line protein derivatization, which allows for higher sensitivity, whilst minimizing the process variability. In order to evaluate this automated process fully, we demonstrate three levels of processing and compare sensitivity, throughput and reproducibility. We demonstrate that high sensitivity analysis of the human plasma proteome is possible down to the low ng/mL or even high pg/mL level with a high degree of technical reproducibility.

Processing of chromatographic data for chemometric analysis of peptide profiles from cheese extracts: a novel approach.

Chemometric analysis of chromatograms plays a fundamental role in characterization of foods or in detection of adulteration. Data for multivariate analysis of chromatographic profiles are usually obtained by visual matching (VM) of peaks, the identities of which, as for peptide profiles from cheese extracts, are often unknown. To avoid the main disadvantages of VM, which is subjective and time-consuming, a novel approach was developed. Fuzzy logic was employed to handle in a systematic way uncertainty in the position of peptide peaks, and chromatograms were processed by a rule-based membership function. Processed data consisted of classes of retention time wherein peak heights were accumulated by using the distance from the center of the class as a weight. The novel approach (fuzzy approach, FA) was compared with VM by using a real data set and by performing multivariate descriptive statistical techniques (principal component analysis, multidimensional scaling, and nonhierarchical cluster analysis). FA provided a fast, reliable, and objective alternative to VM and could be successfully applied for chemometric analysis of chromatographic profiles whenever knowledge of the identity of peaks is lacking or unnecessary.