Phase 1 study to evaluate Crenigacestat (LY3039478) in combination with dexamethasone in patients with T-cell acute lymphoblastic leukemia and lymphoma.

BACKGROUND: Deregulated Notch signaling is implicated in T-cell acute lymphoblastic leukemia (T-ALL)/T-cell lymphoblastic lymphoma (T-LBL). Crenigacestat (LY3039478) prevents cleavage of Notch proteins and may benefit patients with relapsed/refractory T-ALL/T-LBL. METHODS: JJCB was a multicenter, nonrandomized, open-label, dose-escalation, phase 1 study in adult patients with relapsed/refractory T-ALL/T-LBL. Eligible patients received Crenigacestat orally 3 times per week plus dexamethasone at 24 mg twice daily on days 1 to 5 every other week in a 28-day cycle. The starting level of Crenigacestat was 50 mg, and dose escalation was performed with a modified 3+3 scheme for the estimation of dose-limiting toxicity (DLT) at the recommended dose level. RESULTS: In total, 36 patients with T-ALL (n = 31 [86.1%]) or T-LBL (n = 5 [13.9%]) were treated with Crenigacestat and dexamethasone. Six patients (16.7%) experienced DLTs: 2 of 12 (16.7%) in the 75-mg cohort (grade 4 gastrointestinal hemorrhage and grade 3 nausea, vomiting, and diarrhea), 1 of 15 (6.7%) in the 100-mg cohort (grade 3 diarrhea), and 3 of 3 (100%) in the 125-mg cohort (grade 3 diarrhea, nausea, and vomiting). The maximum tolerated dosewas 75 mg plus 24 mg of dexamethasone daily on days 1 to 5. Twenty-eight patients (77.8%) experienced 1 or more treatment-emergent adverse events related to the study treatment. The best overall response was a confirmed response, with 1 patient (2.8%) having a duration of response of 10.51 months. Six patients (16.7%) achieved stable disease, and 12 patients (33.3%) experienced progressive disease. The remaining 17 patients (47.2%) were not evaluable. The median event-free survival was 1.18 months (95% confidence interval, 0.76-2.14 months) among all groups. A pharmacodynamic analysis showed decreased plasma amyloid ß levels. CONCLUSIONS: Crenigacestat demonstrated limited clinical activity at the recommended dose in adult patients with relapsed/refractory T-ALL/T-LBL.

Leveraging historical data into oncology development programs: Two case studies of phase 2 Bayesian augmented control trial designs.

Leveraging historical data into the design and analysis of phase 2 randomized controlled trials can improve efficiency of drug development programs. Such approaches can reduce sample size without loss of power. Potential issues arise when the current control arm is inconsistent with historical data, which may lead to biased estimates of treatment efficacy, loss of power, or inflated type 1 error. Consideration as to how to borrow historical information is important, and in particular, adjustment for prognostic factors should be considered. This paper will illustrate two motivating case studies of oncology Bayesian augmented control (BAC) trials. In the first example, a glioblastoma study, an informative prior was used for the control arm hazard rate. Sample size savings were 15% to 20% by using a BAC design. In the second example, a pancreatic cancer study, a hierarchical model borrowing method was used, which enabled the extent of borrowing to be determined by consistency of observed study data with historical studies. Supporting Bayesian analyses also adjusted for prognostic factors. Incorporating historical data via Bayesian trial design can provide sample size savings, reduce study duration, and enable a more scientific approach to development of novel therapies by avoiding excess recruitment to a control arm. Various sensitivity analyses are necessary to interpret results. Current industry efforts for data transparency have meaningful implications for access to patient-level historical data, which, while not critical, is helpful to adjust for potential imbalances in prognostic factors.

Restoration of cellular integrity following "ballistic" pronuclear exchange during Tetrahymena conjugation.

During sexual reproduction or conjugation, ciliates form a specialized cell adhesion zone for the purpose of exchanging gametic pronuclei. Hundreds of individual membrane fusion events transform the adhesion zone into a perforated membrane curtain, the mating junction. Pronuclei from each mating partner are propelled through this fenestrated membrane junction by a web of short, cris-crossing microtubules. Pronuclear passage results in the formation of two breaches in the membrane junction. Following pronuclear exchange and karyogamy (fertilization), cells seal these twin membrane breaches thereby re-establishing cellular independence. This would seem like a straightforward problem: simply grow membrane in from the edges of each breach in a fashion similar to how animal cells "grow" their cytokinetic furrows or how plant cells construct a cell wall during mitosis. Serial section electron microscopy and 3-D electron tomography reveal that the actual mechanism is less straightforward. Each of the two membrane breaches transforms into a bowed membrane assembly platform. The resulting membrane protrusions continue to grow into the cytoplasm of the mating partner, traverse the cytoplasm in anti-parallel directions and make contact with the plasma membrane that flanks the mating junction. This investigation reveals the details of a novel, developmentally-induced mechanism of membrane disruption and restoration associated with pronuclear exchange and fertilization in the ciliate, Tetrahymena thermophila.

Applications of Bayesian statistical methodology to clinical trial design: A case study of a phase 2 trial with an interim futility assessment in patients with knee osteoarthritis.

Development of new pharmacological treatments for osteoarthritis that address unmet medical needs in a competitive market place is challenging. Bayesian approaches to trial design offer advantages in defining treatment benefits by addressing clinically relevant magnitude of effects relative to comparators and in optimizing efficiency in analysis. Such advantages are illustrated by a motivating case study, a proof of concept, and dose finding study in patients with osteoarthritis. Patients with osteoarthritis were randomized to receive placebo, celecoxib, or 1 of 4 doses of galcanezumab. Primary outcome measure was change from baseline WOMAC pain after 8 weeks of treatment. Literature review of clinical trials with targeted comparator therapies quantified treatment effects versus placebo. Two success criteria were defined: one to address superiority to placebo with adequate precision and another to ensure a clinically relevant treatment effect. Trial simulations used a Bayesian dose response and longitudinal model. An interim analysis for futility was incorporated. Simulations indicated the study had ≥85% power to detect a 14-mm improvement and ≤1% risk for a placebo-like drug to pass. The addition of the second success criterion substantially reduced the risk of an inadequate, weakly efficacious drug proceeding to future development. The study was terminated at the interim analysis due to inadequate analgesic efficacy. A Bayesian approach using probabilistic statements enables clear understanding of success criteria, leading to informed decisions for study conduct. Incorporating an interim analysis can effectively reduce sample size, save resources, and minimize exposure of patients to an inadequate treatment.

Advantages of a wholly Bayesian approach to assessing efficacy in early drug development: a case study.

This paper illustrates how the design and statistical analysis of the primary endpoint of a proof-of-concept study can be formulated within a Bayesian framework and is motivated by and illustrated with a Pfizer case study in chronic kidney disease. It is shown how decision criteria for success can be formulated, and how the study design can be assessed in relation to these, both using the traditional approach of probability of success conditional on the true treatment difference and also using Bayesian assurance and pre-posterior probabilities. The case study illustrates how an informative prior on placebo response can have a dramatic effect in reducing sample size, saving time and resource, and we argue that in some cases, it can be considered unethical not to include relevant literature data in this way.

Early life response to infection.

PURPOSE OF REVIEW: Sepsis is a serious complication in preterm and term infants, yet our understanding of how neonates respond to infection remains poorly defined. RECENT FINDINGS: We describe our current clinical, cellular and molecular understanding of the neonatal host systemic response to infection. We find that host resilience essentially relies on innate immune mechanisms despite there being a complete repertoire of cellular components of the adaptive immune arm. The functional interplay between metabolism, immunity and microbiome further suggests that neonatal vulnerability to infection is not simply due to immaturity of the immune system but how immune homeostasis is regulated. Further research is required for exploring regulatory homeostatic mechanisms between innate and adaptive responses and microbiome colonization at birth, but which can impart an adverse trajectory to infection. SUMMARY: The vulnerability and resilience against infection in neonates, including extreme preterm infants, still remains poorly understood. We advance the view that greater consideration should be given to understanding the set point in the regulation of homeostatic control of innate and adaptive immunity and its interplay with metabolism and the newly acquired microbiome.

Whole blood gene expression profiling of neonates with confirmed bacterial sepsis.

Neonatal infection remains a primary cause of infant morbidity and mortality worldwide and yet our understanding of how human neonates respond to infection remains incomplete. Changes in host gene expression in response to infection may occur in any part of the body, with the continuous interaction between blood and tissues allowing blood cells to act as biosensors for the changes. In this study we have used whole blood transcriptome profiling to systematically identify signatures and the pathway biology underlying the pathogenesis of neonatal infection. Blood samples were collected from neonates at the first clinical signs of suspected sepsis alongside age matched healthy control subjects. Here we report a detailed description of the study design, including clinical data collected, experimental methods used and data analysis workflows and which correspond with data in Gene Expression Omnibus (GEO) data sets (GSE25504). Our data set has allowed identification of a patient invariant 52-gene classifier that predicts bacterial infection with high accuracy and lays the foundation for advancing diagnostic, prognostic and therapeutic strategies for neonatal sepsis.

Identification of a human neonatal immune-metabolic network associated with bacterial infection.

Understanding how human neonates respond to infection remains incomplete. Here, a system-level investigation of neonatal systemic responses to infection shows a surprisingly strong but unbalanced homeostatic immune response; developing an elevated set-point of myeloid regulatory signalling and sugar-lipid metabolism with concomitant inhibition of lymphoid responses. Innate immune-negative feedback opposes innate immune activation while suppression of T-cell co-stimulation is coincident with selective upregulation of CD85 co-inhibitory pathways. By deriving modules of co-expressed RNAs, we identify a limited set of networks associated with bacterial infection that exhibit high levels of inter-patient variability. Whereas, by integrating immune and metabolic pathways, we infer a patient-invariant 52-gene-classifier that predicts bacterial infection with high accuracy using a new independent patient population. This is further shown to have predictive value in identifying infection in suspected cases with blood culture-negative tests. Our results lay the foundation for future translation of host pathways in advancing diagnostic, prognostic and therapeutic strategies for neonatal sepsis.

Patent ductus arteriosus: time to grasp the nettle?

The management of patent ductus arteriosus is controversial, and there are diverse approaches to treatment, ranging from very conservative management through to early and aggressive securing of ductus closure, either pharmacologically or surgically. This lack of consensus on best management reflects a paucity of high quality randomised controlled trials, with many published studies focusing on establishing points of treatment, rather than looking for benefits of intervention over more conservative management. Despite this lack of good evidence views on ductus management can be entrenched, with accompanying loss of equipoise. This review looks at our current situation with regard to ductus arteriosus management and the need for good quality trials especially in the light of other published studies, concerning postnatal steroids, caffeine and oxygen which have demonstrated unexpected benefits - or sometimes unexpected harm - from long-familiar drugs.

Quantitative assessment of human whole blood RNA as a potential biomarker for infectious disease.

Infection remains a significant cause of morbidity and mortality especially in newborn infants. Analytical methods for diagnosing infection are severely limited in terms of sensitivity and specificity and require relatively large samples. It is proposed that stringent regulation of the human transcriptome affords a new molecular diagnostic approach based on measuring a highly specific systemic inflammatory response to infection, detectable at the RNA level. This proposition raises a number of as yet poorly characterised technical and biological variation issues that urgently need to be addressed. Here we report a quantitative assessment of methodological approaches for processing and extraction of RNA from small samples of infant whole blood and applying analysis of variation from biochip measurements. On the basis of testing and selection from a battery of assays we show that sufficient high quality RNA for analysis using multiplex array technology can be obtained from small neonatal samples. These findings formed the basis of implementing a set of robust clinical and experimental standard operating procedures for whole blood RNA samples from 58 infants. Modelling and analysis of variation between samples revealed significant sources of variation from the point of sample collection to processing and signal generation. These experiments further permitted power calculations to be run indicating the tractability and requirements of using changes in RNA expression profiles to detect different states between patient groups. Overall the results of our investigation provide an essential first step toward facilitating an alternative way for diagnosing infection from very small neonatal blood samples, providing methods and requirements for future chip-based studies.