Multiyear Factor VIII Expression after AAV Gene Transfer for Hemophilia A.

BACKGROUND: The goal of gene therapy for patients with hemophilia A is to safely impart long-term stable factor VIII expression that predictably ameliorates bleeding with the use of the lowest possible vector dose. METHODS: In this phase 1-2 trial, we infused an investigational adeno-associated viral (AAV) vector (SPK-8011) for hepatocyte expression of factor VIII in 18 men with hemophilia A. Four dose cohorts were enrolled; the lowest-dose cohort received a dose of 5 × 1011 vector genomes (vg) per kilogram of body weight, and the highest-dose cohort received 2 × 1012 vg per kilogram. Some participants received glucocorticoids within 52 weeks after vector administration either to prevent or to treat a presumed AAV capsid immune response. Trial objectives included evaluation of the safety and preliminary efficacy of SPK-8011 and of the expression and durability of factor VIII. RESULTS: The median safety observation period was 36.6 months (range, 5.5 to 50.3). A total of 33 treatment-related adverse events occurred in 8 participants; 17 events were vector-related, including 1 serious adverse event, and 16 were glucocorticoid-related. Two participants lost all factor VIII expression because of an anti-AAV capsid cellular immune response that was not sensitive to immune suppression. In the remaining 16 participants, factor VIII expression was maintained; 12 of these participants were followed for more than 2 years, and a one-stage factor VIII assay showed no apparent decrease in factor VIII activity over time (mean [±SD] factor VIII activity, 12.9±6.9% of the normal value at 26 to 52 weeks when the participants were not receiving glucocorticoids vs. 12.0±7.1% of the normal value at >52 weeks after vector administration; 95% confidence interval [CI], -2.4 to 0.6 for the difference between matched pairs). The participants had a 91.5% reduction (95% CI, 88.8 to 94.1) in the annualized bleeding rate (median rate, 8.5 events per year [range, 0 to 43.0] before vector administration vs. 0.3 events per year [range, 0 to 6.5] after vector administration). CONCLUSIONS: Sustained factor VIII expression in 16 of 18 participants who received SPK-8011 permitted discontinuation of prophylaxis and a reduction in bleeding episodes. No major safety concerns were reported. (Funded by Spark Therapeutics and the National Heart, Lung, and Blood Institute; ClinicalTrials.gov numbers, NCT03003533 and NCT03432520.).

Inferring the dynamics of mutated hematopoietic stem and progenitor cells induced by IFNα in myeloproliferative neoplasms.

Classical BCR-ABL-negative myeloproliferative neoplasms (MPNs) are clonal disorders of hematopoietic stem cells (HSCs) caused mainly by recurrent mutations in genes encoding JAK2 (JAK2), calreticulin (CALR), or the thrombopoietin receptor (MPL). Interferon α (IFNα) has demonstrated some efficacy in inducing molecular remission in MPNs. To determine factors that influence molecular response rate, we evaluated the long-term molecular efficacy of IFNα in patients with MPN by monitoring the fate of cells carrying driver mutations in a prospective observational and longitudinal study of 48 patients over more than 5 years. We measured the clonal architecture of early and late hematopoietic progenitors (84 845 measurements) and the global variant allele frequency in mature cells (409 measurements) several times per year. Using mathematical modeling and hierarchical Bayesian inference, we further inferred the dynamics of IFNα-targeted mutated HSCs. Our data support the hypothesis that IFNα targets JAK2V617F HSCs by inducing their exit from quiescence and differentiation into progenitors. Our observations indicate that treatment efficacy is higher in homozygous than heterozygous JAK2V617F HSCs and increases with high IFNα dose in heterozygous JAK2V617F HSCs. We also found that the molecular responses of CALRm HSCs to IFNα were heterogeneous, varying between type 1 and type 2 CALRm, and a high dose of IFNα correlates with worse outcomes. Our work indicates that the long-term molecular efficacy of IFNα implies an HSC exhaustion mechanism and depends on both the driver mutation type and IFNα dose.

Robust, Universal Tree Balance Indices.

Balance indices that quantify the symmetry of branching events and the compactness of trees are widely used to compare evolutionary processes or tree-generating algorithms. Yet, existing indices are not defined for all rooted trees, are unreliable for comparing trees with different numbers of leaves, and are sensitive to the presence or absence of rare types. The contributions of this article are twofold. First, we define a new class of robust, universal tree balance indices. These indices take a form similar to Colless' index but can account for population sizes, are defined for trees with any degree distribution, and enable meaningful comparison of trees with different numbers of leaves. Second, we show that for bifurcating and all other full m-ary cladograms (in which every internal node has the same out-degree), one such Colless-like index is equivalent to the normalized reciprocal of Sackin's index. Hence, we both unify and generalize the two most popular existing tree balance indices. Our indices are intrinsically normalized and can be computed in linear time. We conclude that these more widely applicable indices have the potential to supersede those in current use. [Cancer; clone tree; Colless index; Sackin index; species tree; tree balance.].

Drug-induced resistance evolution necessitates less aggressive treatment.

Increasing body of experimental evidence suggests that anticancer and antimicrobial therapies may themselves promote the acquisition of drug resistance by increasing mutability. The successful control of evolving populations requires that such biological costs of control are identified, quantified and included to the evolutionarily informed treatment protocol. Here we identify, characterise and exploit a trade-off between decreasing the target population size and generating a surplus of treatment-induced rescue mutations. We show that the probability of cure is maximized at an intermediate dosage, below the drug concentration yielding maximal population decay, suggesting that treatment outcomes may in some cases be substantially improved by less aggressive treatment strategies. We also provide a general analytical relationship that implicitly links growth rate, pharmacodynamics and dose-dependent mutation rate to an optimal control law. Our results highlight the important, but often neglected, role of fundamental eco-evolutionary costs of control. These costs can often lead to situations, where decreasing the cumulative drug dosage may be preferable even when the objective of the treatment is elimination, and not containment. Taken together, our results thus add to the ongoing criticism of the standard practice of administering aggressive, high-dose therapies and motivate further experimental and clinical investigation of the mutagenicity and other hidden collateral costs of therapies.

Predicting Responders to Reslizumab after 16 Weeks of Treatment Using an Algorithm Derived from Clinical Studies of Patients with Severe Eosinophilic Asthma.

RATIONALE: Reslizumab is a humanized anti-IL-5 monoclonal antibody used as add-on maintenance treatment for patients with uncontrolled eosinophilic asthma. OBJECTIVES: To predict response and nonresponse to intravenous reslizumab at 52 weeks with an algorithm we developed based on clinical indicators from pivotal clinical trials. METHODS: Patients aged 18 years and older who met Global Initiative for Asthma 4 or 5 criteria and received intravenous reslizumab (n = 321) in two trials ( www.clinicaltrials.gov identifiers, NCT01287039 and NCT01285323) were selected as the data source. A mathematical model was constructed that was based on change from baseline to 16 weeks in Asthma Control Questionnaire and Asthma Quality of Life Questionnaire scores and FEV1, and number of clinical asthma exacerbations during the year before enrollment and in the first 16 weeks of treatment, and these measures were evaluated for their ability to predict the outcome at 52 weeks: responder, nonresponder, or indeterminate. MEASUREMENTS AND MAIN RESULTS: The algorithm predicted that 276 patients would be classified as responders; in 248 (89.9%), the prediction was correct. In comparison, 26 patients were predicted to be nonresponders; 50.0% of these predictions were correct. Nineteen patients were classified as indeterminate. The algorithm had 95.4-95.5% sensitivity and 40.6-54.1% specificity. Jackknife and cross-study validation confirmed the robustness of the algorithm. CONCLUSIONS: Our algorithm enabled prediction at 16 weeks of treatment of the response to intravenous reslizumab treatment at 52 weeks, but it was not suitable for predicting nonresponse. A positive score at 16 weeks should encourage continued treatment, and a negative score should prompt close monitoring to determine whether discontinuation is warranted.

Antibiotic stress selects against cooperation in the pathogenic bacterium Pseudomonas aeruginosa.

Cheats are a pervasive threat to public goods production in natural and human communities, as they benefit from the commons without contributing to it. Although ecological antagonisms such as predation, parasitism, competition, and abiotic environmental stress play key roles in shaping population biology, it is unknown how such stresses generally affect the ability of cheats to undermine cooperation. We used theory and experiments to address this question in the pathogenic bacterium, Pseudomonas aeruginosa Although public goods producers were selected against in all populations, our competition experiments showed that antibiotics significantly increased the advantage of nonproducers. Moreover, the dominance of nonproducers in mixed cultures was associated with higher resistance to antibiotics than in either monoculture. Mathematical modeling indicates that accentuated costs to producer phenotypes underlie the observed patterns. Mathematical analysis further shows how these patterns should generalize to other taxa with public goods behaviors. Our findings suggest that explaining the maintenance of cooperative public goods behaviors in certain natural systems will be more challenging than previously thought. Our results also have specific implications for the control of pathogenic bacteria using antibiotics and for understanding natural bacterial ecosystems, where subinhibitory concentrations of antimicrobials frequently occur.

Early Clinical Response in Community-acquired Bacterial Pneumonia: From Clinical Endpoint to Clinical Practice.

BACKGROUND: Early clinical response (ECR) is a new endpoint to determine whether a drug should be approved for community-acquired bacterial pneumonia in the United States. The Omadacycline for Pneumonia Treatment In the Community (OPTIC) phase III study demonstrated noninferiority of omadacycline to moxifloxacin using this endpoint. This study describes the performance of the ECR endpoint and clinical stability relative to a posttreatment evaluation (PTE) of clinical success. METHODS: ECR was defined as symptom improvement 72-120 hours after the first dose of study drug (ECR window), no use of rescue antibiotics, and patient survival. Clinical success at PTE was an investigator assessment of success. Clinical stability was defined based on vital sign stabilization, described in the American Thoracic Society and Infectious Diseases Society of America community-acquired pneumonia treatment guidelines. RESULTS: During the ECR window, ECR was achieved in 81.1% and 82.7% of omadacycline and moxifloxacin patients, respectively. Similar numbers of patients achieved clinical stability in each treatment group (omadacycline 74.6%, moxifloxacin 77.6%). The proportion of patients with improved symptoms who were considered clinically stable increased across the ECR window (69.2-77.6% for omadacycline; 68.0-79.7% for moxifloxacin). There was high concordance (>70%) and high positive predictive value (>90%) of ECR and clinical stability with overall clinical success at PTE. CONCLUSIONS: Omadacycline was noninferior to moxifloxacin, based on a new ECR endpoint. Clinical stability was similarly high when measured in the same time frame as ECR. Both ECR and clinical stability showed high concordance and high positive predictive value with clinical success at PTE. CLINICAL TRIALS REGISTRATION: NCT02531438.

Phase 3 adaptive trial design options in treatment of complicated urinary tract infection.

New antimicrobial drugs for treatment of complicated urinary tract infection (cUTI) are generally assessed in randomized, double-blind, noninferiority clinical trials. Robust historical data for the active comparator inform on treatment effect estimation, yet typically do not substitute for the active comparator data in the proposed trial. We report design options for a phase 3 trial of cUTI using a Bayesian hierarchical model and historical data from 2 well-executed phase 3 registrational trials of doripenem. The methodology is directly applicable to other phase 3 noninferiority settings. In addition to the research design application, we provide a novel methodology for assessing the robustness of type I error control. The model borrows heavily from the prior data when the current active comparator parameter estimate approximated the historical estimate. In contrast, the model had restricted borrowing when the 2 estimates were very different. The alternative trial design, with or without the inclusion of futility stopping criteria, provides a framework for future cUTI phase 3 trials.

A framework for how environment contributes to cancer risk.

Evolutionary theory explains why metazoan species are largely protected against the negative fitness effects of cancers. Nevertheless, cancer is often observed at high incidence across a range of species. Although there are many challenges to quantifying cancer epidemiology and assessing its causes, we claim that most modern-day cancer in animals - and humans in particular - are due to environments deviating from central tendencies of distributions that have prevailed during cancer resistance evolution. Such novel environmental conditions may be natural and/or of anthropogenic origin, and may interface with cancer risk in numerous ways, broadly classifiable as those: increasing organism body size and/or life span, disrupting processes within the organism, and affecting germline. We argue that anthropogenic influences, in particular, explain much of the present-day cancer risk across life, including in humans. Based on a literature survey of animal species and a parameterised mathematical model for humans, we suggest that combined risks of all cancers in a population beyond c. 5% can be explained to some extent by the influence of novel environments. Our framework provides a basis for understanding how natural environmental variation and human activity impact cancer risk, with potential implications for species ecology.

A phase IIa study of afuresertib, an oral pan-AKT inhibitor, in patients with Langerhans cell histiocytosis.

BACKGROUND: Langerhans cell histiocytosis (LCH) is a clonal neoplasm characterized by widely varied clinical presentations, including multisystem involvement and systemic inflammatory symptoms. The AKT pathway is relevant to survival and proliferation of dendritic cells, and is also often upregulated in hematopoietic malignancies. A clinical response in an adult patient with LCH participating in the first-in-human trial of afuresertib prompted this prospective trial. PROCEDURE: The population in the current study included treatment-naïve (n = 7) and recurrent/refractory patients with LCH (n = 10), who received oral afuresertib (125 mg). The majority of patients were treated for > 24 weeks, with four patients receiving treatment for > 48 weeks. RESULTS: Pharmacokinetic analysis showed similar exposures in previously reported patients with other hematologic malignancies. Primary drug-related toxicities included Grade 1/2 nausea, diarrhea, dyspepsia, and vomiting. Grade 3 toxicities included fatigue, diarrhea, and pain (one of each). Another severe adverse event involved soft tissue necrosis. The overall response rate in evaluable subjects was 33% in treatment-naïve patients and 28% in patients with recurrent/refractory disease, which did not meet the predefined Bayesian criteria for efficacy. CONCLUSION: Afuresertib has clinical activity in some patients with newly diagnosed and advanced LCH.

The ubiquity of clonal interference in cancer and other range expansions.

Evolution during range expansions shapes the fate of many biological systems including tumours, microbial communities, and invasive species. A fundamental process of interest is the selective sweep, in which an advantageous mutation evades clonal interference and spreads through the population to fixation. However, most theoretical investigations of selective sweeps have assumed constant population size or have ignored spatial structure. Here we use mathematical modelling and analysis to investigate selective sweep probabilities in populations that spread outwards as they evolve. In the case of constant radial expansion speed, we derive probability distributions for the arrival time and location of the first surviving mutant and hence find surprisingly simple approximate and exact expressions for selective sweep probabilities in one, two and three dimensions, which are independent of mutation rate. Namely, the selective sweep probability is approximately 1-cwt/cmd, where cwt and cm are the wildtype and mutant radial expansion speeds, and d the spatial dimension. Using agent-based simulations, we show that our analytical results accurately predict selective sweep frequencies in the two-dimensional spatial Moran process. We further compare our results with those obtained for alternative growth models. Parameterizing our model for human tumours, we find that selective sweeps are predicted to be rare except during very early solid tumour growth, thus providing a general, pan-cancer explanation for findings from recent sequencing studies.

A seven-step guide to spatial, agent-based modelling of tumour evolution.

Spatial agent-based models are frequently used to investigate the evolution of solid tumours subject to localized cell-cell interactions and microenvironmental heterogeneity. As spatial genomic, transcriptomic and proteomic technologies gain traction, spatial computational models are predicted to become ever more necessary for making sense of complex clinical and experimental data sets, for predicting clinical outcomes, and for optimizing treatment strategies. Here we present a non-technical step by step guide to developing such a model from first principles. Stressing the importance of tailoring the model structure to that of the biological system, we describe methods of increasing complexity, from the basic Eden growth model up to off-lattice simulations with diffusible factors. We examine choices that unavoidably arise in model design, such as implementation, parameterization, visualization and reproducibility. Each topic is illustrated with examples drawn from recent research studies and state of the art modelling platforms. We emphasize the benefits of simpler models that aim to match the complexity of the phenomena of interest, rather than that of the entire biological system. Our guide is aimed at both aspiring modellers and other biologists and oncologists who wish to understand the assumptions and limitations of the models on which major cancer studies now so often depend.

A new universal system of tree shape indices.

The comparison and categorization of tree diagrams is fundamental to large parts of biology, linguistics, computer science, and other fields, yet the indices currently applied to describing tree shape have important flaws that complicate their interpretation and limit their scope. Here we introduce a new system of indices with no such shortcomings. Our indices account for node sizes and branch lengths and are robust to small changes in either attribute. Unlike currently popular phylogenetic diversity, phylogenetic entropy, and tree balance indices, our definitions assign interpretable values to all rooted trees and enable meaningful comparison of any pair of trees. Our self-consistent definitions further unite measures of diversity, richness, balance, symmetry, effective height, effective outdegree, and effective branch count in a coherent system, and we derive numerous simple relationships between these indices. The main practical advantages of our indices are in 1) quantifying diversity in non-ultrametric trees; 2) assessing the balance of trees that have non-uniform branch lengths or node sizes; 3) comparing the balance of trees with different leaf counts or outdegrees; 4) obtaining a coherent, generic, multidimensional quantification of tree shape that is robust to sampling error and inferential error. We illustrate these features by comparing the shapes of trees representing the evolution of HIV and of Uralic languages, and trees generated by computational models of tumour evolution. Given the ubiquity of tree structures, we identify a wide range of applications across diverse domains.

Preventing Evolutionary Rescue in Cancer.

Extinction therapy aims to eradicate tumours by optimally scheduling multiple treatment strikes to exploit the vulnerability of small cell populations to stochastic extinction. This concept was recently shown to be theoretically sound but has not been subjected to thorough mathematical analysis. Here we obtain quantitative estimates of tumour extinction probabilities using a deterministic analytical model and a stochastic simulation model of two-strike extinction therapy, based on evolutionary rescue theory. We find that the optimal time for the second strike is when the tumour is close to its minimum size before relapse. Given that this exact time point may be difficult to determine in practice, we show that striking slightly after the relapse has begun is typically better than switching too early. We further reveal and explain how demographic and environmental parameters influence the treatment outcome. Surprisingly, a low dose in the first strike paired with a high dose in the second is shown to be optimal. As one of the first investigations of extinction therapy, our work establishes a foundation for further theoretical and experimental studies of this promising evolutionarily-informed cancer treatment strategy.

A survey of open questions in adaptive therapy: Bridging mathematics and clinical translation.

Adaptive therapy is a dynamic cancer treatment protocol that updates (or 'adapts') treatment decisions in anticipation of evolving tumor dynamics. This broad term encompasses many possible dynamic treatment protocols of patient-specific dose modulation or dose timing. Adaptive therapy maintains high levels of tumor burden to benefit from the competitive suppression of treatment-sensitive subpopulations on treatment-resistant subpopulations. This evolution-based approach to cancer treatment has been integrated into several ongoing or planned clinical trials, including treatment of metastatic castrate resistant prostate cancer, ovarian cancer, and BRAF-mutant melanoma. In the previous few decades, experimental and clinical investigation of adaptive therapy has progressed synergistically with mathematical and computational modeling. In this work, we discuss 11 open questions in cancer adaptive therapy mathematical modeling. The questions are split into three sections: (1) integrating the appropriate components into mathematical models (2) design and validation of dosing protocols, and (3) challenges and opportunities in clinical translation.

Spatial structure governs the mode of tumour evolution.

Characterizing the mode-the way, manner or pattern-of evolution in tumours is important for clinical forecasting and optimizing cancer treatment. Sequencing studies have inferred various modes, including branching, punctuated and neutral evolution, but it is unclear why a particular pattern predominates in any given tumour. Here we propose that tumour architecture is key to explaining the variety of observed genetic patterns. We examine this hypothesis using spatially explicit population genetics models and demonstrate that, within biologically relevant parameter ranges, different spatial structures can generate four tumour evolutionary modes: rapid clonal expansion, progressive diversification, branching evolution and effectively almost neutral evolution. Quantitative indices for describing and classifying these evolutionary modes are presented. Using these indices, we show that our model predictions are consistent with empirical observations for cancer types with corresponding spatial structures. The manner of cell dispersal and the range of cell-cell interactions are found to be essential factors in accurately characterizing, forecasting and controlling tumour evolution.

A theoretical analysis of tumour containment.

Recent studies have shown that a strategy aiming for containment, not elimination, can control tumour burden more effectively in vitro, in mouse models and in the clinic. These outcomes are consistent with the hypothesis that emergence of resistance to cancer therapy may be prevented or delayed by exploiting competitive ecological interactions between drug-sensitive and drug-resistant tumour cell subpopulations. However, although various mathematical and computational models have been proposed to explain the superiority of particular containment strategies, this evolutionary approach to cancer therapy lacks a rigorous theoretical foundation. Here we combine extensive mathematical analysis and numerical simulations to establish general conditions under which a containment strategy is expected to control tumour burden more effectively than applying the maximum tolerated dose. We show that containment may substantially outperform more aggressive treatment strategies even if resistance incurs no cellular fitness cost. We further provide formulas for predicting the clinical benefits attributable to containment strategies in a wide range of scenarios and compare the outcomes of theoretically optimal treatments with those of more practical protocols. Our results strengthen the rationale for clinical trials of evolutionarily informed cancer therapy, while also clarifying conditions under which containment might fail to outperform standard of care.

Paracrine Behaviors Arbitrate Parasite-Like Interactions Between Tumor Subclones.

Explaining the emergence and maintenance of intratumor heterogeneity is an important question in cancer biology. Tumor cells can generate considerable subclonal diversity, which influences tumor growth rate, treatment resistance, and metastasis, yet we know remarkably little about how cells from different subclones interact. Here, we confronted two murine mammary cancer cell lines to determine both the nature and mechanisms of subclonal cellular interactions in vitro. Surprisingly, we found that, compared to monoculture, growth of the "winner" was enhanced by the presence of the "loser" cell line, whereas growth of the latter was reduced. Mathematical modeling and laboratory assays indicated that these interactions are mediated by the production of paracrine metabolites resulting in the winner subclone effectively "farming" the loser. Our findings add a new level of complexity to the mechanisms underlying subclonal growth dynamics.

Safety and efficacy of omadacycline for treatment of community-acquired bacterial pneumonia and acute bacterial skin and skin structure infections in patients with mild-to-moderate renal impairment.

BACKGROUND: Many antibiotics require dosage adjustments in patients with renal impairment. In Phase III studies, omadacycline was non-inferior to moxifloxacin and linezolid in adults with community-acquired bacterial pneumonia (CABP) and acute bacterial skin and skin structure infections (ABSSSI), respectively. This analysis evaluated efficacy and safety measures from three omadacycline studies by patient renal function. METHODS: Patients were stratified as having normal renal function (creatinine clearance >89 mL/min), mild renal impairment (creatinine clearance 60-89 mL/min) or moderate renal impairment (creatinine clearance <60 mL/min); creatine clearance ≤30 mL/min (severe renal impairment) was an exclusion criterion. Efficacy endpoints were clinical success at the early clinical response (ECR) and post-treatment evaluation (PTE) time-points. Safety was evaluated as treatment-emergent adverse events (TEAEs) and laboratory measures. RESULTS: This subgroup analysis included 773 patients with CABP and 1339 patients with ABSSSI in intent-to-treat (ITT) and modified ITT populations, respectively. Clinical success rates were high at ECR and PTE across the studies (CABP 75-90%; ABSSSI 74-95%), and broadly similar between treatments, irrespective of renal function. Rates of TEAEs in patients with ABSSSI ranged from 33% to 52%, and were similar across renal function groups. In patients with CABP, higher rates were observed in patients with moderate renal impairment (56-61%) compared with patients with normal renal function or mild renal impairment (35-49%). The most common TEAEs were nausea and vomiting. CONCLUSIONS: Clinical success was similar across renal function groups, indicating no notable difference in the efficacy of omadacycline in patients with mild or moderate renal impairment. Omadacycline and comparators displayed similar safety profiles. CLINICALTRIALS. GOV REGISTRY: OPTIC (NCT02531438); OASIS-1 (NCT02378480); OASIS-2 (NCT02877927).

Clinical Efficacy of Patients With Secondary Bacteremia Treated With Omadacycline: Results From Phase 3 Acute Bacterial Skin and Skin Structure Infections and Community-Acquired Bacterial Pneumonia Studies.

In this post hoc analysis of the 63 patients with secondary bacteremia enrolled in the 3 omadacycline phase 3 studies of acute bacterial skin/skin structure infections (ABSSSI) and community-acquired bacterial pneumonia (CABP), we determined that omadacycline is a viable therapeutic option for appropriate patients with secondary bacteremia.