Preventing clonal evolutionary processes in cancer: Insights from mathematical models.
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ABSTRACT:
SUBMITTER: Rodriguez-Brenes IA
PROVIDER: S-EPMC4517241 | biostudies-other | 2015 Jul
REPOSITORIES: biostudies-other
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Project description:Many parthenogenetically reproducing animals produce offspring not clonally but through different mechanisms collectively referred to as automixis. Here, meiosis proceeds normally but is followed by a fusion of meiotic products that restores diploidy. This mechanism typically leads to a reduction in heterozygosity among the offspring compared to the mother. Following a derivation of the rate at which heterozygosity is lost at one and two loci, depending on the number of crossovers between loci and centromere, a number of models are developed to gain a better understanding of basic evolutionary processes in automictic populations. Analytical results are obtained for the expected neutral genetic variation, effective population size, mutation-selection balance, selection with overdominance, the spread of beneficial mutations, and selection on crossover rates. These results are complemented by numerical investigations elucidating how associative overdominance (two off-phase deleterious mutations at linked loci behaving like an overdominant locus) can in some cases maintain heterozygosity for prolonged times, and how clonal interference affects adaptation in automictic populations. These results suggest that although automictic populations are expected to suffer from the lack of gene shuffling with other individuals, they are nevertheless, in some respects, superior to both clonal and outbreeding sexual populations in the way they respond to beneficial and deleterious mutations. Implications for related genetic systems such as intratetrad mating, clonal reproduction, selfing, as well as different forms of mixed sexual and automictic reproduction are discussed.
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Project description:The demand for projections of the future distribution of biodiversity has triggered an upsurge in modelling at the crossroads between ecology and evolution. Despite the enthusiasm around these so-called biodiversity models, most approaches are still criticised for not integrating key processes known to shape species ranges and community structure. Developing an integrative modelling framework for biodiversity distribution promises to improve the reliability of predictions and to give a better understanding of the eco-evolutionary dynamics of species and communities under changing environments. In this article, we briefly review some eco-evolutionary processes and interplays among them, which are essential to provide reliable projections of species distributions and community structure. We identify gaps in theory, quantitative knowledge and data availability hampering the development of an integrated modelling framework. We argue that model development relying on a strong theoretical foundation is essential to inspire new models, manage complexity and maintain tractability. We support our argument with an example of a novel integrated model for species distribution modelling, derived from metapopulation theory, which accounts for abiotic constraints, dispersal, biotic interactions and evolution under changing environmental conditions. We hope such a perspective will motivate exciting and novel research, and challenge others to improve on our proposed approach.
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Project description:This perspective outlines an approach to improve mechanistic understanding of macrophages in inflammation and tissue homeostasis, with a focus on human inflammatory bowel disease (IBD). The approach integrates wet-lab and in-silico experimentation, driven by mechanistic mathematical models of relevant biological processes. Although wet-lab experimentation with genetically modified mouse models and primary human cells and tissues have provided important insights, the role of macrophages in human IBD remains poorly understood. Key open questions include: (1) To what degree hyperinflammatory processes (e.g., gain of cytokine production) and immunodeficiency (e.g., loss of bacterial killing) intersect to drive IBD pathophysiology? and (2) What are the roles of macrophage heterogeneity in IBD onset and progression? Mathematical modeling offers a synergistic approach that can be used to address such questions. Mechanistic models are useful for informing wet-lab experimental designs and provide a knowledge constrained framework for quantitative analysis and interpretation of resulting experimental data. The majority of published mathematical models of macrophage function are based either on animal models, or immortalized human cell lines. These experimental models do not recapitulate important features of human gastrointestinal pathophysiology, and, therefore are limited in the extent to which they can fully inform understanding of human IBD. Thus, we envision a future where mechanistic mathematical models are based on features relevant to human disease and parametrized by richer human datasets, including biopsy tissues taken from IBD patients, human organ-on-a-chip systems and other high-throughput clinical data derived from experimental medicine studies and/or clinical trials on IBD patients.
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Project description:BackgroundTherapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients. We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simple mathematical models.Methodology/principal findingsWe developed a general mathematical model encompassing the basic interactions of a vaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cell vaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes in prostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were divided into each patient's training set and his validation set. The training set, used for model personalization, contained the patient's initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized models were simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set. The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients (the coefficient of determination between the predicted and observed PSA values was R(2)?=?0.972). The model could not account for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validated personalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccination regimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients.Conclusions/significanceUsing a few initial measurements, we constructed robust patient-specific models of PCa immunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value and feasibility of individualized model-suggested immunotherapy protocols.
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Project description:BACKGROUND: Sex-specific differences regarding the transmissibility and the course of infection are the rule rather than the exception in the epidemiology of sexually transmitted infections (STIs). Human papillomavirus (HPV) provides an example: disease outcomes differ between men and women, as does the potential for transmission to the opposite sex. HPV vaccination of preadolescent girls was recently introduced in many countries, and inclusion of boys in the vaccination programs is being discussed. Here, we address the question of whether vaccinating females only, males only, or both sexes is the most effective strategy to reduce the population prevalence of an STI like HPV. METHODS AND FINDINGS: We use a range of two-sex transmission models with varying detail to identify general criteria for allocating a prophylactic vaccine between both sexes. The most effective reduction in the population prevalence of infection is always achieved by single-sex vaccination; vaccinating the sex with the highest prevaccine prevalence is the preferred strategy in most circumstances. Exceptions arise only when the higher prevaccine prevalence is due to a substantially lower rate of natural immunity, or when natural immunity is lifelong, and a prolonged duration of infectiousness coincides with increased transmissibility. Predictions from simple models were confirmed in simulations based on an elaborate HPV transmission model. Our analysis suggests that relatively inefficient genital transmission from males to females might render male vaccination more effective in reducing overall infection levels. However, most existing HPV vaccination programs have achieved sufficient coverage to continue with female-only vaccination. CONCLUSIONS: Increasing vaccine uptake among preadolescent girls is more effective in reducing HPV infection than including boys in existing vaccination programs. As a rule, directing prophylactic immunization at the sex with the highest prevaccine prevalence results in the largest reduction of the population prevalence.
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Project description:Natural killer (NK) cells belong to the first line of host defense against infection and cancer. Cytokines, including interleukin-15 (IL-15), critically regulate NK cell activity, resulting in recognition and direct killing of transformed and infected target cells. NK cells have to adapt and respond in inflamed and often hypoxic areas. Cellular stabilization and accumulation of the transcription factor hypoxia-inducible factor-1? (HIF-1?) is a key mechanism of the cellular hypoxia response. At the same time, HIF-1? plays a critical role in both innate and adaptive immunity. While the HIF-1? hydroxylation and degradation pathway has been recently described with the help of mathematical methods, less is known concerning the mechanistic mathematical description of processes regulating the levels of HIF-1? mRNA and protein. In this work we combine mathematical modeling with experimental laboratory analysis and examine the dynamic relationship between HIF-1? mRNA, HIF-1? protein, and IL-15-mediated upstream signaling events in NK cells from human blood. We propose a system of non-linear ordinary differential equations with positive and negative feedback loops for describing the complex interplay of HIF-1? regulators. The experimental design is optimized with the help of mathematical methods, and numerical optimization techniques yield reliable parameter estimates. The mathematical model allows for the investigation and prediction of HIF-1? stabilization under different inflammatory conditions and provides a better understanding of mechanisms mediating cellular enrichment of HIF-1?. Thanks to the combination of in vitro experimental data and in silico predictions we identified the mammalian target of rapamycin (mTOR), the nuclear factor-?B (NF-?B), and the signal transducer and activator of transcription 3 (STAT3) as central regulators of HIF-1? accumulation. We hypothesize that the regulatory pathway proposed here for NK cells can be extended to other types of immune cells. Understanding the molecular mechanisms involved in the dynamic regulation of the HIF-1? pathway in immune cells is of central importance to the immune cell function and could be a promising strategy in the design of treatments for human inflammatory diseases and cancer.
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