Cancer models, genomic instability and somatic cellular Darwinian evolution

Minimum latency effects for cancer associated with exposures to radiation or other carcinogens

BACKGROUND

In estimating radiation-associated cancer risks a fixed period for the minimum latency is often assumed. Two empirical latency functions have been used to model latency, continuously increasing from 0. A stochastic biologically-based approach yields a still more plausible way of describing latency and can be directly estimated from clinical data.

METHODS

We derived the parameters for a stochastic biologically-based model from tumour growth data for various cancers, and least-squares fitted the two types of empirical latency function to the stochastic model-predicted cumulative probability.

RESULTS

There is wide variation in growth rates among tumours, particularly slow for prostate and thyroid cancer and particularly fast for leukaemia. The slow growth rate for prostate and thyroid tumours implies that the number of tumour cells required for clinical detection cannot greatly exceed 106. For all tumours, both empirical latency functions closely approximated the predicted biological model cumulative probability.

CONCLUSIONS

Our results, illustrating use of a stochastic biologically-based model using clinical data not tied to any particular carcinogen, have implications for estimating latency associated with any mutagen. They apply to tumour growth in general, and may be useful for example, in planning screenings for cancer using imaging techniques.

Genomic Instability Evolutionary Footprints on Human Health: Driving Forces or Side Effects?

In this work, we propose a comprehensive perspective on genomic instability comprising not only the accumulation of mutations but also telomeric shortening, epigenetic alterations and other mechanisms that could contribute to genomic information conservation or corruption. First, we present mechanisms playing a role in genomic instability across the kingdoms of life. Then, we explore the impact of genomic instability on the human being across its evolutionary history and on present-day human health, with a particular focus on aging and complex disorders. Finally, we discuss the role of non-coding RNAs, highlighting future approaches for a better living and an expanded healthy lifespan.

Profound synchrony of age-specific incidence rates and tumor suppression for different cancer types as revealed by the multistage-senescence model of carcinogenesis

The age-specific trend of cancer incidence rates, but not its magnitude, is well described employing the multistage theory of carcinogenesis by Armitage and Doll in combination with the senescence model of Pompei and Wilson. We derived empirical parameters of the multistage-senescence model from U.S. Surveillance, Epidemiology, and End Results (SEER) incidence data from 2000–2003 and 2010–2013 for The Cancer Genome Atlas (TCGA) cancer types. Under the assumption of a constant tumor-specific transition rate between stages, there is an extremely strong linear relationship (P < 0.0001) between the number of stages and the stage transition rate. The senescence tumor suppression factor for 20 non-reproductive cancers is remarkably consistent (0.0099±0.0005); however, five female reproductive cancers have significantly higher tumor suppression. The peak incidence rate for non-reproductive cancers occurs at a younger age for cancers with fewer stages and their carcinogenic stages are of longer duration. Driver gene mutations are shown to contribute on average only about a third of the carcinogenic stages of different tumor types. A tumor’s accumulated incidence, calculated using a two-variable (age, stage) model, is strongly associated with intrinsic cancer risk. During both early adulthood and senescence, the pace of tumor suppression appears to be synchronized across most cancer types, suggesting the presence of overlapping evolutionary processes.

Risk of lung cancer due to external environmental factor and epidemiological data analysis

Lung cancer is a cancer with the fastest growth in the incidence and mortality all over the world, which is an extremely serious threat to human's life and health. Evidences reveal that external environmental factors are the key drivers of lung cancer, such as smoking, radiation exposure and so on. Therefore, it is urgent to explain the mechanism of lung cancer risk due to external environmental factors experimentally and theoretically. However, it is still an open issue regarding how external environment factors affect lung cancer risk. In this paper, we summarize the main mathematical models involved the gene mutations for cancers, and review the application of the models to analyze the mechanism of lung cancer and the risk of lung cancer due to external environmental exposure. In addition, we apply the model described and the epidemiological data to analyze the influence of external environmental factors on lung cancer risk. The result indicates that radiation can cause significantly an increase in the mutation rate of cells, in particular the mutation in stability gene that leads to genomic instability. These studies not only can offer insights into the relationship between external environmental factors and human lung cancer risk, but also can provide theoretical guidance for the prevention and control of lung cancer.

Cancer and the breakdown of multicellularity: What Dictyostelium discoideum, a social amoeba, can teach us

Ancient pathways promoting unicellularity and multicellularity are associated with cancer, the former being pro-oncogenic and the latter acting to suppress oncogenesis. However, there are only a limited number of non-vertebrate models for studying these pathways. Here, we review Dictyostelium discoideum and describe how it can be used to understand these gene networks. D. discoideum has a unicellular and multicellular life cycle, making it possible to study orthologs of cancer-associated genes in both phases. During development, differentiated amoebae form a fruiting body composed of a mass of spores that are supported atop a stalk. A portion of the cells sacrifice themselves to become non-reproductive stalk cells. Cheating disrupts the principles of multicellularity, as cheater cells alter their cell fate to preferentially become spores. Importantly, D. discoideum has gene networks and several strategies for maintaining multicellularity. Therefore, D. discoideum can help us better understand how conserved genes and pathways involved in multicellularity also influence cancer development, potentially identifying new therapeutic avenues.

Adverse outcome pathways, key events, and radiation risk assessment

The overall aim of this contribution to the 'Second Bill Morgan Memorial Special Issue' is to provide a high-level review of a recent report developed by a Committee for the National Council on Radiation Protection and Measurements (NCRP) titled 'Approaches for Integrating Information from Radiation Biology and Epidemiology to Enhance Low-Dose Health Risk Assessment'. It derives from previous NCRP Reports and Commentaries that provide the case for integrating data from radiation biology studies (available and proposed) with epidemiological studies (also available and proposed) to develop Biologically-Based Dose-Response (BBDR) models. In this review, it is proposed for such models to leverage the adverse outcome pathways (AOP) and key events (KE) approach for better characterizing radiation-induced cancers and circulatory disease (as the example for a noncancer outcome). The review discusses the current state of knowledge of mechanisms of carcinogenesis, with an emphasis on radiation-induced cancers, and a similar discussion for circulatory disease. The types of the various informative BBDR models are presented along with a proposed generalized BBDR model for cancer and a more speculative one for circulatory disease. The way forward is presented in a comprehensive discussion of the research needs to address the goal of enhancing health risk assessment of exposures to low doses of radiation. The use of an AOP/KE approach for developing a mechanistic framework for BBDR models of radiation-induced cancer and circulatory disease is considered to be a viable one based upon current knowledge of the mechanisms of formation of these adverse health outcomes and the available technical capabilities and computational advances. The way forward for enhancing low-dose radiation risk estimates will require there to be a tight integration of epidemiology data and radiation biology information to meet the goals of relevance and sensitivity of the adverse health outcomes required for overall health risk assessment at low doses and dose rates.

Transient commensal clonal interactions can drive tumor metastasis

The extent and importance of functional heterogeneity and crosstalk between tumor cells is poorly understood. Here, we describe the generation of clonal populations from a patient-derived ovarian clear cell carcinoma model which forms malignant ascites and solid peritoneal tumors upon intraperitoneal transplantation in mice. The clonal populations are engineered with secreted Gaussia luciferase to monitor tumor growth dynamics and tagged with a unique DNA barcode to track their fate in multiclonal mixtures during tumor progression. Only one clone, CL31, grows robustly, generating exclusively malignant ascites. However, multiclonal mixtures form large solid peritoneal metastases, populated almost entirely by CL31, suggesting that transient cooperative interclonal interactions are sufficient to promote metastasis of CL31. CL31 uniquely harbors ERBB2 amplification, and its acquired metastatic activity in clonal mixtures is dependent on transient exposure to amphiregulin, which is exclusively secreted by non-tumorigenic clones. Amphiregulin enhances CL31 mesothelial clearance, a prerequisite for metastasis. These findings demonstrate that transient, ostensibly innocuous tumor subpopulations can promote metastases via “hit-and-run” commensal interactions.

Cooperative interactions among tumor cells may have important implications for metastasis. Here, the authors examined the spatio-temporal nature of interactions among clonal populations of ovarian carcinoma cells and found that transient interactions cells can promote metastases via commensal interactions.

Meta-analysis of published excess relative risk estimates

A meta-analytic summary effect estimate often is calculated as an inverse-variance-weighted average of study-specific estimates of association. The variances of published estimates of association often are derived from their associated confidence intervals under assumptions typical of Wald-type statistics, such as normality of the parameter. However, in some research areas, such as radiation epidemiology, epidemiological results typically are obtained by fitting linear relative risk models, and associated likelihood-based confidence intervals are often asymmetric; consequently, reasonable estimates of variances associated with study-specific estimates of association may be difficult to infer from the standard approach based on the assumption of a Wald-type interval. Here, a novel method is described for meta-analysis of published results from linear relative risk models that uses a parametric transformation of published results to improve on the normal approximation used to assess confidence intervals. Using simulations, it is illustrated that the meta-analytic summary obtained using the proposed approach yields less biased summary estimates, with better confidence interval coverage, than the summary obtained using the more classical approach to meta-analysis. The proposed approach is illustrated using a previously published example of meta-analysis of epidemiological findings regarding circulatory disease following exposure to low-level ionizing radiation.

Canine mammary tumours: Size matters-a progression from low to highly malignant subtypes

The purpose of this study was to evaluate a possible association between mammary tumour size and increasing degree of malignancy. Data of 625 dogs with a total of 1459 mammary tumours were analysed retrospectively. 80.3% dogs were intact, mean age at diagnosis was 9.7 ± 2.5 years, 75.8% were pure breed dogs. Median body weight was 20.0 kg. Malignant tumours (n = 580) were significantly larger than their benign counterparts (1.94 cm vs 0.90 cm in mean, respectively; P ≤ .0001), resulting in a positive correlation between increasing tumour size and a change from benign to malignant (P ≤ .0001; r_s  = 0.214). When malignant tumours were grouped into four degrees of increasing malignancy (complex/simple/solid/anaplastic carcinomas) a significant positive correlation between increasing tumour size and more malignant tumour degree (P ≤ .0001; r_s  = 0.195) could be demonstrated. In a number of cases, highly malignant tumours were found to arise within less malignant lesions, supporting the concept of a further progression within the malignant tumour subtypes. In patients with multiple tumours, mean tumour sizes for malignant tumours were significantly smaller compared to patients with only one tumour (1.67 vs 2.71 cm in mean, respectively; P < .0001). These findings suggest that mammary tumours progress not only from benign to malignant but also from low to highly malignant. An increase in diameter of only a few millimetres may therefore have a big impact on the patient's outcome.

Epithelial Ovarian Cancer and the Immune System: Biology, Interactions, Challenges and Potential Advances for Immunotherapy

Recent advances in the understanding of immune function and the interactions with tumour cells have led to the development of various cancer immunotherapies and strategies for specific cancer types. However, despite some stunning successes with some malignancies such as melanomas and lung cancer, most patients receive little or no benefit from immunotherapy, which has been attributed to the tumour microenvironment and immune evasion. Although the US Food and Drug Administration have approved immunotherapies for some cancers, to date, only the anti-angiogenic antibody bevacizumab is approved for the treatment of epithelial ovarian cancer. Immunotherapeutic strategies for ovarian cancer are still under development and being tested in numerous clinical trials. A detailed understanding of the interactions between cancer and the immune system is vital for optimisation of immunotherapies either alone or when combined with chemotherapy and other therapies. This article, in two main parts, provides an overview of: (1) components of the normal immune system and current knowledge regarding tumour immunology, biology and their interactions; (2) strategies, and targets, together with challenges and potential innovative approaches for cancer immunotherapy, with attention given to epithelial ovarian cancer.

Change in mutation frequency at a TP53 hotspot during culture of ENU-mutagenised human lymphoblastoid cells

Mutations in oncogenes or tumour suppressor genes cause increases in cell growth capacity. In some cases, fully malignant cancer cells develop after additional mutations occur in initially mutated cells. In such instances, the risk of cancer would increase in response to growth of these initially mutated cells. To ascertain whether such a situation might occur in cultured cells, three independent cultures of human lymphoblastoid GM00130 cells were treated with N-ethyl-N-nitrosourea to induce mutations, and the cells were maintained for 12 weeks. Mutant frequencies and spectra of the cells at the MspI and HaeIII restriction sites located at codons 247-250 of the TP53 gene were examined. Mutant frequencies at both sites in the gene exhibited a declining trend during cell culture and reached background levels after 12 weeks; this was also supported by mutation spectra findings. These results indicate that the mutations detected under our assay conditions are disadvantageous to cell growth.

Enhancing low-dose risk assessment using mechanistic mathematical models of radiation effects

Mechanistic mathematical modeling of ionizing radiation (IR) effects has a long history spanning several decades. Models that mathematically represent current knowledge and hypotheses about how radiation damages cells and organs, leading to deleterious outcomes such as carcinogenesis, are particularly useful for estimating radiation risks at doses that are relevant for radiation protection, but are too low to provide a strong 'signal-to-noise ratio' in epidemiological or experimental studies with realistic sample sizes. Here, I discuss examples of models in several relevant areas, including radionuclide biokinetics, non-targeted IR effects, DNA double-strand break (DSB) rejoining and radiation carcinogenesis. I do not provide a detailed review of the vast modeling literature in these fields, but focus on concepts that we have implemented, such as using continuous probability distributions of exponential rates to model radionuclide biokinetics and DSB rejoining, and combining short and long time scales in carcinogenesis models. Improvements in models, including the ability to generate new hypotheses based on model predictions, may come from the introduction of additional novel concepts and from integrating multiple data types.

Electromagnetic Fields, Genomic Instability and Cancer: A Systems Biological View

This review discusses the use of systems biology in understanding the biological effects of electromagnetic fields, with particular focus on induction of genomic instability and cancer. We introduce basic concepts of the dynamical systems theory such as the state space and attractors and the use of these concepts in understanding the behavior of complex biological systems. We then discuss genomic instability in the framework of the dynamical systems theory, and describe the hypothesis that environmentally induced genomic instability corresponds to abnormal attractor states; large enough environmental perturbations can force the biological system to leave normal evolutionarily optimized attractors (corresponding to normal cell phenotypes) and migrate to less stable variant attractors. We discuss experimental approaches that can be coupled with theoretical systems biology such as testable predictions, derived from the theory and experimental methods, that can be used for measuring the state of the complex biological system. We also review potentially informative studies and make recommendations for further studies.

Multi-stage models for the failure of complex systems, cascading disasters, and the onset of disease

Complex systems can fail through different routes, often progressing through a series of (rate-limiting) steps and modified by environmental exposures. The onset of disease, cancer in particular, is no different. Multi-stage models provide a simple but very general mathematical framework for studying the failure of complex systems, or equivalently, the onset of disease. They include the Armitage-Doll multi-stage cancer model as a particular case, and have potential to provide new insights into how failures and disease, arise and progress. A method described by E.T. Jaynes is developed to provide an analytical solution for a large class of these models, and highlights connections between the convolution of Laplace transforms, sums of random variables, and Schwinger/Feynman parameterisations. Examples include: exact solutions to the Armitage-Doll model, the sum of Gamma-distributed variables with integer-valued shape parameters, a clonal-growth cancer model, and a model for cascading disasters. Applications and limitations of the approach are discussed in the context of recent cancer research. The model is sufficiently general to be used in many contexts, such as engineering, project management, disease progression, and disaster risk for example, allowing the estimation of failure rates in complex systems and projects. The intended result is a mathematical toolkit for applying multi-stage models to the study of failure rates in complex systems and to the onset of disease, cancer in particular.

Cancer and intercellular cooperation

The major transitions approach in evolutionary biology has shown that the intercellular cooperation that characterizes multicellular organisms would never have emerged without some kind of multilevel selection. Relying on this view, the Evolutionary Somatic view of cancer considers cancer as a breakdown of intercellular cooperation and as a loss of the balance between selection processes that take place at different levels of organization (particularly single cell and individual organism). This seems an elegant unifying framework for healthy organism, carcinogenesis, tumour proliferation, metastasis and other phenomena such as ageing. However, the gene-centric version of Darwinian evolution, which is often adopted in cancer research, runs into empirical problems: proto-tumoural and tumoural features in precancerous cells that would undergo 'natural selection' have proved hard to demonstrate; cells are radically context-dependent, and some stages of cancer are poorly related to genetic change. Recent perspectives propose that breakdown of intercellular cooperation could depend on 'fields' and other higher-level phenomena, and could be even mutations independent. Indeed, the field would be the context, allowing (or preventing) genetic mutations to undergo an intra-organism process analogous to natural selection. The complexities surrounding somatic evolution call for integration between multiple incomplete frameworks for interpreting intercellular cooperation and its pathologies.

Blood vessel tortuosity selects against evolution of aggressive tumor cells in confined tissue environments: A modeling approach

Cancer is a disease of cellular regulation, often initiated by genetic mutation within cells, and leading to a heterogeneous cell population within tissues. In the competition for nutrients and growth space within the tumors the phenotype of each cell determines its success. Selection in this process is imposed by both the microenvironment (neighboring cells, extracellular matrix, and diffusing substances), and the whole of the organism through for example the blood supply. In this view, the development of tumor cells is in close interaction with their increasingly changing environment: the more cells can change, the more their environment will change. Furthermore, instabilities are also introduced on the organism level: blood supply can be blocked by increased tissue pressure or the tortuosity of the tumor-neovascular vessels. This coupling between cell, microenvironment, and organism results in behavior that is hard to predict. Here we introduce a cell-based computational model to study the effect of blood flow obstruction on the micro-evolution of cells within a cancerous tissue. We demonstrate that stages of tumor development emerge naturally, without the need for sequential mutation of specific genes. Secondly, we show that instabilities in blood supply can impact the overall development of tumors and lead to the extinction of the dominant aggressive phenotype, showing a clear distinction between the fitness at the cell level and survival of the population. This provides new insights into potential side effects of recent tumor vasculature normalization approaches.

Mathematical models of tissue stem and transit target cell divisions and the risk of radiation- or smoking-associated cancer

There is compelling biological data to suggest that cancer arises from a series of mutations in single target cells, resulting in defects in cell renewal and differentiation processes which lead to malignancy. Because much mutagenic damage is expressed following cell division, more-rapidly renewing tissues could be at higher risk because of the larger number of cell replications. Cairns suggested that renewing tissues may reduce cancer risk by partitioning the dividing cell populations into lineages comprising infrequently-dividing long-lived stem cells and frequently-dividing short-lived daughter transit cells. We develop generalizations of three recent cancer-induction models that account for the joint maintenance and renewal of stem and transit cells, also competing processes of partially transformed cell proliferation and differentiation/apoptosis. We are particularly interested in using these models to separately assess the probabilities of mutation and development of cancer associated with "spontaneous" processes and with those linked to a specific environmental mutagen, specifically ionizing radiation or cigarette smoking. All three models demonstrate substantial variation in cancer risks, by at least 20 orders of magnitude, depending on the assumed number of critical mutations required for cancer, and the stem-cell and transition-cell mutation rates. However, in most cases the conditional probabilities of cancer being mutagen-induced range between 7-96%. The relative risks associated with mutagen exposure compared to background rates are also stable, ranging from 1.0-16.0. Very few cancers, generally <0.5%, arise from mutations occurring solely in stem cells rather than in a combination of stem and transit cells. However, for cancers with 2 or 3 critical mutations, a substantial proportion of cancers, in some cases 100%, have at least one mutation derived from a mutated stem cell. Little difference is made to relative risks if competing processes of proliferation and differentiation in the partially transformed stem and transit cell population are allowed for, nor is any difference made if one assumes that transit cells require an extra mutation to confer malignancy from the number required by stem cells. The probability of a cancer being mutagen-induced correlates across cancer sites with the estimated cumulative number of stem cell divisions in the associated tissue (p<0.05), although in some cases there is sensitivity of findings to removal of high-leverage outliers and in some cases only modest variation in probability, but these issues do not affect the validity of the findings. There are no significant correlations (p>0.3) between lifetime cancer-site specific radiation risk and the probability of that cancer being mutagen-induced. These results do not depend on the assumed critical number of mutations leading to cancer, or on the assumed mutagen-associated mutation rate, within the generally-accepted ranges tested. However, there are borderline significant negative correlations (p = 0.08) between the smoking-associated mortality rate difference (current vs former smokers) and the probability of cancer being mutagen-induced. This is only the case where values of the critical number of mutations leading to cancer, k, is 3 or 4 and not for smaller values (1 or 2), but does not strongly depend on the assumed mutagen-associated mutation rate.

Evolution of genetic instability in heterogeneous tumors

Genetic instability is an important characteristic of cancer. While most cancers develop genetic instability at some stage of their progression, sometimes a temporary rise of instability is followed by the return to a relatively stable genome. Neither the reasons for these dynamics, nor, more generally, the role of instability in tumor progression, are well understood. In this paper we develop a class of mathematical models to study the evolutionary competition dynamics among different sub-populations in a heterogeneous tumor. We observe that despite the complexity of this multi-component and multi-process system, there is only a small number of scenarios expected in the context of the evolution of instability. If the penalty incurred by unstable cells (the decrease in the growth due to deleterious mutations) is high compared with the gain (the production rate of advantageous mutations), then instability does not evolve. In the opposite case, instability evolves and comes to dominate the system. In the intermediate parameter regime, instability is generated but later gives way to stable clones. Moreover, the model also informs us of the patterns of instability for cancer lineages corresponding to different stages of progression. It is predicted that mutations causing instability are merely "passengers" in tumors that have undergone only a small number of malignant mutations. Further down the path of carcinogenesis, however, unstable cells are more likely to give rise to the winning clonal wave that takes over the tumor and carries the evolution forward, thus conferring a causal role of the instability in such cases. Further, each individual clonal wave (i.e. cells harboring a fixed number of malignant driver mutations) experiences its own evolutionary history. It can fall under one of three types of temporal behavior: stable throughout, unstable to stable, or unstable throughout. Which scenario is realized depends on the subtle (but predictable) interplay among mutation rates and the death toll associated with the instability. The modeling approach provided here sheds light onto important aspects of the evolutionary dynamics of instability, which may be relevant to treatment scenarios that target instability or damage repair.

Smoking: additional burden on aging and death

Tobacco smoking is a major cause of lung cancer. It has been suggested that there is an approximately linear dose–response relationship between the number of cigarettes smoked per day and clinical outcome such as lung cancer mortality. It has also been proposed that there is a greater increase in mortality at high doses when the dose is represented by the duration of the smoking habit rather than the number of cigarettes. The multistep carcinogenesis theory indicates that a greater increase in mortality rate at high doses is possible, as is the case between aging and cancer, even though each dose–response relationship between a carcinogenic factor and a carcinogenic step forward is linear. The high incidence of lung cancer after long-term smoking and the decreased relative risk after smoking cessation suggests a similarity between the effects of smoking and aging. Prediction of lung cancer risk in former smokers by simple integration of smoking effects with aging demonstrated a good correlation with that estimated from the relative risk of the period of smoking cessation. In contrast to the smoking period, there appears to be a linear relationship between smoking strength and cancer risk. This might arise if the dose–response relationship between smoking strength and each carcinogenic step is less than linear, or the effects become saturated with a large dose of daily smoking. Such a dose–response relationship could lead to relatively large clinical effects, such as cardiovascular mortality, by low-dose tobacco smoke exposure, e.g., second-hand smoking. Consideration of the dose–response of each effect is important to evaluate the risk arising from each carcinogenic factor.

Beyond two-stage models for lung carcinogenesis in the Mayak workers: implications for plutonium risk

Mechanistic multi-stage models are used to analyze lung-cancer mortality after Plutonium exposure in the Mayak-workers cohort, with follow-up until 2008. Besides the established two-stage model with clonal expansion, models with three mutation stages as well as a model with two distinct pathways to cancer are studied. The results suggest that three-stage models offer an improved description of the data. The best-fitting models point to a mechanism where radiation increases the rate of clonal expansion. This is interpreted in terms of changes in cell-cycle control mediated by bystander signaling or repopulation following cell killing. No statistical evidence for a two-pathway model is found. To elucidate the implications of the different models for radiation risk, several exposure scenarios are studied. Models with a radiation effect at an early stage show a delayed response and a pronounced drop-off with older ages at exposure. Moreover, the dose-response relationship is strongly nonlinear for all three-stage models, revealing a marked increase above a critical dose.

Task-based measures of image quality and their relation to radiation dose and patient risk

The theory of task-based assessment of image quality is reviewed in the context of imaging with ionizing radiation, and objective figures of merit (FOMs) for image quality are summarized. The variation of the FOMs with the task, the observer and especially with the mean number of photons recorded in the image is discussed. Then various standard methods for specifying radiation dose are reviewed and related to the mean number of photons in the image and hence to image quality. Current knowledge of the relation between local radiation dose and the risk of various adverse effects is summarized, and some graphical depictions of the tradeoffs between image quality and risk are introduced. Then various dose-reduction strategies are discussed in terms of their effect on task-based measures of image quality.

The non-targeted effects of radiation are perpetuated by exosomes

Exosomes contain cargo material from endosomes, cytosol, plasma membrane and microRNA molecules, they are released by a number of non-cancer and cancer cells into both the extracellular microenvironment and body fluids such as blood plasma. Recently we demonstrated radiation-induced non-targeted effects [NTE: genomic instability (GI) and bystander effects (BE)] are partially mediated by exosomes, particularly the RNA content. However the mechanistic role of exosomes in NTE is yet to be fully understood. The present study used MCF7 cells to characterise the longevity of exosome-induced activity in the progeny of irradiated and unirradiated bystander cells. Exosomes extracted from conditioned media of irradiated and bystander progeny were added to unirradiated cells. Analysis was carried out at 1 and 20/24 population doublings following medium/exosome transfer for DNA/chromosomal damage. Results confirmed exosomes play a significant role in mediating NTE of ionising radiation (IR). This effect was remarkably persistent, observed >20 doublings post-irradiation in the progeny of bystander cells. Additionally, cell progeny undergoing a BE were themselves capable of inducing BE in other cells via exosomes they released. Furthermore we investigated the role of exosome cargo. Culture media from cells exposed to 2 Gy X-rays was subjected to ultracentrifugation and four inoculants prepared, (a) supernatants with exosomes removed, and pellets with (b) exosome proteins denatured, (c) RNA degraded, and (d) a combination of protein-RNA inactivation. These were added to separate populations of unirradiated cells. The BE was partially inhibited when either exosome protein or exosome RNA were inactivated separately, whilst combined RNA-protein inhibition significantly reduced or eliminated the BE. These results demonstrate that exosomes are associated with long-lived signalling of the NTE of IR. Both RNA and protein molecules of exosomes work in a synergistic manner to initiate NTE, spread these effects to naïve cells, and perpetuate GI in the affected cells.

Anthropogenic selection enhances cancer evolution in Tasmanian devil tumours

The Tasmanian Devil Facial Tumour Disease (DFTD) provides a unique opportunity to elucidate the long-term effects of natural and anthropogenic selection on cancer evolution. Since first observed in 1996, this transmissible cancer has caused local population declines by >90%. So far, four chromosomal DFTD variants (strains) have been described and karyotypic analyses of 253 tumours showed higher levels of tetraploidy in the oldest strain. We propose that increased ploidy in the oldest strain may have evolved in response to effects of genomic decay observed in asexually reproducing organisms. In this study, we focus on the evolutionary response of DFTD to a disease suppression trial. Tumours collected from devils subjected to the removal programme showed accelerated temporal evolution of tetraploidy compared with tumours from other populations where no increase in tetraploid tumours were observed. As ploidy significantly reduces tumour growth rate, we suggest that the disease suppression trial resulted in selection favouring slower growing tumours mediated by an increased level of tetraploidy. Our study reveals that DFTD has the capacity to rapidly respond to novel selective regimes and that disease eradication may result in novel tumour adaptations, which may further imperil the long-term survival of the world's largest carnivorous marsupial.

Uncertainties in estimating health risks associated with exposure to ionising radiation

The information for the present discussion on the uncertainties associated with estimation of radiation risks and probability of disease causation was assembled for the recently published NCRP Report No. 171 on this topic. This memorandum provides a timely overview of the topic, given that quantitative uncertainty analysis is the state of the art in health risk assessment and given its potential importance to developments in radiation protection. Over the past decade the increasing volume of epidemiology data and the supporting radiobiology findings have aided in the reduction of uncertainty in the risk estimates derived. However, it is equally apparent that there remain significant uncertainties related to dose assessment, low dose and low dose-rate extrapolation approaches (e.g. the selection of an appropriate dose and dose-rate effectiveness factor), the biological effectiveness where considerations of the health effects of high-LET and lower-energy low-LET radiations are required and the transfer of risks from a population for which health effects data are available to one for which such data are not available. The impact of radiation on human health has focused in recent years on cancer, although there has been a decided increase in the data for noncancer effects together with more reliable estimates of the risk following radiation exposure, even at relatively low doses (notably for cataracts and cardiovascular disease). New approaches for the estimation of hereditary risk have been developed with the use of human data whenever feasible, although the current estimates of heritable radiation effects still are based on mouse data because of an absence of effects in human studies. Uncertainties associated with estimation of these different types of health effects are discussed in a qualitative and semi-quantitative manner as appropriate. The way forward would seem to require additional epidemiological studies, especially studies of low dose and low dose-rate occupational and perhaps environmental exposures and for exposures to x rays and high-LET radiations used in medicine. The development of models for more reliably combining the epidemiology data with experimental laboratory animal and cellular data can enhance the overall risk assessment approach by providing biologically refined data to strengthen the estimation of effects at low doses as opposed to the sole use of mathematical models of epidemiological data that are primarily driven by medium/high doses. NASA's approach to radiation protection for astronauts, although a unique occupational group, indicates the possible applicability of estimates of risk and their uncertainty in a broader context for developing recommendations on: (1) dose limits for occupational exposure and exposure of members of the public; (2) criteria to limit exposures of workers and members of the public to radon and its short-lived decay products; and (3) the dosimetric quantity (effective dose) used in radiation protection.

Analysis and prediction of pathways in HeLa cells by integrating biological levels of organization with systems-biology approaches

It has recently begun to be considered that cancer is a systemic disease and that it must be studied at every level of complexity using many of the currently available approaches, including high-throughput technologies and bioinformatics. To achieve such understanding in cervical cancer, we collected information on gene, protein and phosphoprotein expression of the HeLa cell line and performed a comprehensive analysis of the different signaling pathways, transcription networks and metabolic events in which they participate. A total expression analysis by RNA-Seq of the HeLa cell line showed that 19,974 genes were transcribed. Of these, 3,360 were over-expressed, and 2,129 under-expressed when compared to the NHEK cell line. A protein-protein interaction network was derived from the over-expressed genes and used to identify central elements and, together with the analysis of over-represented transcription factor motifs, to predict active signaling and regulatory pathways. This was further validated by Metal-Oxide Affinity Chromatography (MOAC) and Tandem Mass Spectrometry (MS/MS) assays which retrieved phosphorylated proteins. The 14-3-3 family members emerge as important regulators in carcinogenesis and as possible clinical targets. We observed that the different over- and under-regulated pathways in cervical cancer could be interrelated through elements that participate in crosstalks, therefore belong to what we term "meta-pathways". Additionally, we highlighted the relations of each one of the differentially represented pathways to one or more of the ten hallmarks of cancer. These features could be maintained in many other types of cancer, regardless of mutations or genomic rearrangements, and favor their robustness, adaptations and the evasion of tissue control. Probably, this could explain why cancer cells are not eliminated by selective pressure and why therapy trials directed against molecular targets are not as effective as expected.

The rs391957 variant cis-regulating oncogene GRP78 expression contributes to the risk of hepatocellular carcinoma

Glucose-regulated protein 78 (GRP78) is one of the most important responders to disease-related stress. We assessed the association of the promoter polymorphisms of GRP78 with risk of hepatocellular carcinoma (HCC) and GRP78 expression in a Chinese population. We examined 1007 patients undergoing diagnostic HCC and 810 unrelated healthy controls. Mechanisms by which the GRP78 promoter polymorphism modulates HCC risk and GRP78 levels were analyzed. The promoter haplotype and diplotype carrying rs391957 (-415bp) allele G and genotype GG was strongly associated with HCC risk. Luciferase reporter assays indicated that the promoter carrying rs391957 allele G (haplotype GCCd) showed increased activity in HepG2 cells and Hela cells. rs391957 was also shown to increase the affinity of the transcriptional activator Ets-2, the resistance to apoptosis, as well as cell instability in stressful microenvironment. Furthermore, compared with allele A, rs391957 allele G was associated with higher levels of GRP78 mRNA and protein in HCC tissues. These findings provided new insights into the pathogenesis of HCC and an unexpected effect of the interaction between rs391957 and Ets-2 on hepatocarcinogenesis, and especially supported the hypothesis that stress-related and evolutionarily conserved genetic variant(s) influencing transcriptional regulation could predict susceptibilities.

[Energy metabolism pathway related genes and adaptive evolution of tumor cells]

The proliferation of tumor cells is an extremely energy-consuming process. However, different from normal cells, tumor cells generate energy via glycolysis even under aerobic conditions, which is one of the ten hallmarks of tumor cells. The switch of energy metabolism results in a series of physiological changes in tumor cells, including rapid generation of ATP and abundant biomass for cell proliferation, which form the basis of tumor cells to successfully adapt to their extreme microenvironment (e.g. lack of oxygen). In this review, we will introduce recent progress in studying somatic mutations on the energy metabolism related genes in tumors, with special focus on the potential factors involving in the "switch" and to decipher the genetic adaptive footprint of the "switch" from the angle of molecular evolution.

Cancer cell growth and survival as a system-level property sustained by enhanced glycolysis and mitochondrial metabolic remodeling

Systems Biology holds that complex cellular functions are generated as system-level properties endowed with robustness, each involving large networks of molecular determinants, generally identified by “omics” analyses. In this paper we describe four basic cancer cell properties that can easily be investigated in vitro: enhanced proliferation, evasion from apoptosis, genomic instability, and inability to undergo oncogene-induced senescence. Focusing our analysis on a K-ras dependent transformation system, we show that enhanced proliferation and evasion from apoptosis are closely linked, and present findings that indicate how a large metabolic remodeling sustains the enhanced growth ability. Network analysis of transcriptional profiling gives the first indication on this remodeling, further supported by biochemical investigations and metabolic flux analysis (MFA). Enhanced glycolysis, down-regulation of TCA cycle, decoupling of glucose and glutamine utilization, with increased reductive carboxylation of glutamine, so to yield a sustained production of growth building blocks and glutathione, are the hallmarks of enhanced proliferation. Low glucose availability specifically induces cell death in K-ras transformed cells, while PKA activation reverts this effect, possibly through at least two mitochondrial targets. The central role of mitochondria in determining the two investigated cancer cell properties is finally discussed. Taken together the findings reported herein indicate that a system-level property is sustained by a cascade of interconnected biochemical pathways that behave differently in normal and in transformed cells.

CHM/REP1 cDNA delivery by lentiviral vectors provides functional expression of the transgene in the retinal pigment epithelium of choroideremia mice

BACKGROUND

Choroideremia (CHM) is a progressive X-linked degeneration of three ocular layers: photoreceptors, retinal pigment epithelium (RPE) and choroid, caused by the loss of Rab Escort Protein-1 (REP1). As a recessive monogenic disorder, CHM is potentially curable by gene addition therapy. The present study aimed to evaluate the potential use of lentiviral vectors carrying CHM/REP1 cDNA transgene for CHM treatment.

METHODS

We generated lentiviral vectors carrying either CHM/REP1 cDNA or EGFP transgene under the control of the elongation factor-1α promoter (EF-1α) or its shortened version EFS. We transduced human (HT1080) and dog (D17) cells, CHM patient's fibroblasts and mouse primary RPE cells in vitro, as well as wild-type and CHM mouse retinas in vivo by subretinal injections. Transgene expression was confirmed by immunoblotting, fluorescence-activated cell sorting, immunofluorescence and confocal microscopy. CHM/REP1 transgene functionality was assessed by an in vitro prenylation assay.

RESULTS

Lentiviral vectors with CHM/REP1 and EGFP transgenes efficiently transduced HT1080, D17 and CHM fibroblast cells; CHM/REP1 transgene lead to an increase in prenylation activity. Subretinal injections of lentiviral vectors into mouse retinas resulted in efficient transduction of the RPE (30-35% of total RPE cells transduced after a 1-µl injection), long-term expression for at least 6  months and a decrease in amount of unprenylated Rabs in the CHM RPE. Transduction of neuroretinal cells was restricted to the injection site.

CONCLUSIONS

Lentiviral CHM/REP1 cDNA transgene rescues the prenylation defect in CHM mouse RPE and thus could be used to restore REP1 activity in the RPE of CHM patients.

Combinatorial drug therapy for cancer in the post-genomic era

Over the past decade, whole genome sequencing and other 'omics' technologies have defined pathogenic driver mutations to which tumor cells are addicted. Such addictions, synthetic lethalities and other tumor vulnerabilities have yielded novel targets for a new generation of cancer drugs to treat discrete, genetically defined patient subgroups. This personalized cancer medicine strategy could eventually replace the conventional one-size-fits-all cytotoxic chemotherapy approach. However, the extraordinary intratumor genetic heterogeneity in cancers revealed by deep sequencing explains why de novo and acquired resistance arise with molecularly targeted drugs and cytotoxic chemotherapy, limiting their utility. One solution to the enduring challenge of polygenic cancer drug resistance is rational combinatorial targeted therapy.

Gompertz' survivorship law as an intrinsic principle of aging

We defend the hypothesis that life-spanning population survivorship curves, as described by Gompertz' law and composed from cross-sectional data (here mortality), reflect an intrinsic aging principle active in each subject of that population. In other words Gompertz' law reflects aging of a prototypical subject, provided minimal (or no) external causes of death (i.e. fatal infections, starvation, accidents). Our approach deviates from the traditional (exponential) Gompertz' hazard function. For instance, the here formulated Gompertz' law accurately describes old-age deceleration of both all-cause mortality and the incidence of some ageing-associated cancers, as illustrated for the Dutch population. We consider the possibility that the old-age expression and progression of cancer and other pathologies becomes suppressed, because of random (and exponential) accumulation of damage during life. Gompertz' law may trigger new concepts and models describing life-spanning physiological and pathological processes of aging. We discuss (and reject) various aging models (e.g. a predominant role of individual variations at birth; reliability theory) and point to the explanatory potential of network models and systemic regulatory models.

An intronic polymorphism in GRP78 improves chemotherapeutic prediction in non-small cell lung cancer

BACKGROUND

Glucose-regulated protein 78 (GRP78) is involved in not only the progression of non-small cell lung cancer (NSCLC) but also chemotherapeutic effects. We hypothesized that an intronic polymorphism (rs430397G>A) in GRP78 affects survival among patients with NSCLC treated with platinum-based chemotherapy.

METHODS

Blood samples of patients with advanced NSCLC (IIIB/IV) were maintained in our specimen bank between 2001 and 2006. Genomic DNA was genotyped for rs430397. Associations between rs430397 and platinum-based treatment response, overall survival (OS), NSCLC-related survival, progression-free survival (PFS), and relapses were evaluated. GRP78 RNA and protein in NSCLC tissues were tested by real-time polymerase chain reaction and immunohistochemistry.

RESULTS

The AA genotype is significantly associated with platinum-based chemoresistance (P = .019) and NSCLC-related death (P = .022). OS, NSCLC-related survival, and PFS of the AA genotype group are decreased compared with the GG and AG genotype groups (log-rank P < .05, respectively). The AA group showed a higher prevalence of early NSCLC relapses than the AG and GG group (P = .030). In addition, the AA genotype showed a significantly increased risk for OS (hazard ratio, 1.95) and PFS (hazard ratio, 1.80) compared with the GG group. Functional analysis showed that NSCLC tissues with genotype AA have higher GRP78 RNA and protein expression compared with those carrying GG at rs430397.

CONCLUSIONS

The rs430397 AA genotype of GRP78 is associated with reduced survival and higher prevalence of early relapses in patients with advanced NSCLC treated with platinum-based chemotherapy.

Ontogenetic variation of the human genome

The human genome demonstrates variable levels of instability during ontogeny. Achieving the highest rate during early prenatal development, it decreases significantly throughout following ontogenetic stages. A failure to decrease or a spontaneous increase of genomic instability can promote infertility, pregnancy losses, chromosomal and genomic diseases, cancer, immunodeficiency, or brain diseases depending on developmental stage at which it occurs. Paradoxically, late ontogeny is associated with increase of genomic instability that is considered a probable mechanism for human aging. The latter is even more appreciable in human diseases associated with pathological or accelerated aging (i.e. Alzheimer's disease and ataxia-telangiectasia). These observations resulted in a hypothesis suggesting that somatic genomic variations throughout ontogeny are determinants of cellular vitality in health and disease including intrauterine development, postnatal life and aging. The most devastative effect of somatic genome variations is observed when it manifests as chromosome instability or aneuploidy, which has been repeatedly noted to produce pathologic conditions and to mediate developmental regulatory and aging processes. However, no commonly accepted concepts on the role of chromosome/genome instability in determination of human health span and life span are available. Here, a review of these ontogenetic variations is given to propose a new "dynamic genome" model for pathological and natural genomic changes throughout life that mimic those of phylogenetic diversity.

The role of the microenvironment in tumor growth and invasion

Mathematical modeling and computational analysis are essential for understanding the dynamics of the complex gene networks that control normal development and homeostasis, and can help to understand how circumvention of that control leads to abnormal outcomes such as cancer. Our objectives here are to discuss the different mechanisms by which the local biochemical and mechanical microenvironment, which is comprised of various signaling molecules, cell types and the extracellular matrix (ECM), affects the progression of potentially-cancerous cells, and to present new results on two aspects of these effects. We first deal with the major processes involved in the progression from a normal cell to a cancerous cell at a level accessible to a general scientific readership, and we then outline a number of mathematical and computational issues that arise in cancer modeling. In Section 2 we present results from a model that deals with the effects of the mechanical properties of the environment on tumor growth, and in Section 3 we report results from a model of the signaling pathways and the tumor microenvironment (TME), and how their interactions affect the development of breast cancer. The results emphasize anew the complexities of the interactions within the TME and their effect on tumor growth, and show that tumor progression is not solely determined by the presence of a clone of mutated immortal cells, but rather that it can be 'community-controlled'.

The origins of cancer robustness and evolvability

Unless diagnosed early, many adult cancers remain incurable diseases. This is despite an intense global research effort to develop effective anticancer therapies, calling into question the use of rational drug design strategies in targeting complex disease states such as cancer. A fundamental challenge facing researchers and clinicians is that cancers are inherently robust biological systems, able to survive, adapt and proliferate despite the perturbations resulting from anticancer drugs. It is essential that the mechanisms underlying tumor robustness be formally studied and characterized, as without a thorough understanding of the principles of tumor robustness, strategies to overcome therapy resistance are unlikely to be found. Degeneracy describes the ability of structurally distinct system components (e.g. proteins, pathways, cells, organisms) to be conditionally interchangeable in their contribution to system traits and it has been broadly implicated in the robustness and evolvability of complex biological systems. Here we focus on one of the most important mechanisms underpinning tumor robustness and degeneracy, the cellular heterogeneity that is the hallmark of most solid tumors. Based on a combination of computational, experimental and clinical studies we argue that stochastic noise is an underlying cause of tumor heterogeneity and particularly degeneracy. Drawing from a number of recent data sets, we propose an integrative model for the evolution of therapy resistance, and discuss recent computational studies that propose new therapeutic strategies aimed at defeating the adaptable cancer phenotype.