Modeling embryogenesis and cancer: an approach based on an equilibrium between the autostabilization of stochastic gene expression and the interdependence of cells for proliferation

From genetic mosaicism to tumorigenesis through indirect genetic effects

Genetic mosaicism has long been linked to aging, and several hypotheses have been proposed to explain the potential connections between mosaicism and susceptibility to cancer. It has been proposed that mosaicism may disrupt tissue homeostasis by affecting intercellular communications and releasing microenvironmental constraints within tissues. The underlying mechanisms driving these tissue-level influences remain unidentified, however. Here, we present an evolutionary perspective on the interplay between mosaicism and cancer, suggesting that the tissue-level impacts of genetic mosaicism can be attributed to Indirect Genetic Effects (IGEs). IGEs can increase the level of cellular stochasticity and phenotypic instability among adjacent cells, thereby elevating the risk of cancer development within the tissue. Moreover, as cells experience phenotypic changes in response to challenging microenvironmental conditions, these changes can initiate a cascade of nongenetic alterations, referred to as Indirect non-Genetic Effects (InGEs), which in turn catalyze IGEs among surrounding cells. We argue that incorporating both InGEs and IGEs into our understanding of the process of oncogenic transformation could trigger a major paradigm shift in cancer research with far-reaching implications for practical applications.

Clinical Tumor Dormancy

This chapter summarizes clinical evidence on tumor dormancy, with a special focus on our research supporting the role of dormancy both in local and distant recurrence of breast cancer following mastectomy. Starting from these premises, we propose a model of neoplastic development that allows us to elucidate several relevant clinical phenomena, including the mammographic paradox, the significance of ipsilateral breast tumor recurrence after conservative surgery, and the effect of surgeries performed after the removal of the primary. We will discuss the biological implications of the dormancy-based model, which are at odds with Somatic Mutation Theory. We will then review new models, alternatives to the Somatic Mutation Theory, for cancer development, with special emphasis on the Dynamic System Theory and the originality of its conceptual approach. Finally, we will put particular emphasis on the view of cancer development as a tissue-level process. We believe that this will help harmonize the molecular biology research with the new conceptual approach and bridge the knowledge gap on dormancy between bench and bedside.

Reimagining Cancer: Moving from the Cellular to the Tissue Level

The current universally accepted explanation of cancer origin and behavior, the somatic mutation theory, is cell-centered and rooted in perturbation of gene function independent of the external environmental context. However, tumors consist of various epithelial and stromal cell populations temporally and spatially organized into an integrated neoplastic community, and they can have properties similar to normal tissues. Accordingly, we review specific normal cellular and tissue traits and behaviors with adaptive temporal and spatial self-organization that result in ordered patterns and structures. A few recent theories have described these tissue-level cancer behaviors, invoking a conceptual shift from the cellular level and highlighting the need for methodologic approaches based on the analysis of complex systems. We propose extending the analytical approach of regulatory networks to the tissue level and introduce the concept of "cancer attractors." These concepts require reevaluation of cancer imaging and investigational approaches and challenge the traditional reductionist approach of cancer molecular biology.

Zebrafish neuromesodermal progenitors undergo a critical state transition in vivo

The transition state model of cell differentiation proposes that a transient window of gene expression stochasticity precedes entry into a differentiated state. Here, we assess this theoretical model in zebrafish neuromesodermal progenitors (NMps) in vivo during late somitogenesis stages. We observed an increase in gene expression variability at the 24 somite stage (24ss) before their differentiation into spinal cord and paraxial mesoderm. Analysis of a published 18ss scRNA-seq dataset showed that the NMp population is noisier than its derivatives. By building in silico composite gene expression maps from image data, we assigned an 'NM index' to in silico NMps based on the expression of neural and mesodermal markers and demonstrated that cell population heterogeneity peaked at 24ss. Further examination revealed cells with gene expression profiles incongruent with their prospective fate. Taken together, our work supports the transition state model within an endogenous cell fate decision making event.

Space Biomedicine: A Unique Opportunity to Rethink the Relationships between Physics and Biology

Space biomedicine has provided significant technological breakthroughs by developing new medical devices, diagnostic tools, and health-supporting systems. Many of these products are currently in use onboard the International Space Station and have been successfully translated into clinical practice on Earth. However, biomedical research performed in space has disclosed exciting, new perspectives regarding the relationships between physics and medicine, thus fostering the rethinking of the theoretical basis of biology. In particular, these studies have stressed the critical role that biophysical forces play in shaping the function and pattern formation of living structures. The experimental models investigated under microgravity conditions allow us to appreciate the complexity of living organisms through a very different perspective. Indeed, biological entities should be conceived as a unique magnification of physical laws driven by local energy and order states overlaid by selection history and constraints, in which the source of the inheritance, variation, and process of selection has expanded from the classical Darwinian definition. The very specific nature of the field in which living organisms behave and evolve in a space environment can be exploited to decipher the underlying, basic processes and mechanisms that are not apparent on Earth. In turn, these findings can provide novel opportunities for testing pharmacological countermeasures that can be instrumental for managing a wide array of health problems and diseases on Earth.

A Darwinian and Physical Look at Stem Cell Biology Helps Understanding the Role of Stochasticity in Development

Single-cell analysis allows biologists to gain huge insight into cell differentiation and tissue structuration. Randomness of differentiation, both in vitro and in vivo, of pluripotent (multipotent) stem cells is now demonstrated to be mainly based on stochastic gene expression. Nevertheless, it remains necessary to incorporate this inherent stochasticity of developmental processes within a coherent scheme. We argue here that the theory called ontophylogenesis is more relevant and better fits with experimental data than alternative theories which have been suggested based on the notions of self-organization and attractor states. The ontophylogenesis theory considers the generation of a differentiated state as a constrained random process: randomness is provided by the stochastic dynamics of biochemical reactions while the environmental constraints, including cell inner structures and cell-cell interactions, drive the system toward a stabilized state of equilibrium. In this conception, biological organization during development can be seen as the result of multiscale constraints produced by the dynamical organization of the biological system which retroacts on the stochastic dynamics at lower scales. This scheme makes it possible to really understand how the generation of reproducible structures at higher organization levels can be fully compatible with probabilistic behavior at the lower levels. It is compatible with the second law of thermodynamics but allows the overtaking of the limitations exhibited by models only based on entropy exchanges which cannot cope with the description nor the dynamics of the mesoscopic and macroscopic organization of biological systems.

Histone Methylation Participates in Gene Expression Control during the Early Development of the Pacific Oyster Crassostrea gigas

Histone methylation patterns are important epigenetic regulators of mammalian development, notably through stem cell identity maintenance by chromatin remodeling and transcriptional control of pluripotency genes. But, the implications of histone marks are poorly understood in distant groups outside vertebrates and ecdysozoan models. However, the development of the Pacific oyster Crassostrea gigas is under the strong epigenetic influence of DNA methylation, and Jumonji histone-demethylase orthologues are highly expressed during C. gigas early life. This suggests a physiological relevance of histone methylation regulation in oyster development, raising the question of functional conservation of this epigenetic pathway in lophotrochozoan. Quantification of histone methylation using fluorescent ELISAs during oyster early life indicated significant variations in monomethyl histone H3 lysine 4 (H3K4me), an overall decrease in H3K9 mono- and tri-methylations, and in H3K36 methylations, respectively, whereas no significant modification could be detected in H3K27 methylation. Early in vivo treatment with the JmjC-specific inhibitor Methylstat induced hypermethylation of all the examined histone H3 lysines and developmental alterations as revealed by scanning electronic microscopy. Using microarrays, we identified 376 genes that were differentially expressed under methylstat treatment, which expression patterns could discriminate between samples as indicated by principal component analysis. Furthermore, Gene Ontology revealed that these genes were related to processes potentially important for embryonic stages such as binding, cell differentiation and development. These results suggest an important physiological significance of histone methylation in the oyster embryonic and larval life, providing, to our knowledge, the first insights into epigenetic regulation by histone methylation in lophotrochozoan development.

SMT and TOFT: Why and How They are Opposite and Incompatible Paradigms

The Somatic Mutation Theory (SMT) has been challenged on its fundamentals by the Tissue Organization Field Theory of Carcinogenesis (TOFT). However, a recent publication has questioned whether TOFT could be a valid alternative theory of carcinogenesis to that presented by SMT. Herein we critically review arguments supporting the irreducible opposition between the two theoretical approaches by highlighting differences regarding the philosophical, methodological and experimental approaches on which they respectively rely. We conclude that SMT has not explained carcinogenesis due to severe epistemological and empirical shortcomings, while TOFT is gaining momentum. The main issue is actually to submit SMT to rigorous testing. This concern includes the imperatives to seek evidence for disproving one's hypothesis, and to consider the whole, and not just selective evidence.

Electrical coupling in ensembles of nonexcitable cells: modeling the spatial map of single cell potentials

We analyze the coupling of model nonexcitable (non-neural) cells assuming that the cell membrane potential is the basic individual property. We obtain this potential on the basis of the inward and outward rectifying voltage-gated channels characteristic of cell membranes. We concentrate on the electrical coupling of a cell ensemble rather than on the biochemical and mechanical characteristics of the individual cells, obtain the map of single cell potentials using simple assumptions, and suggest procedures to collectively modify this spatial map. The response of the cell ensemble to an external perturbation and the consequences of cell isolation, heterogeneity, and ensemble size are also analyzed. The results suggest that simple coupling mechanisms can be significant for the biophysical chemistry of model biomolecular ensembles. In particular, the spatiotemporal map of single cell potentials should be relevant for the uptake and distribution of charged nanoparticles over model cell ensembles and the collective properties of droplet networks incorporating protein ion channels inserted in lipid bilayers.

Epigenetic features in the oyster Crassostrea gigas suggestive of functionally relevant promoter DNA methylation in invertebrates

DNA methylation is evolutionarily conserved. Vertebrates exhibit high, widespread DNA methylation whereas invertebrate genomes are less methylated, predominantly within gene bodies. DNA methylation in invertebrates is associated with transcription level, alternative splicing, and genome evolution, but functional outcomes of DNA methylation remain poorly described in lophotrochozoans. Recent genome-wide approaches improve understanding in distant taxa such as molluscs, where the phylogenetic position, and life traits of Crassostrea gigas make this bivalve an ideal model to study the physiological and evolutionary implications of DNA methylation. We review the literature about DNA methylation in invertebrates and focus on DNA methylation features in the oyster. Indeed, though our MeDIP-seq results confirm predominant intragenic methylation, the profiles depend on the oyster's developmental and reproductive stage. We discuss the perspective that oyster DNA methylation could be biased toward the 5'-end of some genes, depending on physiological status, suggesting important functional outcomes of putative promoter methylation from cell differentiation during early development to sustained adaptation of the species to the environment.

Macroscopic quantum-type potentials in theoretical systems biology

We review in this paper the use of the theory of scale relativity and fractal space-time as a tool particularly well adapted to the possible development of a future genuine systems theoretical biology. We emphasize in particular the concept of quantum-type potentials, since, in many situations, the effect of the fractality of space—or of the underlying medium—can be reduced to the addition of such a potential energy to the classical equations of motion. Various equivalent representations—geodesic, quantum-like, fluid mechanical, stochastic—of these equations are given, as well as several forms of generalized quantum potentials. Examples of their possible intervention in high critical temperature superconductivity and in turbulence are also described, since some biological processes may be similar in some aspects to these physical phenomena. These potential extra energy contributions could have emerged in biology from the very fractal nature of the medium, or from an evolutive advantage, since they involve spontaneous properties of self-organization, morphogenesis, structuration and multi-scale integration. Finally, some examples of applications of the theory to actual biological-like processes and functions are also provided.

DNA methylation is crucial for the early development in the Oyster C. gigas

In vertebrates, epigenetic modifications influence gene transcription, and an appropriate DNA methylation is critical in development. Indeed, a precise temporal and spatial pattern of early gene expression is mandatory for a normal embryogenesis. However, such a regulation and its underlying mechanisms remain poorly understood in more distant organisms such as Lophotrochozoa. Thus, despite DNA in the oyster genome being methylated, the role of DNA methylation in development is unknown. To clarify this point, oyster genomic DNA was examined during early embryogenesis and found differentially methylated. Reverse transcriptase quantitative polymerase chain reaction indicated stage-specific levels of transcripts encoding DNA-methyltransferase (DNMT) and methyl-binding domain proteins. In addition, as highlighted by electronic microscopy and immunohistochemistry, the DNMT inhibitor 5-aza-cytidine induced alterations in the quantity and the localisation of methylated DNA and severe dose-dependent development alterations and was lethal after zygotic genome reinitiation. Furthermore, methyl-DNA-immunoprecipitation-quantitative polymerase chain reaction revealed that the transcription level of most of the homeobox gene orthologues examined, but not of the other early genes investigated, was inversely correlated with their specific DNA methylation. Altogether, our results demonstrate that DNA methylation influences gene expression in Crassostrea gigas and is critical for oyster development, possibly by specifically controlling the transcription level of homeobox orthologues. These findings provide evidence for the importance of epigenetic regulation of development in Lophotrochozoans and bring new insights into the early life of C. gigas, one of the most important aquaculture resources worldwide.

How changes in extracellular matrix mechanics and gene expression variability might combine to drive cancer progression

Changes in extracellular matrix (ECM) structure or mechanics can actively drive cancer progression; however, the underlying mechanism remains unknown. Here we explore whether this process could be mediated by changes in cell shape that lead to increases in genetic noise, given that both factors have been independently shown to alter gene expression and induce cell fate switching. We do this using a computer simulation model that explores the impact of physical changes in the tissue microenvironment under conditions in which physical deformation of cells increases gene expression variability among genetically identical cells. The model reveals that cancerous tissue growth can be driven by physical changes in the microenvironment: when increases in cell shape variability due to growth-dependent increases in cell packing density enhance gene expression variation, heterogeneous autonomous growth and further structural disorganization can result, thereby driving cancer progression via positive feedback. The model parameters that led to this prediction are consistent with experimental measurements of mammary tissues that spontaneously undergo cancer progression in transgenic C3(1)-SV40Tag female mice, which exhibit enhanced stiffness of mammary ducts, as well as progressive increases in variability of cell-cell relations and associated cell shape changes. These results demonstrate the potential for physical changes in the tissue microenvironment (e.g., altered ECM mechanics) to induce a cancerous phenotype or accelerate cancer progression in a clonal population through local changes in cell geometry and increased phenotypic variability, even in the absence of gene mutation.

Stabilizing gene regulatory networks through feedforward loops

The global dynamics of gene regulatory networks are known to show robustness to perturbations in the form of intrinsic and extrinsic noise, as well as mutations of individual genes. One molecular mechanism underlying this robustness has been identified as the action of so-called microRNAs that operate via feedforward loops. We present results of a computational study, using the modeling framework of stochastic Boolean networks, which explores the role that such network motifs play in stabilizing global dynamics. The paper introduces a new measure for the stability of stochastic networks. The results show that certain types of feedforward loops do indeed buffer the network against stochastic effects.

Theoretical aspects of Systems Biology

The natural world consists of hierarchical levels of complexity that range from subatomic particles and molecules to ecosystems and beyond. This implies that, in order to explain the features and behavior of a whole system, a theory might be required that would operate at the corresponding hierarchical level, i.e. where self-organization processes take place. In the past, biological research has focused on questions that could be answered by a reductionist program of genetics. The organism (and its development) was considered an epiphenomenona of its genes. However, a profound rethinking of the biological paradigm is now underway and it is likely that such a process will lead to a conceptual revolution emerging from the ashes of reductionism. This revolution implies the search for general principles on which a cogent theory of biology might rely. Because much of the logic of living systems is located at higher levels, it is imperative to focus on them. Indeed, both evolution and physiology work on these levels. Thus, by no means Systems Biology could be considered a 'simple' 'gradual' extension of Molecular Biology.

Transition probability in cell proliferation, stochasticity in cell differentiation, and the restriction point of the cell cycle in one package

Clonal cells are known to display stochastically varying interdivision times (IMT) and stochastic choices of cell fates. These features are suggested in the present paper to stem from discrete transitions of genes between different modes of their engagement in transcription. These transitions are explained by stochastic events of assembly/disassembly of huge ensembles of transcription factors needed to built-up gene-specific transcription preinitiation complexes (PIC). The time required to assemble a PIC at a gene promoter by random collisions of numerous proteins may be long enough to be comparable with the cell cycle. Independently published findings are reviewed to show that active genes may display discontinuous patterns of transcriptional output consistent with stochastically varying periods of PIC presence or absence at their promoters, and that these periods may reach several hours. This timescale matches the time needed for synchronised clonal cells to pass the restriction point (RP) of the cell cycle. RP is suggested to correspond to cell state where cell fate is determined by competing discrete transcriptional events. Cell fate choice depends on the event that, by chance, has outpaced other events able to commit the cell to alternative fates. Simple modelling based on these premises is consistent with general features of cell kinetics, including RP passage dependance on mitogenic stimulation, IMT distributions conformance to exponentially modified Gaussian, the limited proliferative potential of untransformed cells, relationships between changes in cell proliferation and differentiation, and bimodal distributions of cells over expression levels of genes involved in stem cell differentiation.

Genes at work in random bouts: stochastically discontinuous gene activity makes cell cycle duration and cell fate decisions variable, thus providing for stem cells plasticity

Cell interdivision periods (IDP) in homogenous cell populations vary stochastically. Another aspect of probabilistic cell behavior is randomness in cell differentiation. These features are suggested to result from competing stochastic events of assembly/disassembly of the transcription pre-initiation complex (PIC) at gene promoters. The time needed to assemble a proper PIC from different proteins, which must be numerous enough to make their combination gene specific, may be comparable to the IDP. Nascent mRNA visualization at defined genes and inferences from protein level fluctuations in single cells suggest that some genes do operate in this way. The onset of mRNA production by such genes may miss the time windows provided by the cell cycle, resulting in cells differentiating into those in which the respective mRNAs are either present or absent. This creates a way to generate cell phenotype diversity in multicellular organisms.

Can metabolic plasticity be a cause for cancer? Warburg-Waddington legacy revisited

Fermentation of glucose to lactate in the presence of sufficient oxygen, known as aerobic glycolysis or Warburg effect, is a universal phenotype of cancer cells. Understanding its origin and role in cellular immortalization and transformation has attracted considerable attention in the recent past. Intriguingly, while we now know that Warburg effect is essential for tumor growth and development, it is thought to arise because of genetic and/or epigenetic changes. In contrast to the above, we propose that Warburg effect can also arise due to normal biochemical fluctuations, independent of genetic and epigenetic changes. Cells that have acquired Warburg effect proliferate rapidly to give rise to a population of heterogeneous progenitors of cancer cells. Such cells also generate more lactate and alter the fitness landscape. This dynamic fitness landscape facilitates evolution of cancer cells from its progenitors, in a fashion analogous to Darwinian evolution. Thus, sporadic cancer can also occur first by the acquisition of Warburg effect, then followed by mutation and selection. The idea proposed here circumvents the inherent difficulties associated with the current understanding of tumorigenesis, and is also consistent with many experimental and epidemiological observations. We discuss this model in the context of epigenetics as originally enunciated by Waddington.

ELECTRONIC SUPPLEMENTARY MATERIAL

The online version of this article (doi:10.1007/s13148-011-0030-x) contains supplementary material, which is available to authorized users.

Stochastic variation of transcript abundance in C57BL/6J mice

Background

Transcripts can exhibit significant variation in tissue samples from inbred laboratory mice. We have designed and carried out a microarray experiment to examine transcript variation across samples from adipose, heart, kidney, and liver tissues of C57BL/6J mice and to partition variation into within-mouse and between-mouse components. Within-mouse variance captures variation due to heterogeneity of gene expression within tissues, RNA-extraction, and array processing. Between-mouse variance reflects differences in transcript abundance between genetically identical mice.

Results

The nature and extent of transcript variation differs across tissues. Adipose has the largest total variance and the largest within-mouse variance. Liver has the smallest total variance, but it has the most between-mouse variance. Genes with high variability can be classified into groups with correlated patterns of expression that are enriched for specific biological functions. Variation between mice is associated with circadian rhythm, growth hormone signaling, immune response, androgen regulation, lipid metabolism, and the extracellular matrix. Genes showing correlated patterns of within-mouse variation are also associated with biological functions that largely reflect heterogeneity of cell types within tissues.

Conclusions

Genetically identical mice can experience different individual outcomes for medically important traits. Variation in gene expression observed between genetically identical mice can identify functional classes of genes that are likely to vary in the absence of experimental perturbations, can inform experimental design decisions, and provides a baseline for the interpretation of gene expression data in interventional studies. The extent of transcript variation among genetically identical mice underscores the importance of stochastic and micro-environmental factors and their phenotypic consequences.

A systems biology approach to cancer: fractals, attractors, and nonlinear dynamics

Cancer begins to be recognized as a highly complex disease, and advanced knowledge of the carcinogenic process claims to be acquired by means of supragenomic strategies. Experimental data evidence that tumor emerges from disruption of tissue architecture, and it is therefore consequential that the tissue level should be considered the proper level of observation for carcinogenic studies. This paradigm shift imposes to move from a reductionistic to a systems biology approach. Indeed, cell phenotypes are emergent modes arising through collective nonlinear interactions among different cellular and microenvironmental components, generally described by a phase space diagram, where stable states (attractors) are embedded into a landscape model. Within this framework cell states and cell transitions are generally conceived as mainly specified by the gene-regulatory network. However, the system's dynamics cannot be reduced to only the integrated functioning of the genome-proteome network, and the cell-stroma interacting system must be taken into consideration in order to give a more reliable picture. As cell form represents the spatial geometric configuration shaped by an integrated set of cellular and environmental cues participating in biological functions control, it is conceivable that fractal-shape parameters could be considered as "omics" descriptors of the cell-stroma system. Within this framework it seems that function follows form, and not the other way around.

Computational energetic model of morphogenesis based on multi-agent Cellular Potts Model

The Cellular Potts Model (CPM) is a cellular automaton (CA), developed by Glazier and Graner in 1992, to model the morphogenesis. In this model, the entities are the cells. It has already been improved in many ways; however, a key point in biological systems, not defined in CPM, is energetic exchange between entities. We integrate this energetic concept inside the CPM. We simulate a cell differentiation inside a growing cell tissue. The results are the emergence of dynamic patterns coming from the consumption and production of energy. A model described by CA is less scalable than one described by a multi-agent system (MAS). We have developed a MAS based on the CPM, where a cell agent is implemented from the cell of CPM together with several behaviours, in particular the consumption and production of energy from the consumption of molecules.

Bistable cell fate specification as a result of stochastic fluctuations and collective spatial cell behaviour

BACKGROUND

In culture, isogenic mammalian cells typically display enduring phenotypic heterogeneity that arises from fluctuations of gene expression and other intracellular processes. This diversity is not just simple noise but has biological relevance by generating plasticity. Noise driven plasticity was suggested to be a stem cell-specific feature.

RESULTS

Here we show that the phenotypes of proliferating tissue progenitor cells such as primary mononuclear muscle cells can also spontaneously fluctuate between different states characterized by the either high or low expression of the muscle-specific cell surface molecule CD56 and by the corresponding high or low capacity to form myotubes. Although this capacity is a cell-intrinsic property, the cells switch their phenotype under the constraints imposed by the highly heterogeneous microenvironment created by their own collective movement. The resulting heterogeneous cell population is characterized by a dynamic equilibrium between "high CD56" and "low CD56" phenotype cells with distinct spatial distribution. Computer simulations reveal that this complex dynamic is consistent with a context-dependent noise driven bistable model where local microenvironment acts on the cellular state by encouraging the cell to fluctuate between the phenotypes until the low noise state is found.

CONCLUSIONS

These observations suggest that phenotypic fluctuations may be a general feature of any non-terminally differentiated cell. The cellular microenvironment created by the cells themselves contributes actively and continuously to the generation of fluctuations depending on their phenotype. As a result, the cell phenotype is determined by the joint action of the cell-intrinsic fluctuations and by collective cell-to-cell interactions.

Random discrete competing events vs. dynamic bistable switches in cell proliferation in differentiation

Several recent experiments related to fundamental aspects of cell behaviour, such as passing of the restriction point of cell cycle, which are generally interpreted in accordance with the dynamic paradigm implying the use of differential equations operating with the concentrations of cellular components and rate constants of their interactions, are shown in the present paper to be consistent with a simple model based on discrete competing stochastic events interpreted as assembly of alternative complexes of transcription factors at gene promoters. The model conforms to the transition probability model of cell cycle and to the stochastic approaches to cell differentiation and integrates them with the restriction point concept.

The role of noise and positive feedback in the onset of autosomal dominant diseases

Background

Autosomal dominant (AD) diseases result when a single mutant or non-functioning gene is present on an autosomal chromosome. These diseases often do not emerge at birth. There are presently two prevailing theories explaining the expression of AD diseases. One explanation originates from the Knudson two-hit theory of hereditary cancers, where loss of heterozygosity or occurrence of somatic mutations impairs the function of the wild-type copy. While these somatic second hits may be sufficient for stable disease states, it is often difficult to determine if their occurrence necessarily marks the initiation of disease progression. A more direct consequence of a heterozygous genetic background is haploinsufficiency, referring to a lack of sufficient gene function due to reduced wild-type gene copy number; however, haploinsufficiency can involve a variety of additional mechanisms, such as noise in gene expression or protein levels, injury and second hit mutations in other genes. In this study, we explore the possible contribution to the onset of autosomal dominant diseases from intrinsic factors, such as those determined by the structure of the molecular networks governing normal cellular physiology.

Results

First, simple models of single gene insufficiency using the positive feedback loops that may be derived from a three-component network were studied by computer simulation using Bionet software. The network structure is shown to affect the dynamics considerably; some networks are relatively stable even when large stochastic variations in are present, while others exhibit switch-like dynamics. In the latter cases, once the network switches over to the disease state it remains in that state permanently. Model pathways for two autosomal dominant diseases, AD polycystic kidney disease and mature onset diabetes of youth (MODY) were simulated and the results are compared to known disease characteristics.

Conclusions

By identifying the intrinsic mechanisms involved in the onset of AD diseases, it may be possible to better assess risk factors as well as lead to potential new drug targets. To illustrate the applicability of this study of pathway dynamics, we simulated the primary pathways involved in two autosomal dominant diseases, Polycystic Kidney Disease (PKD) and mature onset diabetes of youth (MODY). Simulations demonstrate that some of the primary disease characteristics are consistent with the positive feedback - stochastic variation theory presented here. This has implications for new drug targets to control these diseases by blocking the positive feedback loop in the relevant pathways.

Models of carcinogenesis: an overview

At least five coherent models of carcinogenesis have been proposed in the history of cancer research in the last century. Model 1 is mainly centered around mutations, and its main focus is on the chemical environment, radiation and viruses. Model 2 has to do mainly with genome instability and it focuses on familiality. Model 3 is based on non-genotoxic mechanisms, and clonal expansion and epigenetics are its main features. We propose a fourth model, which can encompass the previous three, based on the concept of a 'Darwinian' cell selection (we clarify that the term Darwinian needs to be used cautiously, being a short cut for 'somatic cellular selection'). Finally, a fifth model has recently become popular, based on the concept of 'tissue organization'. We describe examples of the five models and how they have been formalized mathematically. The five models largely overlap, both scientifically and historically, but for the sake of clarity, it is useful to treat them separately. We also argue that the five models can be included into a simpler scheme, i.e. two types of models: (i) biological changes in the epithelium alone lead to malignancy and (ii) changes in stroma/extracellular matrix are necessary (along with changes in epithelium) for malignancy. Our description, though simplified, looks realistic, it is able to capture the historical sequence of carcinogenesis theories in the last century and can serve as a frame to make research hypotheses more explicit.

Biophysics and systems biology

Biophysics at the systems level, as distinct from molecular biophysics, acquired its most famous paradigm in the work of Hodgkin and Huxley, who integrated their equations for the nerve impulse in 1952. Their approach has since been extended to other organs of the body, notably including the heart. The modern field of computational biology has expanded rapidly during the first decade of the twenty-first century and, through its contribution to what is now called systems biology, it is set to revise many of the fundamental principles of biology, including the relations between genotypes and phenotypes. Evolutionary theory, in particular, will require re-assessment. To succeed in this, computational and systems biology will need to develop the theoretical framework required to deal with multilevel interactions. While computational power is necessary, and is forthcoming, it is not sufficient. We will also require mathematical insight, perhaps of a nature we have not yet identified. This article is therefore also a challenge to mathematicians to develop such insights.

Synchrony in reaction-diffusion models of morphogenesis: applications to curvature-dependent proliferation and zero-diffusion front waves

The paper presents the classical age-dependent approach of the morphogenesis in the framework of the von Foerster equation, in which we introduce a new constraint and study a new feature: (i) the new constraint concerns cell proliferation along the contour lines of the cell density, depending on the local curvature such as it favours the amplification of the concavities (like in the gastrulation process) and (ii) the new feature consists of considering, on the cell density surface, a remarkable line (the null mean Gaussian curvature line), on which the normal diffusion vanishes, favouring local coexistence of diffusing morphogens, metabolites or cells, and hence the auto-assemblages of these entities. Two applications to biological multi-agents systems are studied, gastrulation and feather morphogenesis.

Distinct sequential cell behaviours direct primitive endoderm formation in the mouse blastocyst

The first two lineages to differentiate from a pluripotent cell population during mammalian development are the extraembryonic trophectoderm (TE) and the primitive endoderm (PrE). Whereas the mechanisms of TE specification have been extensively studied, segregation of PrE and the pluripotent epiblast (EPI) has received comparatively little attention. A current model of PrE specification suggests PrE precursors exhibit an apparently random distribution within the inner cell mass of the early blastocyst and then segregate to their final position lining the cavity by the late blastocyst. We have identified platelet-derived growth factor receptor alpha (Pdgfralpha) as an early-expressed protein that is also a marker of the later PrE lineage. By combining live imaging of embryos expressing a histone H2B-GFP fusion protein reporter under the control of Pdgfra regulatory elements with the analysis of lineage-specific markers, we investigated the events leading to PrE and EPI lineage segregation in the mouse, and correlated our findings using an embryo staging system based on total cell number. Before blastocyst formation, lineage-specific factors are expressed in an overlapping manner. Subsequently, a gradual progression towards a mutually exclusive expression of PrE- and EPI-specific markers occurs. Finally, cell sorting is achieved by a variety of cell behaviours and by selective apoptosis.

The origin of phenotypic heterogeneity in a clonal cell population in vitro

Background

The spontaneous emergence of phenotypic heterogeneity in clonal populations of mammalian cells in vitro is a rule rather than an exception. We consider two simple, mutually non-exclusive models that explain the generation of diverse cell types in a homogeneous population. In the first model, the phenotypic switch is the consequence of extrinsic factors. Initially identical cells may become different because they encounter different local environments that induce adaptive responses. According to the second model, the phenotypic switch is intrinsic to the cells that may occur even in homogeneous environments.

Principal Findings

We have investigated the “extrinsic” and the “intrinsic” mechanisms using computer simulations and experimentation. First, we simulated in silico the emergence of two cell types in a clonal cell population using a multiagent model. Both mechanisms produced stable phenotypic heterogeneity, but the distribution of the cell types was different. The “intrinsic” model predicted an even distribution of the rare phenotype cells, while in the “extrinsic” model these cells formed small clusters. The key predictions of the two models were confronted with the results obtained experimentally using a myogenic cell line.

Conclusions

The observations emphasize the importance of the “ecological” context and suggest that, consistently with the “extrinsic” model, local stochastic interactions between phenotypically identical cells play a key role in the initiation of phenotypic switch. Nevertheless, the “intrinsic” model also shows some other aspects of reality: The phenotypic switch is not triggered exclusively by the local environmental variations, but also depends to some extent on the phenotypic intrinsic robustness of the cells.

What keeps cells in tissues behaving normally in the face of myriad mutations?

The use of a reporter gene in transgenic mice indicates that there are many local mutations and large genomic rearrangements per somatic cell that accumulate with age at different rates per organ and without visible effects. Dissociation of the cells for monolayer culture brings out great heterogeneity of size and loss of function among cells that presumably reflect genetic and epigenetic differences among the cells, but are masked in organized tissue. The regulatory power of a mass of contiguous normal cells is expressed in its capacity to normalize the appearance and growth behavior of solitary homophilic neoplastic cells, and to redirect differentiation of solitary heterophilic stem-like cells. Intimate contact between the interacting cells is required to induce these changes. The normalization of the neoplastic phenotype does not require gap junctional communication between cells, though transdifferentiation might. These varied relationships are manifestations of the unifying biological principle of "order in the large over heterogeneity in the small".

Stochasticity in gene expression: from theories to phenotypes

Genetically identical cells exposed to the same environmental conditions can show significant variation in molecular content and marked differences in phenotypic characteristics. This variability is linked to stochasticity in gene expression, which is generally viewed as having detrimental effects on cellular function with potential implications for disease. However, stochasticity in gene expression can also be advantageous. It can provide the flexibility needed by cells to adapt to fluctuating environments or respond to sudden stresses, and a mechanism by which population heterogeneity can be established during cellular differentiation and development.

Stochastic gene expression, disruption of tissue averaging effects and cancer as a disease of development

Despite the extensive literature describing the somatic genetic alterations in cancer cells, the precise origins of cancer cells remain controversial. In this article, I suggest that the etiology of cancer and the generation of genetic instability in cancer cells should be considered in the light of recent findings on both the stochastic nature of gene expression and its regulation at tissue level. By postulating that gene expression is intrinsically probabilistic and that stabilization of gene expression arises by cellular interactions in "morphogenetic fields", development and cellular differentiation can be rethought in an evolutionary perspective. In particular, this article proposes that disruptions of cellular interactions are the initial source of abnormal gene expression in cancer cells. Consequently, cancer phenotypes such as genetic and epigenetic instabilities, and also the presence of cells with stem cell-like properties, may result from inaccurate and aberrant patterns of gene expression generated by microenvironmental alterations. Finally, the therapeutic implications of this view are discussed.