article: Choroidal neovascularization (CNV) of the macular area of the retina is the major cause of severe vision loss in adults. In CNV, after choriocapillaries initially penetrate Bruch' s membrane (BrM), invading vessels may regress or expand (CNV initiation). Next, during Early and Late CNV, the expanding vasculature usually spreads in one of three distinct patterns: in a layer between BrM and the retinal pigment epithelium (sub-RPE or Type 1 CNV), in a layer between the RPE and the photoreceptors (sub-retinal or Type 2 CNV) or in both loci simultaneously (combined pattern or Type 3 CNV). While most studies hypothesize that CNV primarily results from growth-factor effects or holes in BrM, our three-dimensional simulations of multi-cell model of the normal and pathological maculae recapitulate the three growth patterns, under the hypothesis that CNV results from combinations of impairment of: 1) RPE-RPE epithelial junctional adhesion, 2) Adhesion of the RPE basement membrane complex to BrM (RPE-BrM adhesion), and 3) Adhesion of the RPE to the photoreceptor outer segments (RPE-POS adhesion). Our key findings are that when an endothelial tip cell penetrates BrM: 1) RPE with normal epithelial junctions, basal attachment to BrM and apical attachment to POS resists CNV. 2) Small holes in BrM do not, by themselves, initiate CNV. 3) RPE with normal epithelial junctions and normal apical RPE-POS adhesion, but weak adhesion to BrM (e. g. due to lipid accumulation in BrM) results in Early sub-RPE CNV. 4) Normal adhesion of RBaM to BrM, but reduced apical RPE-POS or epithelial RPE-RPE adhesion (e. g. due to inflammation) results in Early sub-retinal CNV. 5) Simultaneous reduction in RPE-RPE epithelial binding and RPE-BrM adhesion results in either sub-RPE or sub-retinal CNV which often progresses to combined pattern CNV. These findings suggest that defects in adhesion dominate CNV initiation and progression.
  We first review the key components of the retina and the processes commonly hypothesized to underlie CNV. We then discuss our main hypotheses for CNV mechanisms and why we believe adhesion may play an important role in both initiation and progression of CNV. We then use a multi-cell computer simulation of a mechanistic computational model of the choriocapillaris, BrM and photoreceptors to investigate the effects of adhesion variations on CNV initiation and progression. Finally, we focus on how adhesion in the BrM-RPE-POS complex changes due to aging and inflammation both in human retina and in animal models of CNV and discuss the biomedical implications of our results. Sprouting angiogenesis, growth of new blood vessels from preexisting vessels, occurs in response to chemical and mechanical stimuli and to hypoxia in both adult and embryonic tissues. Sprouting angiogenesis requires activation of normally quiescent endothelial cells in pre-existing blood vessels, breakdown of existing basement membranes, migration of activated cells led by one or more endothelial tip cells or immune cells (which can also function as tip cells) in response to environmental and cell-contact cues and proliferation of a subset of activated endothelial cells (stalk cells) with possible recruitment of support cells (pericytes and smooth muscle cells) during blood-vessel maturation [1]. In pathological angiogenesis, e. g. in vascular tumors, vessels do not mature, resulting in leaky capillary vasculature which causes severe edema, inefficient blood transport and reduced oxygenation. Maturation failure can result in a pathological feedback loop, where worsening hypoxia leads to higher levels of proangiogenic factors, including vascular endothelial growth factor A (VEGF-A) and platelet-derived growth factor (PDGF), and the greater excess of proangiogenic factors produces even more inefficient capillaries, worsening the hypoxia. The hallmark of wet or exudative age-related macular degeneration (AMD), which is the leading cause of irreversible blindness in North America, Europe, and Australia [2], is lesioning choroidal neovascularization (CNV), the invasion of the retina by new blood vessels growing from the choriocapillaris (CC). In humans, CNV frequency increases with age, independent of other risk factors or specific insults, though numerous risk factors and insults can greatly increase its probability of occurrence in an individual. CNV in all patients shares the same basic neoangiogenic steps. We distinguish the following three temporal phases: Initiation, when endothelial cells first cross Bruch' s membrane (BrM); Early CNV, when endothelial cells spread and form capillaries in a defined locus, and Late CNV, when additional loci may become involved, often leading to retinal pigment epithelium (RPE) detachment and degeneration, CNV regression/involution and photoreceptor death. The diverse CNV scenarios are categorized based on histological [3] and clinical observations [4]. Neovascular vessels originating from the choroid can grow in the plane between the RPE and BrM (sub-RPE, occult or Type 1 CNV), between the retina and the RPE (sub-retinal, classic or Type 2 CNV) or in both locations (combined or Type 3 CNV). Type 3 CNV can also form as a late stage of Early Type 1 or Early Type 2 CNV. In wet AMD, severe visual loss results from subretinal hemorrhage from the leaky CNV, which leads to the eventual formation of a disciform scar. While CNV is generally a disease of the elderly, with onset occurring after 70 years, progression after onset may be rapid. According to the Macular Photocoagulation Study Group [5], about 40% of patients with untreated Type 1 CNV loose significant visual acuity within 12 months. 23% of these patients develop Type 3 CNV within 3 months and an additional 23% develop Type 3 CNV within 12 months. Current therapeutic strategies depend on the CNV locus (subfoveal, juxtafoveal or extrafoveal) and include photodynamic therapy, laser photocoagulation and most-commonly, anti-angiogenic drugs (Lucentis, Macugen or Avastin) [6]. Long-term prognoses are poor; only 20% of patients with Type 1 CNV have stabilized or improved vision 36 months after initial diagnosis and treatment [5]. Developing more effective targeted intervention strategies will depend on understanding CNV mechanisms. However, because of the structural complexity of the normal and diseased retina and the numerous homeostatic and developmental mechanisms operating concurrently, experiments have yet to identify clearly the mechanisms responsible for either CNV initiation or progression. As a novel approach to developing such understanding, this paper applies quantitative models and computer simulations to test hypotheses for the mechanisms leading to CNV initiation and controlling early and late Type 1,2 and 3 CNV. Multiple hypotheses compete to explain CNV initiation, growth and patterning (for comprehensive reviews, see [7], [8]). These hypotheses form two major groups depending on their primary mechanism of action: 1) VEGF overexpression, and 2) irregularities in BrM (including focal defects and basal deposits). Inflammation affects both mechanisms because it promotes formation of irregularities in BrM and participates in angiogenesis. To better understand CNV, we consider its risk factors and correlated pathological conditions and briefly discuss their relationship to the steps of angiogenesis. Excessive expression of VEGF, mainly in response to injuries and hypoxia, without balancing expression of angiogenesis inhibitors is a major stimulator of neoangiogenesis in most tissues. Excess VEGF has been considered a primary cause of CNV [9] because anti-VEGF drugs can significantly inhibit CNV progression. This hypothesis seems reasonable, because activation, proteolytic activity and survival of ECs depend on VEGF concentrations, and directional migration of tip cells depends on gradients of VEGF, which in turn depend on the composition of the ECM and the proteolytic activity of ECs [10] (in many cases VEGF-A is bound to the ECM and is only sensed by ECs when released by proteolytic enzymes). In animal models, excess secretion of VEGF by the RPE due to subretinal injections of reactive oxygen species (ROS) [11] or adenovirus [12] can induce CNV. However, other studies in transgenic mice show that increased expression of VEGF-A and/or angiopoietin-2 in RPE is not sufficient to initiate CNV and that overexpression of VEGF can only initiate CNV when combined with subretinal injections [13] which disturb the integrity of the RPE, probably by triggering inflammation, reducing RPE-POS contact adhesion and inducing RPE growth [14]–[16]. Also in transgenic mice [17], overexpression of VEGF-A164 in the RPE causes extensive intrachoroidal neovascularization, but does not lead to sub-RPE or sub-retinal CNV, again suggesting that an intact Bruch' s membrane/RPE barrier prevents choroidal neovascularization from penetrating into the subretinal space. Immunohistochemical analyses of human subjects with a history of chorioretinal disease show that compared to age-matched control subjects (mean age about 80 years) their PEDF levels are significantly lower than their VEGF levels in RPE cells, the RPE basal lamina, BrM and the choroidal stroma [9], [18]. This imbalance shows that disturbed angiogenic and antiangiogenic factor levels correlate with late-stage chorioretinal disease, but the relative expression levels of these factors would need to be measured experimentally before CNV initiation to establish whether the imbalance is a cause or a result of CNV. However, secreted proteome profiling in human RPE cell cultures derived from donors with AMD shows a 2- to 3-fold increase in their levels of PEDF compared to age-matched healthy donors [19]. Thus, while the experimental evidence shows a clear increase in proangiogenic factors, this increase may be compensated by an increase in antiangiogenic factors. Whether an imbalance develops is thus not definitively established. Another serious objection to the VEGF-hypothesis is that it fails to explain the distinct loci and progression of CNV. VEGF levels are high throughout the retina and cannot provide spatial cues to lead to the localization of CNV to either the RPE-BrM boundary (Type 1) or the RPE-POS boundary (Type 2). Indeed, no experiment has established the presence of VEGF gradients within the BrM-RPE-POS complex. Both age-related changes of the retina and pathological conditions can increase VEGF expression. Life-long accumulation of lipids in BrM and their gradual oxidation (producing reactive oxygen species and recruiting immune cells) correlate with increased production of VEGF by the RPE and greater likelihood of developing CNV [20]. Hypoxia also temporarily increases the secretion of VEGF in cultured RPE cells by up to 3-fold over 48 hours, followed by a return to baseline [21], [22]. Inflammatory cells also secrete VEGF and other proangiogenic and antiangionegic factors (see Inflammation subsection in supplementary Text S1). Irregularities of BrM include focal breaks and thinning in BrM, abnormal production of ECM by the RPE, and formation of soft drusen. All of these BrM defects correlate with CNV [23], [24]. However, the common hypotheses that BrM presents a physical barrier to the invasion and/or growth of choriocapillaries into the retina and that small gaps in BrM may be responsible for initiation of CNV, contradict several experimental and clinical observations: 1) BrM is never an impenetrable barrier to immune and tip cells and has not been shown to physically block the invasion of activated ECs into the sub-RPE space. BrM is only 2–4 µm thick, with pores up to 0. 5 µm diameter [25]. The BrM elastin layer in the macula of healthy young adults (age<62) can have gaps of up 2 µm [26]. 2) Activated endothelial cells, which are always present in the normal choriocapillaris, probe their micro-environment by sending out processes (like filopodia) as thin as 0. 1 µm and as long as 200 µm even in dense embryonic and adult tissues. Such flilopodial processes can easily cross BrM through its pores. Leukocytes can cross BrM rapidly under both normal and inflammatory conditions [27] (taking at most a few hours to cross the BrM-RPE barrier and only a few minutes to cross the endothelium in an in vitro flow model [28]). ECs digest and penetrate an intact BrM in less than a week when RPE is severely damaged due to phototoxicity in a rat model [29]. 3) The rate of CNV in persons younger than 50 years old is negligible (except in cases of excess inflammatory response in the eyes). 4) The CNV initiation probability when BrM is mechanically disrupted in animal models is about 10% [30]. These observations suggest that focal defects and thinning of BrM do not significantly reduce the already minimal efficacy of the physical barrier function of healthy BrM. Instead, other mechanisms may explain the correlation of focal defects in BrM with CNV, e. g. , breaks in BrM due to calcification may disrupt both the RBaMs and the basement membranes of CC cells, disrupting the epithelial junctional structure of the RPE [23] and activating CC endothelial cells. This simultaneous activation of ECs and disruption of the RPE may explain the correlation of focal defects in BrM with CNV. However, while BrM does not form a mechanical barrier to persistent EC penetration of the retina, BrM and the RPE attached to it clearly do form an effective barrier to choroidal penetration, even in the presence of small holes in BrM. The nature of this barrier is not clear. Haptotaxis may play a role. ECs exhibit strong haptotactic preference for their own basement membrane. The basement membrane of the RPE (RBaM) differs in structure and components from the CC basement membrane (CC BaM) (reviewed in [31]). ECs preferentially adhere to their own basal lamina and new blood vessels follow the pattern of any pre-existing EC-manufactured basal lamina after capillary atrophy [32]. Thus, in the absence of factors that induce directed migration of ECs (chemotaxis or haptotaxis), we hypothesize that activated ECs of the choriocapillaris prefer to stay on the outer side of BrM, which has a high level of CC BaM, and not to invade sub-RPE space, which almost entirely lacks CC BaM. Since overexpression of VEGF and reduction in BrM' s barrier function may not fully explain CNV initiation, multiple types, loci and progression [23], this paper investigates the possible role of additional mechanisms, particularly adhesion defects. While not usually considered crucial to CNV, a great deal of experimental evidence suggests that failures of adhesion are essential for the development of CNV (Table 1). The strict spatial separation of the CC from the normal retina and the distinct loci of Type 1 and Type 2 CNV suggest that the physical structure and properties of the BrM-RPE-POS complex may determine both CNV initiation and progression. Experimental evidence suggests that reduced RBaM-BrM adhesion may enable CNV to invade the sub-RPE space. The differences in properties and effects of hard and soft drusen support this hypothesis. Soft drusen are strong risk factors for CNV and are often associated with detachment of the RPE from BrM, suggesting that they substantially reduce RBaM-BrM adhesion [33]–[35]. However, hard drusen, which contain hyalinised material and attach firmly to the inner collagenous layer of BrM (based on EM images) do not greatly increase the likelihood of CNV [24], [35]. Softening of hard drusen, which reduces their adhesion to RBaM, correlates with CNV [36], [37]. Similarly, the ability of inflammation to induce CNV suggests that impaired lateral adhesion between cells in the RPE promotes Type 2 CNV. Pathological conditions that compromise the integrity of the oBRB by weakening junctional epithelial adhesion in the RPE cause a wide range of neovascular diseases in the retina [38]–[42]. Recent studies show that subretinal drusenoids, which are drusen-like deposits that accumulate between the RPE and photoreceptors, perturb RPE-POS adhesion and correlate with CNV [43]–[45]. Finally, the detachment of the POS from the RPE (retinal detachment) reduces the integrity of the oBRB and significantly increases the risk of CNV in animal models of CNV, suggesting that impaired RPE-POS adhesion also promotes CNV. Since the relative importance, roles and interactions among the different types of adhesion impairment during CNV initiation and progression are unclear, this body of experimental evidence motivated us to study the role of adhesion failures in the BrM-RPE-POS complex in CNV. CNV involves the interaction of two complex components, the retina, with its supporting structures, and the choriocapillaris. We briefly review the functional and structural properties of these components in the context of CNV in supplementary Text S1. To allow unbiased study of CNV mechanisms, our model of the retina-RPE-CC includes objects and processes (Table 2) capable of recapitulating all the major CNV hypotheses (VEGF overexpression, BrM defects, adhesion failures and inflammation). We list our key modeling assumptions in supplementary Text S2. We translate our quantitative model into a computational model in the Methods section in supplementary Text S3 (for a detailed explanation of our modeling terminology see supplementary Text S4). To avoid confusion, we use normal fonts for biological objects and boldface to represent objects and times in the quantitative model, e. g. RPE denotes the model' s representation of biological RPE and one year denotes one simulated biological year. We also use boldface to distinguish the specific simulation interactions of junctional adhesion, labile adhesion and plastic coupling in our model from their biological correlates, but we do not use a separate font to distinguish other modeled and biological processes.
  CNV initiation in our simulations requires: 1) a tip cell, and 2) adhesion failures. A tip cell is not sufficient to initiate CNV if all adhesions are normal. Even when a tip cell makes a hole in BrM, crosses BrM and differentiates into a stalk cell CNV does not initiate if all adhesions are normal (Table S1, adhesion scenario ID: 1). The strong adhesion of RPE cells to neighboring RPE cells, POSs and BrM means that the BrM-RPE-POS ensemble behaves as a mechanically stable complex. This complex effectively obstructs CNV by limiting the proliferation and invasion of stalk cells into the sub-RPE and sub-retinal spaces. We discuss, in greater detail below, how different modes of adhesion failure in the complex allow stalk cells to proliferate and invade. Chemotaxis greatly affects how stalk cells invade the sub-RPE and sub-retinal spaces. Stalk cells migrate via chemotaxis up gradients of both short-diffusing and RPE-derived VEGF-A. RPE-derived VEGF-A is especially important because its concentration is maximal in the RPE, encouraging stalk cells to migrate from the CC into the sub-RPE and sub-retinal spaces. Adhesion between components of the BrM-RPE-POS complex opposes such invasion, inhibiting CNV initiation. Our simulations show that finite-strength adhesive interactions among the components of the BrM-RPE-POS complex can prevent invasion by stalk cells if the adhesion forces are greater than the forces which stalk cells exert on the RPE-RPE and RPE-BrM boundaries due to chemotaxis. Because of the complicated interactions among components during angiogenesis, the existence of such adhesion thresholds is not obvious a priori. Our simulations therefore allow us to refine our understanding of these thresholds to show that EC-EC adhesion is also important in vivo. Self-organization of ECs into a capillary network pattern requires: 1) Strong chemotaxis forces that balance EC-EC adhesion (ECs form clusters rather than networks when chemotaxis to both short-diffusing and RPE-derived VEGF-A is weak), 2) the EC-EC adhesion strength must be comparable to the adhesion strengths in the BrM-RPE-POS complex. Thus the strength of adhesion among RPE-RPE, RPE-BrM and RPE-POS required to resist chemotaxing ECs also depends on EC-EC adhesivity. We performed multiple-regression analysis (see the Methods section in supplementary Text S3 for details) against five adhesion parameters (RRl, RRp, RBl, RBp, ROl) to relate specific adhesion failures to the probability of CNV initiation. The five adhesion parameters and their (multi) linear combinations account for 88% of the observed variance in the CNV initiation probability (adjusted R2 = 0. 83). To visualize the five-dimensional (5D) regression relations, we reduce 5D to 3D by assuming that RRp = RRl and RBp = RBl. We call this reduction symmetric since it assumes that impairing RPE-RPE labile adhesion also impairs RPE-RPE plastic coupling. E. g. , we would expect changes in cytoskeletal architecture due to inflammation to affect both adhesion mechanisms together. We consider asymmetric reductions in adhesion later in this section. Figure 3 shows a 3D volumetric visualization of the CNV initiation probability (Pinit) in the symmetrically reduced parameter space (RRp = RRl and RBp = RBl). The three isosurfaces of CNV initiation probability correspond to Pinit = 0. 25,0. 5 and 0. 75 in order from front to back. Regression predicts a minimum CNV initiation probability of 0. 08 for normal adhesion, while CNV did not initiate in any of our simulation replicas for normal adhesion. Thus the simulated CNV initiation probability for normal adhesion is effectively 0, as observed clinically, while the regression-inferred 0. 08 initiation probability is an artifact of the linear inference, an example of the greater predictive power of mechanistic simulations compared to pure statistical inference. Figure 3 shows that when RPE-POS labile adhesion is normal, even moderate impairment of either RPE-RPE (RRp = RRl) or RPE-BrM (RBp = RBl) junctional adhesion increases the CNV initiation probability to ∼50%. When both RPE-RPE and RPE-BrM junctional adhesion are normal (RRp = RRl = RBp = RBl = 3) and RPE-POS labile adhesion is severely impaired (ROl = 1) CNV initiation probability is also ∼50%. Thus, for severe impairments of any one of the three adhesion failure mechanisms can each independently induce CNV, as predicted both by our regression model and our mechanistic interpretation. Adhesion failures in the BrM-RPE-POS complex show strong combinatorial effects. When either RPE-RPE or RPE-BrM junctional adhesion is moderately impaired and RPE-POS labile adhesion is severely impaired, CNV initiation probability increases to 100%. Table S1 shows that asymmetrical impairment of either RPE-RPE or RPE-BrM plastic coupling alone, without impairment of the corresponding labile adhesion barely increases the probability of CNV initiation. Thus, the plastic coupling strengths have only a minor effect on the ability of the BrM-RPE-POS complex to oppose CNV. We believe that our simulated initiation probabilities are higher than those observed in experiments due to two simplifying assumptions of our model: 1) We assumed that all stalk cells can divide indefinitely. Limiting the number of stalk-cell divisions (due to senescence), would lower the probability of CNV initiation. In in vitro experiments, less than 2% of endothelial cells have high proliferation potential [72], [73], so angiogenic sprouts often fail to grow, or even regress, if the ECs forming the sprouts have low proliferation potential. 2) We assumed that stalk cells adhere equally to both sides of BrM, while BrM and CC basement membrane are histologically distinct. In experiments, ECs haptotax to the basement membrane of the CC on the outer side of BrM (Figure 1), reducing their probability of crossing BrM compared to our simulations. We expect that increasing adhesion between stalk cells and the CC-side of BrM would reduce the CNV initiation probability, since stalk cells would then prefer to remain on the CC-side of BrM, where contact with the preexisting vasculature would inhibit their growth. To classify CNV progression during a simulated year, we determine the early and late loci of stalk cells, using the mean (weighted by the number of stalk cells) MWs during the first and last three months of each simulation whether or not CNV initiates (we can calculate the MW even if CNV fails to spread and thus in the absence of initiation). The mean MW measures the ability of the BrM-RPE-POS complex to confine stalk cells to specific regions. A MW≥0. 75 during a given time interval indicates that most stalk cells lie between BrM and the RPE (in the sub-RPE space) and that they do not contact the POS. We therefore assign the time interval to Type 1 CNV. A MW≤0. 25 during a given time interval indicates that most stalk cells lie between the RPE and the POS (in sub-retinal space) and do not contact BrM. We therefore assign the time interval to Type 2 CNV. 0. 25<MW<0. 75 usually indicates that stalk cells occur in both the sub-RPE and sub-retinal spaces (since few sub-RPE stalk cells touch the POS and few sub-retinal stalk cells touch BrM). We therefore assign the time interval to Type 3 CNV. In a few exceptional cases (Table S10) with 0. 25<MW<0. 75, most stalk cells lie between neighboring RPE cells rather than in either the sub-RPE or sub-retinal spaces (discussed in the Stable Type 3 CNV section in supplementary Text S5). The type of CNV during the early window which we call the early CNV type (the first three months of a simulation) is especially revealing, because all simulations start from the same initial condition. The early CNV type shows the efficacy of the BrM-RPE-POS complex in blocking stalk cell invasion of the sub-RPE and sub-retinal spaces. Since tissue structure and cell function can change significantly in the BrM-RPE-POS complex during a simulated year, changes in CNV type between the early and late windows can result from either structural or barrier-function changes in the BrM-RPE-POS complex. For example, the adhesion failures which typically lead to Early Type 3 CNV differ from those which typically leading to Late Type 3 CNV. Because our simulations are stochastic, different replicas of the same adhesion scenario can lead to different combinations of early and late types of CNV. Such variation is common clinically and indicates that a simple population average of MWs over simulation replicas may reveal neither the types, progression dynamics nor degree of heterogeneity of outcomes. To retain this dynamic and population information, we classify CNV dynamics (progression) in each simulation separately based on its early and late CNV type, for a total of 9 CNV dynamics scenarios (Table 5). We use the term progression when a simulation replica initially develops either Early Type 1 CNV or Early Type 2 CNV and then develops Late Type 3 CNV and translocation when a replica initially develops either Early Type 1 CNV or Early Type 3 CNV, then Late Type 2 CNV or initially develops either Early Type 2 CNV or Early Type 3 CNV, then Late Type 1 CNV. Three translocation scenarios sub-retinal to sub-RPE CNV (T21 CNV), Type 3 to sub-RPE CNV (T31 CNV) and Type 3 to sub-retinal CNV (T32 CNV) did not occur in our simulations. Early Type 1 (ET1) CNV and its progression. Stalk cells remain confined to the sub-RPE space in two main classes of adhesion scenarios: 1) When RPE-BrM labile adhesion is moderately to severely impaired, RPE-BrM plastic coupling satisfies RBl+RBp≤4, and both RPE-RPE and RPE-POS labile adhesion are normal (RRl = 3 and ROl = 3). 2) When both RPE-RPE and RPE-BrM labile adhesion are severely impaired (RRl = 1 and RBl = 1), RPE-BrM plastic coupling is moderately to severely impaired (RBp≤2), and both RPE-RPE plastic coupling and RPE-POS labile adhesion are normal (RRp = 3, ROl = 3) (Table S2, adhesion scenario ID: 83 and 84). In both classes of adhesion scenarios, CNV initiation leads to Early Type 1 CNV (ET1). Table 6 shows the MW and CNV initiation probabilities for the adhesion scenarios most prone to ET1 CNV (MW>0. 9). Multiple-regression analysis of the five adhesivities accounted for 93% of the observed variance in the average MW for all 108 adhesion scenarios (adjusted R2 = 0. 89). Figure 4 shows the stalk cell locus regression-inferred from the average MW as a function of the adhesion parameters obtained by setting RRp = RRl and RBp = RBl. Since Figure 4 shows the stalk cell locus even when CNV fails to initiate, a region prone to ET1 CNV, develops ET1 CNV only if CNV initiates. Severe impairment of RPE-POS labile adhesion greatly reduces the MW, so ET1 CNV can only occur when RPE-POS labile adhesion is near normal. Scenarios with severe impairment of RPE-BrM junctional adhesion (RBp = RBl = 1), and normal RPE-POS labile adhesion are prone to ET1 CNV over a wide range of RPE-RPE junctional adhesion impairment (MW>0. 95 for RRp = RRl>1. 5). The red region with MW>0. 9 has Pinit>0. 8 (Figure 4). In most adhesion scenarios that develop Early Type 1 CNV with MW>90% the CNV remains in the sub-RPE space during one simulated year (Late Type 1 CNV, MW>75%). I. e. they exhibit Stable T1 CNV (S11 CNV) (see Figure 6, Table 7 and supplementary Text S5 for details). Generally, CNV growth speed differs from replica to replica in adhesion scenarios prone to S11 CNV (compare to S22 CNV dynamics, below). Figure 7 shows typical S11 CNV dynamics for 10 simulation replicas of a single adhesion scenario (RRl = 3, RRp = 3, RBl = 2, RBp = 2, ROl = 3) (Table S5, adhesion scenario ID: 38). We visualize snapshots of S11 CNV dynamics in one replica in Figure 8 and Video S1. Adhesion scenarios in which some replicas exhibit T12 CNV can also have replicas which exhibit either S22 or S11 over one simulated year. Figure 9 shows T12 CNV dynamics for 10 simulation replicas of the adhesion scenario (RRl = 3, RRp = 3, RBl = 1, RBp = 1, ROl = 1) (Table S6, adhesion scenario ID: 93). We visualize snapshots of the T12 CNV dynamics in one replica in Figure 10 and Video S2. CNV dynamics is very similar across all replicas in adhesion scenarios prone to P13 CNV and much less heterogeneous than for T12 CNV. Figure 11 shows typical P13 CNV dynamics for 10 simulation replicas of the adhesion scenario (RRl = 1, RRp = 3, RBl = 1, RBp = 2, ROl = 3) (Table S7, adhesion scenario ID: 83). We visualize snapshots of P13 CNV dynamics in one replica in Figure 12 and Video S3.
  Our current model does not include several mechanisms which may also be important to CNV. In future refinements, we will include multiple types of basal deposits and fibrosis (synthesis of new ECM) explicitly to clarify their role in the initiation and progression of CNV. We particularly are interested in how differences in the size and structure of soft and hard drusen affect the initiation and progression of CNV and the frequency of occurrence of RPE detachment and RPE tear formation after therapeutic intervention to treat CNV. Many hypothesized mechanisms for CNV initiation and progression involve irregularities in transport. We plan more realistic models including capillary maturation, blood flow and retinal-CC fluid flow to study how oxygen, nutrient and waste transport promote or inhibit CNV. Since cell adhesion is essential to multicellularity and is important in embryonic development, homeostatic maintenance of adult tissues and diseases like cancer, its importance in CNV is, perhaps, not surprising, given CNV' s many parallels with tumor-induced angiogenesis. However, the role of adhesion in CNV has not been widely appreciated, so neither the relationship between known CNV risk factors and specific adhesion failures, nor the actual adhesivities in the retina and RPE have been quantified experimentally. Quantitative measurements of these adhesion properties and their regulation in the normal and pathological retina would allow more clinically relevant models. Such experiments would greatly reduce uncertainty in our model definition, improve our understanding of CNV initiation and progression. Since measuring adhesivities directly may be difficult, especially in humans, our model also allows us to quantify adhesion failures by looking at how they affect CNV initiation and progression and matching those computational outcomes with experimental observations, then correlating the simulated adhesion changes with experimental risk factors. Beyond retinal CNV, our results on CNV initiation and epithelial breakdown apply to any tissue in which a basement membrane separates a capillary network from a nearby epithelium, e. g. lung and gut. We expect that the relationships between specific classes of adhesion failures and the loci and dynamics of CNV which we observe in our simulations should carry over to the neovascularization-dependent pathologies of those tissues. Ultimately, a database of verified simulations for different adhesion scenarios might allow systematic CNV prediction based on clinically-measurable properties of the eye, especially if the adhesion properties can be inferred noninvasively, e. g. by measuring optically, changes in CC or RPE morphology or autofluorescence due to lipid accumulation. In the absence of direct measurements of adhesivity, our simulations allow us to infer adhesion defects from pathologies. For example, if a patient with a functional retina exhibits micro-detachments of the RPE (due to lipid accumulation or small soft drusen), the relationship between the number and degree of detachments and the underlying classes of adhesion failures predicts the probability of CNV initiation and the distribution of CNV onset times, making clinically-useful suggestions for frequency of follow-up examinations and possible prophylactic interventions. To aid diagnosis and treatment we can also develop statistical analyses of the most significant scenarios capable of producing the observed pattern of disruption in each patient (including the probability of initiation, the time of onset of progression and progression speed, …). Follow-up observations could then narrow the range of admitted hypothetical scenarios to improve the accuracy of the prognosis. More accurate diagnoses may improve both administration of drugs and disease management. One crucial aspect of a model-based approach to CNV diagnosis, prognosis and treatment is that both the simulation database and the statistical predictors could be continuously refined using feedback from both clinical and histopathological sources, so they would improve with use, providing a platform to integrate clinical and histopathological data for even more accurate diagnosis and prognosis.
  All our simulations use the open-source CompuCell3D simulation environment (http: //www. compucell3d. org/) [95]. We ran our simulations on a computer cluster (Quarry, Indiana University) using CompuCell3D v3. 4. 2. A typical simulation replica takes about 30 hours on a single core of a 2. 0 GHz quad-core Intel Xeon 5335 processor. We stored the cell and field-lattice configurations every 6 simulated hours and rendered each snapshot using the integrated post-processing rendering provided by CompuCell3D.
summary: This paper tests hypotheses for the mechanisms of choroidal neovascularization (CNV), the pathological growth of capillaries in response to physical defects in a structured tissue, the retina, showing that previously neglected cell-cell, cell-ECM and ECM-ECM adhesion failures suffice to determine the loci and progression of neovascularization. Surprisingly, a simple theory based on classes of adhesion failures, which involve variation of only five parameters, can coherently explain the heterogeneous range of CNV growth patterns and dynamics. Our results are generally applicable to other types of tissues where capillaries are close to an epithelium, e. g. , lung and gut.
keywords: tissue mechanics
  medicine
  cancer treatment
  immunology
  anatomy and physiology
  computerized simulations
  basic cancer research
  biomechanics
  oncology
  retinal disorders
  physiological processes
  biophysics simulations
  musculoskeletal system
  inflammation
  antiangiogenesis therapy
  biology
  biophysics
  aging
  eye infections
  physics
  computer science
  computer modeling
  clinical immunology
  biophysic al simulations
  immunity
  physiology
  ophthalmology
  computational biology
title: Adhesion Failures Determine the Pattern of Choroidal Neovascularization in the Eye: A Computer Simulation Study