Exploring and challenging the network of angiogenesis

Angiogenesis is one of the hallmarks of cancer and, as such, one of the alternative general targets for anticancer therapy. Since angiogenesis is a complex process involving a high number of interconnected components, a network approach would be a convenient systemic way to analyse responses to directed drug attacks. Herein we show that, although the angiogenic network is easily broken by short combinations of directed attacks, it still remains essentially functional by keeping the global patterns and local efficiency essentially unaltered after these attacks. This is a clear sign of its high robustness and resilience and stresses the need of directed, combined attacks for an effective blockade of the process. The results of this theoretical study could be relevant for the design of new antiangiogenic therapies and the selection of their targets

Low-Dosage Inhibition of DII4 Signaling Promotes Wound Healing by Inducing Functional Neo-Angiogenesis

Recent findings regarding Dll4 function in physiological and pathological conditions indicate that this Notch ligand may constitute an important therapeutic target. Dll4 appears to be a major anti-angiogenic agent, occupying a central role in various angiogenic pathways. The first trials of anti-Dll4 therapy in mice demonstrated a paradoxical effect, as it reduced tumor perfusion and growth despite leading to an increase in vascular density. This is seen as the result of insufficient maturation of the newly formed vasculature causing a circulatory defect and increased tumor hypoxia. As Dll4 function is known to be closely dependent on expression levels, we envisioned that the therapeutic anti-Dll4 dosage could be modulated to result in the increase of adequately functional blood vessels. This would be useful in conditions where vascular function is a limiting factor for recovery, like wound healing and tissue hypoxia, especially in diabetic patients. Our experimental results in mice confirmed this possibility, revealing that low dosage inhibition of Dll4/Notch signaling causes improved vascular function and accelerated wound healing

Mapping tenascin-C interaction with toll-like receptor 4 reveals a new subset of endogenous inflammatory triggers

Pattern recognition underpins innate immunity; the accurate identification of danger, including infection, injury, or tumor, is key to an appropriately targeted immune response. Pathogen detection is increasingly well defined mechanistically, but the discrimination of endogenous inflammatory triggers remains unclear. Tenascin-C, a matrix protein induced upon tissue damage and expressed by tumors, activates toll-like receptor 4 (TLR4)-mediated sterile inflammation. Here we map three sites within tenascin-C that directly and cooperatively interact with TLR4. We also identify a conserved inflammatory epitope in related proteins from diverse families, and demonstrate that its presence targets molecules for TLR detection, while its absence enables escape of innate immune surveillance. These data reveal a unique molecular code that defines endogenous proteins as inflammatory stimuli by marking them for recognition by TLRs

Characterization of the Experimentally Observed Clustering of VEGF Receptors

16th International Conference on Computational Methods in Systems Biology (CMSB) -- SEP 12-14, 2018 -- Masaryk Univ, Fac Informat, Brno, CZECH REPUBLICWester, Michael/0000-0002-3520-7605WOS: 000453218400005Cell membrane-bound receptors control signal initiation in many important cellular signaling pathways. In many such systems, receptor dimerization or cross-linking is a necessary step for activation, making signaling pathways sensitive to the distribution of receptors in the membrane. Microscopic imaging and modern labeling techniques reveal that certain receptor types tend to co-localize in clusters, ranging from a few to tens, and sometimes hundreds of members. The origin of these clusters is not well understood but they are likely not the result of chemical binding. Our goal is to build a simple, descriptive framework which provides quantitative measures that can be compared across samples and systems, as groundwork for more ambitious modeling aimed at uncovering specific biochemical mechanisms. Here we discuss a method of defining clusters based on mutual distance, applying it to a set of transmission microscopy images of VEGF receptors. Preliminary analysis using standard measures such as the Hopkins' statistic reveals a compelling difference between the observed distributions and random placement. A key element to cluster identification is identifying an optimal length parameter L*. Distance based clustering hinges on the separation between two length scales: the typical distance between neighboring points within a cluster vs. the typical distance between clusters. This provides a guiding principle to identify L* from experimentally derived cluster scaling functions. In addition, we assign a geometric shape to each cluster, using a previously developed procedure that relates closely to distance based clustering. We applied the cluster [support] identification procedure to the entire data set. The observed particle distribution results are consistent with the random placement of receptors within the clusters and, to a lesser extent, the random placement of the clusters on the cell membrane. Deviations from uniformity are typically due to large scale gradients in receptor density and/or the emergence of "megaclusters" that are very likely the expression of a different biological function than the one behind the emergence of the quasi-ubiquitous small scale clusters