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Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights

There is an ongoing debate on the therapeutic potential of vaso-modulatory interventions against glioma invasion. Prominent vasculature-targeting therapies involve functional tumour-associated blood vessel deterioration and normalisation. The former aims at tumour infarction and nutrient deprivation medi- ated by vascular targeting agents that induce occlusion/collapse of tumour blood vessels. In contrast, the therapeutic intention of normalising the abnormal structure and function of tumour vascular net- works, e.g. via alleviating stress-induced vaso-occlusion, is to improve chemo-, immuno- and radiation therapy efficacy. Although both strategies have shown therapeutic potential, it remains unclear why they often fail to control glioma invasion into the surrounding healthy brain tissue. To shed light on this issue, we propose a mathematical model of glioma invasion focusing on the interplay between the mi- gration/proliferation dichotomy (Go-or-Grow) of glioma cells and modulations of the functional tumour vasculature. Vaso-modulatory interventions are modelled by varying the degree of vaso-occlusion. We discovered the existence of a critical cell proliferation/diffusion ratio that separates glioma invasion re- sponses to vaso-modulatory interventions into two distinct regimes. While for tumours, belonging to one regime, vascular modulations reduce the tumour front speed and increase the infiltration width, for those in the other regime the invasion speed increases and infiltration width decreases. We show how these in silico findings can be used to guide individualised approaches of vaso-modulatory treatment strategies and thereby improve success rates.

q-bio.TO↗

Reaction-diffusion waves of blood coagulation

One of the main characteristics of blood coagulation is the speed of clot growth. This parameter strongly depends on the speed of propagation of the thrombin concentration in blood plasma. In the current work we consider mathematical model of the coagulation cascade and study the existence, stability and speed of propagation of the reaction-diffusion waves of blood coagulation. We also develop a simplified one equation model that describes the main features of the thrombin wave propagation. For this equation we estimate the wave speed analytically. The resulting formulas give a good approximation for the speed of wave propagation in a more complex model as well as for the experimental data.

math.DS↗

Critical fluctuations of the electrical activity of the heart: Shortcomings of models of excitability and interpretation

We report unexpected evidence of critical fluctuations of the electric potential of the heart during atrial fibrillation in humans. Scale invariance and long range correlations are found, which we show cannot be accounted for solely with the property of excitability, since disorder emerges by the formation of chaotic patterns in excitable media. To shed light on the data, we discuss the hypothesis that, in fact, fibrillation appears through a phase transition, which we compare on phenomenological grounds to a quenched-in disorder magnetic transition. We infer that, during propagation of pulses, random pinning might occur due to random modulation of the gap junction channels.

q-bio.TO↗

Active microrheology of Chaetopterus mucus determines three intrinsic lengthscales that govern material properties

We characterize the scale-dependent rheological properties of mucus from the Chaetopterus marine worm and determine the intrinsic lengthscales controlling distinct rheological and structural regimes. Mucus produced by this ubiquitous filter feeder serves a host of roles including filtration, protection and trapping nutrients. The ease of clean mucus extraction coupled with similarities to human mucus rheology also make Chaetopterus mucus a potential model system for elucidating human mucus mechanics. We use optically trapped microsphere probes of 2-10 microns, to induce oscillatory strains and measure mucus stress response. We show that viscoelastic properties are highly dependent on the strain scale (l) with three distinct regimes emerging: microscale: l_1<4 microns, mesoscale: l_2~4-10 microns, and macroscale: l_3>10 microns. While mucus response is similar to water for l_1 indicating that probes rarely contact the mucus mesh, for l_2 the response is distinctly more viscous and independent of probe size, demonstrating that the mucus behaves as a continuum. However, this principally viscous mesoscale response is distinct from the largely elastic macroscopic mucus response. Only for l_3 does the response mimic macroscopic elasticity, with rigid constraints strongly resisting microsphere displacement. Our results demonstrate that a uniform mesh model for mucus with a single lengthscale modulating the crossover from water-like to elastic is too simplistic. Rather, the mucus responds as a hierarchical network with a loose microscopic mesh controlling mechanics for l_2, coupled with a mesoscale rigid scaffold responsible for the macroscopic gel-like mechanics beyond l_3. Our results shed important new light onto the design of drug delivery platforms, preventing pathogen penetration, and improving filtration, coating and clearance capabilities of mucus.

cond-mat.soft↗

An ecological resilience perspective on cancer: insights from a toy model

In this paper we propose an ecological resilience point of view on cancer. This view is based on the analysis of a simple ODE model for the interactions between cancer and normal cells. The model presents two regimes for tumor growth. In the first, cancer arises due to three reasons: a partial corruption of the functions that avoid the growth of mutated cells, an aggressive phenotype of tumor cells and exposure to external carcinogenic factors. In this case, treatments may be effective if they drive the system to the basin of attraction of the cancer cure state. In the second regime, cancer arises because the repair system is intrinsically corrupted. In this case, the complete cure is not possible since the cancer cure state is no more stable, but tumor recurrence may be delayed if treatment is prolongued. We review three indicators of the resilience of a stable equilibrium, related with size and shape of its basin of attraction: latitude, precariousness and resistance. A novel method to calculate these indicators is proposed. This method is simpler and more efficient than those currently used, and may be easily applied to other population dynamics models. We apply this method to the model and investigate how these indicators behave with parameters changes. Finally, we present some simulations to illustrate how the resilience analysis can be applied to validated models in order to obtain indicators for personalized cancer treatments. Keywords: Tumor growth; Chemotherapy; Basins of Attraction; Regime shifts; Critical transitions

q-bio.PE↗

Role of phytochemicals in the chemoprevention of tumors

Phytochemicals are plant-derived secondary metabolites, which may exert many biological activities in humans, including anticancer properties. Although recent findings appear to support their role in cancer prevention and treatment, this issue is still controversial. Anti-cancer activity of phytochemicals mainly depends on their multi-target mechanism of action, including antimutagenic, antioxidant and antiproliferative activities. Furthermore, they may modulate the host immune response to cancer, reducing inflammatory microenvironment and enhancing lymphocyte onco-surveillance. Since carcinogenesis is multi-factorial and involves several signaling pathways, multi-targeted agents as phytochemicals may represent promising anticancer compounds. This narrative review aims to analyze the current literature on phytochemicals highlighting their specific targets on carcinogenic molecular pathways and their chemopreventive role. A full comprehension of their activity at molecular and cellular levels will contribute for a better understanding of phytochemical clinical efficacy, thus promoting the identification of new effective plant-derived therapeutics.

q-bio.BM↗

Treatment of gastric cancer cells with non-thermal atmospheric plasma generated in water

Non-thermal atmospheric plasma (NTAP) can be applied to living tissues and cells as a novel technology for cancer therapy. Even though studies report on the successful use of NTAP to directly irradiate cancer cells, this technology can cause cell death only in the upper 3-5 cell layers. We report on a NTAP argon solution generated in DI water for treating human gastric cancer cells (NCl-N87). Our findings showed that the plasma generated in DI water during a 30-minute treatment had the strongest affect in inducing apoptosis in cultured human gastric cancer cells. This result can be attributed to presence of reactive oxygen species (ROS) and reactive nitrogen species (RNS) produced in water during treatment. Furthermore, the data showed that elevated levels of RNS may play an even more significant role than ROS in the rate of apoptosis in gastric cancer cells.

q-bio.TO↗

Estimating the EMG response exclusively to fatigue during sustained static maximum voluntary contraction

The increase of surface electromyography (sEMG) root-mean-square (RMS) is very frequently used to determine fatigue. However, as RMS is also influenced by muscle force,its effective usage as indicator of fatigue is mainly limited to isometric, constant force tasks.This research develops a simple me-thodto preclude the effect of muscle force, hereby estimates the EMG amplitude response exclusively to fatigue with RMS. Experiment was carried out on the biceps brachiis of 15 subjects (7males, 8 females) during sustained static maximum voluntary contractions (sMVC).Result shows that the sEMG RMS response to fatigue increasesto 21.27% while muscle force decreasing to 50%MVC, which implies that more and more extra effort is needed as muscle fatigue intensifies. It would be promising to use the RMS response exclusively to fatigue as an indicator of muscle fatigue.

q-bio.TO↗

Relationship between Periodontal disease and Asthma among overweight/obese adults

Aim: To assess the relationship between oral health and asthma. Methods: Data from 1,315 overweight or obese individuals, aged 40-65 years was used. Asthma was self-reported, while periodontitis, bleeding on probing (BOP), and plaque index were determined by clinical examinations. Results: Using logistic regression adjusting for gender, smoking status, age, body mass index, family history of asthma, and income level, revealed that the odds ratio (OR) of asthma for a participant with severe periodontitis was 0.44 (95% confidence interval: 0.27, 0.70) that of a participant with none/mild periodontitis . On the other hand, proportion of BOP sites, and plaque index were not statistically significant. For a participant with severe periodontitis, the OR of taking asthma medication was 0.20 (95% confidence interval: 0.09, 0.43) that of a participant with none/mild periodontitis. Moreover, proportion of BOP sites was statistically associated to use of asthma medication while plaque index still remained non-significant. Conclusion: Participants with severe periodontitis were less likely to have asthma. Stronger evidence of an inverse association was found when using asthma medication as outcome. Keywords: asthma; periodontal disease; asthma medication; periodontitis; hygiene hypothesis

q-bio.TO↗

Multi-Organ Cancer Classification and Survival Analysis

Accurate and robust cell nuclei classification is the cornerstone for a wider range of tasks in digital and Computational Pathology. However, most machine learning systems require extensive labeling from expert pathologists for each individual problem at hand, with no or limited abilities for knowledge transfer between datasets and organ sites. In this paper we implement and evaluate a variety of deep neural network models and model ensembles for nuclei classification in renal cell cancer (RCC) and prostate cancer (PCa). We propose a convolutional neural network system based on residual learning which significantly improves over the state-of-the-art in cell nuclei classification. Finally, we show that the combination of tissue types during training increases not only classification accuracy but also overall survival analysis.

q-bio.QM↗

Constraint-based modeling and simulation of cell populations

The intratumor heterogeneity has been recognized to characterize cancer cells impairing the efficacy of cancer treatments. We here propose an extension of constraint-based modeling approach in order to simulate metabolism of cell populations with the aim to provide a more complete characterization of these systems, especially focusing on the relationships among their components. We tested our methodology by using a toy-model and taking into account the main metabolic pathways involved in cancer metabolic rewiring. This toy-model is used as individual to construct a population model characterized by multiple interacting individuals, all having the same topology and stoichiometry, and sharing the same nutrients supply. We observed that, in our population, cancer cells cooperate with each other to reach a common objective, but without necessarily having the same metabolic traits. We also noticed that the heterogeneity emerging from the population model is due to the mismatch between the objective of the individual members and the objective of the entire population.

q-bio.QM↗

Structured Models of Cell Migration Incorporating Molecular Binding Processes

The dynamic interplay between collective cell movement and the various molecules involved in the accompanying cell signalling mechanisms plays a crucial role in many biological processes including normal tissue development and pathological scenarios such as wound healing and cancer. Information about the various structures embedded within these processes allows a detailed exploration of the binding of molecular species to cell-surface receptors within the evolving cell population. In this paper we establish a general spatio-temporal-structural framework that enables the description of molecular binding to cell membranes coupled with the cell population dynamics. We first provide a general theoretical description for this approach and then illustrate it with two examples arising from cancer invasion.

q-bio.CB↗

Perspective: Melanoma diagnosis and monitoring: Sunrise for melanoma therapy but early detection remains in the shade

Melanoma is one of the most dangerous forms of cancer. The five-year survival rate is 98% if it is detected early. However, this rate plummets to 63% for regional disease and 17% when tumors have metastasized, that is, spread to distant sites. Furthermore, the incidence of melanoma has been rising by about 3% per year, whereas the incidence of cancers that are more common is decreasing. A handful of targeted therapies have recently become available that have finally shown real promise for treatment, but for reasons that remain unclear only a fraction of patients respond long term. These drugs often increase survival by only a few months in metastatic patient groups before relapse occurs. More effective treatment may be possible if a diagnosis can be made when the tumor burden is still low. Here, an overview of the current state-of-the-art is provided along with an argument for newer technologies towards early point-of-care diagnosis of melanoma.

q-bio.TO↗

A mathematical model for growth of solid tumors and combination therapy with an application to colorectal cancer

We present a mathematical model, based on ordinary differential equations, for the evolution of solid tumors and their response to treatment. Specifically the effects of a cytotoxic agent and a monoclonal antibody are included as control term in the equations. The variables considered here are: the number of cancerous cells sensitive to chemotherapy, the number of cancerous cells resistant to chemotherapy, the degree of angiogenesis and the average intensity of VEGF. The rules that govern the quantities mentioned above are based on a geometrical argument: we approximate the tumor mass as a sphere and thus derive basic formulae for the normoxic cells and for VEGF production. The monoclonal antibody acts on VEGF and thus has in uence to the global degree of angiogenesis. Numerical estimates on some of the parameters are performed in order to match the main landmark in tumor progression and reaction to treatment in the specific case of colorectal cancer.

q-bio.TO↗

Optimal control of treatment time in a diffuse interface model of tumor growth

We consider an optimal control problem for a diffuse interface model of tumor growth. The state equations couples a Cahn-Hilliard equation and a reaction-diffusion equation, which models the growth of a tumor in the presence of a nutrient and surrounded by host tissue. The introduction of cytotoxic drugs into the system serves to eliminate the tumor cells and in this setting the concentration of the cytotoxic drugs will act as the control variable. Furthermore, we allow the objective functional to depend on a free time variable, which represents the unknown treatment time to be optimized. As a result, we obtain first order necessary optimality conditions for both the cytotoxic concentration and the treatment time.

math.OC↗

Stem Cells: The Good, the Bad and the Ugly

Cancer stem cells are controlled by developmental networks that are often topologically indistinguishable from normal, healthy stem cells. The question is why cancer stem cells can be both phenotypically distinct and have morphological effects so different from normal stem cells. The difference between cancer stem cells and normal stem cells lies not in differences their network architecture, but rather in the spatial-temporal locality of their activation in the genome and the resulting expression in the body. The metastatic potential cancer stem cells is not based primarily on their network divergence from normal stem cells, but on non-network based genetic changes that enable the evolution of gene-based phenotypic properties of the cell that permit its escape and travel to other parts of the body. Stem cell network theory allows the precise prediction of stem cell behavioral dynamics and a mathematical description of stem cell proliferation for both normal and cancer stem cells. It indicates that the best therapeutic approach is to tackle the highest order stem cells first, otherwise spontaneous remission of so called cured cancers will always be a danger. Stem cell networks point to a pathway to new methods to diagnose and cure not only stem cell cancers but cancers generally.

q-bio.TO↗

Cancer treatment scheduling and dynamic heterogeneity in social dilemmas of tumour acidity and vasculature

Background: Tumours are diverse ecosystems with persistent heterogeneity in various cancer hallmarks like self-sufficiency of growth factor production for angiogenesis and reprogramming of energy-metabolism for aerobic glycolysis. This heterogeneity has consequences for diagnosis, treatment, and disease progression. Methods: We introduce the double goods game to study the dynamics of these traits using evolutionary game theory. We model glycolytic acid production as a public good for all tumour cells and oxygen from vascularization via VEGF production as a club good benefiting non-glycolytic tumour cells. This results in three viable phenotypic strategies: glycolytic, angiogenic, and aerobic non-angiogenic. Results: We classify the dynamics into three qualitatively distinct regimes: (1) fully glycolytic, (2) fully angiogenic, or (3) polyclonal in all three cell types. The third regime allows for dynamic heterogeneity even with linear goods, something that was not possible in prior public good models that considered glycolysis or growth-factor production in isolation. Conclusion: The cyclic dynamics of the polyclonal regime stress the importance of timing for anti-glycolysis treatments like lonidamine. The existence of qualitatively different dynamic regimes highlights the order effects of treatments. In particular, we consider the potential of vascular renormalization as a neoadjuvant therapy before follow up with interventions like buffer therapy.

q-bio.PE↗

Physical limits to biomechanical sensing

Cells actively probe and respond to the stiffness of their surroundings. Since mechanosensory cells in connective tissue are surrounded by a disordered network of biopolymers, their in vivo mechanical environment can be extremely heterogeneous. Here, we investigate how this heterogeneity impacts mechanosensing by modeling the cell as an idealized local stiffness sensor inside a disordered fiber network. For all types of networks we study, including experimentally-imaged collagen and fibrin architectures, we find that measurements applied at different points throughout a given network yield a strikingly broad range of local stiffnesses, spanning roughly two decades. We verify via simulations and scaling arguments that this broad range of local stiffnesses is a generic property of disordered fiber networks, and show that the range can be further increased by tuning specific network features, including the presence of long fibers and the proximity to elastic transitions. These features additionally allow for a highly tunable dependence of stiffness on probe length. Finally, we show that to obtain optimal, reliable estimates of global tissue stiffness, a cell must adjust its size, shape, and position to integrate multiple stiffness measurements over extended regions of space.

cond-mat.soft↗