Workshop 3: Hybrid Multi-Scale Modelling and Validation

(March 27,2017 - March 31,2017 )

Organizers


Tomas Alarcon
Mathematical Biology, Centre de Recerca Matemàtica
Helen Byrne
Centre for Collaborative Applied Mathematics, University of Oxford
James Glazier
Biocomplexity Institute, Department of Physics, Indiana University

The aim of this workshop is to review the state of the art in hybrid multi-scale modelling in cancer and development with an emphasis in the crucial issue of how tissue structure and individual cell behaviour come together to robustly generate a functional tissue.

Recent results regarding tumorigenesis in epithelial tissues have shown that the geometrical arrangement of cells within epithelial sheets, analysed in terms of a Voronoi tessellation, is a key factor in determining whether malignantly infected cells are likely to invade the tissue. This scenario implies that, beyond the emergence of cells with malignant phenotypes generated by gene mutations or other mechanisms, other factors such as tissue geometrical organization must be taken into consideration. Furthermore, this situation requires the formulation and analysis of models that account for both individual cell behaviour and tissue organisation at a larger scale, i.e. we must resort to hybrid multi-scale mathematical frameworks. By studying the mechanisms that must be de-regulated in order to allow for tumours to emerge, we expect that we can reverse-engineer the underlying mechanisms that have been evolved to guarantee robust, normal tissue function and geometrical structure.

A key element in this approach is the interface between mathematical models and image acquisition and analysis. This is a critical issue, as this interface is essential for crucial steps in the modelling process such as model parametrisation and model validation. In fact, this workshop is timely because, due to huge recent advances in the general area of biomedical imaging, the major obstacle for the acceptance of these models, namely, lack of appropriate data to carry out parametrisation and validation, may become easier to overcome in the near future.

The workshop will be organised around three main areas:

  1. Individual cell behaviour. This area will explore the mechanisms for cell fate decision and their connection to cancer and development. Two subject of particular interest are (cancer) stem cells and the effect of random noise on cell-decision making.
  2. Image analysis. The emphasis in this theme will be on the interface between mathematical models and image analysis techniques by exploring, for example, how vertex models of epithelial tissues can be calibrated from images obtained by confocal microscopy.
  3. Hybrid multi-scale modelling. This theme will explore the state-of-the-art on the subject trying to emphasise how models of individual cell behaviour can be coupled to larger-scale models accounting for tissue organisation and, particularly, the interface between hybrid models and image analysis.

Accepted Speakers

Rafael Barrio
Departamento de Sistemas Complejos, Universidad Nacional Autonoma de Mexico
Aviv Bergman
Systems and Computational Biology, Albert Einstein College of Medicine
Guy Blanchard
Physiology, Development & Neuroscience, University of Cambridge
Philippe Buchler
Institute for Surgical Technology & Biomechanics, University of Bern
Guillaume Charras
London Centre for Nanotechnology, University College London
Dirk Drasdo
Bioinformatics, Physical and Mathematical Biology, Institut National de Recherche en Informatique Automatique (INRIA)
John Fozard
Centre for Systems Biology, John Innes Centre
Jonathan Harrison
Mathematical Institute, University of Oxford
John King
School of Mathematical Sciences, University of Nottingham
Paul Macklin
Intelligent Systems Engineering, Indiana University
Christopher Mitchell
Biomedical Science, Ulster University
Inke Nathke
Cell & Developmental Biology, University of Dundee
Hans Othmer
School of Mathematics, University of Minnesota
Shayn Peirce-Cottler
Vascular and Tissue Systems Bioengineering, University of Virginia
Katarzyna Rejniak
H. Lee Moffitt Cancer Center & Research Institute, H. Lee Moffitt Cancer Center & Research Institute
Jens Rittscher
Department of Engineering Science, University of Oxford
Endre Somogyi
Computer Science, Indiana University
Angélique Stéphanou
Laboratoire TIMC-IMAG / UMR 5525, CNRS
Gillian Tozer
Oncology & Metabolism, University of Sheffield
Cornelis Weijer
Life Sciences, University of Dundee
Guang Yao
Molecular and Cellular Biology, University of Arizona
Monday, March 27, 2017
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:15 AM

Breakfast

09:15 AM
09:30 AM

Welcome, overview, Introductions

09:30 AM
09:45 AM

Introduction by Workshop Organizers

09:45 AM
10:30 AM
Hans Othmer - A mathematical model of the Hippo growth control pathway in developing tissues

The Hippo pathway, which is a central pathway in the control of cell proliferation and apoptosis in Drosophila and mammalian cells, contains a core kinase mechanism that affects control of the cell cycle and growth. Studies involving over- and under-expression of components in the morphogen and Hippo pathways in Drosophila reveal conditions that lead to over- or undergrowth. In this talk we discuss a mathematical model that incorporates the current understanding of the Hippo signal transduction network in Drosophila and which can explain qualitatively both the observations on whole-disc manipulations and the results arising from mutant clones. We find that a number of non-intuitive experimental results can be explained by subtle changes in the balances between inputs to the Hippo pathway. Since signal transduction and growth control pathways are highly conserved across species and directly involved in tumor growth, much of what is learned about Drosophila will have relevance to growth control in mammalian systems.

10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Katarzyna Rejniak - Up-close and personal with drug delivery: the medical imaging-informed hybrid models of micro-pharmacodynamics

Tumor heterogeneity€”either genetic, phenotypic, metabolic or mechanical€“is believed to constitute a barrier against effective chemotherapeutic treatments, and may facilitate the development of anti-cancer drug resistance. However, typical pharmacological studies relay on compartmental well-mixed models and neglect temporal and spatial variability in properties of both the tumor and its microenvironment. We will present a novel in silico model microPK/PD of drug pharmacokinetics and pharmacodynamics on the microscopic cell-to-tissue scale that allows to track drug efficacy within the tissue on the level of individual cells. We use a palette of medical imaging techniques: immunohistochemical staining, bright filed microscopy and confocal fluorescent imaging, to inform and calibrate our models. In particular, we take into account the properties of tumor cells, cell colonies and tumor microenvironment that together allow us to examine drug intratumoral distribution in the in silico-reconstructed tumor organoids. We will discuss how such a modeling approach can be used to build a predictor of tumor chemoresistance based on clinical biopsies routinely collected for cancer diagnosis. The use of data from individual patients€™ tumors hold promise for designing personalized treatments.

11:45 AM
12:30 PM
Paul Macklin - From single models to community advances: open source codes and data standards

Problems in tissue engineering, developmental biology, cancer, and related areas require that we study 3-D multicellular systems, coupling dynamics at many scales such as protein signaling, cell phenotype "decisions," biotransport, and mechanics. Developing, calibrating, and validating models to study these systems requires not only sophisticated tools, but also a huge variety of data ranging from molecular to clinical scales. No one research team can develop all the necessary software and gather all the required data on their own, so we present our recent work to (1) contribute scalable open source software to simulate 3-D biotransport of many substrates (BioFVM), 3-D multicellular systems (PhysiCell), and extraction of cell phenotype from high-throughput experiments (CellPD), (2) help build a community for collaboration by creating a standard for multicellular data (MultiCellDS), and (3) work with this community to link biosimulation software and open data repositories through data standards.

12:30 PM
02:30 PM

Lunch Break

02:30 PM
03:15 PM
Guang Yao - Heterogeneous quiescence exit displays a memory of preceding cell cycle position and division

The reactivation of quiescent cells upon growth stimulation is critical to tissue repair and homeostasis. The quiescence-exit process is highly noisy even for genetically identical cells under the same environmental conditions; underlying reasons for this quiescence-exit heterogeneity are poorly understood. Here, by modelling and experimentally measuring and perturbing the distribution of a population of quiescent cells in their responses to growth signals, we found that quiescent cells display a memory of their preceding cell cycle positions and division histories. We further show that the deterministic positional memory of quiescent cells, coupled with the stochastic dynamics of an Rb-E2F bistable switch, jointly and quantitatively defines the heterogeneous exit from cellular quiescence.

03:15 PM
04:00 PM
Inke Nathke - The relationship between cell and tissue dynamics in healthy and precancerous epithelium

My research aims to understand how specific molecular events change cells and ultimately whole tissues during early stages of disease, specifically cancer and inflammation. My specific focus is on the intestinal epithelium and the contribution of mutations in the adenomatous polyposis coli (Apc) gene, found in >90% of cell colorectal cancers. We study how the APC protein contributes to cellular behaviour and function of epithelia. We examine how cells make decisions about differentiation, how they move and divide, how they know where they are, and how they work together to build a functional tissue. We are becoming increasingly interested in understanding how cell biological functions of cells that are regulated by APC contribute to their mechanical properties. This requires a better understanding and new tools to measure and model mechanical properties of cells and tissue dynamics and the relationship between them.

04:00 PM
06:00 PM

Reception and poster session in MBI Lounge

06:00 PM

Shuttle pick-up from MBI

Tuesday, March 28, 2017
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:45 AM
James Glazier - Coupled multiscale modeling and pathway analysis for prediction of drug efficacy in cystic kidney diseases

Extensive research has uncovered many genetic changes associated with autosomal dominant polycystic kidney disease (ADPKD) and effects of ADPKD mutations on signaling pathways. However, we still do not know the precise sequence of events that lead to cyst initiation. One of the key changes during the initiation of cysts is abnormal expression of the juvenile cell adhesion molecule cadherin-8. We examined two hypothetical cell-level mechanisms by which abnormal expression of cadherin-8 could initiate cyst formation: i) reduction of cell-cell adhesion, which then leads to changes in cell proliferation or ii) direct reduction of contact inhibition of proliferation with no change in cell-cell adhesion. To test these mechanisms we built a 3D virtual-tissue (VT) computer model of the renal tubule using the CompuCell3D (CC3D) modeling environment (Swat et al., 2012). Our VT simulations showed that while both mechanisms could initiate cyst formation, only the loss of adhesion mechanism produced morphologies matching in vitro cadherin- 8 induced cysts (Belmonte et al., 2016).


Concurrently, we used the Transcriptogram method for whole-genome gene expression analysis to analyze microarray data from cell lines developed from cell isolates from normal kidney and from both non-cystic nephrons and cysts from the kidney of a patient with ADPKD. We identified novel pathways altered in ADPKD. Transcriptogram significance metrics identified increased expression of cGMP phosphodiesterases as the highest priority pathways for study (de Almeida et al., 2016). Our modeling and experimental efforts then focused on cGMP phosphodiesterase inhibitors, a class of drugs already FDA approved for other uses.


Using pathway analysis we linked the cell behaviors known to drive cyst formation with increased cGMP phosphodiesterase expression and constructed models of these pathways using Cell Designer. We are currently calibrating these pathway models using biological data. Preliminary in vitro and mouse model testing of phosphodiesterase inhibitors to reduce cyst formation have shown efficacy. We will next incorporate these pathway models into our CC3D VT cystogenesis model to predict drug effects on cyst formation.

09:45 AM
10:30 AM
John Fozard - Investigating growth within curved layers of cells using the Cellular Potts Model

The cellular Potts model (CPM) has been applied to investigate the behaviours of many different multicellular tissues. For some plant tissues, such as leaves and the shoot apical meristem, a single curved layer of cells is of primary interest. This curved layer can be represented by a triangulated surface, and we consider the formulation of the CPM on such an irregular, non-uniform lattice. Such a formulation is then used to apply segmentation methods, based upon the CPM, to quantify geometric properties of cells within curved layers of cells, using data from confocal microscopy images. We further explore coupling cell-scale models to coarser discretizations of organ shape, and use these to explore plant organ growth and development.

10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Dirk Drasdo - A step towards virtual experiments in organ micro-architectures: growth factor signaling, ammonia detoxification and drug metabolism in a virtual liver lobule

In vivo experiments are expensive, time consuming, and underlie strict ethic rules. Their results only partially apply to human. Modern experimental methods composed of imaging at high resolution, in 3D, or in living tissues provide information that increasingly permit development of multi-level computational models, that allow for virtual experiments. In such models, hypotheses on molecular, cell-level or tissue-level mechanisms can be implemented and their consequence be tested in-silico. Prospectively, this can permit feeding computational models with patient-specific information at each of the above levels and studying the prospective impact of therapeutic interventions.


As a step towards a virtual liver lobule, we in this presentation will show how stepwise a multilevel model of drug-induced damage, regeneration and the detoxification of ammonia during regeneration is developed.


Hyperammonemia is a severe complication after drug induced liver damage, for example resulting from overdosing acetaminophen (paracetamol), and can lead to encephalopathy and dead of the patient. A set of chemical reactions identified by Häussinger (1983) and Gebhardt (1983) has become the biological consensus model for ammonia detoxification in healthy liver.


We will show how the iterative application of a pipeline consisting of confocal scanning microscopy, image analysis and modeling can be used to design a predictive model of tissue regeneration and metabolism suited to guide modeling driven experimental strategies (Drasdo, J. Hepat. 2014). In the case of hyperammonenia such a strategy has led to the model-guided identification of a so far unrecognized mechanism in ammonia detoxification that has the potential to improve therapy (Schliess, Hepatology, 2014; Ghallab, J. Hepat. 2016). While the former works based on a integrative model, that links a compartment model of ammonia detoxification with a spatial-temporal micro-architectural agent-based model of liver regeneration after drug induced liver damage, we here compare the integrated model with a full multi-scale, multi-level model whereby the detoxification reactions are executed in each individual hepatocyte, and discuss critical differences. Finally, we extend the multiscale model by integrating a model of toxic damage by acetaminophen in each hepatocyte, as well as hgf induced cell progression during the regeneration of tissue damage caused by acetaminophen.

11:45 AM
12:30 PM
Shayn Peirce-Cottler - Agent-based modeling of cells in tissues to understand and predict disease

The most prevalent, devastating, and complex diseases of our time, such as diabetes, cardiovascular disease, and infectious diseases, result from the interactions of heterogeneous cells with one another and with their environment. However, the emergence of disease from these interactions at the multi-cell level is still poorly understood, and drugs typically target single molecular pathways while disregarding how cellular heterogeneities might affect drug efficacy at the tissue-level. To address this void, we develop new computational tools in combination with experimental approaches in order to integrate and predict how individual cell behaviors dynamically give rise to physiological and pathological tissue-level adaptations. Leveraging the versatility and adaptability of agent-based modeling, we have simulated structural adaptations of large and small blood vessels, skeletal muscle regeneration following injury, and immune cell trafficking and differentiation during inflammation and infection. Our studies have suggested new mechanistic hypotheses and provided guidance for the design of novel therapies.

12:30 PM
02:00 PM

Lunch Break

02:00 PM
02:45 PM
Jens Rittscher - Quantitative Methods for High-Throughput Live Cell Imaging

Building on recent advances in computer vision and machine learning we are now in the position to monitor complex biological environments and events in the same way are analysing natural scenes. While challenges remain, algorithms for cell segmentation and tracking have matured significantly and can now be used in more routine high-throughput settings. Improved microscopy and imaging platforms not only allow us to image subcellular events at high spatial and temporal resolution, we can now image large tissue sections and capture how various different proteins modulate the cellular microenvironment. Enabled by advances in cell culturing technologies 3D cultures can restore specific biochemical and morphological features that are similar to their in vivo counterparts. This holds the potential for improving relevance of in vitro studies, improving our ability to predict what occurs in vivo.


We are now working towards establishing the spatial and temporal context for biological events and processes. Quantitative image analysis methods are necessary for monitoring the tissue formation process and enabling longer duration time-lapse imaging. The talk will highlight opportunities of interfacing imaging with mathematical modelling. One such example will be the modelling of cellular behaviour. Our current research focuses on analysing cellular viability, the interaction of epithelial cell populations and the evolution of organoid cell cultures.

02:45 PM
03:15 PM

Break

03:15 PM
04:00 PM
Timothy Secomb - Hybrid multi-scale modelling of angiogenesis

Development of an adequate and efficient network of microvessels throughout tissues is a prerequisite for normal growth and maintenance of normal function. Abnormalities in vascular structure play a central role in numerous pathologies. In particular, the aberrant structure of tumor microcirculation causes regions of tissue hypoxia that interfere with the action of treatments by radiation and chemotherapy. The total number of vessel segments in the human body is more than 10. Clearly, therefore, the structure of the microcirculation is not specified by genetic information down to the level of individual vessels. Instead, the observed structures of microvessel networks represent the outcome of a set of generic behaviors exhibited by individual cells in vessel walls, responding to the stimuli that they experience, which result in angiogenesis, structural remodeling and pruning of vessels. We have developed hybrid multiscale models to investigate these behaviors. In these models, network structure is explicitly represented as a set of discrete nodes and segments, whose lengths and diameters evolve with time according to the assumed underlying cellular responses. The concentrations of oxygen and growth factors in the surrounding tissue are governed by continuous reaction-diffusion equations, which are solved numerically using a Green’s function approach. Examples of the application of the models in two and three dimensions are presented. The models provide insight into the key mechanisms needed to generate functional network structures. For instance, it is found that upstream conducted responses, propagated along vessel walls, play an essential role. If conducted responses are reduced, flow is diverted from long to short flow pathways. This may be a major cause of poor perfusion in vascularized solid tumors.

04:00 PM
05:00 PM

Informal discussion

05:00 PM

Shuttle pick-up from MBI

Wednesday, March 29, 2017
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:45 AM
Gillian Tozer - Tumour Microcirculation, Vascular Targeting and Biomarkers: insight from pre-clinical models

Since clinical approval in 2004 of the vascular endothelial growth factor (VEGFA) blocking antibody, bevacizumab (Avastin), for treatment of colorectal cancer, a substantial number of additional anti-angiogenic compounds are now available for cancer treatment. Although these compounds are primarily targeted against the angiogenic process itself, they undoubtedly have additional effects on already established tumour blood vessels. In addition, a number of so-called tumour vascular disrupting agents (VDAs), which are specifically designed to target established tumour blood vessels, are in clinical trials. Despite this success, resistance to treatment is a major problem, with lack of predictive biomarkers to select those patients most likely to benefit from vascular targeted treatments a major limitation and biomarkers of response technically challenging.


VEGFA exists as multiple isoforms generated through alternative splicing and proteolysis. Recent retrospective analyses of data from several large phase III clinical trials have found an association between high concentrations of soluble VEGFA isoforms in plasma and poor prognosis, but also improved response to bevacizumab, making them potential predictive biomarkers. Using mouse fibrosarcoma cells genetically modified to express single isoforms of VEGFA, we have investigated the role of individual VEGFA isoforms in tumour vascularisation, patterning and function, metastasis and response to VEGFA pathway inhibitors and VDAs. Notably, soluble VEGFA-120 was associated with increased metastasis to the lung and a good response to the anti-VEGFA blocking antibody, B20-4.1.1. (the mouse equivalent of bevacizumab). Expression of VEGFA-120 was associated with highly permeable and dilated blood vessels in the primary tumour and a modified extracellular matrix, which could account for the increased metastasis. Analytical methods for measuring vascular and metabolic parameters in intravital microscopy and magnetic resonance imaging/spectroscopy (MRI/MRS) of tumours will be discussed.

09:45 AM
10:30 AM
Cornelis Weijer - Cellular behaviours underlying tissue dynamics during primitive streak formation in the chick embryo

Gastrulation involves embryo wide tissue reorganizations and deformations driven by coordinated cell shape changes and rearrangements. Using a dedicated lightsheet microscope we are able to follow over 200.000 cells in the early embryo. We show that the large scale tissue deformations resulting in the formation the primitive streak in the chick embryo are driven by anisotropic pulling forces. These forces are generated by local cell shape changes and cell rearrangements of mesendoderm cells. These cell rearrangements are mediated by sequential, directional contraction of aligned apical junctions in neighboring cells. These processes are driven contraction of apical acto-myosin II cables. We will discuss our attempts to analyse and model how these cell shape changes and intercalations can self-organise on the tissue scale to result in the formation of the primitive streak.

10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Angélique Stéphanou - Hybrid Multiscale modelling for the design of a virtual tumour

The design of a patient-specific virtual tumour is an important step towards personalized medicine since the virtual tumour can be used to define the most adapted and efficient treatment protocol. However this requires to capture the description of many key events of tumour development, including angiogenesis, matrix remodelling, hypoxia, cell heterogeneity that will all influence the tumour growth kinetics and degree of tumour invasiveness. To that end, an integrated hybrid and multiscale approach has been developed based on data acquired on a preclinical mouse model as a proof of concept.


Fluorescence imaging is exploited to build case-specific virtual tumours and to validate their spatiotemporal evolution. The validity of the model will be discussed as well as its potential to identify the best therapeutic strategy for each individual tumour case.

11:45 AM
12:30 PM
Christopher Mitchell - Multi-scalar modelling of the microvasculature: how do biologists and modellers get it less wrong?

From conception to old age, all the cells in our body are less than 50 micrometers from capillaries; the functional units of the circulatory system that meet all the metabolic requirements of the organs they supply. The capillaries in each organ are also uniquely adapted in each organ to meet its€™ functional requirements. The microcirculation is also able to rapidly respond to (large and small scale) damage or disease by regenerating functional capillaries (using a variety of different processes), in order to maintain tissue homeostasis. Getting the multi-scalar biological principles and modelling less wrong will depend on cross-disciplinary understanding of the unique features of the tissue microvasculature and the tissue it supplies as well as validating the approaches (both biological and modelling) across a range of contexts.

12:30 PM
02:00 PM

Lunch Break

02:00 PM
02:45 PM
Aviv Bergman - Cancer Motility, a Systems Biological View

Currently, research into carcinogenesis focuses on the importance of driver mutations in creating a suitable genetic background for tumor cell progression, including motility and metastasis. I will propose an alternative view in which driver mutations may facilitate tumor progression, however non-genetic control and regulatory mechanisms within the cell ultimately enable and are responsible for the progression to malignancy.

02:45 PM
03:30 PM
Yi Jiang
03:30 PM
03:45 PM

Break

03:45 PM
05:00 PM

Informal discussion

05:00 PM

Shuttle pick-up from MBI

Thursday, March 30, 2017
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:45 AM
Rafael Barrio - Model for the early development of meristems

Stem cells are identical in many scales, they share the same molecular composition, DNA, genes and genetic networks, yet they should acquire di?erent properties to form a functional tissue. Therefore, they must interact and get some external information from their environment, either spatial (dynamical fields) or temporal (lineage). In this work we test to what extent coupled chemical and physical fields can underlie the cell€™s positional information during development. We choose the root apical meristem of Arabidopsis thaliana to model the emergence of cellular patterns. We built a model to study the dynamics and interactions between the cell divisions, the local auxin concentration and physical elastic fields.

09:45 AM
10:30 AM
Guillaume Charras - Long and short time-scale rheology of living cell monolayers

One-cell thick monolayers are the simplest tissues in multi-cellular organisms, yet they fulfil critical mechanical roles in development and normal physiology. To study their mechanics, we use an experimental system for tensile testing of freely suspended cultured monolayers that enables the examination of their mechanical behaviour at multi-, uni-, and sub-cellular scales. Using uniaxial stress relaxation experiments, we examined the rheology of cell monolayers on time-scales of seconds, minutes, and hours. At the shortest time-scales, ATP-independent processes dominated relaxation and followed a power law behaviour in response to the large imposed deformation. At minute time-scales, relaxation was ATP-dependent and myosin allowed the tissue to behave as a solid on minute long time-scales. At hour time-scales, oriented cell divisions drove relaxation of tissue and the return to resting cell packing. As the application of a stretch naturally elongates cells within the monolayer along the stretch axis, oriented divisions in our system are a direct consequence of the propensity of cells to divide along their interphase long axis and does not require cells to detect mechanical cues other than their own shape.

10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Guy Blanchard - Identifying and modeling contractile trans-tissue structures in morphogenesis

Recent advances in the live imaging of embryonic development promise to revolutionise our understanding of morphogenetic processes. Tissue mechanics are a vital link between cellular protein expression and the changing shapes of embryos, but remain one of the least well-understood aspects of development. As a computational biologist and image analyst, I develop methods to analyse in vivo morphogenetic movements and to infer biomechanical parameters. This approach can be broken down into five steps. First, 4D imaging datasets are translated into cell trajectories and the evolution of cell shapes over time. Second, local tissue deformation rates are quantified and broken down into the additive contributions of different cell behaviours. Third, the fluorescence intensity of tagged Myosin motors are quantified as a proxy for cell contractility. Fourth, the above information is combined to estimate mechanical parameters in vivo. Finally, we test our understanding with computational models. I will summarise progress we are making in these five areas in multiple tissues of the Drosophila fly embryo. We find that supra-cellular mechanical structures are important drivers of tissue morphogenesis.

11:45 AM
12:30 PM
Jonathan Harrison - The impact of collecting data at varying temporal resolution on parameter inference for biological transport models

When collecting time series data of biological transport processes, it is necessary to observe the system at discrete time points, for example via an imaging experiment. This can introduce errors when the motion is approximated with discrete steps. We study the impact of collecting data at different temporal resolutions on parameter inference for biological transport models. In this work, we have performed exact inference for velocity jump process models in a Bayesian framework. This allows us to obtain estimates of the turning rate and noise amplitude for noisy observations of this transport process. We show sensitivity of these estimates to changes in time discretisation and noise amplitude. For a fixed photon budget, our results suggest that better estimates of parameters can be obtained when imaging more frequently with more noise than imaging sparsely with low noise.

12:30 PM
02:00 PM

Lunch Break

02:00 PM
02:45 PM
Endre Somogyi
02:45 PM
03:30 PM
Roeland Merks
03:30 PM
03:45 PM

Break

03:45 PM
05:00 PM

Informal discussion

05:00 PM

Shuttle pick-up from MBI

06:30 PM
07:00 PM

Cash Bar

07:00 PM
09:00 PM

Banquet in the Fusion Room @ Crowne Plaza Hotel

Friday, March 31, 2017
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:45 AM
Philippe Buchler - Mechanically-coupled Reaction-Diffusion model of Glioma Growth

Brain tumours represent a rare but serious medical condition. With an incidence of six cases per 100000, gliomas are the most frequent primary brain tumours in adults, accounting for 70% of cases. Gliomas are classified into four grades by increasing aggressiveness, based on their microscopic structure and cellular activity. Glioblastoma multiforme (GBM) is the most frequent and most malignant sub-type of glioma (grade IV), accounting for about 50% of diffuse gliomas. These tumours infiltrate surrounding healthy tissue, grow rapidly and form a necrotic core of high cell density, which is accompanied by compression and displacement of surrounding tissue. This so-called mass-effect leads to an increase in intra-cranial pressure and the progressive on-set of a multitude of pressure-related symptoms, such as headache and nausea. Compensation mechanisms for regulating intra-cranial pressure fail beyond a critical tumour volume, so that any additional volume increase will result in a decisive rise in intra- cranial pressure and related acute clinical worsening, including coma or death due to herniation


Given the importance of mechanical effects, we have started a systematic numerical analysis of the dependence of morphological and mechanical tumour characteristics on their growth location. This study is part of an ongoing effort to establish a model of the macroscopic mechanical aspects of tumour growth that can also be integrated into multi-scale cancer models, such as those proposed by the CHIC project.

09:45 AM
10:30 AM
John King - Organization of vascular pattern in plant roots

In higher plants the root vascular tissue or stele contains the xylem vessels, which transport water and nutrients from root to shoot, and the phloem, which transport photosynthetic products (sugars) from shoot to root. In Arabidopsis there are exactly two xylem vessels and two phloem vessels in every root, arranged in a diarch pattern, and regulated and organised by the two plant hormones, auxin and cytokinin. Mathematical modelling has shown that an embryonic asymmetry in auxin, originating from the two cotyledons, may establish the vascular pattern prior to germination, and that once established this pattern is robust to perturbations in hormone concentrations. However, the models have not yet been able to explain how the patterning of the vascular bundles of monocots, such as cereals that may have ten or more xylem poles, can originate from a single cotyledon auxin source. Furthermore, it can be shown that vascular pattern may be altered in growing roots via experimental manipulation, suggesting some post-embryonic patterning mechanism is present. A variety of modelling approaches to investigate how such de-novo patterning with multiple xylem and phloem vessels may occur in plant roots will be outlined. (Joint work with Nathan Mellor, Anthony Bishopp and Britta Kuempers).

10:30 AM
11:00 AM

Break

11:00 AM
12:00 PM

Informal discussions and workshop wrap up

12:00 PM

Shuttle pick-up from MBI (One to airport and one back to hotel)

Name Email Affiliation
Alarcon, Tomas talarcon@crm.cat Mathematical Biology, Centre de Recerca Matemàtica
Almet, Axel axel.almet@maths.ox.ac.uk Mathematical Institute, University of Oxford
Barrio, Rafael barrio@fisica.unam.mx Departamento de Sistemas Complejos, Universidad Nacional Autonoma de Mexico
Bergman, Aviv aviv@einstein.yu.edu Systems and Computational Biology, Albert Einstein College of Medicine
Blanchard, Guy gb288@cam.ac.uk Physiology, Development & Neuroscience, University of Cambridge
Buchler, Philippe philippe.buechler@istb.unibe.ch Institute for Surgical Technology & Biomechanics, University of Bern
Bull, Joshua joshua.bull@st-hughs.ox.ac.uk Mathematical Institute, University of Oxford
Byrne, Helen byrneh@maths.ox.ac.uk Centre for Collaborative Applied Mathematics, University of Oxford
Calvo, Juan juancalvo@ugr.es Matemática Aplicada, Universidad de Granada
Charras, Guillaume g.charras@ucl.ac.uk London Centre for Nanotechnology, University College London
Davit, Yohan yohan.davit@imft.fr UMR 5502 INPT-UPS-CNRS, Institut de Mécanique des Fluides de Toulouse
Dhawan, Andrew adhawan@qmed.ca Oncology, University of Oxford
Drasdo, Dirk dirk.dras@gmail.com Bioinformatics, Physical and Mathematical Biology, Institut National de Recherche en Informatique Automatique (INRIA)
Ferreira, Marina m.amado-ferreira14@imperial.ac.uk Department of Mathematics, Imperial College London
Fletcher, Alexander a.g.fletcher@sheffield.ac.uk School of Mathematics and Statistics, University of Sheffield
Fozard, John john.fozard@jic.ac.uk Centre for Systems Biology, John Innes Centre
Glazier, James glazier@indiana.edu Biocomplexity Institute, Department of Physics, Indiana University
Grogan, James grogan@maths.ox.ac.uk Mathematical Insitute, University of Oxford
Harrison, Jonathan harrison@maths.ox.ac.uk Mathematical Institute, University of Oxford
Jiang, Yi yjiang12@gsu.edu Mathematics and Statistics, Georgia State University
Karolak, Aleksandra Aleksandra.Karolak@moffitt.org Integrated mathematical oncology, H. Lee Moffitt Cancer Center and Research Institute
King, John john.king@nottingham.ac.uk School of Mathematical Sciences, University of Nottingham
Klapper, Isaac klapper@temple.edu Mathematics, Temple University
Kumar, Bharat kumar.637@buckeyemail.osu.edu Biomedical Engineering, The Ohio State University
Linder, Daniel Biostatistics, Medical College of Georgia
Macklin, Paul macklinp@iu.edu Intelligent Systems Engineering, Indiana University
McFadden, Francesca freale1@umbc.edu Mathematics, University of Maryland Baltimore County
Merks, Roeland Roeland.Merks@cwi.nl Biomodeling and Biosystems Analysis Group, Center for Mathematics and Computer Science (CWI)
Minucci, Sarah sarah.minucci@gmail.com Mathematics, Virginia Commonwealth University
Mitchell, Christopher ca.mitchell@ulster.ac.uk Biomedical Science, Ulster University
Nathke, Inke inke@lifesci.dundee.ac.uk Cell & Developmental Biology, University of Dundee
Othmer, Hans othmer@math.umn.edu School of Mathematics, University of Minnesota
Peirce-Cottler, Shayn smp6p@virginia.edu Vascular and Tissue Systems Bioengineering, University of Virginia
Reilly, Matthew reilly.196@osu.edu Biomedical Engineering, The Ohio State University
Rejniak, Katarzyna Kasia.Rejniak@moffitt.org H. Lee Moffitt Cancer Center & Research Institute, H. Lee Moffitt Cancer Center & Research Institute
Reynolds, Angela areynolds2@vcu.edu Mathematics and Applied Mathematics, Virginia Commonwealth University
Rittscher, Jens jens.rittscher@eng.ox.ac.uk Department of Engineering Science, University of Oxford
Secomb, Timothy secomb@u.arizona.edu Physiology, University of Arizona
Somogyi, Endre somogyie@indiana.edu Computer Science, Indiana University
Stphanou, Anglique angelique.stephanou@imag.fr Laboratoire TIMC-IMAG / UMR 5525, CNRS
Tania, Nessy ntania@smith.edu Mathematics & Statistics, Smith College
Tozer, Gillian g.tozer@sheffield.ac.uk Oncology & Metabolism, University of Sheffield
Weijer, Cornelis c.j.weijer@dundee.ac.uk Life Sciences, University of Dundee
Williamson, Drew dfw36@case.edu Translational Hematology and Oncology Research, Cleveland Clinic Foundation
Wood, Brian brian.wood@oregonstate.edu School of Chemical, Biological, and Environmental Engineering,, Oregon State University
Wu, Hao School of Mathematics, University of Minnesota Twin Cities
Yao, Guang guangyao@arizona.edu Molecular and Cellular Biology, University of Arizona
Yoon, Nara nxy47@case.edu Translational Hematology and Oncology Research, Cleveland Clinic Foundation
Model for the early development of meristems

Stem cells are identical in many scales, they share the same molecular composition, DNA, genes and genetic networks, yet they should acquire di?erent properties to form a functional tissue. Therefore, they must interact and get some external information from their environment, either spatial (dynamical fields) or temporal (lineage). In this work we test to what extent coupled chemical and physical fields can underlie the cell’s positional information during development. We choose the root apical meristem of Arabidopsis thaliana to model the emergence of cellular patterns. We built a model to study the dynamics and interactions between the cell divisions, the local auxin concentration and physical elastic fields.

Cancer Motility, a Systems Biological View

Currently, research into carcinogenesis focuses on the importance of driver mutations in creating a suitable genetic background for tumor cell progression, including motility and metastasis. I will propose an alternative view in which driver mutations may facilitate tumor progression, however non-genetic control and regulatory mechanisms within the cell ultimately enable and are responsible for the progression to malignancy.

Identifying and modeling contractile trans-tissue structures in morphogenesis

Recent advances in the live imaging of embryonic development promise to revolutionise our understanding of morphogenetic processes. Tissue mechanics are a vital link between cellular protein expression and the changing shapes of embryos, but remain one of the least well-understood aspects of development. As a computational biologist and image analyst, I develop methods to analyse in vivo morphogenetic movements and to infer biomechanical parameters. This approach can be broken down into five steps. First, 4D imaging datasets are translated into cell trajectories and the evolution of cell shapes over time. Second, local tissue deformation rates are quantified and broken down into the additive contributions of different cell behaviours. Third, the fluorescence intensity of tagged Myosin motors are quantified as a proxy for cell contractility. Fourth, the above information is combined to estimate mechanical parameters in vivo. Finally, we test our understanding with computational models. I will summarise progress we are making in these five areas in multiple tissues of the Drosophila fly embryo. We find that supra-cellular mechanical structures are important drivers of tissue morphogenesis.

Mechanically-coupled Reaction-Diffusion model of Glioma Growth

Brain tumours represent a rare but serious medical condition. With an incidence of six cases per 100000, gliomas are the most frequent primary brain tumours in adults, accounting for 70% of cases. Gliomas are classified into four grades by increasing aggressiveness, based on their microscopic structure and cellular activity. Glioblastoma multiforme (GBM) is the most frequent and most malignant sub-type of glioma (grade IV), accounting for about 50% of diffuse gliomas. These tumours infiltrate surrounding healthy tissue, grow rapidly and form a necrotic core of high cell density, which is accompanied by compression and displacement of surrounding tissue. This so-called mass-effect leads to an increase in intra-cranial pressure and the progressive on-set of a multitude of pressure-related symptoms, such as headache and nausea. Compensation mechanisms for regulating intra-cranial pressure fail beyond a critical tumour volume, so that any additional volume increase will result in a decisive rise in intra- cranial pressure and related acute clinical worsening, including coma or death due to herniation


Given the importance of mechanical effects, we have started a systematic numerical analysis of the dependence of morphological and mechanical tumour characteristics on their growth location. This study is part of an ongoing effort to establish a model of the macroscopic mechanical aspects of tumour growth that can also be integrated into multi-scale cancer models, such as those proposed by the CHIC project.

Long and short time-scale rheology of living cell monolayers

One-cell thick monolayers are the simplest tissues in multi-cellular organisms, yet they fulfil critical mechanical roles in development and normal physiology. To study their mechanics, we use an experimental system for tensile testing of freely suspended cultured monolayers that enables the examination of their mechanical behaviour at multi-, uni-, and sub-cellular scales. Using uniaxial stress relaxation experiments, we examined the rheology of cell monolayers on time-scales of seconds, minutes, and hours. At the shortest time-scales, ATP-independent processes dominated relaxation and followed a power law behaviour in response to the large imposed deformation. At minute time-scales, relaxation was ATP-dependent and myosin allowed the tissue to behave as a solid on minute long time-scales. At hour time-scales, oriented cell divisions drove relaxation of tissue and the return to resting cell packing. As the application of a stretch naturally elongates cells within the monolayer along the stretch axis, oriented divisions in our system are a direct consequence of the propensity of cells to divide along their interphase long axis and does not require cells to detect mechanical cues other than their own shape.

A step towards virtual experiments in organ micro-architectures: growth factor signaling, ammonia detoxification and drug metabolism in a virtual liver lobule

In vivo experiments are expensive, time consuming, and underlie strict ethic rules. Their results only partially apply to human. Modern experimental methods composed of imaging at high resolution, in 3D, or in living tissues provide information that increasingly permit development of multi-level computational models, that allow for virtual experiments. In such models, hypotheses on molecular, cell-level or tissue-level mechanisms can be implemented and their consequence be tested in-silico. Prospectively, this can permit feeding computational models with patient-specific information at each of the above levels and studying the prospective impact of therapeutic interventions.


As a step towards a virtual liver lobule, we in this presentation will show how stepwise a multilevel model of drug-induced damage, regeneration and the detoxification of ammonia during regeneration is developed.


Hyperammonemia is a severe complication after drug induced liver damage, for example resulting from overdosing acetaminophen (paracetamol), and can lead to encephalopathy and dead of the patient. A set of chemical reactions identified by Häussinger (1983) and Gebhardt (1983) has become the biological consensus model for ammonia detoxification in healthy liver.


We will show how the iterative application of a pipeline consisting of confocal scanning microscopy, image analysis and modeling can be used to design a predictive model of tissue regeneration and metabolism suited to guide modeling driven experimental strategies (Drasdo, J. Hepat. 2014). In the case of hyperammonenia such a strategy has led to the model-guided identification of a so far unrecognized mechanism in ammonia detoxification that has the potential to improve therapy (Schliess, Hepatology, 2014; Ghallab, J. Hepat. 2016). While the former works based on a integrative model, that links a compartment model of ammonia detoxification with a spatial-temporal micro-architectural agent-based model of liver regeneration after drug induced liver damage, we here compare the integrated model with a full multi-scale, multi-level model whereby the detoxification reactions are executed in each individual hepatocyte, and discuss critical differences. Finally, we extend the multiscale model by integrating a model of toxic damage by acetaminophen in each hepatocyte, as well as hgf induced cell progression during the regeneration of tissue damage caused by acetaminophen.

Investigating growth within curved layers of cells using the Cellular Potts Model

The cellular Potts model (CPM) has been applied to investigate the behaviours of many different multicellular tissues. For some plant tissues, such as leaves and the shoot apical meristem, a single curved layer of cells is of primary interest. This curved layer can be represented by a triangulated surface, and we consider the formulation of the CPM on such an irregular, non-uniform lattice. Such a formulation is then used to apply segmentation methods, based upon the CPM, to quantify geometric properties of cells within curved layers of cells, using data from confocal microscopy images. We further explore coupling cell-scale models to coarser discretizations of organ shape, and use these to explore plant organ growth and development.

Coupled multiscale modeling and pathway analysis for prediction of drug efficacy in cystic kidney diseases

Extensive research has uncovered many genetic changes associated with autosomal dominant polycystic kidney disease (ADPKD) and effects of ADPKD mutations on signaling pathways. However, we still do not know the precise sequence of events that lead to cyst initiation. One of the key changes during the initiation of cysts is abnormal expression of the juvenile cell adhesion molecule cadherin-8. We examined two hypothetical cell-level mechanisms by which abnormal expression of cadherin-8 could initiate cyst formation: i) reduction of cell-cell adhesion, which then leads to changes in cell proliferation or ii) direct reduction of contact inhibition of proliferation with no change in cell-cell adhesion. To test these mechanisms we built a 3D virtual-tissue (VT) computer model of the renal tubule using the CompuCell3D (CC3D) modeling environment (Swat et al., 2012). Our VT simulations showed that while both mechanisms could initiate cyst formation, only the loss of adhesion mechanism produced morphologies matching in vitro cadherin- 8 induced cysts (Belmonte et al., 2016).


Concurrently, we used the Transcriptogram method for whole-genome gene expression analysis to analyze microarray data from cell lines developed from cell isolates from normal kidney and from both non-cystic nephrons and cysts from the kidney of a patient with ADPKD. We identified novel pathways altered in ADPKD. Transcriptogram significance metrics identified increased expression of cGMP phosphodiesterases as the highest priority pathways for study (de Almeida et al., 2016). Our modeling and experimental efforts then focused on cGMP phosphodiesterase inhibitors, a class of drugs already FDA approved for other uses.


Using pathway analysis we linked the cell behaviors known to drive cyst formation with increased cGMP phosphodiesterase expression and constructed models of these pathways using Cell Designer. We are currently calibrating these pathway models using biological data. Preliminary in vitro and mouse model testing of phosphodiesterase inhibitors to reduce cyst formation have shown efficacy. We will next incorporate these pathway models into our CC3D VT cystogenesis model to predict drug effects on cyst formation.

The impact of collecting data at varying temporal resolution on parameter inference for biological transport models

When collecting time series data of biological transport processes, it is necessary to observe the system at discrete time points, for example via an imaging experiment. This can introduce errors when the motion is approximated with discrete steps. We study the impact of collecting data at different temporal resolutions on parameter inference for biological transport models. In this work, we have performed exact inference for velocity jump process models in a Bayesian framework. This allows us to obtain estimates of the turning rate and noise amplitude for noisy observations of this transport process. We show sensitivity of these estimates to changes in time discretisation and noise amplitude. For a fixed photon budget, our results suggest that better estimates of parameters can be obtained when imaging more frequently with more noise than imaging sparsely with low noise.

Organization of vascular pattern in plant roots

In higher plants the root vascular tissue or stele contains the xylem vessels, which transport water and nutrients from root to shoot, and the phloem, which transport photosynthetic products (sugars) from shoot to root. In Arabidopsis there are exactly two xylem vessels and two phloem vessels in every root, arranged in a diarch pattern, and regulated and organised by the two plant hormones, auxin and cytokinin. Mathematical modelling has shown that an embryonic asymmetry in auxin, originating from the two cotyledons, may establish the vascular pattern prior to germination, and that once established this pattern is robust to perturbations in hormone concentrations. However, the models have not yet been able to explain how the patterning of the vascular bundles of monocots, such as cereals that may have ten or more xylem poles, can originate from a single cotyledon auxin source. Furthermore, it can be shown that vascular pattern may be altered in growing roots via experimental manipulation, suggesting some post-embryonic patterning mechanism is present. A variety of modelling approaches to investigate how such de-novo patterning with multiple xylem and phloem vessels may occur in plant roots will be outlined. (Joint work with Nathan Mellor, Anthony Bishopp and Britta Kuempers).

From single models to community advances: open source codes and data standards

Problems in tissue engineering, developmental biology, cancer, and related areas require that we study 3-D multicellular systems, coupling dynamics at many scales such as protein signaling, cell phenotype "decisions," biotransport, and mechanics. Developing, calibrating, and validating models to study these systems requires not only sophisticated tools, but also a huge variety of data ranging from molecular to clinical scales. No one research team can develop all the necessary software and gather all the required data on their own, so we present our recent work to (1) contribute scalable open source software to simulate 3-D biotransport of many substrates (BioFVM), 3-D multicellular systems (PhysiCell), and extraction of cell phenotype from high-throughput experiments (CellPD), (2) help build a community for collaboration by creating a standard for multicellular data (MultiCellDS), and (3) work with this community to link biosimulation software and open data repositories through data standards.

Multi-scalar modelling of the microvasculature: how do biologists and modellers get it less wrong?

From conception to old age, all the cells in our body are less than 50 micrometers from capillaries; the functional units of the circulatory system that meet all the metabolic requirements of the organs they supply. The capillaries in each organ are also uniquely adapted in each organ to meet its’ functional requirements. The microcirculation is also able to rapidly respond to (large and small scale) damage or disease by regenerating functional capillaries (using a variety of different processes), in order to maintain tissue homeostasis. Getting the multi-scalar biological principles and modelling less wrong will depend on cross-disciplinary understanding of the unique features of the tissue microvasculature and the tissue it supplies as well as validating the approaches (both biological and modelling) across a range of contexts.

The relationship between cell and tissue dynamics in healthy and precancerous epithelium

My research aims to understand how specific molecular events change cells and ultimately whole tissues during early stages of disease, specifically cancer and inflammation. My specific focus is on the intestinal epithelium and the contribution of mutations in the adenomatous polyposis coli (Apc) gene, found in >90% of cell colorectal cancers. We study how the APC protein contributes to cellular behaviour and function of epithelia. We examine how cells make decisions about differentiation, how they move and divide, how they know where they are, and how they work together to build a functional tissue. We are becoming increasingly interested in understanding how cell biological functions of cells that are regulated by APC contribute to their mechanical properties. This requires a better understanding and new tools to measure and model mechanical properties of cells and tissue dynamics and the relationship between them.

A mathematical model of the Hippo growth control pathway in developing tissues

The Hippo pathway, which is a central pathway in the control of cell proliferation and apoptosis in Drosophila and mammalian cells, contains a core kinase mechanism that affects control of the cell cycle and growth. Studies involving over- and under-expression of components in the morphogen and Hippo pathways in Drosophila reveal conditions that lead to over- or undergrowth. In this talk we discuss a mathematical model that incorporates the current understanding of the Hippo signal transduction network in Drosophila and which can explain qualitatively both the observations on whole-disc manipulations and the results arising from mutant clones. We find that a number of non-intuitive experimental results can be explained by subtle changes in the balances between inputs to the Hippo pathway. Since signal transduction and growth control pathways are highly conserved across species and directly involved in tumor growth, much of what is learned about Drosophila will have relevance to growth control in mammalian systems.

Agent-based modeling of cells in tissues to understand and predict disease

The most prevalent, devastating, and complex diseases of our time, such as diabetes, cardiovascular disease, and infectious diseases, result from the interactions of heterogeneous cells with one another and with their environment. However, the emergence of disease from these interactions at the multi-cell level is still poorly understood, and drugs typically target single molecular pathways while disregarding how cellular heterogeneities might affect drug efficacy at the tissue-level. To address this void, we develop new computational tools in combination with experimental approaches in order to integrate and predict how individual cell behaviors dynamically give rise to physiological and pathological tissue-level adaptations. Leveraging the versatility and adaptability of agent-based modeling, we have simulated structural adaptations of large and small blood vessels, skeletal muscle regeneration following injury, and immune cell trafficking and differentiation during inflammation and infection. Our studies have suggested new mechanistic hypotheses and provided guidance for the design of novel therapies.

Up-close and personal with drug delivery: the medical imaging-informed hybrid models of micro-pharmacodynamics

Tumor heterogeneity—either genetic, phenotypic, metabolic or mechanical–is believed to constitute a barrier against effective chemotherapeutic treatments, and may facilitate the development of anti-cancer drug resistance. However, typical pharmacological studies relay on compartmental well-mixed models and neglect temporal and spatial variability in properties of both the tumor and its microenvironment. We will present a novel in silico model microPK/PD of drug pharmacokinetics and pharmacodynamics on the microscopic cell-to-tissue scale that allows to track drug efficacy within the tissue on the level of individual cells. We use a palette of medical imaging techniques: immunohistochemical staining, bright filed microscopy and confocal fluorescent imaging, to inform and calibrate our models. In particular, we take into account the properties of tumor cells, cell colonies and tumor microenvironment that together allow us to examine drug intratumoral distribution in the in silico-reconstructed tumor organoids. We will discuss how such a modeling approach can be used to build a predictor of tumor chemoresistance based on clinical biopsies routinely collected for cancer diagnosis. The use of data from individual patients’ tumors hold promise for designing personalized treatments.

Quantitative Methods for High-Throughput Live Cell Imaging

Building on recent advances in computer vision and machine learning we are now in the position to monitor complex biological environments and events in the same way are analysing natural scenes. While challenges remain, algorithms for cell segmentation and tracking have matured significantly and can now be used in more routine high-throughput settings. Improved microscopy and imaging platforms not only allow us to image subcellular events at high spatial and temporal resolution, we can now image large tissue sections and capture how various different proteins modulate the cellular microenvironment. Enabled by advances in cell culturing technologies 3D cultures can restore specific biochemical and morphological features that are similar to their in vivo counterparts. This holds the potential for improving relevance of in vitro studies, improving our ability to predict what occurs in vivo.


We are now working towards establishing the spatial and temporal context for biological events and processes. Quantitative image analysis methods are necessary for monitoring the tissue formation process and enabling longer duration time-lapse imaging. The talk will highlight opportunities of interfacing imaging with mathematical modelling. One such example will be the modelling of cellular behaviour. Our current research focuses on analysing cellular viability, the interaction of epithelial cell populations and the evolution of organoid cell cultures.

Hybrid Multiscale modelling for the design of a virtual tumour

The design of a patient-specific virtual tumour is an important step towards personalized medicine since the virtual tumour can be used to define the most adapted and efficient treatment protocol. However this requires to capture the description of many key events of tumour development, including angiogenesis, matrix remodelling, hypoxia, cell heterogeneity that will all influence the tumour growth kinetics and degree of tumour invasiveness. To that end, an integrated hybrid and multiscale approach has been developed based on data acquired on a preclinical mouse model as a proof of concept.


Fluorescence imaging is exploited to build case-specific virtual tumours and to validate their spatiotemporal evolution. The validity of the model will be discussed as well as its potential to identify the best therapeutic strategy for each individual tumour case.

Tumour Microcirculation, Vascular Targeting and Biomarkers: insight from pre-clinical models

Since clinical approval in 2004 of the vascular endothelial growth factor (VEGFA) blocking antibody, bevacizumab (Avastin), for treatment of colorectal cancer, a substantial number of additional anti-angiogenic compounds are now available for cancer treatment. Although these compounds are primarily targeted against the angiogenic process itself, they undoubtedly have additional effects on already established tumour blood vessels. In addition, a number of so-called tumour vascular disrupting agents (VDAs), which are specifically designed to target established tumour blood vessels, are in clinical trials. Despite this success, resistance to treatment is a major problem, with lack of predictive biomarkers to select those patients most likely to benefit from vascular targeted treatments a major limitation and biomarkers of response technically challenging.


VEGFA exists as multiple isoforms generated through alternative splicing and proteolysis. Recent retrospective analyses of data from several large phase III clinical trials have found an association between high concentrations of soluble VEGFA isoforms in plasma and poor prognosis, but also improved response to bevacizumab, making them potential predictive biomarkers. Using mouse fibrosarcoma cells genetically modified to express single isoforms of VEGFA, we have investigated the role of individual VEGFA isoforms in tumour vascularisation, patterning and function, metastasis and response to VEGFA pathway inhibitors and VDAs. Notably, soluble VEGFA-120 was associated with increased metastasis to the lung and a good response to the anti-VEGFA blocking antibody, B20-4.1.1. (the mouse equivalent of bevacizumab). Expression of VEGFA-120 was associated with highly permeable and dilated blood vessels in the primary tumour and a modified extracellular matrix, which could account for the increased metastasis. Analytical methods for measuring vascular and metabolic parameters in intravital microscopy and magnetic resonance imaging/spectroscopy (MRI/MRS) of tumours will be discussed.

Cellular behaviours underlying tissue dynamics during primitive streak formation in the chick embryo

Gastrulation involves embryo wide tissue reorganizations and deformations driven by coordinated cell shape changes and rearrangements. Using a dedicated lightsheet microscope we are able to follow over 200.000 cells in the early embryo. We show that the large scale tissue deformations resulting in the formation the primitive streak in the chick embryo are driven by anisotropic pulling forces. These forces are generated by local cell shape changes and cell rearrangements of mesendoderm cells. These cell rearrangements are mediated by sequential, directional contraction of aligned apical junctions in neighboring cells. These processes are driven contraction of apical acto-myosin II cables. We will discuss our attempts to analyse and model how these cell shape changes and intercalations can self-organise on the tissue scale to result in the formation of the primitive streak.

Heterogeneous quiescence exit displays a memory of preceding cell cycle position and division

The reactivation of quiescent cells upon growth stimulation is critical to tissue repair and homeostasis. The quiescence-exit process is highly noisy even for genetically identical cells under the same environmental conditions; underlying reasons for this quiescence-exit heterogeneity are poorly understood. Here, by modelling and experimentally measuring and perturbing the distribution of a population of quiescent cells in their responses to growth signals, we found that quiescent cells display a memory of their preceding cell cycle positions and division histories. We further show that the deterministic positional memory of quiescent cells, coupled with the stochastic dynamics of an Rb-E2F bistable switch, jointly and quantitatively defines the heterogeneous exit from cellular quiescence.

Posters

Image-based quantification and computational predictions of optimized imaging agent delivery to pancreatic tumors expressing TLR2

The current therapies continuously fail to provide successful results for pancreatic adenocarcinoma, one of the most deadly cancers with only 6% overall 5-year survival rate. The improvement of techniques for early detection, predicting of treatment efficacy and monitoring of tumor spread during and after surgical procedures remain under focused research. By combining an intravital fluorescence microscopy with computational modeling we developed a novel method to assess behavior (diffusion and binding) of imaging agents targeted to pancreatic cancer cells. Our long-standing goal is to provide a prospective tool for the prediction of optimized delivery of targeted agents based on individual patient data.

In addition to an important role toll-like receptor 2 (TLR2) plays in the immune system response, our team reported that TLR2 is a bona fide cell-surface marker for targeting pancreatic cancer. TLR2 recognizes a vast number of biomolecules, including lipoproteins, such as a novel TLR2 ligand designed in our laboratory (TLR2L). Recent development of an intravital fluorescence microscopy method allowed for the real time in vivo imaging of the TLR2L conjugated to near-infrared fluorescent dye, Cyanine 5 (TLR2L-Cy5) and its penetration through the tissue of pancreatic adenocarcinoma tumor xenografts in mice with endogenous expression of TLR2. In order to quantify the space- and time-dependent dynamics of TLR2L we combined intravital dorsal window chamber experiments with computational modeling of TLR2L-Cy5 diffusion and internalization following intravenous administration. Our computational model accounts for explicitly defined tissue morphology composed of individual tumor cells, extracellular matrix interpenetrated by the interstitial fluid, and tumor vasculature. We also model individual molecules of a fluorescent imaging agent that extravasate via influx from blood capillaries, spread through the tumor and become internalized by the cells.

Microscopic level computer simulations allowed for detailed assessment of targeted imaging agent extravasation, interstitial diffusion and intracellular accumulation on the cell-to-tissue level in virtual tumor tissue architecture. Results revealed a non-uniform spatial saturation of the TLR2L-Cy5 on the plasma membrane and inside the cell. We further extended the model to account for the effects of heterogeneity in nanoparticles diffusion and binding affinity and identified the cross-dependence between diffusive properties of targeted agents and their affinity to receptors. Results revealed that agents of distinct affinities could reach similar efficacies of binding to cells. Moreover, we identified the optimized dose-response protocols appropriate for any targeted agent with a priori known physical and biochemical properties. After extending the model for different agent delivery schemes we also showed that the time of extravasation plays an important role in ligand kinetics and distribution within tissue. In addition to improvement in drug delivery schemes, our model predicts which biochemical and physical properties of targeted agents could be tuned for the maximum effect in patient-specific extracellular matrix environments, tumor topologies and receptor expression levels.

We present an interdisciplinary approach to quantify diffusion and cellular uptake of an imaging agent targeted to pancreatic cancer cell lines expressing the TLR2 receptor. This integrated approach can be used in the future for the development of other targeted imaging and therapeutic agents, for other solid tumors, and for optimizing the administration schedules and time points for data collection from individual human tumor xenografts in order to improve treatment efficacy.

Hybrid multi-scale modelling of angiogenesis

Development of an adequate and efficient network of microvessels throughout tissues is a prerequisite for normal growth and maintenance of normal function. Abnormalities in vascular structure play a central role in numerous pathologies. In particular, the aberrant structure of tumor microcirculation causes regions of tissue hypoxia that interfere with the action of treatments by radiation and chemotherapy. The total number of vessel segments in the human body is more than 10. Clearly, therefore, the structure of the microcirculation is not specified by genetic information down to the level of individual vessels. Instead, the observed structures of microvessel networks represent the outcome of a set of generic behaviors exhibited by individual cells in vessel walls, responding to the stimuli that they experience, which result in angiogenesis, structural remodeling and pruning of vessels. We have developed hybrid multiscale models to investigate these behaviors. In these models, network structure is explicitly represented as a set of discrete nodes and segments, whose lengths and diameters evolve with time according to the assumed underlying cellular responses. The concentrations of oxygen and growth factors in the surrounding tissue are governed by continuous reaction-diffusion equations, which are solved numerically using a Green’s function approach. Examples of the application of the models in two and three dimensions are presented. The models provide insight into the key mechanisms needed to generate functional network structures. For instance, it is found that upstream conducted responses, propagated along vessel walls, play an essential role. If conducted responses are reduced, flow is diverted from long to short flow pathways. This may be a major cause of poor perfusion in vascularized solid tumors.

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Mechanically-coupled Reaction-Diffusion model of Glioma Growth
Philippe Buchler

Brain tumours represent a rare but serious medical condition. With an incidence of six cases per 100000, gliomas are the most frequent primary brain tumours in adults, accounting for 70% of cases. Gliomas are classified into four grades by increas

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A mathematical model of the Hippo growth control pathway in developing tissues
Hans Othmer

The Hippo pathway, which is a central pathway in the control of cell proliferation and apoptosis in Drosophila and mammalian cells, contains a core kinase mechanism that affects control of the cell cycle and growth. Studies involving over- a

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From single models to community advances: open source codes and data standards
Paul Macklin

Problems in tissue engineering, developmental biology, cancer, and related areas require that we study 3-D multicellular systems, coupling dynamics at many scales such as protein signaling, cell phenotype "decisions," biotransport,

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Coupled multiscale modeling and pathway analysis for prediction of drug efficacy in cystic kidney diseases
James Glazier

Extensive research has uncovered many genetic changes associated with autosomal dominant polycystic kidney disease (ADPKD) and effects of ADPKD mutations on signaling pathways. However, we still do not know the precise sequence of events tha

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Agent-based modeling of cells in tissues to understand and predict disease
Shayn Peirce-Cottler

The most prevalent, devastating, and complex diseases of our time, such as diabetes, cardiovascular disease, and infectious diseases, result from the interactions of heterogeneous cells with one another and with their environment. However, t

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Quantitative Methods for High-Throughput Live Cell Imaging
Jens Rittscher

Building on recent advances in computer vision and machine learning we are now in the position to monitor complex biological environments and events in the same way are analysing natural scenes. While challenges remain, algorithms for cell s

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Tumour Microcirculation, Vascular Targeting and Biomarkers: insight from pre-clinical models
Gillian Tozer

Since clinical approval in 2004 of the vascular endothelial growth factor (VEGFA) blocking antibody, bevacizumab (Avastin), for treatment of colorectal cancer, a substantial number of additional anti-angiogenic compounds are now available fo

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Model for the early development of meristems
Rafael Barrio

Stem cells are identical in many scales, they share the same molecular composition, DNA, genes and genetic networks, yet they should acquire di?erent properties to form a functional tissue. Therefore, they must interact and get some external

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The impact of collecting data at varying temporal resolution on parameter inference for biological transport models
Jonathan Harrison

When collecting time series data of biological transport processes, it is necessary to observe the system at discrete time points, for example via an imaging experiment. This can introduce errors when the motion is approximated with discrete

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Endre Somogyi