An in silico platform for the study of epithelial pre-invasive neoplastic development

Quantification of large scale DNA organization for predicting prostate cancer recurrence

This study investigates whether Genomic Organization at Large Scales (which we propose to call GOALS) as quantified via nuclear phenotype characteristics and cell sociology features (describing cell organization within tissue) collected from prostate tissue microarrays (TMAs) can separate biochemical failure from biochemical nonevidence of disease (BNED) after radical prostatectomy (RP). Of the 78 prostate cancer tissue cores collected from patients treated with RP, 16 who developed biochemical relapse (failure group) and 16 who were BNED patients (nonfailure group) were included in the analyses (36 cores from 32 patients). A section from this TMA was stained stoichiometrically for DNA using the Feulgen-Thionin methodology, and scanned with a Pannoramic MIDI scanner. Approximately 110 nuclear phenotypic features, predominately quantifying large scale DNA organization (GOALS), were extracted from each segmented nuclei. In addition, the centers of these segmented nuclei defined a Voronoi tessellation and subsequent architectural analysis. Prostate TMA core classification as biochemical failure or BNED after RP using GOALS features was conducted (a) based on cell type and cell position within the epithelium (all cells, all epithelial cells, epithelial >2 cell layers away from basement membrane) from all cores, and (b) based on epithelial cells more than two cell layers from the basement membrane using a Classifier trained on Gleason 6, 8, 9 (16 cores) only and applied to a Test set consisting of the Gleason 7 cores (20 cores). Successful core classification as biochemical failure or BNED after RP by a linear classifier was 75% using all cells, 83% using all epithelial cells, and 86% using epithelial >2 layers. Overall success of predicted classification by the linear Classifier of (b) was 87.5% using the Training Set and 80% using the Test Set. Overall success of predicted progression using Gleason score alone was 75% for Gleason >7 as failures and 69% for Gleason >6 as failures. © 2017 International Society for Advancement of Cytometry.

Virtual cell imaging: A review on simulation methods employed in image cytometry

The simulations of cells and microscope images thereof have been used to facilitate the development, selection, and validation of image analysis algorithms employed in cytometry as well as for modeling and understanding cell structure and dynamics beyond what is visible in the eyepiece. The simulation approaches vary from simple parametric models of specific cell components-especially shapes of cells and cell nuclei-to learning-based synthesis and multi-stage simulation models for complex scenes that simultaneously visualize multiple object types and incorporate various properties of the imaged objects and laws of image formation. This review covers advances in artificial digital cell generation at scales ranging from particles up to tissue synthesis and microscope image simulation methods, provides examples of the use of simulated images for various purposes ranging from subcellular object detection to cell tracking, and discusses how such simulators have been validated. Finally, the future possibilities and limitations of simulation-based validation are considered. © 2016 International Society for Advancement of Cytometry.

Discrete Element Framework for Modelling Extracellular Matrix, Deformable Cells and Subcellular Components

This paper presents a framework for modelling biological tissues based on discrete particles. Cell components (e.g. cell membranes, cell cytoskeleton, cell nucleus) and extracellular matrix (e.g. collagen) are represented using collections of particles. Simple particle to particle interaction laws are used to simulate and control complex physical interaction types (e.g. cell-cell adhesion via cadherins, integrin basement membrane attachment, cytoskeletal mechanical properties). Particles may be given the capacity to change their properties and behaviours in response to changes in the cellular microenvironment (e.g., in response to cell-cell signalling or mechanical loadings). Each particle is in effect an ‘agent’, meaning that the agent can sense local environmental information and respond according to pre-determined or stochastic events. The behaviour of the proposed framework is exemplified through several biological problems of ongoing interest. These examples illustrate how the modelling framework allows enormous flexibility for representing the mechanical behaviour of different tissues, and we argue this is a more intuitive approach than perhaps offered by traditional continuum methods. Because of this flexibility, we believe the discrete modelling framework provides an avenue for biologists and bioengineers to explore the behaviour of tissue systems in a computational laboratory.

Modelling is an important tool in understanding the behaviour of biological tissues. In this paper we advocate a new modelling framework in which cells and tissues are represented by a collection of particles with associated properties. The particles interact with each other and can change their behaviour in response to changes in their environment. We demonstrate how the propose framework can be used to represent the mechanical behaviour of different tissues with much greater flexibility as compared to traditional continuum based methods.

Geometrical and topological analysis of in vivo confocal microscopy images reveals dynamic maturation of epidermal structures during the first years of life

Reflectance confocal microscopy is successfully used in infant skin research. Infant skin structure, function, and composition are undergoing a maturation process. We aimed to uncover how the epidermal architecture and cellular topology change with time. Images were collected from three age groups of healthy infants between one and four years of age and adults. Cell centers were manually identified on the images at the stratum granulosum (SG) and stratum spinosum (SS) levels. Voronoi diagrams were used to calculate geometrical and topological parameters. Infant cell density is higher than that of adults and decreases with age. Projected cell area, cell perimeter, and average distance to the nearest neighbors increase with age but do so distinctly between the two layers. Structural entropy is different between the two strata, but remains constant with time. For all ages and layers, the distribution of the number of nearest neighbors is typical of a cooperator network architecture. The topological analysis provides evidence of the maturation process in infant skin. The differences between infant and adult are more pronounced in the SG than SS, while cell cooperation is evident in all cases of healthy skin examined.

Neuroblastoma after childhood: prognostic relevance of segmental chromosome aberrations, ATRX protein status, and immune cell infiltration

Neuroblastoma (NB) is a common malignancy in children but rarely occurs during adolescence or adulthood. This subgroup is characterized by an indolent disease course, almost uniformly fatal, yet little is known about the biologic characteristics. The aim of this study was to identify differential features regarding DNA copy number alterations, α-thalassemia/mental retardation syndrome X-linked (ATRX) protein expression, and the presence of tumor-associated inflammatory cells. Thirty-one NB patients older than 10 years who were included in the Spanish NB Registry were considered for the current study; seven young and middle-aged adult patients (range 18-60 years) formed part of the cohort. We performed single nucleotide polymorphism arrays, immunohistochemistry for immune markers (CD4, CD8, CD20, CD11b, CD11c, and CD68), and ATRX protein expression. Assorted genetic profiles were found with a predominant presence of a segmental chromosome aberration (SCA) profile. Preadolescent and adolescent NB tumors showed a higher number of SCA, including 17q gain and 11q deletion. There was also a marked infiltration of immune cells, mainly high and heterogeneous, in young and middle-aged adult tumors. ATRX negative expression was present in the tumors. The characteristics of preadolescent, adolescent, young adult, and middle-aged adult NB tumors are different, not only from childhood NB tumors but also from each other. Similar examinations of a larger number of such tumor tissues from cooperative groups should lead to a better older age–dependent tumor pattern and to innovative, individual risk-adapted therapeutic approaches for these patients.

Biotensegrity of the extracellular matrix: physiology, dynamic mechanical balance, and implications in oncology and mechanotherapy

Cells have the capacity to convert mechanical stimuli into chemical changes. This process is based on the tensegrity principle, a mechanism of tensional integrity. To date, this principle has been demonstrated to act in physiological processes such as mechanotransduction and mechanosensing at different scales (from cell sensing through integrins to molecular mechanical interventions or even localized massage). The process involves intra- and extracellular components, including the participation of extracellular matrix (ECM) and microtubules that act as compression structures, and actin filaments which act as tension structures. The nucleus itself has its own tensegrity system which is implicated in cell proliferation, differentiation, and apoptosis. Despite present advances, only the tip of the iceberg has so far been uncovered regarding the role of ECM compounds in influencing biotensegrity in pathological processes. Groups of cells, together with the surrounding ground substance, are subject to different and specific forces that certainly influence biological processes. In this paper, we review the current knowledge on the role of ECM elements in determining biotensegrity in malignant processes and describe their implication in therapeutic response, resistance to chemo- and radiotherapy, and subsequent tumor progression. Original data based on the study of neuroblastic tumors will be provided.

Cooperation and competition in the dynamics of tissue architecture during homeostasis and tumorigenesis

The construction of a network of cell-to-cell contacts makes it possible to characterize the patterns and spatial organization of tissues. Such networks are highly dynamic, depending on the changes of the tissue architecture caused by cell division, death and migration. Local competitive and cooperative cell-to-cell interactions influence the choices cells make. We review the literature on quantitative data of epithelial tissue topology and present a dynamical network model that can be used to explore the evolutionary dynamics of a two dimensional tissue architecture with arbitrary cell-to-cell interactions. In particular, we show that various forms of experimentally observed types of interactions can be modelled using game theory. We discuss a model of cooperative and non-cooperative cell-to-cell communication that can capture the interplay between cellular competition and tissue dynamics. We conclude with an outlook on the possible uses of this approach in modelling tumorigenesis and tissue homeostasis.