Efficient protocols to control glioma growth

In this paper we consider a mathematical model to describe glioma evolution. The model is established combining the viscoelastic behaviour of the brain tissue with a mass conservation law that takes into account the effect of chemotherapy. For the non Fickian model we establish an upper bound for the tumor mass that leads to a sufficient condition to control tumor growth. Based on the theoretical upper bound, protocol for chemotherapy treatment are proposed. Numerical experiments are included to illustrate the behaviour of the model as well as the efficiency of the presented protocols

Computer simulation of glioma growth and morphology

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion

The role of stiffness in the proliferation of brain tumors

In this paper we present a mathematical model to describe the evolution of glioma cells taking into account the viscoelastic properties of brain tissue. A theoretical stability analysis gives information to design protocols which efficiency is illustrated by a number of numerical simulations

Focus on the Physics of Cancer

Despite the spectacular achievements of molecular biology in the second half of the twentieth century and the crucial advances it permitted in cancer research, the fight against cancer has brought some disillusions. It is nowadays more and more apparent that getting a global picture of the very diverse and interlinked aspects of cancer development necessitates, in synergy with these achievements, other perspectives and investigating tools. In this undertaking, multidisciplinary approaches that include quantitative sciences in general and physics in particular play a crucial role. This `focus on' collection contains 19 articles representative of the diversity and state-of-the-art of the contributions that physics can bring to the field of cancer research.Comment: Invited editorial review for the `Focus on the Physics of Cancer' published by the New journal of Physics in 2011--201

Emergent Properties of Tumor Microenvironment in a Real-life Model of Multicell Tumor Spheroids

Multicellular tumor spheroids are an important {\it in vitro} model of the pre-vascular phase of solid tumors, for sizes well below the diagnostic limit: therefore a biophysical model of spheroids has the ability to shed light on the internal workings and organization of tumors at a critical phase of their development. To this end, we have developed a computer program that integrates the behavior of individual cells and their interactions with other cells and the surrounding environment. It is based on a quantitative description of metabolism, growth, proliferation and death of single tumor cells, and on equations that model biochemical and mechanical cell-cell and cell-environment interactions. The program reproduces existing experimental data on spheroids, and yields unique views of their microenvironment. Simulations show complex internal flows and motions of nutrients, metabolites and cells, that are otherwise unobservable with current experimental techniques, and give novel clues on tumor development and strong hints for future therapies.Comment: 20 pages, 10 figures. Accepted for publication in PLOS One. The published version contains links to a supplementary text and three video file

Registration of brain tumor images using hyper-elastic regularization

In this paper, we present a method to estimate a deformation field between two instances of a brain volume having tumor. The novelties include the assessment of the disease progress by observing the healthy tissue deformation and usage of the Neo-Hookean strain energy density model as a regularizer in deformable registration framework. Implementations on synthetic and patient data provide promising results, which might have relevant use in clinical problems

In silico estimates of the free energy rates in growing tumor spheroids

The physics of solid tumor growth can be considered at three distinct size scales: the tumor scale, the cell-extracellular matrix (ECM) scale and the sub-cellular scale. In this paper we consider the tumor scale in the interest of eventually developing a system-level understanding of the progression of cancer. At this scale, cell populations and chemical species are best treated as concentration fields that vary with time and space. The cells have chemo-mechanical interactions with each other and with the ECM, consume glucose and oxygen that are transported through the tumor, and create chemical byproducts. We present a continuum mathematical model for the biochemical dynamics and mechanics that govern tumor growth. The biochemical dynamics and mechanics also engender free energy changes that serve as universal measures for comparison of these processes. Within our mathematical framework we therefore consider the free energy inequality, which arises from the first and second laws of thermodynamics. With the model we compute preliminary estimates of the free energy rates of a growing tumor in its pre-vascular stage by using currently available data from single cells and multicellular tumor spheroids.Comment: 27 pages with 5 figures and 2 tables. Figures and tables appear at the end of the pape

Recursive Least Squares Filtering Algorithms for On-Line Viscoelastic Characterization of Biosamples

The mechanical characterization of biological samples is a fundamental issue in biology and related fields, such as tissue and cell mechanics, regenerative medicine and diagnosis of diseases. In this paper, a novel approach for the identification of the stiffness and damping coefficients of biosamples is introduced. According to the proposed method, a MEMS-based microgripper in operational condition is used as a measurement tool. The mechanical model describing the dynamics of the gripper-sample system considers the pseudo-rigid body model for the microgripper, and the Kelvin–Voigt constitutive law of viscoelasticity for the sample. Then, two algorithms based on recursive least square (RLS) methods are implemented for the estimation of the mechanical coefficients, that are the forgetting factor based RLS and the normalised gradient based RLS algorithms. Numerical simulations are performed to verify the effectiveness of the proposed approach. Results confirm the feasibility of the method that enables the ability to perform simultaneously two tasks: sample manipulation and parameters identification

A SYNTHETIC HUMAN BRAIN ECM HYDROGEL FOR TIGHT CONTROL OF ASTROCYTE ACTIVATION

Bioengineers have aimed to design instructive extracellular matrix (ECM) models that can tailor the protein composition and biomechanics of the brain in vitro in order to study how astrocytes remodel the brain during trauma and inflammation. However, these parameters cannot be independently controlled in protein-based models, and although tunable in synthetic systems, current astrocyte cultures fail to retain their characteristic stellate morphology without becoming activated. To this date, there is no biomaterial model that can retain astrocyte quiescence in vitro. This dissertation sought to develop such an in vitro model that would enable the study of specific ECM factors that control astrocyte activation while retaining quiescent astrocytes in vitro. Here we introduce a synthetic hydrogel, that for the first time shows maintenance of astrocyte quiescence and control over activation on demand. We first characterized the human brain ECM via proteomics, and the brain biomechanics via needle-induced cavitation rheology and volume-controlled cavity expansion and incorporated the top ECM components responsible for integrin-mediated and MMP-mediated degradation alongside matched mechanical properties into a fully synthetic hydrogel. Using this hydrogel, composed of just PEG and peptides, we demonstrate control over astrocyte activation via tuning of the integrin-binding and MMP-degradable profile or via cytokine molecules, in contrast to other protein-based models like collagen where astrocytes remain in a reactive state. Finally, to aid with the implementation of biomaterials as in vitro platforms to predict in vivo physiology, the correlation between current 2D, 3D and in vivo studies of glioblastoma motility was explored, and how an effect size can help standardize comparison across labs and culture dimensions. An additional study highlighted the importance of adopting growth rate in drug metric responses and how these can be implemented in current biomaterial platforms. Overall, this work can help integrate biomaterials as models to predict in vivo physiology. This brain hydrogel system can be used as a new platform to model the physiological state of quiescent astrocytes and their reactivity upon injury, for the first time, in vitro

Engineering PNIPAAm Biomaterial Scaffolds to Model Microenvironmental Regulation of Glioblastoma Stem-Like Cells

abstract: Following diagnosis of a glioblastoma (GBM) brain tumor, surgical resection, chemotherapy and radiation together yield a median patient survival of only 15 months. Importantly, standard treatments fail to address the dynamic regulation of the brain tumor microenvironment that actively supports tumor progression and treatment resistance. Moreover, specialized niches within the tumor microenvironment maintain a population of highly malignant glioblastoma stem-like cells (GSCs). GSCs are resistant to traditional chemotherapy and radiation therapy and are likely responsible for near universal rates of tumor recurrence and associated morbidity. Thus, disrupting microenvironmental support for GSCs could be critical to more effective GBM therapies. Three-dimensional (3D) culture models of the tumor microenvironment are powerful tools for identifying key biochemical and biophysical inputs that may support or inhibit malignant behaviors. Here, we developed synthetic poly(N-isopropylacrylamide-co-Jeffamine M-1000® acrylamide) or PNJ copolymers as a model 3D system for culturing GBM cell lines and low-passage patient-derived GSCs in vitro. These temperature responsive scaffolds reversibly transition from soluble to insoluble in aqueous solution by heating from room temperature to body temperature, thereby enabling easy encapsulation and release of cells in a 3D scaffold. We also designed this system with the capacity for presenting the cell-adhesion peptide sequence RGD for adherent culture conditions. Using this system, we identified conditions that promoted GBM proliferation, invasion, GSC phenotypes, and radiation resistance. In particular, using two separate patient-derived GSC models, we observed that PNJ scaffolds regulated self-renewal, provided protection from radiation induced cell death, and may promote stem cell plasticity in response to radiation. Furthermore, PNJ scaffolds produced de novo activation of the transcription factor HIF2α, which is critical to GSC tumorigenicity and stem plasticity. All together, these studies establish the robust utility of PNJ biomaterials as in vitro models for studying microenvironmental regulation of GSC behaviors and treatment resistance.Dissertation/ThesisDoctoral Dissertation Biomedical Engineering 201