Polymyositis is an inflammatory myopathy characterized by muscle invasion of T-cells penetrating the basal lamina and displacing the plasma membrane of normal muscle fibers. This investigation presents a technology for the direct mapping of protein networks involved in T-cell invasion in situ. Simultaneous localization of 17 adhesive cell surface receptors reveals 18 different combinatorial expression patterns (CEP), which are unique for the T-cell invasion process in muscle tissue. Each invasion step can be assigned to specific CEP on the surface of individual T-cells. This indicates, that the T-cell invasion is enciphered combinatorially in the T-cells' adhesive cell surface proteome fraction. Given 217 possible combinations, the T-cell appears to have at its disposal a highly non-random restricted repertoire to specify migratory pathways at the cell surface. These higher-level order functions in the cellular proteome cannot be detected by large-scale protein profiling techniques from tissue homogenates. High-throughput whole cell mapping machines working on structurally intact tissues, as shown here, will allow to measure how cells of different origin (immune cells, tumor cells) combine cell surface receptors to encipher specificity and selectivity for interactions.

Walter Schubert

Polymyositis, Topological Proteomics Technology and Paradigm for Cell Invasion Dynamics

This paper deals with the modeling of the immune response to the evolution of the progression of endothelial cells which have lost the differentiation and start their evolution towards metastatic states. The modeling is developed in the framework of the so-called kinetic cellular theory. The model is critically analyzed on the basis of analytic solutions, asymptotic behaviors and numerical simulations that illustrate the scenarios predicted by the model. Finally, possible developments and generalizations that could describe other known phenomena are pointed out.

D. Ambrosi

N. Bellomo

L. Preziosi

Modelling Tumor Progression, Heterogeneity, and Immune Competition

In this paper a mathematical model that describes macrophage infiltration into avascular tumours is presented. The qualitative accuracy of the model is assessed by comparing numerical results with independent experimental data that describe the infiltration of macrophages into two types of spheroids: chemoattractant-producing (hepa-1) and chemoattractant-deficient (or C4) spheroids. A combination of analytical and numerical techniques are used to show how the infiltration pattern depends on the motility mechanisms involved (i.e. random motion and chemotaxis) and to explain the observed differences in macrophage infiltration into the hepa-1 and C4 spheroids. Model predictions are generated to show how the spheroid's size and spatial structure and the ability of its constituent cells influence macrophage infiltration. For example, chemoattractant-producing spheroids are shown to recruit larger numbers of macrophages than chemoattractant-deficient spheroids of the same size and spatial structure. The biological implications of these results are also discussed briefly.

C. E. Kelly

R. D. Leek

H. M. Byrne

S. M. Cox

A. L. Harris

C. E. Lewis

Modelling Macrophage Infiltration into Avascular Tumours

A neural cell detection system (NCDS) for the automatic quantitation of fluorescent lymphocytes in tissue sections was used to analyze CD26 expression in muscle-invasive T-cells. CD26 is a cell surface dipeptidyl-peptidase IV (DPP IV) involved in co-stimulatory activation of T-cells and also in adhesive events. The NCDS system acquires visual knowledge from a set of training cell image patches selected by a user. The trained system evaluates an image in 2 min calculating (i) the number, (ii) the positions and (iii) the phenotypes of the fluorescent cells. In the present study we have used the NCDS to identity DPP IV (CD26) expressing invasive lymphocytes in sarcoid myopathy and to analyze the associated cell surface phenotypes. We find highly unusual phenotypes characterized by differential combination of seven cell surface receptors usually involved in co-stimulatory events in T-lymphocytes. The data support a differential adhesive rather than a co-stimulatory role of CD26 in muscle-invasive cells. The adaptability of the NCDS algorithm to diverse types of cells should enable us to approach any invasion process, including invasion of malignant cells.

W. Schubert

M. Friedenberger

R. Haars

M. Bode

L. Philipsen

T. Nattkemper

H. Ritter

Automatic Recognition of Muscle-Invasive T-Lymphocytes Expressing Dipeptidyl-Peptidase IV (CD26) and Analysis of the Associated Cell Surface Phenotypes

Mark Chaplain

Special Issue on &#8220;Mathematical Modelling and Simulation of Aspects of Cancer Growth&#8221;

This paper reviews a number of the mathematical models used in cancer modelling and then chooses a specific cancer, breast carcinoma, to illustrate how the modelling can be used in aiding detection. We then discuss mathematical models that underpin mammographic image analysis, which complements models of tumour growth and facilitates diagnosis and treatment of cancer. Mammographic images are notoriously difficult to interpret, and we give an overview of the primary image enhancement technologies that have been introduced, before focusing on a more detailed description of some of our own recent work on the use of physics-based modelling in mammography. This theoretical approach to image analysis yields a wealth of information that could be incorporated into the mathematical models, and we conclude by describing how current mathematical models might be enhanced by use of this information, and how these models in turn will help to meet some of the major challenges in cancer detection.

D. J. Gavaghan

J. M. Brady

C. P. Behrenbruch

R. P. Highnam

P. K. Maini

Breast Cancer: Modelling and Detection

Marchuk&#39;s model of a general immune reaction is presented in the paper. The results of investigation of the model are summarized. The qualitative behaviour of solutions to the model and its simplification is described. Many illustrations of recovery process, oscillations or lethal outcomes of a disease are shown. The model with time-dependent immune reactivity is also considered. Periodic dynamics caused by different reasons are compared.In the last section adaptation of the model to tumour&#8211;immune interactions is proposed. The role of interleukins in immune processes is taken into account to adapt Marchuk&#39;s model to tumour growth dynamics. Possible immunotherapy is also considered in the proposed model. Some preliminary analysis of the model is presented.

Urszula Fory&#347;

Marchuk&#39;s Model of Immune System Dynamics with Application to Tumour Growth

In this paper, a model of cellular tumor dynamics in competition with the immune system is proposed. The characteristic scale of the phenomenon is the cellular one and the model is developed with probabilistic methods analogous to those of the kinetic theory. The interacting individuals are the cells of the populations involved in the competition between the tumor and the immune system. Interactions can change the activation state of the tumor and cause tumor proliferation or destruction. The model is expressed in terms of a bi-linear system of integro-differential equations. Some preliminary mathematical analysis of the model as well as computational simulations are presented.

Luisa Arlotti

Andrea Gamba

Miroslaw Lachowicz

A Kinetic Model of Tumor/Immune System Cellular Interactions

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Computational and Mathematical Methods in Medicine

Mathematical Modelling and Simulation of Aspects of Cancer Growth