Date : 7/01/09

Laboratory
IMNC (Imaging and Modeling for Neurobiology and Oncology)
Paris 7/Paris 11 Universities/CNRS; UMR 8165
IMNC Laboratory
15 rue Georges Clémenceau
Bat 104
91406 Orsay Cedex
France
Director : Yves Charon

PhD Supervisor
Basile Grammaticos
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co-supervisor : Mathilde Badoual
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phone : + 33 1 69 15 72 01

Subjects / Tools-Methodologies
1. Modeling migrating cancerous cell that / numerical simulations, cellular automata
2. Statistical analysis of histological slices from h / image processing, statistical analysis
3. Related problems of statistical physics / mean field approximation, EDP...

Summary of lab's interests

The laboratory IMNC at the Orsay Campus, near Paris, offers a stimulating interdisciplinary environment, where physicists and biologists work together on common projects.
The research activity of the laboratory is composed of three main axes: the study of the cerebral metabolism (neurobiology), the design of per-operative imagers for cancer (oncology) and modeling biological systems (dynamic systems, statistical physics, oncology etc).

Summary of project

Background: Cell migration is a phenomenon that occurs in normal processes such as development, wound healing, immune responseÖ but happens equally in pathologies such as cancer. We are interested in modeling tumoral cell migration, in the case of specific brain tumors, high-grade gliomas [1,2]. The ability of cancerous cells to detach from the main tumor mass and to invade the normal surrounding tissue make these tumors very dangerous and leads to a very bad prognosis for the patients.

During migration, tumor cells interact strongly (mechanically and chemically) with their environment, i.e. with the substrate, with other tumor cells as well as with normal cells.

Modeling these biological processes will hopefully help to understand the complex mechanisms of tumor growth and could also lead to clinical applications in a long term. For example, it could help to predict the evolution of a tumor, or to plan treatments.

Pioneer modeling works have already highlighted the fact that the visible part of a glioma on a clinical imaging examination represents only the emerged part of the iceberg: the density of invading cells is too low to appear on a MRI exam, but these migrating cells make recurrence after surgery very common [3], hence contributing to the poor outcome of patients with this pathology.

The objective of this training period and of the PhD thesis that will follow is to establish a model of migrating cancerous cell that interact with their environment, and to compare the results with experimental data (from in vitro experiments) or clinical data. In addition, the candidate will have the possibility to participate to the experiments and/or to address problems of statistical physics.

We are working in collaboration with biologists that provide in vitro experimental data, and with clinicians for histological data.

With the biology team \"Physiopathologie de la communication et de la diffÈrenciation cellulaire\", directed by Marc Mesnil in the Institut de Physiologie et Biologie Cellulaires UMR 6187 (Poitiers University), we will build a model of cell migration in two and three dimensions, on various substrates such as collagen or brain slices. Subsequently, we should be able to integrate in our model the angiogenesis process (emergence of newly created blood vessels to supply the tumor with oxygen and glucose).

The second part of the thesis will be devoted to the clinical modeling of tumor growth. In collaboration with Sainte-Anne Hospital (Paris), we wish to perform a statistical analysis of histological slices from highly invasive tumors (oligodendroglioma): search for spatial correlations of cancerous cells, or between cancerous and normal cells or blood vesselsÖ This should allow a better understanding of the organization of these pathological tissues. Ideally, a model for the evolution of these tumors towards malignancy shall be proposed.
This modeling work will naturally lead to study problems of statistical physics, for example, the collective behavior of complex systems that are out of equilibrium and/or with frozen disorder. The candidate will have the opportunity to learn or to improve his knowledge of the following techniques: numerical simulations, cellular automata, manipulation and numerical resolution of partial derivative equations, image processing (cell counting, statistical analysis of correlations), systems of interacting particles, mean field approximation, analytical perturbative methods.

The candidate will have the opportunity to participate to experiments of cellular biology if he/she wishes to.

Refs: [1] Aubert M, Badoual M, FÈreol S, Christov C, Grammaticos B, 2006, A cellular automaton model for the migration of glioma cells, Phys. Biol. 3, 93-100.
[2] Aubert M, Badoual M, Christov C and Grammaticos B, 2008, A model for glioma cell migration on collagen and astrocytes, J. R. Soc. Interface 5, 75-83.
[3] http://www.pathology.washington.edu/research/labs/labpage.php?LAB=swanson