Publications in Journals


R.H. Chisholm, T. Lorenzi, A. Lorz, A. Larsen, L. Almeida, A. Escargueil, J. Clairambault,
Emergence of drug tolerance in cancer cell populations: an evolutionary outcome of selection, nongenetic instability and stressinduced adaptation  Submitted
In recent experiments on isogenetic cancer cell lines, it was observed that exposure to high doses of anticancer drugs can induce the emergence of a subpopulation of lessproliferative, drugtolerant cells, that display markers associated with cancer stem cells. After a period of time, some of the surviving stemlike cells were observed to change their phenotype to resume normal proliferation, and eventually repopulate the sample. Interestingly, these evolutionary dynamics were shown to be the result of epigenetic modifications, rather than genetic mutations. We propose a theoretical mechanism for the transient emergence of such drug tolerance, that might be a mandatory intermediate state towards established drug resistance. We formulate both an individualbased model and an integrodifferential equation model of phenotypic evolution in a cell population exposed to cytotoxic drugs. The outcomes of both models suggest that, on intermediate time scales, selection, nongenetic instability, stressinduced adaptation and the interplay between these mechanisms can push an actively proliferating cell population to transition into a lessproliferative and drugtolerant state. Hence, the cell population experiences much less stress in the presence of the drugs and, in the long run, reacquires a proliferative phenotype, due to selection pressure and phenotypic fluctuations. These results provide a possible evolutionary explanation for the experimental results presented by Sharma and coworkers. Furthermore, our results highlight how the transient appearance of the lessproliferative and drugtolerant cells is strictly related to the usage of high doses of cytotoxic drugs. Finally, we show how stemlike characteristics can act to stabilise the transient, less proliferative and drugtolerant subpopulation for a longer period of time.

A. Lorz, T. Lorenzi, J. Clairambault, A. Escargueil, B. Perthame,
Modeling the effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in solid tumors  Accepted in Bulletin of Mathematical Biology 
preprint Histopathological evidence supports the idea that the emergence of phenotypic heterogeneity and resistance to cytotoxic drugs can be considered as a process of adaptation, or evolution, in tumor cell populations. In this framework, can we explain intratumor heterogeneity in terms of cell adaptation to local conditions? How do anticancer therapies affect the outcome of cell competition for nutrients within solid tumors? Can we overcome the emergence of resistance and favor the eradication of cancer cells by using combination therapies? Bearing these questions in mind, we develop a model describing cell dynamics inside a tumor spheroid under the effects of cytotoxic and cytostatic drugs. Cancer cells are assumed to be structured as a population by two real variables standing for space position and the expression level of a cytotoxic resistant phenotype. The model takes explicitly into account the dynamics of resources and anticancer drugs as well as their interactions with the cell population under treatment. We analyze the effects of space structure and combination therapies on phenotypic heterogeneity and chemotherapeutic resistance. Furthermore, we study the efficacy of combined therapy protocols based on constant infusion and/or bangbang delivery of cytotoxic and cytostatic drugs.

A. Lorz, and B. Perthame,
Longterm behaviour of phenotypically structured models  Proceedings of the Royal Society A, Vol. 470, no. 2167, 2014 
published version 
preprint Phenotypically structured equations arise in population biology to describe the interaction of species with their environment that brings the nutrients. This interaction usually leads to the selection of the fittest individuals. Models used in this area are highly nonlinear, and the question of long term behaviour is usually not solved. However, there is a particular class of models for which convergence to an Evolutionary Stable Distribution is proved, namely when the quasistatic assumption is made. This means that the environment, and thus the nutrient supply, reacts immediately to the population dynamics. One possible proof is based on a Total Variation bound for the appropriate quantity.
We extend this proof to cases where the nutrient is regenerated gradually. A simple example is the chemostat with a rendering factor, then our result does not use any smallness assumption. For a more general setting, we can treat the case with a fast equilibration of the nutrient concentration.

A. Lorz, P. Markowich, B. Perthame,
Bernoulli variational problem and beyond  Archive for Rational Mechanics and Analysis, Vol. 212, 2014, pp. 415443 
published version 
preprint The question of 'cutting the tail' of the solution of an elliptic equation arises naturally in several contexts and leads to a singular perturbation problem under the form of a strong cutoff. We consider both the PDE with a drift and the symmetric case where a variational problem can be stated.
It is known that, in both cases, the same critical scale arises for the size of the singular perturbation. More interesting is that in both cases another critical parameter (of order one) arises that decides when the limiting behaviour is nondegenerate. We study both theoretically and numerically the values of this critical parameter and, in the symmetric case, ask if the variational solution leads to the same value as for the maximal solution of the PDE. Finally we propose a weak formulation of the limiting Bernoulli problem which incorporates both Dirichlet and Neumann boundary condition.

T. Lorenzi, A. Lorz, G. Restori,
Asymptotic Dynamics in Populations Structured by Sensitivity to Global Warming and Habitat Shrinking  Acta Applicandae Mathematicae, Vol. 131, 2014, pp. 4967 
published version How to recast effects of habitat shrinking and global warming on evolutionary dynamics into continuous mutation/selection models?
Bearing this question in mind, we consider differential equations for structured populations, which include mutation, proliferation and competition for resources.
Since mutations are assumed to be small and to occur on a longer time scale than proliferation, a parameter $\varepsilon$ is introduced to model the ratio between these time scales as well as the average size of mutations. A wellposedness result is proposed and the asymptotic behavior of the density of individuals is studied in the limit $\varepsilon \rightarrow 0$. In particular, we prove the weak convergence of the density to a sum of Dirac masses and characterize the related concentration points. Moreover, we provide numerical simulations illustrating the theorems and showing
an interesting sample of solutions depending on parameters and initial data.

F. Thomas, D. Fisher, P. Fort, J.P. Marie, S. Daoust, B. Roche, C. Grunau, C. Cosseau, G. Mitta, S. Baghdiguian, F. Rousset, P. Lassus, E. Assenat, D. Grégoire, D. Missé, A. Lorz, F. Billy, W. Vainchenker, F. Delhommeau, S. Koscielny, R. Itzykson, R. Tang, F. Fava, A. Ballesta, T. Lepoutre, L. Krasinska, V. Dulic, P. Raynaud, P. Blache, C. QuittauPrevostel, E. Vignal, H. Trauchessec, B. Perthame, J. Clairambault, V. Volpert, E. Solary, U. Hibner, M. E. Hochberg,
Applying ecological and evolutionary theory to cancer: a long and winding road  Evolutionary Applications, Vol. 6, 2013, pp. 110 
published version Since the mid 1970s, cancer has been described as a process of Darwinian evolution, with somatic cellular selection and evolution being the fundamental processes leading to malignancy and its many manifestations (neoangiogenesis, evasion of the immune system, metastasis, and resistance to therapies). Historically, little attention has been placed on applications of evolutionary biology to understanding and controlling neoplastic progression and to prevent therapeutic failures. This is now beginning to change, and there is a growing international interest in the interface between cancer and evolutionary biology. The objective of this introduction is first to describe the basic ideas and concepts linking evolutionary biology to cancer. We then present four major fronts where the evolutionary perspective is most developed, namely laboratory and clinical models, mathematical models, databases, and techniques and assays. Finally, we discuss several of the most promising challenges and future prospects in this interdisciplinary research direction in the war against cancer.

A. Lorz, T. Lorenzi, M. E. Hochberg, J. Clairambault, B. Perthame,
Populational adaptive evolution, chemotherapeutic resistance and multiple anticancer therapies  ESAIM: Mathematical Modelling and Numerical Analysis, Vol. 47, 2013, pp. 377399 
published version 
preprint Resistance to chemotherapies, particularly to anticancer treatments, is an increasing medical concern. Among the many mechanisms at work in cancers, one of the most important is the selection of tumor cells expressing resistance genes or phenotypes. Motivated by the theory of mutationselection in adaptive evolution, we propose a model based on a continuous variable that represents the expression level of a resistance gene (or genes, yielding a phenotype) influencing in healthy and tumor cells birth/death rates, effects of chemotherapies (both cytotoxic and cytostatic) and mutations. We extend previous work by demonstrating how qualitatively different actions of chemotherapeutic and cytostatic treatments may induce different levels of resistance.
The mathematical interest of our study is in the formalism of constrained HamiltonJacobi equations in the framework of viscosity solutions. We derive the longterm temporal dynamics of the fittest traits in the regime of small mutations. In the context of adaptive cancer management, we also analyse whether an optimal drug level is better than the maximal tolerated dose.

A. Chertock, K. Fellner, A. Kurganov, A. Lorz, P. Markowich,
Sinking, merging and stationary plumes in a coupled chemotaxisfluid model: a highresolution numerical approach  Journal of Fluid Mechanics, Vol. 694, 2012, pp. 155190 
published version 
preprint Aquatic bacteria like Bacillus subtilis are heavier than water yet they are able to swim up an oxygen gradient and concentrate in a
layer below the water surface, which will undergo RayleighTaylor type instabilities for sufficiently high concentrations.
In several articles, a simplified chemotaxisfluid system has been proposed as a model for modestly diluted cellsuspensions. It
couples a convective chemotaxis system for the oxygenconsuming and oxytactic bacteria with the incompressible NavierStokes equations
subject to a gravitational force proportional to the relative surplus of the celldensity compared to the waterdensity.
In this paper, we derive a highresolution vorticitybased hybrid finitevolume finitedifference scheme, which allows us to investigate the
nonlinear dynamics of a twodimensional chemotaxis fluid system with boundary conditions matching an experiment. We present
selected numerical examples, which illustrate (i) the formation of sinking plumes, (ii) the possible merging of neighbouring plumes and (iii)
the convergence towards numerically stable stationary plumes. The examples with stable stationary plumes show how the surfacedirected
oxytaxis continuously feeds cells into a highconcentration layer near the surface, from where the fluidflow (recurring upwards in the space
between the plumes) transports the cells into the plumes, where then gravity makes the cells sink and constitutes the driving force in
maintaining the fluidconvection and, thus, in shaping the plumes into (numerically) stable stationary states.


 A. Lorz, S. Mirrahimi, B. Perthame, Dirac mass dynamics in a multidimensional nonlocal parabolic equation  Communications in Partial Differential Equations, Vol. 36, 2011, pp. 10711098  published version  preprint
Nonlocal LotkaVolterra models have the property that solutions concentrate as Dirac masses in the limit of small diffusion. Is it possible to describe the dynamics of the limiting concentration points and of the weights of the Dirac masses? What is the long time asymptotics of these Dirac masses? Can several Dirac masses coexist?
We will explain how these questions relate to the socalled ''constrained HamiltonJacobi equation'' and how a form of canonical equation can be established. This equation has been established assuming smoothness. Here we build a framework where smooth solutions exist and thus the full theory can be developed rigorously. We also show that our form of canonical equation comes with a kind of Lyapunov functional.
Numerical simulations show that the trajectories can exhibit unexpected dynamics well explained by this equation.
Our motivation comes from population adaptive evolution a branch of mathematical ecology which models darwinian evolution.

M. Di Francesco, A. Lorz, P. Markowich,
Chemotaxis fluid coupled model for swimming bacteria with nonlinear diffusion: global existence and asymptotic behavior  Discrete and Continuous Dynamical Systems, Series A, Vol. 28, No. 4, 2010, pp. 14371453 
published version 
preprint We study a system
arising in the modelling of the motion of swimming bacteria under the effect of diffusion, oxygentaxis and transport through an incompressible fluid. The novelty with respect to previous papers in the literature lies in the presence of nonlinear porousmediumlike diffusion in the equation for the density $n$ of the bacteria, motivated by a finite size effect. We prove that, under the constraint $m\in(3/2, 2]$ for the adiabatic exponent, such system features global in time solutions in two space dimensions for large data. Moreover, in the case $m=2$ we prove that solutions converge to constant states in the largetime limit. The proofs rely on standard energy methods and on a basic entropy estimate which cannot be achieved in the case $m=1$. The case $m=2$ is very special as we can provide a Lyapounov functional. We generalize our results to the threedimensional case and obtain a smaller range of exponents $m\in(m^*,2]$ with $m^*>3/2$, due to the use of classical Sobolev inequalities.

R.J. Duan, A. Lorz, P. Markowich,
Global Solutions to the coupled chemotaxisfluid equations  Communications in Partial Differential Equations, Vol. 35, No. 9, 2010, pp. 16351673 
published version 
preprint In this paper, we are concerned with a model arising from biology,
which is a coupled system of the chemotaxis equations and the
viscous incompressible fluid equations through transport and
external forcing. The global existence of solutions to the Cauchy
problem is investigated under certain conditions. Precisely, for the
ChemotaxisNavierStokes system over three space dimensions, we
obtain global existence and rates of convergence on classical
solutions near constant states. When the fluid motion is described
by the simpler Stokes equations, we prove global existence of weak
solutions in two space dimensions for cell density with finite mass,
firstorder spatial moment and entropy provided that the external
forcing is weak or the substrate concentration is small.

Proceedings

F. Billy, J. Clairambault, O. Fercoq, T. Lorenzi, A. Lorz, B. Perthame,
Modelling targets for anticancer drug control optimization in physiologically structured cell population models  AIP Conference Proceedings, Vol. 1479, 2012, pp. 13231326 
published version The main two pitfalls of therapeutics in clinical oncology, that limit increasing drug doses, are unwanted toxic side effects on healthy cell populations and occurrence of resistance to drugs in cancer cell populations.
Depending on the constraint considered in the control problem at stake, toxicity or drug resistance, we present two different ways to model the evolution of proliferating cell populations, healthy and cancer, under the control of anticancer drugs.
In the first case, we use a McKendrick agestructured model of the cell cycle, whereas in the second case, we use a model of evolutionary dynamics, physiologically structured according to a continuous phenotype standing for drug resistance.
In both cases, we mention how drug targets may be chosen so as to accurately represent the effects of cytotoxic and of cytostatic drugs, separately, and how one may consider the problem of optimisation of combined therapies.

A. Decoene, A. Lorz, S. Martin. B. Maury, M. Tang, Simulation of selfpropelled chemotactic bacteria in a Stokes flow  ESAIM: Proceedings, Vol. 30, 2010, pp. 105124  published version  preprint
We present a method to simulate the motion of selfpropelled rigid particles in a twodimensional Stokesian fluid, taking into account chemotactic behaviour. Selfpropulsion is modelled as a point force associated to each particle, placed at a certain distance from its gravity centre. The method for solving the fluid flow and the motion of the bacteria is based on a variational formulation on the whole domain, including fluid and particles: rigid motion is enforced by penalizing the strain rate tensor on the rigid domain, while incompressibility is treated by duality. This leads to a minimization problem over unconstrained functional spaces which can be easily implemented from any finite element Stokes solver. In order to ensure robustness, a projection algorithm is used to deal with contacts between particles. The particles are meant to represent bacteria of the \emph{Escherichia coli} type, which interact with their chemical environment through consumption of nutrients and orientation in some favorable direction. Our model takes into account the interaction with oxygen. An advectiondiffusion equation on the oxygen concentration is solved in the fluid domain, with a source term accounting for oxygen consumption by the bacteria. In addition, selfpropulsion is deactivated for those particles which cannot consume enough oxygen. Finally, the model includes random changes in the orientation of the individual bacteria, with a frequency that depends on the surrounding oxygen concentration, in order to favor the direction of the concentration gradient and thus to reproduce chemotactic behaviour. Numerical simulations implemented with FreeFem++ are presented.