In Silico implementation of evolutionary paradigm in therapy design: Towards anti-cancer therapy as Darwinian process.

In here presented in silico study we suggest a way how to implement the evolutionary principles into anti-cancer therapy design. We hypothesize that instead of its ongoing supervised adaptation, the therapy may be constructed as a self-sustaining evolutionary process in a dynamic fitness landscape established implicitly by evolving cancer cells, microenvironment and the therapy itself. For these purposes, we replace a unified therapy with the 'therapy species', which is a population of heterogeneous elementary therapies, and propose a way how to turn the toxicity of the elementary therapy into its fitness in a way conforming to evolutionary causation. As a result, not only the therapies govern the evolution of different cell phenotypes, but the cells' resistances govern the evolution of the therapies as well. We illustrate the approach by the minimalistic ad hoc evolutionary model. Its results indicate that the resistant cells could bias the evolution towards more toxic elementary therapies by inhibiting the less toxic ones. As the evolutionary causation of cancer drug resistance has been intensively studied for a few decades, we refer to cancer as a special case to illustrate purely theoretical analysis.

A new conceptual framework for the therapy by optimized multidimensional pulses of therapeutic activity. The case of multiple myeloma model.

We developed simulation methodology to assess eventual therapeutic efficiency of exogenous multiparametric changes in a four-component cellular system described by the system of ordinary differential equations. The method is numerically implemented to simulate the temporal behavior of a cellular system of multiple myeloma cells. The problem is conceived as an inverse optimization task where the alternative temporal changes of selected parameters of the ordinary differential equations represent candidate solutions and the objective function quantifies the goals of the therapy. The system under study consists of two main cellular components, tumor cells and their cellular environment, respectively. The subset of model parameters closely related to the environment is substituted by exogenous time dependencies - therapeutic pulses combining continuous functions and discrete parameters subordinated thereafter to the optimization. Synergistic interaction of temporal parametric changes has been observed and quantified whereby two or more dynamic parameters show effects that absent if either parameter is stimulated alone. We expect that the theoretical insight into unstable tumor growth provided by the sensitivity and optimization studies could, eventually, help in designing combination therapies.

Optimization aspects of carcinogenesis.

Any process in which competing solutions replicate with errors and numbers of their copies depend on their respective fitnesses is the evolutionary optimization process. As during carcinogenesis mutated genomes replicate according to their respective qualities, carcinogenesis obviously qualifies as the evolutionary optimization process and conforms to common mathematical basis. The optimization view accents statistical nature of carcinogenesis proposing that during it the crucial role is actually played by the allocation of trials. Optimal allocation of trials requires reliable schemas' fitnesses estimations which necessitate appropriate, fitness landscape dependent, statistics of population. In the spirit of the applied conceptual framework, features which are known to decrease efficiency of any evolutionary optimization procedure (or inhibit it completely) are anticipated as "therapies" and reviewed. Strict adherence to the evolutionary optimization framework leads us to some counterintuitive implications which are, however, in agreement with recent experimental findings, such as sometimes observed more aggressive and malignant growth of therapy surviving cancer cells.

Monomer dynamics in single- and double-stranded DNA coils.

In our paper (Tothova et al., Czech. J. Phys. 55, 221 (2005)), the first observation of the kinetics of individual polymer monomers using the fluorescence correlation technique (R. Shusterman et al., Phys. Rev. Lett. 92, 048303 (2004)) has been interpreted within the bead-spring theory. Optimizing the joint Rouse-Zimm model to the experimental data, the phenomenological parameters for the statistical-mechanical description of the universal behavior of double- and single-stranded DNA and the dominant types of their dynamics have been determined. Recently, these data have been corrected (R. Shusterman et al., Phys. Rev. Lett. 98, 029901 (2007)). In the present work, the fits of the theory to the new data are given. The main conclusions of our preceding paper remain unchanged but some of the polymer parameters have changed. The new data allow a significantly better agreement with the theory than the previous ones. Our calculations confirm that dsDNA follows mainly the classical Zimm-type kinetics rather than the Rouse one as it was proposed by Shusterman et al. Single-stranded DNA also behaves predominantly as the Zimm polymer. To support these conclusions, we analyze the draining effects on the monomer dynamics and the applicability of simple "universal" laws, according to which the monomer mean square displacement scales with the time as t 1/2 and t 2/3 for the Rouse and Zimm polymers, respectively.

Interpretation of static and dynamic neutron and light scattering from microemulsion droplets: effects of shape fluctuations

The theory of static and dynamic scattering of neutrons and light on microemulsion droplets is developed. The droplets are modeled by double-layered fluid spheres immersed in another fluid. The surface layer of arbitrary thickness thermally fluctuates in the shape. The scattering functions are consistently calculated up to the second order of the fluctuations. The bulk fluids and the layer are characterized by different scattering length densities (or dielectric constants). Involving the Helfrich's concept of interfacial elasticity, the theory is applied for the description of small-angle neutron scattering (SANS), neutron spin echo (NSE), and dynamic light scattering (DLS) experiments on dilute microemulsions. From the fits to the experimental data the bending elasticity and the Gaussian modulus are extracted. Due to the corrected account for the fluctuations, their values differ markedly from those obtained in the original works. The theory well describes the SANS experiments. In the case of DLS, we had to assume the shell of the solvent molecules to be built of several layers. Previous theories were in a sharp disagreement with the NSE experiments. A better agreement with these experiments is obtained if the dissipation in the surface layer is included into the consideration. From the experiments, the viscosity of the layer is estimated for a concrete microemulsion system.

Internal DNA modes below 25 cm-1: a resonance Raman spectroscopy observation.

The first resonance Raman scattering observation of the low-frequency (LF) region (below 40 up to 12 cm-1) of DNA motions is presented. Since the concentration of the studied DNA solution was very low (1 mg/ml), the spectra features reflect internal vibrations of the macromolecule. The decomposition of the spectra into Lorentzians clearly indicate three intrahelical DNA modes: the corresponding peaks are located at the frequencies 16, 19, and 23 (+/- 1) cm-1. This result is in agreement with our quasi-continuity model of the LF B-form DNA dynamics (V. Lisy, P. Miskovsky and P. Schreiber, J. Biomol. Struct. Dyn. 13, 707 (1996)). The fit of the experimental frequencies to the theory, using the Genetic Algorithms approach, allowed us to make some conclusions about the model force constants which could be found by independent conformational energy calculations. Possible positions of five lowest-frequency DNA peaks, predicted by the model, are discussed.