[Mathematical and computational methods to model chemotherapy- induced resistance]. / Matematikai és számítógépes módszerek a kemoterápiás kezelések során kialakuló rezisztencia modellezésére.

Chemotherapy plays an important role in the treatment of cancer. While clinical chemotherapy protocols can lead to remission in some patients, in many cases tumor progression occurs despite continued treatment. In the present study we summarize mathematical approaches to model tumor growth and response to treatment, focusing on anticancer therapy resistance. We present results obtained at the recently founded Cybermedical Competence Center at Óbuda University, focusing on the development of a new therapy optimization concept that aims to optimize traditional chemotherapy.

Two main mutational processes operate in the absence of DNA mismatch repair.

The analysis of tumour genome sequences has demonstrated high rates of base substitution mutagenesis upon the inactivation of DNA mismatch repair (MMR), and the resulting somatic mutations in MMR deficient tumours appear to significantly enhance the response to immune therapy. A handful of different algorithmically derived base substitution mutation signatures have been attributed to MMR deficiency in tumour somatic mutation datasets. In contrast, mutation data obtained from whole genome sequences of isogenic wild type and MMR deficient cell lines in this study, as well as from published sources, show a more uniform experimental mutation spectrum of MMR deficiency. In order to resolve this discrepancy, we reanalysed mutation data from MMR deficient tumour whole exome and whole genome sequences. We derived two base substitution signatures using non-negative matrix factorisation, which together adequately describe mutagenesis in all tumour and cell line samples. The two new signatures broadly resemble COSMIC signatures 6 and 20, but perform better than existing COSMIC signatures at identifying MMR deficient tumours in mutation signature deconstruction. We show that the contribution of the two identified signatures, one of which is dominated by C to T mutations at CpG sites, is biased by the different sequence composition of the exome and the whole genome. We further show that the identity of the inactivated MMR gene, the tissue type, the mutational burden or the patient's age does not influence the mutation spectrum, but that a tendency for a greater contribution by the CpG mutational process is observed in tumours as compared to cultured cells. Our analysis suggest that two separable mutational processes operate in the genomes of MMR deficient cells.

Identifying new topoisomerase II poison scaffolds by combining publicly available toxicity data and 2D/3D-based virtual screening.

Molecular descriptor (2D) and three dimensional (3D) shape based similarity methods are widely used in ligand based virtual drug design. In the present study pairwise structure comparisons among a set of 4858 DTP compounds tested in the NCI60 tumor cell line anticancer drug screen were computed using chemical hashed fingerprints and 3D molecule shapes to calculate 2D and 3D similarities, respectively. Additionally, pairwise biological activity similarities were calculated by correlating the 60 element vectors of pGI50 values corresponding to the cytotoxicity of the compounds across the NCI60 panel. Subsequently, we compared the power of 2D and 3D structural similarity metrics to predict the toxicity pattern of compounds. We found that while the positive predictive value and sensitivity of 3D and molecular descriptor based approaches to predict biological activity are similar, a subset of molecule pairs yielded contradictory results. By simultaneously requiring similarity of biological activities and 3D shapes, and dissimilarity of molecular descriptor based comparisons, we identify pairs of scaffold hopping candidates displaying characteristic core structural changes such as heteroatom/heterocycle change and ring closure. Attempts to discover scaffold hopping candidates of mitoxantrone recovered known Topoisomerase II (Top2) inhibitors, and also predicted new, previously unknown chemotypes possessing in vitro Top2 inhibitory activity.

Shotgun Lipidomic Profiling of the NCI60 Cell Line Panel Using Rapid Evaporative Ionization Mass Spectrometry.

Rapid evaporative ionization mass spectrometry (REIMS) was used for the rapid mass spectrometric profiling of cancer cell lines. Spectral reproducibility was assessed for three different cell lines, and the extent of interclass differences and intraclass variance was found to allow the identification of these cell lines based on the REIMS data. Subsequently, the NCI60 cell line panel was subjected to REIMS analysis, and the resulting data set was investigated for its distinction of individual cell lines and different tissue types of origin. Information content of REIMS spectral profiles of cell lines were found to be similar to those obtained from mammalian tissues although pronounced differences in relative lipid intensity were observed. Ultimately, REIMS was shown to detect changes in lipid content of cell lines due to mycoplasma infection. The data show that REIMS is an attractive means to study cell lines involving minimal sample preparation and analysis times in the range of seconds.

Design, synthesis and biological evaluation of thiosemicarbazones, hydrazinobenzothiazoles and arylhydrazones as anticancer agents with a potential to overcome multidrug resistance.

There is a constant need for new therapies against multidrug resistant (MDR) cancer. An attractive strategy is to develop chelators that display significant antitumor activity in multidrug resistant cancer cell lines overexpressing the drug efflux pump P-glycoprotein. In this study we used a panel of sensitive and MDR cancer cell lines to evaluate the toxicity of picolinylidene and salicylidene thiosemicarbazone, arylhydrazone, as well as picolinylidene and salicylidene hydrazino-benzothiazole derivatives. Our results confirm the collateral sensitivity of MDR cells to isatin-ß-thiosemicarbazones, and identify several chelator scaffolds with a potential to overcome multidrug resistance. Analysis of structure-activity-relationships within the investigated compound library indicates that NNS and NNN donor chelators show superior toxicity as compared to ONS derivatives regardless of the resistance status of the cells.

Boolean modelling reveals new regulatory connections between transcription factors orchestrating the development of the ventral spinal cord.

We have assembled a network of cell-fate determining transcription factors that play a key role in the specification of the ventral neuronal subtypes of the spinal cord on the basis of published transcriptional interactions. Asynchronous Boolean modelling of the network was used to compare simulation results with reported experimental observations. Such comparison highlighted the need to include additional regulatory connections in order to obtain the fixed point attractors of the model associated with the five known progenitor cell types located in the ventral spinal cord. The revised gene regulatory network reproduced previously observed cell state switches between progenitor cells observed in knock-out animal models or in experiments where the transcription factors were overexpressed. Furthermore the network predicted the inhibition of Irx3 by Nkx2.2 and this prediction was tested experimentally. Our results provide evidence for the existence of an as yet undescribed inhibitory connection which could potentially have significance beyond the ventral spinal cord. The work presented in this paper demonstrates the strength of Boolean modelling for identifying gene regulatory networks.

Buckling as an origin of ordered cuticular patterns in flower petals.

The optical properties of plant surfaces are strongly determined by the shape of epidermal cells and by the patterning of the cuticle on top of the cells. Combinations of particular cell shapes with particular nanoscale structures can generate a wide range of optical effects. Perhaps most notably, the development of ordered ridges of cuticle on top of flat petal cells can produce diffraction-grating-like structures. A diffraction grating is one of a number of mechanisms known to produce 'structural colours', which are more intense and pure than chemical colours and can appear iridescent. We explore the concept that mechanical buckling of the cuticle on the petal epidermis might explain the formation of cuticular ridges, using a theoretical model that accounts for the development of compressive stresses in the cuticle arising from competition between anisotropic expansion of epidermal cells and isotropic cuticle production. Model predictions rationalize cuticle patterns, including those with long-range order having the potential to generate iridescence, for a range of different flower species.

Early gene regulation of osteogenesis in embryonic stem cells.

The early gene regulatory networks (GRNs) that mediate stem cell differentiation are complex, and the underlying regulatory associations can be difficult to map accurately. In this study, the expression profiles of the genes Dlx5, Msx2 and Runx2 in mouse embryonic stem cells were monitored over a 48 hour period after exposure to the growth factors BMP2 and TGFß1. Candidate GRNs of early osteogenesis were constructed based on published experimental findings and simulation results of Boolean and ordinary differential equation models were compared with our experimental data in order to test the validity of these models. Three gene regulatory networks were found to be consistent with the data, one of these networks exhibited sustained oscillation, a behaviour which is consistent with the general view of embryonic stem cell plasticity. The work cycle presented in this paper illustrates how mathematical modelling can be used to elucidate from gene expression profiles GRNs that are consistent with experimental data.

Time scale and dimension analysis of a budding yeast cell cycle model.

BACKGROUND: The progress through the eukaryotic cell division cycle is driven by an underlying molecular regulatory network. Cell cycle progression can be considered as a series of irreversible transitions from one steady state to another in the correct order. Although this view has been put forward some time ago, it has not been quantitatively proven yet. Bifurcation analysis of a model for the budding yeast cell cycle has identified only two different steady states (one for G1 and one for mitosis) using cell mass as a bifurcation parameter. By analyzing the same model, using different methods of dynamical systems theory, we provide evidence for transitions among several different steady states during the budding yeast cell cycle. RESULTS: By calculating the eigenvalues of the Jacobian of kinetic differential equations we have determined the stability of the cell cycle trajectories of the Chen model. Based on the sign of the real part of the eigenvalues, the cell cycle can be divided into excitation and relaxation periods. During an excitation period, the cell cycle control system leaves a formerly stable steady state and, accordingly, excitation periods can be associated with irreversible cell cycle transitions like START, entry into mitosis and exit from mitosis. During relaxation periods, the control system asymptotically approaches the new steady state. We also show that the dynamical dimension of the Chen's model fluctuates by increasing during excitation periods followed by decrease during relaxation periods. In each relaxation period the dynamical dimension of the model drops to one, indicating a period where kinetic processes are in steady state and all concentration changes are driven by the increase of cytoplasmic growth. CONCLUSION: We apply two numerical methods, which have not been used to analyze biological control systems. These methods are more sensitive than the bifurcation analysis used before because they identify those transitions between steady states that are not controlled by a bifurcation parameter (e.g. cell mass). Therefore by applying these tools for a cell cycle control model, we provide a deeper understanding of the dynamical transitions in the underlying molecular network.