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As part of their progression from normal to malignant cells, human tumors acquire a marked genomic instability, which is likely due in part to the progressive shortening and transient loss of telomeres from chromosome ends. Loss of telomeres allows chromosomes to fuse end-to-end, triggering chromosome fusion-bridge-breakage cycles that lead to genome rearrangements, loss of heterozygosity, and gene amplification. Our objective was to study the initial steps in this process using site-specific double strand breaks (DSBs) adjacent to interstitial telomere sequence (ITS) and a color-based detection system on a specially engineered chromosome. Over the course of this grant we have determined the inherent instability of ITS, shown that a DSB on the chromosome can lead to the seeding of new telomeres, defined the orientation of the APRT gene on the chromosome, identified chromosome loss as a problem, redesigned the test chromosome to avoid chromosome loss, constructed a new targeting vector, prepared an appropriate recipient cell line, developed the color-based detection system, and created a cell line carrying the redesigned chromosome. Characterization of the new cell line will set the stage for many of the experiments proposed in the original application; we will pursue those studies with funding currently being requested from other sources.

This article is from Theoretical Biology & Medical Modelling , volume 9 . Abstract Background: The invasion-metastasis cascade of cancer involves a process of parallel progression. A biological interface (module) in which cells is linked with ECM (extracellular matrix) by CAMs (cell adhesion molecules) has been proposed as a tool for tracing cancer spatiotemporal dynamics. Methods: A mathematical model was established to simulate cancer cell migration. Human uterine leiomyoma specimens, in vitro cell migration assay, quantitative real-time PCR, western blotting, dynamic viscosity, and an in vivo C57BL6 mouse model were used to verify the predictive findings of our model. Results: The return to origin probability (RTOP) and its related CAM expression ratio in tumors, so-called "tumor self-seeding", gradually decreased with increased tumor size, and approached the 3D Pólya random walk constant (0.340537) in a periodic structure. The biphasic pattern of cancer cell migration revealed that cancer cells initially grew together and subsequently began spreading. A higher viscosity of fillers applied to the cancer surface was associated with a significantly greater inhibitory effect on cancer migration, in accordance with the Stokes-Einstein equation. Conclusion: The positional probability and cell-CAM-ECM interface (module) in the fractal framework helped us decipher cancer spatiotemporal dynamics; in addition we modeled the methods of cancer control by manipulating the microenvironment plasticity or inhibiting the CAM expression to the Pólya random walk, Pólya constant.

 Prey predator population dynamics has been frequently studied in literature to model many robust but contrastive biological populations. In this paper, based on prey predator population dynamics, a nonlinear model to predict the behavior of virus treatment of cancer cells is suggested. Based on the goals of virus curing and consideration of some practical issues, the suggested model has the capability to cover these following cases: both cancer cells and viruses vanish, one is eliminated by the other, or both survive in a robust periodically convergent manner or both become divergent. Relative to the values of some parameters such as the virus intrinsic growth rate, carrying capacity, capturing rate, half saturation constant, maximal tumor cells growth rate, and tumor cells mortality rate, and the initial population values of both tumor cells and viruses, some examples are solved. These examples exhibit logical and feasible behavior for the system. They show under which conditions the virus therapy fails or succeeds; as well when the bifurcation occurs or when the trajectories converge to a limit cycle.

This article is from eLife , volume 2 . Abstract In solid tumors, targeted treatments can lead to dramatic regressions, but responses are often short-lived because resistant cancer cells arise. The major strategy proposed for overcoming resistance is combination therapy. We present a mathematical model describing the evolutionary dynamics of lesions in response to treatment. We first studied 20 melanoma patients receiving vemurafenib. We then applied our model to an independent set of pancreatic, colorectal, and melanoma cancer patients with metastatic disease. We find that dual therapy results in long-term disease control for most patients, if there are no single mutations that cause cross-resistance to both drugs; in patients with large disease burden, triple therapy is needed. We also find that simultaneous therapy with two drugs is much more effective than sequential therapy. Our results provide realistic expectations for the efficacy of new drug combinations and inform the design of trials for new cancer therapeutics.DOI:http://dx.doi.org/10.7554/eLife.00747.001

Prey predator population dynamics has been frequently studied in literature to model many robust but contrastive biological populations. In this paper, based on prey predator population dynamics, a nonlinear model to predict the behavior of virus treatment of cancer cells is suggested. Based on the goals of virus curing and consideration of some practical issues, the suggested model has the capability to cover these following cases: both cancer cells and viruses vanish, one is eliminated by the other, or both survive in a robust periodically convergent manner or both become divergent. Relative to the values of some parameters such as the virus intrinsic growth rate, carrying capacity, capturing rate, half saturation constant, maximal tumor cells growth rate, and tumor cells mortality rate, and the initial population values of both tumor cells and viruses, some examples are solved. These examples exhibit logical and feasible behavior for the system. They show under which conditions the virus therapy fails or succeeds; as well when the bifurcation occurs or when the trajectories converge to a limit cycle.

Due to a prolonged contracting process in the purchase of our image analysis system and to an even longer and more involved contracting process that required extensive and technically demanding justification in the purchase of our flow cytometer/cell sorter, we have been delayed almost one year in initiating our studies of breast cancer cells. Breast Cancer

The objective of this USAMRMC training and researching project is: (1) to train the PI in the optics, biology and biochemistry fields towards a multi-disciplinary prostate cancer researcher; and (2) to understand and investigate the receptor target contrast agents and energy transfer from contrast agents to prostate cancer cells using ultrafast time-resolved spectroscopy.

Our long-term goal is to correlate the undesired escape from androgen deprivation therapy with specific molecular events in Androgen Receptor signaling in order to determine the best molecular targets for prostate cancer treatment. Studies supported by this grant indicate that the failure of tumors to respond to anti-androgen therapy corresponded best with an increased nuclear transport of AR. However, an intramolecular fold and AR dimerization, both activated abnormally by heterologous hormones (estrogen and progestin) and measured by fluorescence resonance energy transfer of CFP and YFP-tagged ARs), also was linked to four different AR mutants associated with treatment-refractory prostate proliferation. High throughput methods were developed to measure AR folding, dimerization and nuclear transport. These methods will facilitate the future identification of new drugs that block AR folding, dimerization and nuclear transport and that may prove useful in treatment-refractory therapy.

Stem cells have the potential to produce lineages of non-stem cell populations (differentiated cells) via a ubiquitous hierarchal division scheme. Differentiation of a stem cell into (partially) differentiated cells can happen either symmetrically or asymmetrically. The selection dynamics of a mutant cancer stem cell should be investigated in the light of a stem cell proliferation hierarchy and presence of a non-stem cell population. By constructing a three-compartment Moran-type model composed of normal stem cells, mutant (cancer) stem cells and differentiated cells, we derive the replicator dynamics of stem cell frequencies where asymmetric differentiation and differentiated cell death rates are included in the model. We determine how these new factors change the conditions for a successful mutant invasion and discuss the variation on the steady state fraction of the population as different model parameters are changed. By including the phenotypic plasticity/dedifferentiation, in which a progenitor/differentiated cell can transform back into a cancer stem cell, we show that the effective fitness of mutant stem cells is not only determined by their proliferation and death rates but also according to their dedifferentiation potential. By numerically solving the model we derive the phase diagram of the advantageous and disadvantageous phases of cancer stem cells in the space of proliferation and dedifferentiation potentials. The result shows that at high enough dedifferentiation rates even a previously disadvantageous mutant can take over the population of normal stem cells. This observation has implications in different areas of cancer research including experimental observations that imply metastatic cancer stem cell types might have lower proliferation potential than other stem cell phenotypes while showing much more phenotypic plasticity and can undergo clonal expansion.

Human tumors acquire a marked genomic instability as part of their progression from normal to malignant cells. This instability is likely due in part to the progressive shortening and transient loss of telomeres from chromosome ends. Loss of telomeres allows chromosomes to fuse end-to-end, triggering chromosome fusion- bridge-breakage cycles that lead to genome rearrangements, loss of heterozygosity, and gene amplification. The initial steps in chromosome fusion-bridge-breakage cycles are being studied by introducing site-specific double-strand breaks adjacent to interstitial telomere sequences in a marked region of specially engineered test chromosome, A modified gene for the Green Fluorescent Protein (GFP) is being constructed to permit detection of chromatid fusion, the first step in fusion-bridge-breakage cycles. By varying the length of the telomere sequence, we can measure the length of telomere sequence that is required to protect chromosome ends and prevent genomic instability in breast cancer cells. A test chromosome is being constructed using the APRT locus in CHO cells, which will permit a measure of the effects of telomere sequences on the frequencies of chromatid fusion and chromosome loss. After these initial studies we will transfer the engineered hamster chromosome by microcell fusion into human breast cancer cells at different tumor stages.

This article is from PLoS Computational Biology , volume 10 . Abstract Computational prediction of cancer associated SNPs from the large pool of SNP dataset is now being used as a tool for detecting the probable oncogenes, which are further examined in the wet lab experiments. The lack in prediction accuracy has been a major hurdle in relying on the computational results obtained by implementing multiple tools, platforms and algorithms for cancer associated SNP prediction. Our result obtained from the initial computational compilations suggests the strong chance of Aurora-A G325W mutation (rs11539196) to cause hepatocellular carcinoma. The implementation of molecular dynamics simulation (MDS) approaches has significantly aided in raising the prediction accuracy of these results, but measuring the difference in the convergence time of mutant protein structures has been a challenging task while setting the simulation timescale. The convergence time of most of the protein structures may vary from 10 ns to 100 ns or more, depending upon its size. Thus, in this work we have implemented 200 ns of MDS to aid the final results obtained from computational SNP prediction technique. The MDS results have significantly explained the atomic alteration related with the mutant protein and are useful in elaborating the change in structural conformations coupled with the computationally predicted cancer associated mutation. With further advancements in the computational techniques, it will become much easier to predict such mutations with higher accuracy level.

A recently proposed single progenitor cell model for skin cell proliferation [Clayton et al., Nature v446, 185 (2007)] is extended to incorporate homeostasis as a fixed point of the dynamics. Unlimited cell proliferation in such a model can be viewed as a paradigm for the onset of cancer. A novel way in which this can arise is if the homeostatic fixed point becomes metastable, so that the cell populations can escape from the homeostatic basin of attraction by a large but rare stochastic fluctuation. Such an event can be viewed as the final step in a multi-stage model of carcinogenesis. This offers a possible explanation for the peculiar epidemiology of lung cancer in ex-smokers.

Internalization by cells of macromolecular drugs and drug loaded nanoparticles can be most advantageous in overcoming several limitations in cancer prevention and treatment. These systems are generally considered to be impermeable to cell membranes. However, internalization has been observed to occur via endocytosis. Affinity for cell membrane and high uptake is improved by several mechanisms including increased hydrophobicity, presence of surface charge or presence of targeting moieties in macromolecules or on nanoparticles. Specific targeting of deranged epithelial cells in the breast with biodegradable, controlled drug release nanoparticle systems is an attractive approach to solving problems or prevention and treatment of breast cancer. In this study, we sought to demonstrate that nanoparticles coated with an epidermal growth factor (EGF) would be preferentially internalized in MCF-7 breast cancer cells. Optimal nanoparticle sizes ranging in size of 120 200 nm were obtained using acetone and polyvinyl alcohol (PVA). Freeze dried nanoparticles were readily re-suspendable. MCF-7 cells were incubated with EGF-coated and non-coated nanoparticles. Observation cells by confocal microscopy after incubation with coated and non-coated nanoparticles failed to reveal nanoparticle internalization by MCF-7 cells.

This article is from BMB reports , volume 45 . Abstract Tissue inhibitor of metalloproteinases (TIMPs; TIMP-1, -2, -3 and -4) are endogenous inhibitor for matrix metalloproteinases (MMPs) that are responsible for remodeling the extracellular matrix (ECM) and involved in migration, invasion and metastasis of tumor cells. Unlike under normal conditions, the imbalance between MMPs and TIMPs is associated with various diseased states. Among TIMPs, TIMP-1, a 184-residue protein, is the only N-linked glycoprotein with glycosylation sites at N30 and N78. The structural analysis of the catalytic domain of human stromelysin-1 (MMP-3) and human TIMP-1 suggests new possibilities of the role of TIMP-1 glycan moieties as a tuner for the proteolytic activities by MMPs. Because the TIMP-1 glycosylation participate in the interaction, aberrant glycosylation of TIMP-1 presumably affects the interaction, thereby leading to pathogenic dysfunction in cancer cells. TIMP-1 has not only the cell proliferation activities but also anti-oncogenic properties. Cancer cells appear to utilize these bilateral aspects of TIMP-1 for cancer progression; an elevated TIMP-1 level exerts to cancer development via MMP-independent pathway during the early phase of tumor formation, whereas it is the aberrant glycosylation of TIMP-1 that overcome the high anti-proteolytic burden. The aberrant glycosylation of TIMP-1 can thus be used as staging and/or prognostic biomarker in colon cancer. [BMB Reports 2012; 45(11): 623-628]

We investigate the catalytic reactions model used in cell modeling. The reaction kinetic is defined through the energies of different species of molecules following random independent distribution. The related statistical physics model has three phases and these three phases emerged in the dynamics: fast dynamics phase, slow dynamic phase and ultra-slow dynamic phase. The phenomenon we found is a rather general, does not depend on the details of the model. We assume as a hypothesis that the transition between these phases (glassiness degrees) is related to cancer. The imbalance in the rate of processes between key aspects of the cell (gene regulation, protein-protein interaction, metabolical networks) creates a change in the fine tuning between these key aspects, affects the logics of the cell and initiates cancer. It is probable that cancer is a change of phase resulting from increased and deregulated metabolic reactions.

The paradigm of phenotypic plasticity indicates reversible relations of different cancer cell phenotypes, which extends the cellular hierarchy proposed by the classical cancer stem cell (CSC) theory. Since it is still question able if the phenotypic plasticity is a crucial improvement to the hierarchical model or just a minor extension to it, it is worthwhile to explore the dynamic behavior characterizing the reversible phenotypic plasticity. In this study we compare the hierarchical model and the reversible model in predicting the cell-state dynamics observed in biological experiments. Our results show that the hierarchical model shows significant disadvantages over the reversible model in describing both long-term stability (phenotypic equilibrium) and short-term transient dynamics (overshoot) of cancer cells. In a very specific case in which the total growth of population due to each cell type is identical, the hierarchical model predicts neither phenotypic equilibrium nor overshoot, whereas thereversible model succeeds in predicting both of them. Even though the performance of the hierarchical model can be improved by relaxing the specific assumption, its prediction to the phenotypic equilibrium strongly depends on a precondition that may be unrealistic in biological experiments, and it also fails to capture the overshoot of CSCs. By comparison, it is more likely for the reversible model to correctly describe the stability of the phenotypic mixture and various types of overshoot behavior.

Gene transcription mediated by RNA polymerase II (pol-II) is a key step in gene expression. The dynamics of pol-II moving along the transcribed region influences the rate and timing of gene expression. In this work we present a probabilistic model of transcription dynamics which is fitted to pol-II occupancy time course data measured using ChIP-Seq. The model can be used to estimate transcription speed and to infer the temporal pol-II activity profile at the gene promoter. Model parameters are determined using either maximum likelihood estimation or via Bayesian inference using Markov chain Monte Carlo sampling. The Bayesian approach provides confidence intervals for parameter estimates and allows the use of priors that capture domain knowledge, e.g. the expected range of transcription speeds, based on previous experiments. The model describes the movement of pol-II down the gene body and can be used to identify the time of induction for transcriptionally engaged genes. By clustering the inferred promoter activity time profiles, we are able to determine which genes respond quickly to stimuli and group genes that share activity profiles and may therefore be co-regulated. We apply our methodology to biological data obtained using ChIP-seq to measure pol-II occupancy genome-wide when MCF-7 human breast cancer cells are treated with estradiol (E2). The transcription speeds we obtain agree with those obtained previously for smaller numbers of genes with the advantage that our approach can be applied genome-wide. We validate the biological significance of the pol-II promoter activity clusters by investigating cluster-specific transcription factor binding patterns and determining canonical pathway enrichment.

This article is from BMC Cancer , volume 13 . Abstract Background: Changes in cell shape and plasticity in cytoskeletal dynamics are critically involved in cell adhesion, migration, invasion and the overall process of metastasis. Previous work in our laboratory demonstrated that the synthetic steroid mifepristone inhibited the growth of highly metastatic cancer cells, while simultaneously causing striking changes in cellular morphology. Here we assessed whether such morphological alterations developed in response to cytostatic concentrations of mifepristone are reversible or permanent, involve rearrangement of cytoskeletal proteins, and/or affect the adhesive capacity of the cells. Methods: Cancer cell lines of the ovary (SKOV-3), breast (MDA-MB-231), prostate (LNCaP), and nervous system (U87MG) were exposed to cytostatic concentrations of mifepristone and studied by phase-contrast microscopy. The transient or permanent nature of the cytostasis and morphological changes caused by mifepristone was assessed, as well as the rearrangement of cytoskeletal proteins. De-adhesion and adhesion assays were utilized to determine if mifepristone-arrested and morphologically dysregulated cells had abnormal de-adhesion/adhesion dynamics when compared to vehicle-treated controls. Results: Mifepristone-treated cells displayed a long, thin, spindle-like shape with boundaries resembling those of loosely adhered cells. Growth arrest and morphology changes caused by mifepristone were reversible in SKOV-3, MDA-MB-231 and U87MG, but not in LNCaP cells that instead became senescent. All cancer cell types exposed to mifepristone displayed greatly increased actin ruffling in association with accelerated de-adhesion from the culture plate, and delayed adhesion capacity to various extracellular matrix components. Conclusions: Cytostatic concentrations of mifepristone induced alterations in the cellular structure of a panel of aggressive, highly metastatic cancer cells of different tissues of origin. Such changes were associated with re-distribution of actin fibers that mainly form non-adhesive membrane ruffles, leading to dysregulated cellular adhesion capacity.

The dynamics of invasion of cancer cells into the human body tissues and metastasis are the main causes of death in patients with cancer. This study deals with theoretical investigation of the dynamics of invasion of cancer cells for tumour growths in human body tissues using discretized Cahn-Hilliard, concentration and reaction-diffusion equations which were solved by Finite Difference Method with the aid of MATLAB computer software. A Crank-Nicolson numerical scheme was developed for the discretized model equations. The numerical result obtained was used to describe the dynamics of cancer invasion of tissues with respect to cancer cells density on tumour growth, turbulence and mobility, and the equilibrium between charge and discharge of cancer cells. The results of the study provide new insights into combating cancer disease by providing mitigating and intervention measures to this major health problem.

The purpose of this proposal was to investigate the response of prostate cancer to a series of camptothecin analogs, which are drugs that target DNA topoisomerase I. This final report summarizes the accomplishments toward the original goals of the project. We note that while some experimental problems were encountered that limited the completion of all tasks, good progress was made overall on the proposed research.

Estrogen plays a critical role in the development and progression of breast cancer. The biological activities of estrogen are mediated by estrogen receptors (ER). In addition, a large number of proteins termed cofactors are involved in ER signaling. Therapeutic agents, such as tamoxifen, also bind ER, but block proliferation in breast cells. However, tamoxifen increases the risk of endometrial cancer. We have used chromatin immunoprecipitation (ChIP) to investigate cofactor involvement in ER signaling in vivo and to understand the mechanisms underlying the different actions of tamoxifen in breast and endometrial cells. We have found that differences in cofactor expression underlie tissue-specific effects of tamoxifen. Chip, in combination with tiled arrays of individual chromosomes, has been used to identify distant ER-binding sequences that regulate gene expression. Gene expression profiling has been used to identify differential regulation of ER targets in breast and endometrial cells, and these targets have been evaluated for their ability to regulate cell proliferation. The detailed understanding of tissue and ligand-dependent changes in gene expression gained through these studies will lead to more effective therapies for ER-dependent breast cancer.

Estrogen plays a critical role in the development and progression of breast cancer. While endocrine therapies play an important part in breast cancer treatment, the failure of these therapies reflects a lack of knowledge concerning the molecular mechanisms involved in estrogen signaling. The biological activities of estrogen are mediated by estrogen receptors (ER) . In addition, a large number of proteins termed cofactors are involved in ER signaling. Until recently, our knowledge regarding these cofactors was based on their ability to bind receptors in vitro and affect transcriptional activation in transfection experiments. The in vivo role of these cofactors and the specific target genes involved in breast cancer are not well known. Therapeutic agents, such as tamoxifen, also bind ER, but block proliferation in breast cells. However, tamoxifen increases the risk of endometrial cancer. We have used chromatin immunoprecipitation (ChIP) to investigate cofactor involvement in ER signaling in vivo and to understand the mechanisms underlying the different actions of tamoxifen in breast and endometrial cells. We are in the process of using ChIP to identify the set of genes regulated by ER and its cofactors in these tissues. The detailed understanding of tissue- and ligand-dependent changes in gene expression gained through these studies will lead to more effective therapies for ER-dependent breast cancer.

In the present work we investigate the chemotactically and proteolytically driven tissue invasion by cancer cells. The model employed is a system of advection-reaction-diffusion equations that features the role of the serine protease urokinase-type plasminogen activator. The analytical and numerical study of this system constitutes a challenge due to the merging, emerging, and travelling concentrations that the solutions exhibit. Classical numerical methods applied to this system necessitate very fine discretization grids to resolve these dynamics in an accurate way. To reduce the computational cost without sacrificing the accuracy of the solution, we apply adaptive mesh refinement techniques, in particular h-refinement. Extended numerical experiments exhibit that this approach provides with a higher order, stable, and robust numerical method for this system. We elaborate on several mesh refinement criteria and compare the results with the ones in the literature. We prove, for a simpler version of this model, $L^\infty$ bounds for the solutions, we study the stability of its conditional steady states, and conclude that it can serve as a test case for further development of mesh refinement techniques for cancer invasion simulations.

Estrogen plays a critical role in the development and progression of breast cancer. While endocrine therapies play an important part in breast cancer treatment, the failure of these therapies reflects a lack of knowledge concerning the molecular mechanisms involved in estrogen signaling. The biological activities of estrogen are mediated by estrogen receptors (ER) . In addition, a large number of proteins termed cofactors are involved in ER signaling. Until recently, our knowledge regarding these cofactors was based on their ability to bind receptors in vitro and affect transcriptional activation in transfection experiments. The in vivo role of these cofactors and the specific target genes involved in breast cancer are not well known.

The purpose of this proposal was to investigate the response of prostate cancer to a series of camptothecin analogs, which are drugs that target DNA topoisomerase I. Toward task 1 of our proposal, we used immunofluorescence staining. However, this did not provide satisfactory results due to non-specificity of the rabbit serum used. We focused predominantly on tasks related to the data obtained from the completed task 3. We developed a very potent camptothecin analog that shows good activity in prostate cancer.

Primary human breast cancer tissues obtained from biopsies or mastectomies were characterized in terms of DNA content by flow cytometric and digital image analyses and expression of growth factor receptors, e.g. estrogen and progesterone receptors. One breast tumor biopsy was accompanied by an axillary lymph node which contained metastatic tumor. The primary (breast) tumor contained two aneuploid stem lines with DNA indices of 1.4 and 1.9 and S-phase fractions of 19.8% and 7.4%, respectively. Metastatic tumor in the axillary lymph node contained only one aneuploid stem line with an S-phase fraction of 9. 6% and a DNA index of 1.7 suggesting the possibility of the emergence of a sub- line in the metastatic tumor. Flow cytometric analysis of mutant p53 expression of BT-474, DU-4475 and SK-BR3 cells indicated that significant differences existed between these three cell lines in terms of time during culture when p53 is expressed and variations in cell-cycle specific expression. These findings have particular relevance to previous reports which showed that the p53 tumor suppressor gene product is involved in the induction of apoptosis as the result of growth factor deprivation possibly by down-requlating bcl-2 expression. A DNA 3'-OH digoxigenin-nucleotide end extension-FITC-anti-digoxigenin labeling technique was used for detecting the presence of fragmented DNA in intact cell nuclei as a marker for apoptosis in etoposide-treated BT-474 and MCF-7 cells. Cell cycle analysis indicated that the number of apoptotic cells increased markedly after 16-23 hours of culture and that these cells were detected primarily in the S-phase fraction.

The purpose of this proposal was to investigate the response of prostate cancer to a series of camptothecin analogs, which are drugs that target DNA topoisomerase I. This final report summarizes the accomplishments toward the tasks outlined in the original proposal for this grant. The goal of the project was to try to understand why, despite the availability of topoisomerase I in prostate cancer, chemotherapeutic agents that target this enzyme are ineffective in treating prostate cancer. Members of the camptothecin family that specifically target topo I were studied in prostate cancer cell lines grown in vitro. The project was meant to attack this problem from three separate directions using three assays. The first assay was that of initial topo I distribution in normal and cancer cells and its response to camptothecin analog treatment. The second assay was for selection of camptothecin analogs that form slowly reversing topo I-DNA complexes. The third was measurement of the onset of apoptosis in prostate cells treated with the different analogs. This final report documents the work performed throughout the lifetime of the funded project. The authors note that while some experimental problems were encountered that limited the completion of all tasks, good progress was made overall on the proposed research.

Scope of the present work is to frame into a rigorous, quantitative scaffold - stemmed from stochastic process theory - two sets of experiments designed to infer the spontaneous organization of leukocytes against cancer cells, namely mice splenocytes vs. B16 mouse tumor cells, and embedded in an "ad hoc" microfluidic environment developed on a LabOnChip technology. In the former, splenocytes from knocked out (KO) mice engineered to silence the transcription factor IRF-8, crucial for the development and function of several immune populations, were used. In this case lymphocytes and cancer cells exhibited a poor reciprocal exchange, resulting in the inability of coordinating or mounting an effective immune response against melanoma. In the second class of tests, wild type (WT) splenocytes were able to interact with and to coordinate a response against the tumor cells through physical interaction. The environment where cells moved was built of by two different chambers, containing respectively melanoma cells and splenocytes, connected by capillary migration channels allowing leucocytes to migrate from their chamber toward the melanoma one. We collected and analyzed data on the motility of the cells and found that the first ensemble of IRF-8 KO cells performed pure uncorrelated random walks, while WT splenocytes were able to make singular drifted random walks, that, averaged over the ensemble of cells, collapsed on a straight ballistic motion for the system as a whole. At a finer level of investigation, we found that IRF-8 KO splenocytes moved rather uniformly since their step lengths were exponentially distributed, while WT counterpart displayed a qualitatively broader motion as their step lengths along the direction of the melanoma were log-normally distributed.

This article is from Evolutionary Applications , volume 6 . Abstract If the occurrence of cancer is the result of a random lottery among cells, then body mass, a surrogate for cells number, should predict cancer incidence. Despite some support in humans, this assertion does not hold over the range of different natural animal species where cancer incidence is known. Explaining the so-called ‘Peto's paradox' is likely to increase our understanding of how cancer defense mechanisms are shaped by natural selection. Here, we study how body mass may affect the evolutionary dynamics of tumor suppressor gene (TSG) inactivation and oncogene activation in natural animal species. We show that the rate of TSG inactivation should evolve to lower values along a gradient of body mass in a nonlinear manner, having a threshold beyond which benefits to adaptive traits cannot overcome their costs. We also show that oncogenes may be frequently activated within populations of large organisms. We then propose experimental settings that can be employed to identify protection mechanisms against cancer. We finally highlight fundamental species traits that natural selection should favor against carcinogenesis. We conclude on the necessity of comparing genomes between populations of a single species or genomes between species to better understand how evolution has molded protective mechanisms against cancer development and associated mortality.

1. Role of inter-domain water clusters in large-scale dynamics of proteins; 2. Description of large-scale dynamics of proteins based on generalized Stokes-Einstein and Eyring-Polany equation; 3. Dynamic model of protein-ligand complexes formation; 4. The life-time of quasiparticles and frequencies of their excitation; 5. Mesoscopic mechanism of enzyme catalysis; 6. The mechanism of ATP hydrolysis energy utilization in muscle contraction and protein polymerization; 7. Water activity as a regulative factor in the intra- and inter-cell processes; 8. Water and cancer.

The Human Immunodeficiency Virus (HIV) targets CD4 T-cells which are crucial in regulating the immune systems response to foreignpathogens and cancerous cell development. Furthermore, several studies link HIV infection with the proliferation of specific forms ofcancer such as Kaposi Sarcoma and Non-Hodgkins Lymphoma; HIV infected individuals can be several thousand times more likely to bediagnosed with cancer. In this project, we seek to apply systems of nonlinear ordinary differential equations to analyze how the dynamics ofprimary infection affect the proliferation of cancer. We first begin by characterizing the dynamics of HIV infection. During HIV-1 primaryinfection, we know that the virus concentration increases, reaches a peak, and then decreases until it reaches a set point. We studiedlongitudinal data from 18 subjects identified as HIV positive during plasma donation screening and applied several models to analyze thedynamics of the systems and determine the most effective model for characterizing the infection. We prove existence, uniqueness,positivity, and boundedness, investigate the qualitative behavior of the models, and find the conditions that guarantee the asymptoticstability of the equilibria. In addition, we conduct numerical simulations and sensitivity analyses to illustrate and extend the theoreticalresults. Furthermore, we develop and study a new Tumor-Immunodeficiency model which integrates the effects of an immunodeficiency oncancerous tumor cell development.

This article is from PLoS ONE , volume 9 . Abstract Recent works have highlighted a double role for the Transforming Growth Factor (-): it inhibits cancer in healthy cells and potentiates tumor progression during late stage of tumorigenicity, respectively; therefore it has been termed the “Jekyll and Hyde” of cancer or, alternatively, an “excellent servant but a bad master”. It remains unclear how this molecule could have the two opposite behaviours. In this work, we propose a - multi scale mathematical model at molecular, cellular and tissue scales. The multi scalar behaviours of the - are described by three coupled models built up together which can approximatively be related to distinct microscopic, mesoscopic, and macroscopic scales, respectively. We first model the dynamics of - at the single-cell level by taking into account the intracellular and extracellular balance and the autocrine and paracrine behaviour of -. Then we use the average estimates of the - from the first model to understand its dynamics in a model of duct breast tissue. Although the cellular model and the tissue model describe phenomena at different time scales, their cumulative dynamics explain the changes in the role of - in the progression from healthy to pre-tumoral to cancer. We estimate various parameters by using available gene expression datasets. Despite the fact that our model does not describe an explicit tissue geometry, it provides quantitative inference on the stage and progression of breast cancer tissue invasion that could be compared with epidemiological data in literature. Finally in the last model, we investigated the invasion of breast cancer cells in the bone niches and the subsequent disregulation of bone remodeling processes. The bone model provides an effective description of the bone dynamics in healthy and early stages cancer conditions and offers an evolutionary ecological perspective of the dynamics of the competition between cancer and healthy cells.

This article is from BMC Cancer , volume 12 . Abstract Background: The multicellular tumor spheroid (MCTS) is an in vitro model associating malignant-cell microenvironment and 3D organization as currently observed in avascular tumors. Methods: In order to evaluate the relevance of this model for pre-clinical studies of drug combinations, we analyzed the effect of gemcitabine alone and in combination with the CHIR-124 CHK1 inhibitor in a Capan-2 pancreatic cell MCTS model. Results: Compared to monolayer cultures, Capan-2 MCTS exhibited resistance to gemcitabine cytotoxic effect. This resistance was amplified in EGF-deprived quiescent spheroid suggesting that quiescent cells are playing a role in gemcitabine multicellular resistance. After a prolonged incubation with gemcitabine, DNA damages and massive apoptosis were observed throughout the spheroid while cell cycle arrest was restricted to the outer cell layer, indicating that gemcitabine-induced apoptosis is directly correlated to DNA damages. The combination of gemcitabine and CHIR-124 in this MCTS model, enhanced the sensitivity to the gemcitabine antiproliferative effect in correlation with an increase in DNA damage and apoptosis. Conclusions: These results demonstrate that our pancreatic MCTS model, suitable for both screening and imaging analysis, is a valuable advanced tool for evaluating the spatio-temporal effect of drugs and drug combinations in a chemoresistant and microenvironment-depending tumor model.

Human tumors acquire a marked genomic instability as part of their progression from normal to malignant cells. This instability is likely due in part to the progressive shortening and transient loss of telomeres from chromosome ends. Loss of telomeres allows chromosomes to fuse end-to-end, triggering chromosome fusion-bridge-breakage cycles that lead to genome rearrangements, loss of heterozygosity, and gene amplification. The initial steps in chromosome fusion-bridge-breakage cycles are being studied by introducing site-specific double-strand breaks adjacent to interstitial telomere sequences in a marked region of a specially engineered test chromosome. A color-based detection system based on the green fluorescent protein is being developed to aid in detection of the early steps in fusion-bridge- breakage cycles. By varying the length of the telomere sequence, we will measure the length of telomere sequence that is required to protect chromosome ends and prevent genomic instability in breast cancer cells. A test chromosome is being constructed using the APRT locus in CHO cells, which will permit a measure of the effects of telomere sequence on the frequencies of chromatid fusion. Once the properties of the test chromosome are characterized in CHO cells we will transfer the engineered chromosome by microcell fusion into human breast cancer cells at different stages of tumor progression.