9 resultados para Brain Growth

em DigitalCommons@The Texas Medical Center


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Brain metastasis is a common cause of mortality in cancer patients. Approximately 20-30% of breast cancer patients acquire brain metastasis, yet potential therapeutic targets remain largely unknown. The type I insulin-like growth factor receptor (IGF- IR) is known to play a role in the progression of breast cancer and is currently being investigated in the clinical setting for various types of cancer. The present study demonstrates that the IGF-IR signaling axis is constitutively active in brain-seeking sublines of breast cancer cells, driving an increase in in vitro metastatic properties. We demonstrate that IGF-IR signaling is activated in an autocrine manner as a result of IGFBP3 overexpression in brain-seeking cells. Transient and stable knockdown of IGF-IR results in a downregulation of IGF-IR downstream signaling through phospho-AKT, as well as decreased in vitro migration and invasion of MDA- MB-231Br brain-seeking cells. Using an in vivo experimental brain metastasis model, we show that IGF-IR ablation attenuates the establishment of brain metastases and prolongs survival. Finally, we demonstrate that the malignancy of brain-seeking cells is attenuated by pharmacological inhibition with picropodophyllin, an IGF-IR-specific tyrosine kinase inhibitor. Together, our data suggest that the IGF-IR is an important mediator of brain metastasis and its ablation delays the onset of brain metastases in our model system.

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Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

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Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

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Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

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We previously found that FoxM1B is overexpressed in human glioblastomas and that forced FoxM1B expression in anaplastic astrocytoma cells leads to the formation of highly angiogenic glioblastoma in nude mice. However, the molecular mechanisms by which FoxM1B enhances glioma angiogenesis are currently unknown. In this study, we found that vascular endothelial growth factor (VEGF) is a direct transcriptional target of FoxM1B. FoxM1B overexpression increased VEGF expression, whereas blockade of FoxM1 expression suppressed VEGF expression in glioma cells. Transfection of FoxM1 into glioma cells directly activated the VEGF promoter, and inhibition of FoxM1 expression by FoxM1 siRNA suppressed VEGF promoter activation. We identified two FoxM1-binding sites in the VEGF promoter that specifically bound to the FoxM1 protein. Mutation of these FoxM1-binding sites significantly attenuated VEGF promoter activity. Furthermore, FoxM1 overexpression increased and inhibition of FoxM1 expression suppressed the angiogenic ability of glioma cells. Finally, an immunohistochemical analysis of 59 human glioblastoma specimens also showed a significant correlation between FoxM1 overexpression and elevated VEGF expression. Our findings provide both clinical and mechanistic evidence that FoxM1 contributes to glioma progression by enhancing VEGF gene transcription and thus tumor angiogenesis.

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Diffusion tensor imaging (DTI) and immunohistochemistry were performed in spinal cord injured rats to understand the basis for activation of multiple regions in the brain observed in functional magnetic resonance imaging (fMRI) studies. The measured fractional anisotropy (FA), a scalar measure of diffusion anisotropy, along the region encompassing corticospinal tracts (CST) indicates significant differences between control and injured groups in the 3 to 4 mm area posterior to bregma that correspond to internal capsule and cerebral peduncle. Additionally, DTI-based tractography in injured animals showed increased number of fibers that extend towards the cortex terminating in the regions that were activated in fMRI. Both the internal capsule and cerebral peduncle demonstrated an increase in GFAP-immunoreactivity compared to control animals. GAP-43 expression also indicates plasticity in the internal capsule. These studies suggest that the previously observed multiple regions of activation in spinal cord injury are, at least in part, due to the formation of new fibers.

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Several interactive parameters of protein-calorie malnutrition imposed during postnatal ontogeny on the myelination of rat brain wre investigated. Postnatal starvation depresses the rate of myelin protein synthesis to approximately the same extent in all major brain regions examined (cerebral cortex, cerebellum, striatum, hippocampus, hypothalamus, midbrain and medulla), indicating a relatively uniform reduction in myelination throughout the brain. Early starvation from birth through 8 days, as well as starvation occurring late, from 14 to 30 days, produced no lasting deficit in myelin accumulation. Starvation from birth through 14 days or from birth through 20 days produces lasting, significant myelin deficits in all brain regions when examined following ad libitum feeding to 60 days of age. These data, in combination with the metabolic studies of myelin synthesis, show that severe starvation occurring during the 2nd and 3rd weeks of postnatal life produces an immediate reduction in myelin synthesis, and that the subsequent deficit in myelin accumulation is irreversible by nutritional rehabilitation. With respect to the relative severity of nutritional restriction occurring during this "critical" interval of brain ontogeny, additional studies showed that mild undernourishment (producing less than 20 percent growth lag) produces no myelin deficit. There appears to be a threshold effect such that undernutrition producing a growth lag of between 20 to 30 percent first produces a measurable deficit. Increasingly severe regimens of nutritional restriction which produce approximately 30, 40 and 50 percent body weight lags result in initial myelin deficits of 25, 55 and 60 percent, respectively. Initial myelin deficits do not recover following nutritional rehabilitation, although myelin continues to increase in both normal and all undernourished populations. At the cellular level, severe postnatal nutritional restriction appears to depress both the initial synthesis of myelin precursor proteins (as demonstrated for proteolipid protein) as well as their subsequent assembly into myelin membrane. All of the findings of the present studies are consistent with a hypothetical model of undernutrition-induced brain hypomyelination in which the primary defect consists of a failure of oligodendroglia to myelinate a substantial percentage of axons, resulting in a greatly decreased ratio of myelinated to unmyelinated axons. ^

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Brain metastasis, which occurs in 40%-60% of patients with advanced melanoma, has led directly to death in the majority of cases. Unfortunately, little is known about the biological and molecular basis of melanoma brain metastases. In our previous study, we developed a model to study human melanoma brain metastasis and found that Stat3 activity was increased in human brain metastatic melanoma cells when compared with that in cutaneous melanoma cells. The increased activation of Stat3 is also responsible for affecting melanoma angiogenesis in vivo and melanoma cell invasion in vitro and significantly affecting the expression of bFGF, VEGF, and MMP-2 in vivo and in vitro. Interestingly, a member of a new family of cytokine-inducible inhibitors of signal transduction, termed suppressors of cytokine signaling 1 (SOCS1) was found to negatively regulate the Janus kinase signal transducer and activator of transcription (Jak/STAT) signaling cascade. Here we report that restoration of SOCS1 expression by transfecting of SOCS1-expressing vector effectively inhibited melanoma brain metastasis through inhibiting Stat3 activation and further affecting melanoma angiogenesis and melanoma cell invasion in vitro, and significantly affected the expression of vascular endothelial growth factor (VEGF) and matrix metalloproteinase-2 (MMP-2) in vitro and in vivo. In addition, we used cDNA array to compare mRNA expression in the SOCS1-transfected and vector-transfected cell lines and found some genes are tightly correlated to the restoration of SOCS1. One of them is Caveolin-1 (Cav-1). Cav-1 was reported to function as a tumor suppressor gene by several groups. Finally, the Cav-1 expression is up-regulated in SOCS1-overexpressing cell line. Further study found the regulation of Cav-1 by SOCS1 occurs through inhibiting Stat3 activation. Activated Stat3 binds directly to Cav-1 promoter and the Cav-1 promoter within -575bp is essential for active Stat3 binding. My studies reveal that Stat3 activation and SOCS1 expression play important roles in melanoma metastases. Moreover, the expression between SOCS1, Stat3 and Cav-1 forms a feedback regulation loop. ^

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Background: Activation of the sympathetic nervous system (SNS) in response to chronic biobehavioral stress results in high levels of catecholamines and persistent activation of adrenergic signaling, which promotes tumor growth and progression. However it is unknown how catecholamine levels within the tumor exceed systemic levels in circulation. I hypothesized that neo-innervation of tumors is required for stress-mediated effects on tumor growth. Results: First, I examined whether sympathetic nerves are present in human ovarian cancer samples as well as orthotopic ovarian cancer models. Immunohistochemical (IHC) staining for neurofilament revealed that catecholaminergic neurons are present within tumor tissue. In order to determine whether chronic stress affects the density of nerves in the tumor, I utilized an orthotopic mouse model of ovarian cancer that was exposed to daily restraint stress. IHC analysis revealed that nerve density in tumors increased by more than three-fold in stressed animals versus non-stressed controls. IHC analysis suggested that this results from both recruitment of existing neurons (axonogenesis) as well as new neuron formation (neurogenesis) within the tumor. To determine how tumors are recruiting nerve growth, I utilized a PCR array analysis of 84 nerve growth related genes and their receptors, which showed that stimulation of the SKOV3 ovarian cancer cell line with norepinephrine (NE) leads to increased expression of several neurotrophins, including brain-derived neurotrophic factor (BDNF). Neurite extension assays showed that media conditioned by ovarian cancer cell lines is capable of inducing neurite outgrowth in differentiated neuron-like PC12 cells, and NE treatment of cancer cells potentiates this effect. Norepinephrine-induced neurite extension was abolished after BDNF silencing by siRNA, suggesting that BDNF is critical to tumor cell-induced nerve growth. in vivo BDNF inhibition resulted in complete abrogation of stress-induced increases in tumor weight and nerve density, as well as downstream markers of stress. Discussion: These studies indicate that adrenergic signalling induced by chronic stress promotes neo-innervation in the tumor microenvironment. This results in a mutually beneficial relationship between the tumor cells and neurons. This work is crucial for providing a link between chronic stress and its effects on the tumor and its microenvironment. The data shown here aims to open new venues that can be used in development of therapies designed to block the stress effects on tumor growth.