978 resultados para Ovaries Tumors
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The aim of this investigation was to test the hypothesis that testicular germ cell tumors (TGCTs) are hormone-dependent cancers. Human TGCT cells were implanted in the left testis of male severe combined immunodeficient mice receiving either no treatment or hormone manipulation treatment [blockade of gonadotropin-releasing hormone secretion and/or signaling using leuprolide or leuprolide plus exogenous testosterone]. Real-time RT-PCR analysis was used to determine the expression profiles of hormone pathway-associated genes. Tumor burden was significantly smaller in mice receiving both leuprolide and testosterone. Real-time RTPCR analysis of follicle-stimulating hormone (FSH) receptor, luteinizing hormone (LH) receptor and P450 aromatase revealed changes in expression in normal testis tissue related to presence of xenograft tumors and manipulation of hormone levels but a complete absence of expression of these genes in tumor cells themselves. This was confirmed in human specimens of TGCT. Reduced TGCT growth in vivo was associated with significant downregulation of LH receptor and P450 aromatase expression in normal testes. In conclusion, manipulation of hormone levels influenced the growth of TGCT in vivo, while the presence of xenografted tumors influenced the expression of hormone-related genes in otherwise untreated animals. Human TGCTs, both in the animal model and in clinical specimens, appear not to express receptors for FSH or LH. Similarly, expression of the P450 aromatase gene is absent in TGCTs. Impaired estrogen synthesis and/or signaling may be at least partly responsible for inhibition of TGCT growth in the animal model. (c) 2005 Wiley-Liss, Inc.
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Merlin has broad tumor-suppressor functions as its mutations have been identified in multiple benign tumors and malignant cancers. In all schwannomas, the majority of meningiomas and 1/3 of ependymomas Merlin loss is causative. In neurofibromatosis type 2, a dominantly inherited tumor disease because of the loss of Merlin, patients suffer from multiple nervous system tumors and die on average around age 40. Chemotherapy is not effective and tumor localization and multiplicity make surgery and radiosurgery challenging and morbidity is often considerable. Thus, a new therapeutic approach is needed for these tumors. Using a primary human in vitro model for Merlin-deficient tumors, we report that the Ras/Raf/mitogen-activated protein, extracellular signal-regulated kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) scaffold, kinase suppressor of Ras 1 (KSR1), has a vital role in promoting schwannomas development. We show that KSR1 overexpression is involved in many pathological phenotypes caused by Merlin loss, namely multipolar morphology, enhanced cell-matrix adhesion, focal adhesion and, most importantly, increased proliferation and survival. Our data demonstrate that KSR1 has a wider role than MEK1/2 in the development of schwannomas because adhesion is more dependent on KSR1 than MEK1/2. Immunoprecipitation analysis reveals that KSR1 is a novel binding partner of Merlin, which suppresses KSR1's function by inhibiting the binding between KSR1 and c-Raf. Our proteomic analysis also demonstrates that KSR1 interacts with several Merlin downstream effectors, including E3 ubiquitin ligase CRL4DCAF1. Further functional studies suggests that KSR1 and DCAF1 may co-operate to regulate schwannomas formation. Taken together, these findings suggest that KSR1 serves as a potential therapeutic target for Merlin-deficient tumors.
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Background/Aim: Heparanase (HPA) contributes to breast cancer metastasis by facilitating the breakdown of the basement membrane and extracellular matrix. High expression of HPA is thought to be associated with increased nodal involvement and poor survival in patients with breast cancer. Overexpression of cyclooxygenase-2 (COX-2) in breast cancer is associated with indicators of poor prognosis such as lymph node metastasis, poor differentiation, and large tumor size. The underlying mechanism by which HPA and COX-2 overexpression increases the metastatic potential of breast cancer is not fully-understood. To enhance our understanding over these mechanisms, we aimed to investigate the relationship between the size of the tumor and HPA expression, tumor grade as well as lymph node status in patients with breast cancer. Materials and Methods: Immunohistochemical analysis of HPA and COX-2 expression was performed on 246 breast tumor samples. The expression of HPA was correlated with COX-2 expression, tumor grade, lymph node status, oestrogen receptor status. Results: The overexpression of HPA and COX-2 was associated with increased likelihood of lymph node positivity in large, high-grade tumors. High-grade tumors with size greater than 20 mm, that overexpressed HPA, were 4-times more likely to be associated with lymph node involvement (OR 4.71, CI 1.21-18.25). Whereas, tumors greater than 20 mm in size were 5-times more likely to metastasize to the regional lymph nodes, if associated with overexpression of COX-2 (OR 5.5, CI 1.2-24.8). Conclusion: Expression of HPA appears to be a key mechanism by which large, highgrade breast tumors metastasize to regional lymph nodes, while COX-2 overexpression may be an independent predictor of lymph node positivity.
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Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.
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The etiology of central nervous system tumors (CNSTs) is mainly unknown. Aside from extremely rare genetic conditions, such as neurofibromatosis and tuberous sclerosis, the only unequivocally identified risk factor is exposure to ionizing radiation, and this explains only a very small fraction of cases. Using meta-analysis, gene networking and bioinformatics methods, this dissertation explored the hypothesis that environmental exposures produce genetic and epigenetic alterations that may be involved in the etiology of CNSTs. A meta-analysis of epidemiological studies of pesticides and pediatric brain tumors revealed a significantly increased risk of brain tumors among children whose mothers had farm-related exposures during pregnancy. A dose response was recognized when this risk estimate was compared to those for risk of brain tumors from maternal exposure to non-agricultural pesticides during pregnancy, and risk of brain tumors among children exposed to agricultural activities. Through meta-analysis of several microarray studies which compared normal tissue to astrocytomas, we were able to identify a list of 554 genes which were differentially expressed in the majority of astrocytomas. Many of these genes have in fact been implicated in development of astrocytoma, including EGFR, HIF-1α, c-Myc, WNT5A, and IDH3A. Reverse engineering of these 554 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I-IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme (GBM) were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. Lastly, bioinformatics analysis of environmental databases and curated published results on GBM was able to identify numerous potential pathways and geneenvironment interactions that may play key roles in astrocytoma development. Findings from this research have strong potential to advance our understanding of the etiology and susceptibility to CNSTs. Validation of our ‘key genes’ and pathways could potentially lead to useful tools for early detection and novel therapeutic options for these tumors.
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Androgen receptor (AR) is commonly expressed in both the epithelium of normal mammary glands and in breast cancers. AR expression in breast cancers is independent of estrogen receptor alpha (ERα) status and is frequently associated with overexpression of the ERBB2 oncogene. AR signaling effects on breast cancer progression may depend on ERα and ERBB2 status. Up to 30% of human breast cancers are driven by overactive ERBB2 signaling and it is not clear whether AR expression affects any steps of tumor progression in this cohort of patients. To test this, we generated mammary specific Ar depleted mice (MARKO) by combining the floxed allele of Ar with the MMTV-cre transgene on an MMTV-NeuNT background and compared them to littermate MMTV-NeuNT, Arfl/+ control females. Heterozygous MARKO females displayed reduced levels of AR in mammary glands with mosaic AR expression in ductal epithelium. The loss of AR dramatically accelerated the onset of MMTV-NeuNT tumors in female MARKO mice. In this report we show that accelerated MMTV-NeuNT-dependent tumorigenesis is due specifically to the loss of AR, as hormonal levels, estrogen and progesterone receptors expression, and MMTV-NeuNT expression were similar between MARKO and control groups. MMTV-NeuNT induced tumors in both cohorts displayed distinct loss of AR in addition to ERα, PR, and the pioneer factor FOXA1. Erbb3 mRNA levels were significantly elevated in tumors in comparison to normal mammary glands. Thus the loss of AR in mouse mammary epithelium accelerates malignant transformation rather than the rate of tumorigenesis.
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Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.
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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.
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We propose a mathematically well-founded approach for locating the source (initial state) of density functions evolved within a nonlinear reaction-diffusion model. The reconstruction of the initial source is an ill-posed inverse problem since the solution is highly unstable with respect to measurement noise. To address this instability problem, we introduce a regularization procedure based on the nonlinear Landweber method for the stable determination of the source location. This amounts to solving a sequence of well-posed forward reaction-diffusion problems. The developed framework is general, and as a special instance we consider the problem of source localization of brain tumors. We show numerically that the source of the initial densities of tumor cells are reconstructed well on both imaging data consisting of simple and complex geometric structures.
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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.
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New targeted approaches to ovarian clear cell carcinomas (OCCC) are needed, given the limited treatment options in this disease and the poor response to standard chemotherapy. Using a series of high-throughput cell-based drug screens in OCCC tumor cell models, we have identified a synthetic lethal (SL) interaction between the kinase inhibitor dasatinib and a key driver in OCCC, ARID1A mutation. Imposing ARID1A deficiency upon a variety of human or mouse cells induced dasatinib sensitivity, both in vitro and in vivo, suggesting that this is a robust synthetic lethal interaction. The sensitivity of ARID1A-deficient cells to dasatinib was associated with G1 -S cell-cycle arrest and was dependent upon both p21 and Rb. Using focused siRNA screens and kinase profiling, we showed that ARID1A-mutant OCCC tumor cells are addicted to the dasatinib target YES1. This suggests that dasatinib merits investigation for the treatment of patients with ARID1Amutant OCCC. Mol Cancer Ther; 15(7); 1472-84. Ó2016 AACR.