3 resultados para Cancer du col utérin

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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The DOK1 gene is a putative tumour suppressor gene located on the human chromosome 2p13 which is frequently rearranged in leukaemia and other human tumours. We previously reported that the DOK1 gene can be mutated and its expression down-regulated in human malignancies. However, the mechanism underlying DOK1 silencing remains largely unknown. We show here that unscheduled silencing of DOK1 expression through aberrant hypermethylation is a frequent event in a variety of human malignancies. DOK1 was found to be silenced in nine head and neck cancer (HNC) cell lines studied and DOK1 CpG hypermethylation correlated with loss of gene expression in these cells. DOK1 expression could be restored via demethylating treatment using 5-aza-2'deoxycytidine. In addition, transduction of cancer cell lines with DOK1 impaired their proliferation, consistent with the critical role of epigenetic silencing of DOK1 in the development and maintenance of malignant cells. We further observed that DOK1 hypermethylation occurs frequently in a variety of primary human neoplasm including solid tumours (93% in HNC, 81% in lung cancer) and haematopoietic malignancy (64% in Burkitt's lymphoma). Control blood samples and exfoliated mouth epithelial cells from healthy individuals showed a low level of DOK1 methylation, suggesting that DOK1 hypermethylation is a tumour specific event. Finally, an inverse correlation was observed between the level of DOK1 gene methylation and its expression in tumour and adjacent non tumour tissues. Thus, hypermethylation of DOK1 is a potentially critical event in human carcinogenesis, and may be a potential cancer biomarker and an attractive target for epigenetic-based therapy.

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Background: Prognosis of prostate cancer (PCa) is based mainly in histological aspects together with PSA serum levels that not always reflect the real aggressive potential of the neoplasia. The micro RNA (miRNA) mir-21 has been shown to regulate invasiveness in cancer through translational repression of the Metaloproteinase (MMP) inhibitor RECK. Our aim is to investigate the levels of expression of RECK and miR-21 in PCa comparing with classical prognostic factors and disease outcome and also test if RECK is a target of miR-21 in in vitro study using PCa cell line. Materials and methods: To determine if RECK is a target of miR-21 in prostate cancer we performed an in vitro assay with PCa cell line DU-145 transfected with pre-miR-21 and anti-miR-21. To determine miR-21 and RECK expression levels in PCa samples we performed quantitative real-time polymerase chain reaction (qRT-PCR). Results: The in vitro assays showed a decrease in expression levels of RECK after transfection with pre-miR-21, and an increase of MMP9 that is regulated by RECK compared to PCa cells treated with anti-miR-21. We defined three profiles to compare the prognostic factors. The first was characterized by miR-21 and RECK underexpression (N = 25) the second was characterized by miR-21 overexpression and RECK underexpression (N = 12), and the third was characterized by miR-21 underexpression and RECK overexpression (N = 16). From men who presented the second profile (miR-21 overexpression and RECK underexpression) 91.7% were staged pT3. For the other two groups 48.0%, and 46.7% of patients were staged pT3 (p = 0.025). Conclusions: Our results demonstrate RECK as a target of miR-21. We believe that miR-21 may be important in PCa progression through its regulation of RECK, a known regulator of tumor cell invasion.

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Background: Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. Methods: We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer. Results: Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [p(trend)] = 2.5 x 10(-3)). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76-0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found. Conclusion: This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config).