973 resultados para gene loss


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Alcohol consumption and tobacco smoking are major causes of head and neck cancers, and regional differences point to the importance of research into gene-environment interactions. Much interest has been focused on polymorphisms of CYP1A1 and of GSTM1 and GSTT1, but a number of studies have not demonstrated significant effects. This has mostly been ascribed to small sample sizes. In general, the impact of polymorphisms of metabolic enzymes appears inconsistent, with some reports of weak-to-moderate associations, and with others of no elevation of risks. The classical cytochrome P450 isoenzyme considered for metabolic activation of polycyclic aromatic hydrocarbons (PAH) is CYP1A1. A new member of the CYP1 family, CYP1B1, was cloned in 1994, currently representing the only member of the CYP1B subfamily. A number of single nucleotide polymorphisms of the CYP1B1 gene have been reported. The amino acid substitutions Val432Leu (CYP1B1*3) and Asn453Ser (CYP1B1*4), located in the heme binding domain of CYP1B1, appear as likely candidates to be linked with biological effects. CYP1B1 activates a wide range of PAH, aromatic and heterocyclic amines. Very recently, the CYP1B1 codon 432 polymorphism (CYP1B1*3) has been identified as a susceptibility factor in smoking-related head-and-neck squamous cell cancer. The impact of this polymorphic variant of CYP1B1 on cancer risk was also reflected by an association with the frequency of somatic mutations of the p53 gene. Combined genotype analysis of CYP1B1 and the glutathione transferases GSTM1 or GSTT1 has pointed to interactive effects. This provides new molecular evidence that tobacco smoke-specific compounds relevant to head and neck carcinogenesis are metabolically activated through CYP1B1 and is consistent with a major pathogenetic relevance of PAH as ingredients of tobacco smoke.

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The Driver Behaviour Questionnaire (DBQ) continues to be the most widely utilised self-report scale globally to assess crash risk and aberrant driving behaviours among motorists. However, the scale also attracts criticism regarding its perceived limited ability to accurately identify those most at risk of crash involvement. This study reports on the utilisation of the DBQ to examine the self-reported driving behaviours (and crash outcomes) of drivers in three separate Australian fleet samples (N = 443, N = 3414, & N = 4792), and whether combining the samples increases the tool’s predictive ability. Either on-line or paper versions of the questionnaire were completed by fleet employees in three organisations. Factor analytic techniques identified either three or four factor solutions (in each of the separate studies) and the combined sample produced expected factors of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Highway code violations (and mean scores) were comparable across the studies. However, across the three samples, multivariate analyses revealed that exposure to the road was the best predictor of crash involvement at work, rather than DBQ constructs. Furthermore, combining the scores to produce a sample of 8649 drivers did not improve the predictive ability of the tool for identifying crashes (e.g., 0.4% correctly identified) or for demerit point loss (0.3%). The paper outlines the major findings of this comparative sample study in regards to utilising self-report measurement tools to identify “at risk” drivers as well as the application of such data to future research endeavours.

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PURPOSE/OBJECTIVES: To identify latent classes of individuals with distinct quality-of-life (QOL) trajectories, to evaluate for differences in demographic characteristics between the latent classes, and to evaluate for variations in pro- and anti-inflammatory cytokine genes between the latent classes. DESIGN: Descriptive, longitudinal study. SETTING: Two radiation therapy departments located in a comprehensive cancer center and a community-based oncology program in northern California. SAMPLE: 168 outpatients with prostate, breast, brain, or lung cancer and 85 of their family caregivers (FCs). METHODS: Growth mixture modeling (GMM) was employed to identify latent classes of individuals based on QOL scores measured prior to, during, and for four months following completion of radiation therapy. Single nucleotide polymorphisms (SNPs) and haplotypes in 16 candidate cytokine genes were tested between the latent classes. Logistic regression was used to evaluate the relationships among genotypic and phenotypic characteristics and QOL GMM group membership. MAIN RESEARCH VARIABLES: QOL latent class membership and variations in cytokine genes. FINDINGS: Two latent QOL classes were found: higher and lower. Patients and FCs who were younger, identified with an ethnic minority group, had poorer functional status, or had children living at home were more likely to belong to the lower QOL class. After controlling for significant covariates, between-group differences were found in SNPs in interleukin 1 receptor 2 (IL1R2) and nuclear factor kappa beta 2 (NFKB2). For IL1R2, carrying one or two doses of the rare C allele was associated with decreased odds of belonging to the lower QOL class. For NFKB2, carriers with two doses of the rare G allele were more likely to belong to the lower QOL class. CONCLUSIONS: Unique genetic markers in cytokine genes may partially explain interindividual variability in QOL. IMPLICATIONS FOR NURSING: Determination of high-risk characteristics and unique genetic markers would allow for earlier identification of patients with cancer and FCs at higher risk for poorer QOL. Knowledge of these risk factors could assist in the development of more targeted clinical or supportive care interventions for those identified.

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Background: Loss of erythrocyte membrane protein band 4.1-like 3 (EPB41L3; aliases: protein 4.1B, differentially expressed in adenocarcinoma of the lung-1 (Dal-1)) expression has been implicated in tumor progression. Objective: To evaluate literature describing the role of EPB41L3 in tumorigenesis and metastasis, and to consider whether targeting this gene would be useful in the treatment of prostate cancer. Methods: A literature review of studies describing EPB41L3 and its aliases was conducted. Online databases (NCBI, SwissProt) were also interrogated to collect further data. Results/conclusion: A growing body of evidence supports a role for loss of EPB41L3 in tumor progression, including in prostate cancer. Therapeutic strategies that could be harnessed to upregulate EPB41L3 gene expression in prostate cancer cells are currently being developed.

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A disintegrin and metalloprotease with thrombospondin motifs protein 1 (ADAMTS1) is a protease commonly up-regulated in metastatic carcinoma. Its overexpression in cancer cells promotes experimental metastasis, but whether ADAMTS1 is essential for metastatic progression is unknown. To address this question, we investigated mammary cancer progression and spontaneous metastasis in the MMTV-PyMT mouse mammary tumor model in Adamts1 knockout mice. Adamts1−/−/PyMT mice displayed significantly reduced mammary tumor and lung metastatic tumor burden and increased survival, compared with their wild-type and heterozygous littermates. Histological examination revealed an increased proportion of tumors with ductal carcinoma in situ and a lower proportion of high-grade invasive tumors in Adamts1−/−/PyMT mice, compared with Adamts1+/+/PyMT mice. Increased apoptosis with unaltered proliferation and vascular density in the Adamts1−/−/PyMT tumors suggested that reduced cell survival accounts for the lower tumor burden in ADAMTS1-deficient mice. Furthermore, Adamts1−/− tumor stroma had significantly lesser amounts of proteolytically cleaved versican and increased numbers of CD45+ leukocytes. Characterization of immune cell gene expression indicated that cytotoxic cell activation was increased in Adamts1−/− tumors, compared with Adamts1+/+ tumors. This finding is supported by significantly elevated IL-12+ cell numbers in Adamts1−/− tumors. Thus, in vivo ADAMTS1 may promote mammary tumor growth and progression to metastasis in the PyMT model and is a potential therapeutic target to prevent metastatic breast cancer.

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To identify key regulatory mechanisms in the growth and development of the human endometrium, microarray analysis was performed on uncultured human endometrium collected during menstruation (M) and the late-proliferative (LATE-P)-phase of the menstrual cycle, as well as after 24 h incubation in the presence of oestradiol (17beta-E2). We demonstrate the expression of novel gene transcripts in the human endometrium. i.e. mucin-9, novel oestrogen-responsive gene transcripts, i.e. gelsolin and flotillin-1, and genes known to be expressed in human endometrium but not yet shown to be oestrogen responsive, i.e. connexin-37 and TFF1/pS2. Genes reported to be expressed during the implantation window and implicated in progesterone action, i.e. secretoglobin family 2A, member 2 (mammaglobin) and homeobox-containing proteins, were up-regulated in uncultured LATE-P-phase endometrium compared to M-phase endometrium. Some gene transcripts are regulated directly by 17beta-E2 alone, others are influenced by the in vivo environment as well. These observations emphasise that the regulation of endometrium maturation by oestrogen entails more then just stimulation of cell proliferation.