128 research outputs found

    Screening for coping style increases the power of gene expression studies

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    Background: Individuals of many vertebrate species show different stress coping styles and these have a striking influence on how gene expression shifts in response to a variety of challenges. Principal Findings: This is clearly illustrated by a study in which common carp displaying behavioural predictors of different coping styles (characterised by a proactive, adrenaline-based or a reactive, cortisol-based response) were subjected to inflammatory challenge and specific gene transcripts measured in individual brains. Proactive and reactive fish differed in baseline gene expression and also showed diametrically opposite responses to the challenge for 80% of the genes investigated. Significance: Incorporating coping style as an explanatory variable can account for some the unexplained variation that is common in gene expression studies, can uncover important effects that would otherwise have passed unnoticed and greatly enhances the interpretive value of gene expression data

    Apolipoprotein A-II Influences Apolipoprotein E-Linked Cardiovascular Disease Risk in Women with High Levels of HDL Cholesterol and C-Reactive Protein

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    Background: In a previous report by our group, high levels of apolipoprotein E (apoE) were demonstrated to be associated with risk of incident cardiovascular disease in women with high levels of C-reactive protein (CRP) in the setting of both low (designated as HR1 subjects) and high (designated as HR2 subjects) levels of high-density lipoprotein cholesterol (HDL-C). To assess whether apolipoprotein A-II (apoA-II) plays a role in apoE-associated risk in the two female groups. Methodology/Principal: Outcome event mapping, a graphical data exploratory tool; Cox proportional hazards multivariable regression; and curve-fitting modeling were used to examine apoA-II influence on apoE-associated risk focusing on HDL particles with apolipoprotein A-I (apoA-I) without apoA-II (LpA-I) and HDL particles with both apoA-I and apoA-II (LpA-I:A-II). Results of outcome mappings as a function of apoE levels and the ratio of apoA-II to apoA-I revealed within each of the two populations, a high-risk subgroup characterized in each situation by high levels of apoE and additionally: in HR1, by a low value of the apoA-II/apoA-I ratio; and in HR2, by a moderate value of the apoA-II/apoA-I ratio. Furthermore, derived estimates of LpA-I and LpA-I:A-II levels revealed for high-risk versus remaining subjects: in HR1, higher levels of LpA-I and lower levels of LpA-I:A-II; and in HR2 the reverse, lower levels of LpA-I and higher levels of LpA-I:A-II. Results of multivariable risk modeling as a function of LpA-I and LpA-I:A-II (dichotomized as highest quartile versus combined three lower quartiles) revealed association of risk only for high levels of LpA-I:A-II in the HR2 subgroup (hazard ratio 5.31, 95% CI 1.12-25.17, p = 0.036). Furthermore, high LpA-I: A-II levels interacted with high apoE levels in establishing subgroup risk. Conclusions/Significance: We conclude that apoA-II plays a significant role in apoE-associated risk of incident CVD in women with high levels of HDL-C and CRP

    Human Macrophages and Dendritic Cells Can Equally Present MART-1 Antigen to CD8+ T Cells after Phagocytosis of Gamma-Irradiated Melanoma Cells

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    Dendritic cells (DC) can achieve cross-presentation of naturally-occurring tumor-associated antigens after phagocytosis and processing of dying tumor cells. They have been used in different clinical settings to vaccinate cancer patients. We have previously used gamma-irradiated MART-1 expressing melanoma cells as a source of antigens to vaccinate melanoma patients by injecting irradiated cells with BCG and GM-CSF or to load immature DC and use them as a vaccine. Other clinical trials have used IFN-gamma activated macrophage killer cells (MAK) to treat cancer patients. However, the clinical use of MAK has been based on their direct tumoricidal activity rather than on their ability to act as antigen-presenting cells to stimulate an adaptive antitumor response. Thus, in the present work, we compared the fate of MART-1 after phagocytosis of gamma-irradiated cells by clinical grade DC or MAK as well as the ability of these cells to cross present MART-1 to CD8+ T cells. Using a high affinity antibody against MART-1, 2A9, which specifically stains melanoma tumors, melanoma cell lines and normal melanocytes, the expression level of MART-1 in melanoma cell lines could be related to their ability to stimulate IFN-gamma production by a MART-1 specific HLA-A*0201-restricted CD8+ T cell clone. Confocal microscopy with Alexa Fluor®647-labelled 2A9 also showed that MART-1 could be detected in tumor cells attached and/or fused to phagocytes and even inside these cells as early as 1 h and up to 24 h or 48 h after initiation of co-cultures between gamma-irradiated melanoma cells and MAK or DC, respectively. Interestingly, MART-1 was cross-presented to MART-1 specific T cells by both MAK and DC co-cultured with melanoma gamma-irradiated cells for different time-points. Thus, naturally occurring MART-1 melanoma antigen can be taken-up from dying melanoma cells into DC or MAK and both cell types can induce specific CD8+ T cell cross-presentation thereafter

    Cell Cycle Gene Networks Are Associated with Melanoma Prognosis

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    BACKGROUND: Our understanding of the molecular pathways that underlie melanoma remains incomplete. Although several published microarray studies of clinical melanomas have provided valuable information, we found only limited concordance between these studies. Therefore, we took an in vitro functional genomics approach to understand melanoma molecular pathways. METHODOLOGY/PRINCIPAL FINDINGS: Affymetrix microarray data were generated from A375 melanoma cells treated in vitro with siRNAs against 45 transcription factors and signaling molecules. Analysis of this data using unsupervised hierarchical clustering and Bayesian gene networks identified proliferation-association RNA clusters, which were co-ordinately expressed across the A375 cells and also across melanomas from patients. The abundance in metastatic melanomas of these cellular proliferation clusters and their putative upstream regulators was significantly associated with patient prognosis. An 8-gene classifier derived from gene network hub genes correctly classified the prognosis of 23/26 metastatic melanoma patients in a cross-validation study. Unlike the RNA clusters associated with cellular proliferation described above, co-ordinately expressed RNA clusters associated with immune response were clearly identified across melanoma tumours from patients but not across the siRNA-treated A375 cells, in which immune responses are not active. Three uncharacterised genes, which the gene networks predicted to be upstream of apoptosis- or cellular proliferation-associated RNAs, were found to significantly alter apoptosis and cell number when over-expressed in vitro. CONCLUSIONS/SIGNIFICANCE: This analysis identified co-expression of RNAs that encode functionally-related proteins, in particular, proliferation-associated RNA clusters that are linked to melanoma patient prognosis. Our analysis suggests that A375 cells in vitro may be valid models in which to study the gene expression modules that underlie some melanoma biological processes (e.g., proliferation) but not others (e.g., immune response). The gene expression modules identified here, and the RNAs predicted by Bayesian network inference to be upstream of these modules, are potential prognostic biomarkers and drug targets
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