225 research outputs found

    Enhanced SOX10 and KIT expression in cutaneous melanoma

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    Elf-1 and Stat5 bind to a critical element in a new enhancer of the human interleukin-2 receptor alpha gene

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    The interleukin 2 receptor alpha-chain (IL-2R alpha) gene is a key regulator of lymphocyte proliferation. IL-2R alpha is rapidly and potently induced in T cells in response to mitogenic stimuli. Interleukin 2 (IL-2) stimulates IL-2R alpha. transcription, thereby amplifying expression of its own high-affinity receptor. IL-2R alpha transcription is at least in part controlled by two positive regulatory regions, PRRI and PRRII. PRRI is an inducible proximal enhancer, located between nucleotides -276 and -244, which contains NF-kappaB and SRE/CArG motifs. PRRII is a T-cell-specific enhancer, located between nucleotides -137 and -64, which binds the T-cell-specific Ets protein Elf-1 and HMG-I(Y) proteins. However, none of these proximal regions account for the induction of IL-2R alpha transcription by IL-2. To find new regulatory regions of the IL-2R alpha gene, 8.5 kb of the 5' end noncoding sequence of the IL-2R alpha gene have been sequenced. We identified an 86-nucleotide fragment that is 90% identical to the recently characterized murine IL-2-responsive element (mIL-2rE). This putative human IL-2rE, designated PRRIII, confers IL-2 responsiveness on a heterologous promoter. PRRIII contains a Stat protein binding site that overlaps with an EBS motif (GASd/EBSd). These are essential for IL-2 inducibility of PRRIII/CAT reporter constructs. IL-2 induced the binding of Stat5a and b proteins to the human GASd element. To confirm the physiological relevance of these findings, we carried out in vivo footprinting experiments which showed that stimulation of IL-2R alpha expression correlated with occupancy of the GASd element. Our data demonstrate a major role of the GASd/EBSd element in IL-2R alpha regulation and suggest that the T-cell-specific Elf-1 factor can serve as a transcriptional repressor

    Gene set analysis for longitudinal gene expression data

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    <p>Abstract</p> <p>Background</p> <p>Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. GSA performs statistical tests for independent microarray samples at the level of gene sets rather than individual genes. Nowadays, an increasing number of microarray studies are conducted to explore the dynamic changes of gene expression in a variety of species and biological scenarios. In these longitudinal studies, gene expression is repeatedly measured over time such that a GSA needs to take into account the within-gene correlations in addition to possible between-gene correlations.</p> <p>Results</p> <p>We provide a robust nonparametric approach to compare the expressions of longitudinally measured sets of genes under multiple treatments or experimental conditions. The limiting distributions of our statistics are derived when the number of genes goes to infinity while the number of replications can be small. When the number of genes in a gene set is small, we recommend permutation tests based on our nonparametric test statistics to achieve reliable type I error and better power while incorporating unknown correlations between and within-genes. Simulation results demonstrate that the proposed method has a greater power than other methods for various data distributions and heteroscedastic correlation structures. This method was used for an IL-2 stimulation study and significantly altered gene sets were identified.</p> <p>Conclusions</p> <p>The simulation study and the real data application showed that the proposed gene set analysis provides a promising tool for longitudinal microarray analysis. R scripts for simulating longitudinal data and calculating the nonparametric statistics are posted on the North Dakota INBRE website <url>http://ndinbre.org/programs/bioinformatics.php</url>. Raw microarray data is available in Gene Expression Omnibus (National Center for Biotechnology Information) with accession number GSE6085.</p

    Malignant melanoma of the conjunctiva: a case report with examination of KIT and PDGFRA

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    Although many clinicopathological studies of malignant melanoma of the conjunctiva have been reported, there have been no studies of the expression and gene mutations of KIT and PDGFRA in melanoma of the conjunctiva. A 69-year-old Japanese woman consulted our hospital because of black mass (0.7 × 0.7 × 0.6 cm) in the conjunctiva. A biopsy was taken. The biopsy showed malignant epithelioid cells with melanin deposition. Immunohistochemically, the tumor was positive for S100 protein, HMB45, p53, Ki-67 (labeling=30%), KIT and PDGFRA. The tumor was negative for pancytokeratins (AE1/3 and CAM5.2). A genetic analysis using PCR-direct sequencing revealed no mutations of KIT gene (exons 9, 11, 13, and 17) and PDGFRA gene (exons 12 and 18). The pathological diagnosis was conjunctival melanoma. Despite chemotherapy, the patient developed multiple metastases of melanoma, and died of melanoma 7 years after the biopsy. In conclusion, the author reported a case of melanoma of conjunctive expressing KIT and PDGFRA proteins without gene mutations of KIT and PDGFRA

    Novel Biomarkers Distinguishing Active Tuberculosis from Latent Infection Identified by Gene Expression Profile of Peripheral Blood Mononuclear Cells

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    BACKGROUND: Humans infected with Mycobacterium tuberculosis (MTB) can delete the pathogen or otherwise become latent infection or active disease. However, the factors influencing the pathogen clearance and disease progression from latent infection are poorly understood. This study attempted to use a genome-wide transcriptome approach to identify immune factors associated with MTB infection and novel biomarkers that can distinguish active disease from latent infection. METHODOLOGY/PRINCIPAL FINDINGS: Using microarray analysis, we comprehensively determined the transcriptional difference in purified protein derivative (PPD) stimulated peripheral blood mononuclear cells (PBMCs) in 12 individuals divided into three groups: TB patients (TB), latent TB infection individuals (LTBI) and healthy controls (HC) (n = 4 per group). A transcriptional profiling of 506 differentially expressed genes could correctly group study individuals into three clusters. Moreover, 55- and 229-transcript signatures for tuberculosis infection (TB&LTBI) and active disease (TB) were identified, respectively. The validation study by quantitative real-time PCR (qPCR) performed in 83 individuals confirmed the expression patterns of 81% of the microarray identified genes. Decision tree analysis indicated that three genes of CXCL10, ATP10A and TLR6 could differentiate TB from LTBI subjects. Additional validation was performed to assess the diagnostic ability of the three biomarkers within 36 subjects, which yielded a sensitivity of 71% and specificity of 89%. CONCLUSIONS/SIGNIFICANCE: The transcription profiles of PBMCs induced by PPD identified distinctive gene expression patterns associated with different infectious status and provided new insights into human immune responses to MTB. Furthermore, this study indicated that a combination of CXCL10, ATP10A and TLR6 could be used as novel biomarkers for the discrimination of TB from LTBI

    The Potential Influence of Common Viral Infections Diagnosed during Hospitalization among Critically Ill Patients in the United States

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    Viruses are the most common source of infection among immunocompetent individuals, yet they are not considered a clinically meaningful risk factor among the critically ill. This work examines the association of viral infections diagnosed during the hospital stay or not documented as present on admission to the outcomes of ICU patients with no evidence of immunosuppression on admission. This is a population-based retrospective cohort study of University HealthSystem Consortium (UHC) academic centers in the U.S. from the years 2006 to 2009. The UHC is an alliance of over 90% of the non-profit academic medical centers in the U.S. A total of 209,695 critically ill patients were used in this analysis. Eight hospital complications were examined. Patients were grouped into four cohorts: absence of infection, bacterial infection only, viral infection only, and bacterial and viral infection during same hospital admission. Viral infections diagnosed during hospitalization significantly increased the risk of all complications. There was also a seasonal pattern for viral infections. Specific viruses associated with poor outcomes included influenza, RSV, CMV, and HSV. Patients who had both viral and bacterial infections during the same hospitalization had the greatest risk of mortality RR 6.58, 95% CI (5.47, 7.91); multi-organ failure RR 8.25, 95% CI (7.50, 9.07); and septic shock RR 271.2, 95% CI (188.0, 391.3). Viral infections may play a significant yet unrecognized role in the outcomes of ICU patients. They may serve as biological markers or play an active role in the development of certain adverse complications by interacting with coincident bacterial infection

    A novel outbred mouse model of 2009 pandemic influenza and bacterial co-infection severity

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    Influenza viruses pose a significant health risk and annually impose a great cost to patients and the health care system. The molecular determinants of influenza severity, often exacerbated by secondary bacterial infection, are largely unclear. We generated a novel outbred mouse model of influenza virus, Staphylococcus aureus, and coinfection utilizing influenza A/CA/07/2009 virus and S. aureus (USA300). Outbred mice displayed a wide range of pathologic phenotypes following influenza virus or co-infection ranging broadly in severity. Influenza viral burden positively correlated with weight loss although lung histopathology did not. Inflammatory cytokines including IL-6, TNF-α, G-CSF, and CXCL10 positively correlated with both weight loss and viral burden. In S. aureus infection, IL-1β, G-CSF, TNF-α, and IL-6 positively correlated with weight loss and bacterial burden. In co-infection, IL-1β production correlated with decreased weight loss suggesting a protective role. The data demonstrate an approach to identify biomarkers of severe disease and to understand pathogenic mechanisms in pneumonia. © 2013 McHugh et al

    Noncutaneous malignant melanoma: a prognostic model from a retrospective multicenter study

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    Abstract Background We performed multicenter study to define clinical characteristics of noncutaneous melanomas and to establish prognostic factors patients who received curative resection. Methods Of the 141 patients who were diagnosed of non-cutaneous melanoma at 4 institutions in Korea between June 1992 and May 2005, 129 (91.5%) satisfied the selection criteria. Results Of the 129 noncutaneous melanoma patients, 14 patients had ocular melanoma and 115 patients had mucosal melanoma. For mucosal melanoma, anorectum was the most common anatomic site (n = 39, 30.2%) which was followed by nasal cavity (n = 30, 23.3%), genitourinary (n = 21, 16.3%), oral cavity (n = 14, 10.9%), upper gastrointestinal tract (n = 6, 4.7%) and maxillary sinus (n = 5, 3.9%) in the order of frequency. With the median 64.5 (range 4.3-213.0) months follow-up, the median overall survival were 24.4 months (95% CI 13.2-35.5) for all patients, and 34.6 (95% CI 24.5-44.7) months for curatively resected mucosal melanoma patients. Adverse prognostic factors of survival for 87 curatively resected mucosal melanoma patients were complete resection (R1 resection margin), and age > 50 years. For 14 ocular melanoma, Survival outcome was much better than mucosal melanoma with 73.3% of 2 year OS and 51.2 months of median OS (P = .04). Conclusion Prognosis differed according to primary sites of noncutaneous melanoma. Based on our study, noncutaneous melanoma patients should be treated differently to improve survival outcome.Peer Reviewe