993 research outputs found

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    ZEB1 drives prometastatic actin cytoskeletal remodeling by downregulating miR-34a expression

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    Metastatic cancer is extremely difficult to treat, and the presence of metastases greatly reduces a cancer patient’s likelihood of long-term survival. The ZEB1 transcriptional repressor promotes metastasis through downregulation of microRNAs (miRs) that are strong inducers of epithelial differentiation and inhibitors of stem cell factors. Given that each miR can target multiple genes with diverse functions, we posited that the prometastatic network controlled by ZEB1 extends beyond these processes. We tested this hypothesis using a mouse model of human lung adenocarcinoma metastasis driven by ZEB1, human lung carcinoma cells, and human breast carcinoma cells. Transcriptional profiling studies revealed that ZEB1 controls the expression of numerous oncogenic and tumor-suppressive miRs, including miR-34a. Ectopic expression of miR-34a decreased tumor cell invasion and metastasis, inhibited the formation of promigratory cytoskeletal structures, suppressed activation of the RHO GTPase family, and regulated a gene expression signature enriched in cytoskeletal functions and predictive of outcome in human lung adenocarcinomas. We identified several miR-34a target genes, including Arhgap1, which encodes a RHO GTPase activating protein that was required for tumor cell invasion. These findings demonstrate that ZEB1 drives prometastatic actin cytoskeletal remodeling by downregulating miR-34a expression and provide a compelling rationale to develop miR-34a as a therapeutic agent in lung cancer patients.Young-Ho Ahn, Don L. Gibbons, Deepavali Chakravarti, Chad J. Creighton, Zain H. Rizvi, Henry P. Adams, Alexander Pertsemlidis, Philip A. Gregory, Josephine A. Wright, Gregory J. Goodall, Elsa R. Flores and Jonathan M. Kuri

    Genetic susceptibility to chronic wasting disease in free-ranging white-tailed deer: Complement component C1q and Prnp polymorphisms

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    The genetic basis of susceptibility to chronic wasting disease (CWD) in free-ranging cervids is of great interest. Association studies of disease susceptibility in free-ranging populations, however, face considerable challenges including: the need for large sample sizes when disease is rare, animals of unknown pedigree create a risk of spurious results due to population admixture, and the inability to control disease exposure or dose. We used an innovative matched case–control design and conditional logistic regression to evaluate associations between polymorphisms of complement C1q and prion protein (Prnp) genes and CWD infection in white-tailed deer from the CWD endemic area in southcentral Wisconsin. To reduce problems due to admixture or disease-risk confounding, we used neutral genetic (microsatellite) data to identify closely related CWD-positive (n = 68) and CWD-negative (n = 91) female deer to serve as matched cases and controls. Cases and controls were also matched on factors (sex, location, age) previously demonstrated to affect CWD infection risk. For Prnp, deer with at least one Serine (S) at amino acid 96 were significantly less likely to be CWD-positive relative to deer homozygous for Glycine (G). This is the first characterization of genes associated with the complement system in white-tailed deer. No tests for association between any C1q polymorphism and CWD infection were significant at p \u3c 0.05. After controlling for Prnp, we found weak support for an elevated risk of CWD infection in deer with at least one Glycine (G) at amino acid 56 of the C1qC gene. While we documented numerous amino acid polymorphisms in C1q genes none appear to be strongly associated with CWD susceptibility

    Digital Genome-Wide ncRNA Expression, Including SnoRNAs, across 11 Human Tissues Using PolyA-Neutral Amplification

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    Non-coding RNAs (ncRNAs) are an essential class of molecular species that have been difficult to monitor on high throughput platforms due to frequent lack of polyadenylation. Using a polyadenylation-neutral amplification protocol and next-generation sequencing, we explore ncRNA expression in eleven human tissues. ncRNAs 7SL, U2, 7SK, and HBII-52 are expressed at levels far exceeding mRNAs. C/D and H/ACA box snoRNAs are associated with rRNA methylation and pseudouridylation, respectively: spleen expresses both, hypothalamus expresses mainly C/D box snoRNAs, and testes show enriched expression of both H/ACA box snoRNAs and RNA telomerase TERC. Within the snoRNA 14q cluster, 14q(I-6) is expressed at much higher levels than other cluster members. More reads align to mitochondrial than nuclear tRNAs. Many lincRNAs are actively transcribed, particularly those overlapping known ncRNAs. Within the Prader-Willi syndrome loci, the snoRNA HBII-85 (group I) cluster is highly expressed in hypothalamus, greater than in other tissues and greater than group II or III. Additionally, within the disease locus we find novel transcription across a 400,000 nt span in ovaries. This genome-wide polyA-neutral expression compendium demonstrates the richness of ncRNA expression, their high expression patterns, their function-specific expression patterns, and is publicly available

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Juxtaposing BTE and ATE – on the role of the European insurance industry in funding civil litigation