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Dose-dependent benefits of quercetin on tumorigenesis in the C3(1)/SV40Tag transgenic mouse model of breast cancer

CANCER BIOLOGY & THERAPY 2014年第11期15卷 1456-1467页

作者： Steiner, J. L. Davis, J. M. McClellan, J. L. Enos, R. T. Carson, J. A. Fayad, R. Nagarkatti, M. Nagarkatti, P. S. Altomare, D. Creek, K. E. Murphy, E. A. Univ S Carolina Sch Med Dept Pathol Microbiol & Immunol Columbia SC 29208 USA Univ S Carolina Dept Exercise Sci Columbia SC 29208 USA Univ S Carolina South Carolina Coll Pharm Dept Drug Discovery & Biomed Sci Columbia SC 29208 USA

Breast cancer is the leading cause of cancer related death in women. Quercetin is a flavonol shown to have anti-carcinogenic actions. However, few studies have investigated the dose-dependent effects of quercetin on tumorigenesis and none have used the C3(1)/SV40 Tag breast cancer mouse model. At 4 weeks of age female C3(1)/SV40 Tag mice were randomized to one of four dietary treatments (n = 15-16/group): control (no quercetin), low-dose quercetin (0.02% diet), moderate-dose quercetin (0.2% diet), or high-dose quercetin (2% diet). Tumor number and volume was assessed twice a week and at sacrifice (20 wks). Results showed an inverted 'U' dose-dependent effect of dietary quercetin on tumor number and volume;at sacrifice the moderate dose was most efficacious and reduced tumor number 20% and tumor volume 78% compared to control mice (C3-Con: 9.0 +/- 0.9;C3-0.2%: 7.3 +/- 0.9) and (C3-Con: 2061.8 +/- 977.0 mm(3);and C3-0.2%: 462.9 +/- 75.9 mm(3)). Tumor volume at sacrifice was also reduced by the moderate dose compared to the high and low doses (C3-2%: 1163.2 +/- 305.9 mm(3);C3-0.02%: 1401.5 +/- 555.6 mm(3)), as was tumor number (C3-2%: 10.7 +/- 1.3 mm(3);C3-0.02%: 8.1 +/- 1.1 mm(3)). gene expression microarray analysis performed on mammary glands from C3-Con and C3-0.2% mice determined that 31 genes were down-regulated and 9 genes were up-regulated more than 2-fold (P < 0.05) by quercetin treatment. We report the novel finding that there is a distinct dose-dependent effect of quercetin on tumor number and volume in a transgenic mouse model of human breast cancer, which is associated with a specific gene expression signature related to quercetin treatment.

关键词： mammary tumorigenesis gene expression microarray flavonoid dose-response

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HES-Mediated Repression of Pten in Caenorhabditis elegans

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G3-geneS GENOMES geneTICS 2015年第12期5卷 2619-2628页

作者： Chou, Han Ting Vazquez, Raymarie Gomez Wang, Kun Campbell, Richard Milledge, Gaolin Zheng Walthall, Walter W. Johnson, Casonya M. Georgia State Univ Dept Biol Atlanta GA 30303 USA Georgia State Univ Ctr Obes Reversal Atlanta GA 30303 USA NYU Sch Med Dept Environm Hlth Sci Div Biostat New York NY 10016 USA N Carolina Cent Univ Dept Math & Comp Sci Durham NC 27707 USA

The hairy/enhancer-of-split (HES) group of transcription factors controls embryonic development, often by acting downstream of the Notch signaling pathway;however, little is known about postembryonic roles of these proteins. In Caenorhabditis elegans, the six proteins that make up the REF-1 family are considered to be HES orthologs that act in both Notch-dependent and Notch-independent pathways to regulate embryonic events. To further our understanding of how the REF-1 family works to coordinate postembryonic cellular events, we performed a functional characterization of the REF-1 family member, HLH-25. We show that, after embryogenesis, hlh-25 expression persists throughout every developmental stage, including dauer, into adulthood. Like animals that carry loss-of-function alleles in genes required for normal cell-cycle progression, the phenotypes of hlh-25 animals include reduced brood size, unfertilized oocytes, and abnormal gonad morphology. Using gene expression microarray, we show that the HLH-25 transcriptional network correlates with the phenotypes of hlh-25 animals and that the C. elegans Pten ortholog, daf-18, is one major hub in the network. Finally, we show that HLH-25 regulates C. elegans lifespan and dauer recovery, which correlates with a role in the transcriptional repression of daf-18 activity. Collectively, these data provide the first genetic evidence that HLH-25 may be a functional ortholog of mammalian HES1, which represses PTEN activity in mice and human cells.

关键词： hairy enhancer-of-split dauer recovery gonad morphology unfertilized oocytes gene expression microarray

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Mineralocorticoid receptors are present in skeletal muscle and represent a potential therapeutic target

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FASEB JOURNAL 2015年第11期29卷 4544-4554页

作者： Chadwick, Jessica A. Hauck, J. Spencer Lowe, Jeovanna Shaw, Jeremiah J. Guttridge, Denis C. Gomez-Sanchez, Celso E. Gomez-Sanchez, Elise P. Rafael-Fortney, Jill A. Ohio State Univ Coll Med Dept Mol & Cellular Biochem Columbus OH 43210 USA Ohio State Univ Coll Med Dept Physiol & Cell Biol Columbus OH 43210 USA Ohio State Univ Coll Med Dept Mol Virol Immunol & Med Genet Columbus OH 43210 USA Univ Mississippi Med Ctr Dept Internal Med Jackson MS 39216 USA Univ Mississippi Med Ctr Dept Pharmacol & Toxicol Jackson MS 39216 USA

Early treatment with heart failure drugs lisinopril and spironolactone improves skeletal muscle pathology in Duchenne muscular dystrophy (DMD) mouse models. The angiotensin converting enzyme inhibitor lisinopril and mineralocorticoid receptor (MR) antagonist spironolactone indirectly and directly target MR. The presence and function of MR in skeletal muscle have not been explored. MR mRNA and protein are present in all tested skeletal muscles from both wild-typemice and DMD mouse models. MR expression is cell autonomous in both undifferentiated myoblasts and differentiated myotubes from mouse and human skeletal muscle cultures. To test for MR function in skeletal muscle, global gene expression analysis was conducted on human myotubes treated with MR agonist (aldosterone;EC50 1.3 nM) or antagonist (spironolactone;IC50 1.6 nM), and 53 gene expression differences were identified. Five differences were conserved in quadriceps muscles from dystrophic mice treated with spironolactone plus lisinopril (IC50 0.1 nM) compared with untreated controls. genes down-regulated morethan 2-fold by MR antagonism included FOS, ANKRD1, and GADD45B, with known roles in skeletal muscle, in addition to NPR3 and SERPINA3, bona fide targets of MR in other tissues. MR is a novel drug target in skeletal muscle and use of clinically safe antagonists may be beneficial for muscle diseases.

关键词： aldosterone gene expression microarray muscular dystrophy spironolactone steroid hormone receptors

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Identification of differentially expressed genes in primary Sjogren's syndrome

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JOURNAL OF CELLULAR BIOCHEMISTRY 2019年第10期120卷 17368-17377页

作者： Zhang, Lei Xu, Poshi Wang, Xiaoyu Zhang, Zongshan Zhao, Wenxin Li, Zhengmin Yang, Guangxia Liu, Panpan Fuwai Cent China Cardiovasc Hosp Dept Lab Med 1 Fuwai Rd Zhengzhou 450000 Henan Peoples R China Henan Prov Peoples Hosp Dept Obstet & Gynecol Zhengzhou Henan Peoples R China

Primary Sjogren's syndrome (pSS) is a chronic systemic autoimmune disease that affects exocrine glands. To study the molecular mechanism and identify crucial genes/pathways in pSS pathogenesis, the microarray-based whole-genome gene expression profiles from salivary glands of patients with pSS and non-sicca controls were retrieved. After normalization and subsequent batch effect adjustment, significance analysis of microarrays method was applied to five available datasets, and 379 differentially expressed genes (DEGs) were identified. The 300 upregulated DEGs were enriched in gene Ontology terms of immune and inflammatory responses, including antigen processing and presentation, interferon-mediated signaling pathway, and chemotaxis. Previously reported pSS-associated genes, including HLA-DRA, TAP2, PRDM1, and IFI16, were found to be significantly upregulated. The downregulated DEGs were enriched in pathways of salivary secretion, carbohydrate digestion and absorption, and starch and sucrose metabolism, implying dysfunction of salivary glands during pathogenesis. Next, a protein-protein interaction network was constructed, and B2M, an upregulated DEG, was shown to be a hub, suggesting its potential involvement in pSS development. In summary, we found the activation of pSS-associated genes in pathogenesis, and provide clues for salivary glands dysfunction. Experimental investigation on the identified DEGs in this study will deepen our understanding on pSS.

关键词： differentially expressed genes gene expression microarray meta-analysis primary Sjogren's syndrome salivary glands

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Early transcriptional control of ENaC (de) ubiquitylation by aldosterone

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KIDNEY INTERNATIONAL 2008年第6期73卷 691-696页

作者： Verrey, F. Fakitsas, P. Adam, G. Staub, O. Univ Zurich Inst Physiol CH-8057 Zurich Switzerland Univ Zurich Ctr Integrat Human Physiol ZIHP CH-8057 Zurich Switzerland Univ Lausanne Dept Pharmacol & Toxicol Lausanne Switzerland

Aldosterone increases sodium reabsorption across kidney target tubules already before it increases the number of transport proteins, indicating that the early functional response to aldosterone depends on the activation of preexisting channels and pumps. A central mediator of this action is the early aldosterone-induced kinase Sgk1 that derepresses the surface expression and activity of the epithelial sodium channel (ENaC). A main mechanism by which Sgk1 exerts this de-repression is the phosphorylation of the ubiquitin ligase Nedd4-2 that is thereby prevented from ubiquitylating ENaC. Among a series of new early aldosterone-induced gene products recently identified in kidney target tubules, an additional regulator of ENaC ubiquitylation, the deubiquitylating enzyme Usp2-45, was identified. Coexpression of Usp2-45 was shown to increase ENaC surface expression and activity, and to decrease its ubiquitylation in expression systems, whereas other Usps such as the splice variant Usp2-69 had no effect. Since both Sgk1 and Usp2-45 are similarly induced in distal colon as well, in contrast to other gene products strongly induced in kidney that are not regulated in colon, we suggest that (de) ubiquitylation is the major ENaC regulatory mechanism targeted by aldosterone in the short-term via transcriptional regulation.

关键词： gene expression microarray mouse kidney cortical collecting duct transepithelial sodium transport ubiquitin Usp2-45 SGK

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LINEAR COHERENT BI-CLUSTERING VIA BEAM SEARCHING AND SAMPLE SET CLUSTERING

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DISCRETE MATHEMATICS ALGORITHMS AND APPLICATIONS 2012年第2期4卷 1250023-1-1250023-20页

作者： Shi, Yi Hasan, Maryam Cai, Zhipeng Lin, Guohui Schuurmans, Dale Univ Alberta Dept Comp Sci 2-21 Athabasca Hall Edmonton AB T6G 2E8 Canada Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA

We propose a new bi-clustering algorithm, LinCoh, for finding linear coherent bi-clusters in gene expression microarray data. Our method exploits a robust technique for identifying conditionally correlated genes, combined with an efficient density-based search for clustering sample sets. Experimental results on both synthetic and real datasets demonstrated that LinCoh consistently finds more accurate and higher quality bi-clusters than existing bi-clustering algorithms.

关键词： Bi-clustering sample set clustering gene expression microarray gene ontology

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Liknon feature selection for microarrays

Liknon feature selection for Microarrays

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7th International Workshop on Fuzzy Logic and Applications

作者： Pranckeviciene, Erinija Somorjai, Ray Natl Res Council Canada Inst Biodiagnost 435 Ellice Ave Winnipeg MB R3B 1Y6 Canada

ISBN: (纸本)9783540733997

Many real-world classification problems involve very sparse and high-dimensional data. The successes of LIKNON - linear programming support vector machine (LPSVM) for feature selection, motivates a more thorough analysis of the method when applied to sparse, multivariate data. Due to the sparseness, the selection of a classification model is greatly influenced by the characteristics of that particular dataset. Robust feature/model selection methods are desirable. LIKNON is claimed to have such robustness properties. Its feature selection operates by selecting the groups of features with large differences between the resultants of the two classes. The degree of desired difference is controlled by the regularization parameter. We study the practical value of LIKNON-based feature/model selection for microarray data. Our findings support the claims about the robustness of the method.

关键词： feature selection gene expression microarray linear programming support vector machine LIKNON regularization parameter sample to feature ratio

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TNBCtype: A Subtyping Tool for Triple-Negative Breast Cancer

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CANCER INFORMATICS 2012年第11期11卷 147-156页

作者： Chen, Xi Li, Jiang Gray, William Lehmann, Brian Bauer, Joshua Shyr, Yu Pietenpol, Jennifer Vanderbilt Univ Dept Biostat Nashville TN 37232 USA Vanderbilt Univ Ctr Quantitat Sci Nashville TN 37232 USA Vanderbilt Univ Dept Biochem Nashville TN 37232 USA Vanderbilt Univ Vanderbilt Inst Chem Biol Nashville TN 37232 USA Vanderbilt Univ Vanderbilt Ingram Canc Ctr Nashville TN 37232 USA

Motivation: Triple-negative breast cancer (TNBC) is a heterogeneous breast cancer group, and identification of molecular subtypes is essential for understanding the biological characteristics and clinical behaviors of TNBC as well as for developing personalized treatments. Based on 3,247 gene expression profiles from 21 breast cancer data sets, we discovered six TNBC subtypes from 587 TNBC samples with unique gene expression patterns and ontologies. Cell line models representing each of the TNBC subtypes also displayed different sensitivities to targeted therapeutic agents. Classification of TNBC into subtypes will advance further genomic research and clinical applications. Result: We developed a web-based subtyping tool TNBCtype for candidate TNBC samples using our gene expression meta data and classification methods. Given a gene expression data matrix, this tool will display for each candidate sample the predicted subtype, the corresponding correlation coefficient, and the permutation P-value. We offer a user-friendly web interface to predict the subtypes for new TNBC samples that may facilitate diagnostics, biomarker selection, drug discovery, and the more tailored treatment of breast cancer.

关键词： triple-negative breast cancer gene expression microarray meta-analysis classification subtypes

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A STABLE gene SELECTION METHOD BASED ON SAMPLE WEIGHTING

A STABLE GENE SELECTION METHOD BASED ON SAMPLE WEIGHTING

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26th IEEE Annual Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Wang, Guoyin Gao, Juan Hu, Feng Chongqing Univ Posts & Telecommun Chongqing Key Lab Computat Intelligence Chongqing 400065 Peoples R China

ISBN: (纸本)9781479900336;9781479900312

In microarray analysis, the selection of informative gene is an essential issue for tissue classification and successful treatment because of its ability to improve the accuracy and decrease computational complexity. However, the gene subsets selected by the same method often vary significantly with some variations of the samples in the same data set. Thus, the stability of the selected genes is an aspect as important as the predictive ability to quantify a feature selection algorithm. This work is an attempt to improve the stability of feature selection methods from the point of view of sample importance. We propose an efficient mean deviation-based sample weighting algorithm to improve the stability of feature selection methods by assigning a weight to each sample according to the mean deviation of its local value in giving samples. We perform a series of experiments with four frequently studied public data sets, and the experimental results validate that the proposed method improves the stability of common feature selection algorithms such as ReliefF without sacrificing the classification performance. Furthermore, more stable gene feature sets obtained by the proposed method than the state-of-the-art ensemble method and margin-based sample weighting algorithm.

关键词： Feature selection Stability gene expression microarray Classification performance

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Exploratory Visual Analysis of Statistical Results from microarray Experiments Comparing High and Low Grade Glioma

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CANCER INFORMATICS 2007年第Systems Biology期5卷 19-24页

作者： Reif, David Israel, Mark Moore, Jason Dartmouth Hitchcock Med Ctr Computat Genet Lab Lebanon NH 03756 USA Dartmouth Hitchcock Med Ctr Norris Cotton Canc Ctr Lebanon NH 03756 USA Dartmouth Hitchcock Med Ctr One Med Ctr Dr Lebanon NH 03766 USA

The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occuring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis.

关键词： glioma gene expression microarray statistics biological interpretation visualization annotation databases

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