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      Activated amelogenin Y-linked ( AMELY) regulation and angiogenesis in human hepatocellular carcinoma by biocomputation

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          Abstract

          In the present study, a comparison of the biological processes and gene ontology (GO) in human hepatocellular carcinoma (HCC) with high expression (fold change ≥2) of amelogenin Y-linked (AMELY)-activated upstream regulation networks with non-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) with low expression of activated networks was performed. The principle biological processes involved in non-tumor hepatitis/cirrhotic tissues include positive regulation of mismatch repair, regulation of transcription from RNA polymerase II promoters, negative regulation of cell-cell adhesion, protein ubiquitinatin and protein catabolism. The main biological processes involved in the development of HCC include positive regulation of calcium ion transport into the cytosol, cell proliferation, DNA replication, fibroblast proliferation, immune response, microtubule polymerization and protein secretion. Specific transcription from RNA polymerase II promoters, regulation of angiogenesis, cell growth, protein metabolism, Wnt receptor signaling pathways, negative regulation of endothelial cell differentiation, microtubule depolymerization, peptidase activity and progression through the cell cycle are also involved. Positive regulation of transcription is involved in both processes. An activated AMELY-coupled upstream positive regulation of immune response-mediated protein secretion to Wnt signaling and calcium into cytosol-induced regulation of cell growth and angiogenesis in HCC is proposed. The AMELY upstream regulation molecular network model was constructed with BUB1B, CST6, ESM1, HOXA5, LEF1, MAPT, MYBL2, NOTCH3, PLA2G1B, PROK1, ROBO1, SCML2 and UBE2C in HCC from a Gene Expression Omnibus (GEO) dataset by gene regulation network inference methods and our programming methods.

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          Most cited references38

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          Gene expression in fixed tissues and outcome in hepatocellular carcinoma.

          It is a challenge to identify patients who, after undergoing potentially curative treatment for hepatocellular carcinoma, are at greatest risk for recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissue. We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed, paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of tissue samples from 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (P=0.04). We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlated with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. Copyright 2008 Massachusetts Medical Society.
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            Calcium store sensor stromal-interaction molecule 1-dependent signaling plays an important role in cervical cancer growth, migration, and angiogenesis.

            Store-operated Ca(2+) entry (SOCE) is the principal Ca(2+) entry mechanism in nonexcitable cells. Stromal-interaction molecule 1 (STIM1) is an endoplasmic reticulum Ca(2+) sensor that triggers SOCE activation. However, the role of STIM1 in regulating cancer progression remains controversial and its clinical relevance is unclear. Here we show that STIM1-dependent signaling is important for cervical cancer cell proliferation, migration, and angiogenesis. STIM1 overexpression in tumor tissue is noted in 71% cases of early-stage cervical cancer. In tumor tissues, the level of STIM1 expression is significantly associated with the risk of metastasis and survival. EGF-stimulated cancer cell migration requires STIM1 expression and EGF increases the interaction between STIM1 and Orai1 in juxta-membrane areas, and thus induces Ca(2+) influx. STIM1 involves the activation of Ca(2+)-regulated protease calpain, as well as Ca(2+)-regulated cytoplasmic kinase Pyk2, which regulate the focal-adhesion dynamics of migratory cervical cancer cells. Because of an increase of p21 protein levels and a decrease of Cdc25C protein levels, STIM1-silencing in cervical cancer cells significantly inhibits cell proliferation by arresting the cell cycle at the S and G2/M phases. STIM1 also regulates the production of VEGF in cervical cancer cells. Interference with STIM1 expression or blockade of SOCE activity inhibits tumor angiogenesis and growth in animal models, confirming the crucial role of STIM1-mediated Ca(2+) influx in aggravating tumor development in vivo. These results make STIM1-dependent signaling an attractive target for therapeutic intervention.
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              Inferring gene regulatory networks from multiple microarray datasets.

              Microarray gene expression data has increasingly become the common data source that can provide insights into biological processes at a system-wide level. One of the major problems with microarrays is that a dataset consists of relatively few time points with respect to a large number of genes, which makes the problem of inferring gene regulatory network an ill-posed one. On the other hand, gene expression data generated by different groups worldwide are increasingly accumulated on many species and can be accessed from public databases or individual websites, although each experiment has only a limited number of time-points. This paper proposes a novel method to combine multiple time-course microarray datasets from different conditions for inferring gene regulatory networks. The proposed method is called GNR (Gene Network Reconstruction tool) which is based on linear programming and a decomposition procedure. The method theoretically ensures the derivation of the most consistent network structure with respect to all of the datasets, thereby not only significantly alleviating the problem of data scarcity but also remarkably improving the prediction reliability. We tested GNR using both simulated data and experimental data in yeast and Arabidopsis. The result demonstrates the effectiveness of GNR in terms of predicting new gene regulatory relationship in yeast and Arabidopsis. The software is available from http://zhangorup.aporc.org/bioinfo/grninfer/, http://digbio.missouri.edu/grninfer/ and http://intelligent.eic.osaka-sandai.ac.jp or upon request from the authors.
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                Author and article information

                Journal
                Oncol Lett
                Oncol Lett
                OL
                Oncology Letters
                D.A. Spandidos
                1792-1074
                1792-1082
                March 2013
                10 January 2013
                10 January 2013
                : 5
                : 3
                : 1075-1079
                Affiliations
                [1 ]Biomedical Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876;
                [2 ]Lab of Computational Linguistics, School of Humanities and Social Sciences, Tsinghua University, Beijing 100084;
                [3 ]Shandong Longkou Yimin Molecular Drug Network Research and Development Center, Shandong 265700, P.R. China
                Author notes
                Correspondence to: Professor Lin Wang, Biomedical Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, 10 Xitucheng road, Haidian, Beijing 100876, P.R. China, E-mail: wanglin98@ 123456tsinghua.org.cn
                [*]

                Contributed equally

                Article
                ol-05-03-1075
                10.3892/ol.2013.1122
                3576279
                23426651
                b784edc7-1715-4ce1-8782-ab1c39045f97
                Copyright © 2013, Spandidos Publications

                This is an open-access article licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. The article may be redistributed, reproduced, and reused for non-commercial purposes, provided the original source is properly cited.

                History
                : 14 October 2012
                : 07 January 2013
                Categories
                Articles

                Oncology & Radiotherapy
                activated amelogenin y-linked (amely) upstream regulation network,wnt signaling,calcium signaling,cell growth,angiogenesis,theoretical analysis,hepatocellular carcinoma

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