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Ovarian Cancer

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Cover of 'Ovarian Cancer'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Ovarian Cancer Genome
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    Chapter 2 Identifying Associations Between Genomic Alterations in Tumors
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    Chapter 3 Analysis of Genome-Wide DNA Methylation Profiles by BeadChip Technology
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    Chapter 4 Integrative Prediction of Gene Function and Platinum-Free Survival from Genomic and Epigenetic Features in Ovarian Cancer
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    Chapter 5 Survival prediction based on inherited gene variation analysis.
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    Chapter 6 Main principles and outcomes of DNA methylation analysis.
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    Chapter 7 Methylation-specific PCR.
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    Chapter 8 Bisulfite sequencing of cloned alleles.
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    Chapter 9 Bisulfite pyrosequencing.
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    Chapter 10 RNA Networks in Ovarian Cancer
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    Chapter 11 Microarray-Based Transcriptome Profiling of Ovarian Cancer Cells
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    Chapter 12 Deep transcriptome profiling of ovarian cancer cells using next-generation sequencing approach.
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    Chapter 13 Assessment of mRNA Splice Variants by qRT-PCR.
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    Chapter 14 MicroRNA Profiling in Ovarian Cancer
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    Chapter 15 Detailed Analysis of Promoter-Associated RNA
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    Chapter 16 Integrating Multiple Types of Data to Identify MicroRNA–Gene Co-modules
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    Chapter 17 Energy Metabolism and Changes in Cellular Composition in Ovarian Cancer
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    Chapter 18 Metabolomic Profiling of Ovarian Carcinomas Using Mass Spectrometry
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    Chapter 19 Choline Metabolic Profiling by Magnetic Resonance Spectroscopy
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    Chapter 20 Proteomic Profiling of Ovarian Cancer Models Using TMT-LC-MS/MS
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    Chapter 21 Characterization of Signalling Pathways by Reverse Phase Protein Arrays
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    Chapter 22 N-Glycosylation Analysis by HPAEC-PAD and Mass Spectrometry
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    Chapter 23 In Vivo and In Vitro Properties of Ovarian Cancer Cells
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    Chapter 24 Establishment of Primary Cultures from Ovarian Tumor Tissue and Ascites Fluid
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    Chapter 25 Ovarian Cancer Stem Cells Enrichment
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    Chapter 26 Assessment of resistance to anoikis in ovarian cancer.
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    Chapter 27 Analysis of EMT by Flow Cytometry and Immunohistochemistry.
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    Chapter 28 Challenges in Experimental Modeling of Ovarian Cancerogenesis
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    Chapter 29 Transformation of the human ovarian surface epithelium with genetically defined elements.
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    Chapter 30 In Vitro Model of Spontaneous Mouse OSE Transformation.
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    Chapter 31 Orthotopic, Syngeneic Mouse Model to Study the Effects of Epithelial–Stromal Interaction
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    Chapter 32 Immunocompetent Mouse Model of Ovarian Cancer for In Vivo Imaging
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    Chapter 33 Drug Delivery Approaches for Ovarian Cancer Therapy
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    Chapter 34 Polymer-Based Delivery of RNA-Based Therapeutics in Ovarian Cancer
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    Chapter 35 Ligand-coupled lipoprotein for ovarian cancer-specific drug delivery.
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    Chapter 36 Ovarian Cancer
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    Chapter 37 Exosomes as a potential tool for a specific delivery of functional molecules.
Attention for Chapter 37: Exosomes as a potential tool for a specific delivery of functional molecules.
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Chapter title
Exosomes as a potential tool for a specific delivery of functional molecules.
Chapter number 37
Book title
Ovarian Cancer
Published in
Methods in molecular biology, January 2013
DOI 10.1007/978-1-62703-547-7_37
Pubmed ID
Book ISBNs
978-1-62703-546-0, 978-1-62703-547-7
Authors

Irina Nazarenko, Anne-Kathleen Rupp, Peter Altevogt, Nazarenko, Irina, Rupp, Anne-Kathleen, Altevogt, Peter

Abstract

Extracellular membrane vesicles derived from the endosomal compartments and released by the fusion of the multivesicular bodies with the cell membrane are referred as exosomes (Exo) [Van Niel et al., J Biochem 140:13-21, 2006]. They function as mediators of intercellular communication and are employed by the organism in the regulation of systemic and local processes. Meantime, Exo are recognized as an indispensable entity of physiological fluids [Caby et al., Int Immunol 17:879-887, 2005; Lasser et al., J Transl Med 9:9, 2011; Lasser et al., Am J Rhinol Allergy 25:89-93, 2011]. Exo and other types of extracellular vesicles, e.g., exosome-like vesicles [van Niel et al., Gastroenterology 121:337-349, 2001] and microvesicles (MV) [Daveloose et al., Thromb Res 22:195-201, 1981], contain multiple functional molecules including lipids [Vidal et al., J Cell Physiol 140:455-462, 1989]; proteins [Simpson et al., Expert Rev Proteomics 6:267-283, 2009]; mRNA [Valadi et al., Nat Cell Biol 9:654-659, 2007]; DNA [Waldenstrom et al., PLoS One 7:e34653, 2012]; noncoding RNA, e.g., miRNA [Simpson et al., Expert Rev Proteomics 6:267-283, 2009]; and retrotransposon elements [Balaj et al., Nat Commun 2:180, 2011]. Assessment of the biological functions of Exo showed that they deliver specifically their cargo from the donor to recipient cells. Albeit the molecular mechanisms of this process are not fully understood, approaches for the application of Exo and MV as a tool for a cell-specific delivery of signalling molecules were successfully tested in in vitro and in vivo models [Maguire et al., Mol Ther 20:960-971, 2012]. Ovarian cancer cells release Exo, which bind stroma cells as well as donor cancer cells [Escrevente et al., BMC Cancer 11:108, 2011]. Here we describe an experimental approach for the assessment of Exo interaction and uptake by target cells. Methods for the isolation and purification of Exo from cell culture supernatants are included. To allow visualization of vesicle uptake, labelling of Exo with different fluorescent dyes, such as CFSE, PKH, DHPE, and DiOC18, is presented. Finally, we explain qualitative and quantitative analysis of Exo uptake by immunofluorescence and flow cytometry, respectively.

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Geographical breakdown

Country Count As %
Denmark 2 2%
Uruguay 1 1%
Germany 1 1%
Unknown 77 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 27%
Student > Ph. D. Student 18 22%
Student > Master 11 14%
Student > Bachelor 7 9%
Professor > Associate Professor 4 5%
Other 7 9%
Unknown 12 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 27%
Biochemistry, Genetics and Molecular Biology 17 21%
Medicine and Dentistry 16 20%
Nursing and Health Professions 1 1%
Computer Science 1 1%
Other 10 12%
Unknown 14 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 August 2013.
All research outputs
#18,968,525
of 23,510,717 outputs
Outputs from Methods in molecular biology
#8,178
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Outputs of similar age
#222,038
of 284,648 outputs
Outputs of similar age from Methods in molecular biology
#222
of 339 outputs
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