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MicroRNA and Cancer

Overview of attention for book
Cover of 'MicroRNA and Cancer'

Table of Contents

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    Book Overview
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    Chapter 1 Noncoding RNAs in DNA Damage Response: Opportunities for Cancer Therapeutics
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    Chapter 2 MicroRNAs in Breast Cancer: Diagnostic and Therapeutic Potential
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    Chapter 3 Involvement of miRNAs and Pseudogenes in Cancer
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    Chapter 4 MicroRNAs Reprogram Tumor Immune Response
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    Chapter 5 Apolipoprotein B mRNA Editing Enzyme, Catalytic Polypeptide-Like Gene Expression, RNA Editing, and MicroRNAs Regulation
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    Chapter 6 MicroRNAs Change the Landscape of Cancer Resistance
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    Chapter 7 MicroRNA, Noise, and Gene Expression Regulation
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    Chapter 8 Deep Sequencing Reveals a MicroRNA Expression Signature in Triple-Negative Breast Cancer
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    Chapter 9 Detection of Plasma MicroRNA Signature in Osteosarcoma Patients
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    Chapter 10 Identification of E6/E7-Dependent MicroRNAs in HPV-Positive Cancer Cells
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    Chapter 11 Combination of Anti-miRNAs Oligonucleotides with Low Amounts of Chemotherapeutic Agents for Pancreatic Cancer Therapy
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    Chapter 12 Evaluation of MicroRNA Delivery In Vivo
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    Chapter 13 Angiogenesis Analysis by In Vitro Coculture Assays in Transwell Chambers in Ovarian Cancer
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    Chapter 14 Application of Individual qPCR Performance Parameters for Quality Control of Circulating MicroRNA Data
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    Chapter 15 Construction of Multi-Potent MicroRNA Sponge and Its Functional Evaluation
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    Chapter 16 MicroRNA Sequencing Data Analysis Toolkits
Attention for Chapter 9: Detection of Plasma MicroRNA Signature in Osteosarcoma Patients
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Citations

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Chapter title
Detection of Plasma MicroRNA Signature in Osteosarcoma Patients
Chapter number 9
Book title
MicroRNA and Cancer
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7435-1_9
Pubmed ID
Book ISBNs
978-1-4939-7433-7, 978-1-4939-7435-1
Authors

Wendy Allen-Rhoades, Jason T. Yustein, Allen-Rhoades, Wendy, Yustein, Jason T.

Abstract

Circulating microRNAs are increasingly being used as noninvasive prognostic and predictive biomarkers for various types of cancer. We describe a method that uses real-time quantitative PCR (qPCR) for establishing a signature plasma microRNA profile that can distinguish patients with osteosarcoma from healthy control samples.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 38%
Unspecified 1 13%
Professor > Associate Professor 1 13%
Student > Bachelor 1 13%
Student > Postgraduate 1 13%
Other 0 0%
Unknown 1 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 25%
Medicine and Dentistry 2 25%
Immunology and Microbiology 1 13%
Unspecified 1 13%
Unknown 2 25%