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Urothelial Carcinoma

Overview of attention for book
Cover of 'Urothelial Carcinoma'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Analysis of Chromosomal Alterations in Urothelial Carcinoma
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    Chapter 2 Analysis of Point Mutations in Clinical Samples of Urothelial Carcinoma
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    Chapter 3 A Versatile Assay for Detection of Aberrant DNA Methylation in Bladder Cancer.
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    Chapter 4 Immunohistochemical Analysis of Urothelial Carcinoma Tissues for Proliferation and Differentiation Markers
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    Chapter 5 Molecular Subtype Profiling of Urothelial Carcinoma Using a Subtype-Specific Immunohistochemistry Panel
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    Chapter 6 Defining the Pathways of Urogenital Schistosomiasis-Associated Urothelial Carcinogenesis through Transgenic and Bladder Wall Egg Injection Models.
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    Chapter 7 Algorithm for the Automated Evaluation of NAT2 Genotypes
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    Chapter 8 Detection of APOBEC3 Proteins and Catalytic Activity in Urothelial Carcinoma
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    Chapter 9 Oxidative Stress in Urothelial Carcinogenesis: Measurements of Protein Carbonylation and Intracellular Production of Reactive Oxygen Species
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    Chapter 10 Urothelial Carcinoma Stem Cells: Current Concepts, Controversies, and Methods.
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    Chapter 11 In Vitro Differentiation and Propagation of Urothelium from Pluripotent Stem Cell Lines.
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    Chapter 12 Spheroid Cultures of Primary Urothelial Cancer Cells: Cancer Tissue-Originated Spheroid (CTOS) Method
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    Chapter 13 The N-butyl-N-4-hydroxybutyl Nitrosamine Mouse Urinary Bladder Cancer Model.
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    Chapter 14 Patient-Derived Bladder Cancer Xenografts
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    Chapter 15 Orthotopic Mouse Models of Urothelial Cancer
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    Chapter 16 Quantification of MicroRNAs in Urine-Derived Specimens.
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    Chapter 17 Quantitative RNA Analysis from Urine Using Real Time PCR
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    Chapter 18 DNA Methylation Analysis from Body Fluids.
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    Chapter 19 Urinary Protein Markers for the Detection and Prognostication of Urothelial Carcinoma
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    Chapter 20 Isolation and Characterization of CTCs from Patients with Cancer of a Urothelial Origin
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    Chapter 21 Epigenetic Treatment Options in Urothelial Carcinoma.
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    Chapter 22 Evaluation of Protein Levels of the Receptor Tyrosine Kinase ErbB3 in Serum
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    Chapter 23 Targeting the PI3K/AKT/mTOR Pathway in Bladder Cancer
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    Chapter 24 Visualization and Quantitative Measurement of Drug-Induced Platinum Adducts in the Nuclear DNA of Individual Cells by an Immuno-Cytological Assay
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    Chapter 25 Erratum to: Urinary Protein Markers for the Detection and Prognostication of Urothelial Carcinoma
Attention for Chapter 16: Quantification of MicroRNAs in Urine-Derived Specimens.
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Chapter title
Quantification of MicroRNAs in Urine-Derived Specimens.
Chapter number 16
Book title
Urothelial Carcinoma
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7234-0_16
Pubmed ID
Book ISBNs
978-1-4939-7233-3, 978-1-4939-7234-0
Authors

Fuessel, Susanne, Lohse-Fischer, Andrea, Vu Van, Dana, Salomo, Karsten, Erdmann, Kati, Wirth, Manfred P, Susanne Fuessel, Andrea Lohse-Fischer, Dana Vu Van, Karsten Salomo, Kati Erdmann, Manfred P. Wirth, Wirth, Manfred P.

Abstract

MicroRNAs are small noncoding RNAs which regulate the expression of genes involved in a multitude of cellular processes. Dysregulation of microRNAs and-in consequence-of the affected pathways is frequently observed in numerous pathologies including cancers. Therefore, tumor-related alterations in microRNA expression and function can reflect molecular processes of tumor onset and progression qualifying microRNAs as potential diagnostic and prognostic biomarkers.In particular, microRNAs with differential expression in bladder cancer (BCa) might represent promising tools for noninvasive tumor detection in urine. This would be helpful not only for diagnostic and monitoring purposes but also for therapeutic decisions. Detection and quantification of BCa-associated microRNAs in urine can be performed using the cellular sediment, which also contains BCa cells, or in exosomes originating from those cells. Methods for isolation of exosomes from urine, extraction of total RNA from cells and exosomes as well as techniques for RNA quantification, reverse transcription, and qPCR-based quantification of microRNA expression levels are described herein.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 26%
Researcher 7 20%
Student > Master 4 11%
Student > Bachelor 3 9%
Other 2 6%
Other 3 9%
Unknown 7 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 40%
Medicine and Dentistry 6 17%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Engineering 2 6%
Agricultural and Biological Sciences 1 3%
Other 1 3%
Unknown 9 26%
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 22 September 2017.
All research outputs
#18,074,317
of 23,225,652 outputs
Outputs from Methods in molecular biology
#7,379
of 13,315 outputs
Outputs of similar age
#311,260
of 443,294 outputs
Outputs of similar age from Methods in molecular biology
#869
of 1,500 outputs
Altmetric has tracked 23,225,652 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,315 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 443,294 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,500 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.