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Non-coding RNAs in Colorectal Cancer

Overview of attention for book
Attention for Chapter 10: Non-coding RNAs Enabling Prognostic Stratification and Prediction of Therapeutic Response in Colorectal Cancer Patients.
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Chapter title
Non-coding RNAs Enabling Prognostic Stratification and Prediction of Therapeutic Response in Colorectal Cancer Patients.
Chapter number 10
Book title
Non-coding RNAs in Colorectal Cancer
Published in
Advances in experimental medicine and biology, August 2016
DOI 10.1007/978-3-319-42059-2_10
Pubmed ID
Book ISBNs
978-3-31-942057-8, 978-3-31-942059-2
Authors

Samantha O. Perakis, Joseph E. Thomas, Martin Pichler

Editors

Ondrej Slaby, George A. Calin

Abstract

Colorectal cancer (CRC) is a heterogeneous disease and current treatment options for patients are associated with a wide range of outcomes and tumor responses. Although the traditional TNM staging system continues to serve as a crucial tool for estimating CRC prognosis and for stratification of treatment choices and long-term survival, it remains limited as it relies on macroscopic features and cases of surgical resection, fails to incorporate new molecular data and information, and cannot perfectly predict the variety of outcomes and responses to treatment associated with tumors of the same stage. Although additional histopathologic features have recently been applied in order to better classify individual tumors, the future might incorporate the use of novel molecular and genetic markers in order to maximize therapeutic outcome and to provide accurate prognosis. Such novel biomarkers, in addition to individual patient tumor phenotyping and other validated genetic markers, could facilitate the prediction of risk of progression in CRC patients and help assess overall survival. Recent findings point to the emerging role of non-protein-coding regions of the genome in their contribution to the progression of cancer and tumor formation. Two major subclasses of non-coding RNAs (ncRNAs), microRNAs and long non-coding RNAs, are often dysregulated in CRC and have demonstrated their diagnostic and prognostic potential as biomarkers. These ncRNAs are promising molecular classifiers and could assist in the stratification of patients into appropriate risk groups to guide therapeutic decisions and their expression patterns could help determine prognosis and predict therapeutic options in CRC.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 6%
Unknown 17 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 22%
Student > Ph. D. Student 3 17%
Student > Bachelor 2 11%
Student > Postgraduate 2 11%
Researcher 2 11%
Other 2 11%
Unknown 3 17%
Readers by discipline Count As %
Medicine and Dentistry 7 39%
Biochemistry, Genetics and Molecular Biology 2 11%
Agricultural and Biological Sciences 2 11%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Nursing and Health Professions 1 6%
Other 2 11%
Unknown 3 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 22 July 2017.
All research outputs
#20,341,859
of 22,888,307 outputs
Outputs from Advances in experimental medicine and biology
#3,972
of 4,952 outputs
Outputs of similar age
#293,970
of 336,879 outputs
Outputs of similar age from Advances in experimental medicine and biology
#62
of 81 outputs
Altmetric has tracked 22,888,307 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,952 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 1st percentile – i.e., 1% 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 336,879 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.