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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Oncology
Article . 2009 . Peer-reviewed
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Oncology
Article . 2010
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Prognostic Applications of Gene Expression Signatures in Breast Cancer

Authors: Normanno N.; De Luca A.; Carotenuto P.; Lamura L.; Oliva I.; D'Alessio A.;

Prognostic Applications of Gene Expression Signatures in Breast Cancer

Abstract

Analysis by DNA microarrays has led to the identification of molecular subtypes of breast carcinomas that show a distinct expression profile. Several studies have demonstrated that this ‘intrinsic subtype’ classification has a strong prognostic value. In addition, gene expression profiling techniques have been used to identify gene signatures that could be associated with the outcome of breast cancer patients. Several different genomic tests have been shown to better define the prognosis of early-stage breast cancer patients as compared with conventional clinical and pathological characteristics of the tumors, and some assays are already commercially available. However, it must be emphasized that the prognostic power of these genetic classifiers has not been confirmed yet in prospective trials. Genetic signatures that might predict the activity of specific chemotherapy agents have also been developed by using gene expression profiling techniques. The same approach has been used to identify gene signatures associated with the activation of oncogenic pathways that might represent targets for molecular therapy of breast cancer. By using these approaches, gene expression techniques might significantly improve our ability to predict the risk of recurrence and to tailor the treatment for each individual breast cancer patient.

Country
Italy
Related Organizations
Keywords

Tumor, Gene Expression Profiling, Breast cancer; Gene expression profiling; Prognosis; Biomarkers, Tumor; Breast Neoplasms; Female; Humans; Prognosis; Gene Expression Profiling; Oligonucleotide Array Sequence Analysis, Breast Neoplasms, Prognosis, Gene expression profiling, Breast cancer, Biomarkers, Tumor, Humans, Female, Biomarkers, Oligonucleotide Array Sequence Analysis

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    18
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Average
Average
Top 10%
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