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Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models

The application of high-throughput genomic technologies has revealed that individual breast tumors display a variety of molecular features that require more personalized approaches to treatment. Several recent studies have demonstrated that a cross-species analytic approach provides a powerful means...

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Detalles Bibliográficos
Autores principales: Bennett, Christina N, Green, Jeffrey E
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2614501/
https://www.ncbi.nlm.nih.gov/pubmed/18828875
http://dx.doi.org/10.1186/bcr2125
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author Bennett, Christina N
Green, Jeffrey E
author_facet Bennett, Christina N
Green, Jeffrey E
author_sort Bennett, Christina N
collection PubMed
description The application of high-throughput genomic technologies has revealed that individual breast tumors display a variety of molecular features that require more personalized approaches to treatment. Several recent studies have demonstrated that a cross-species analytic approach provides a powerful means to filter through genetic complexity by identifying evolutionarily conserved genetic networks that are fundamental to the oncogenic process. Mouse-human tumor comparisons will provide insights into cellular origins of tumor subtypes, define interactive oncogenetic networks, identify potential novel therapeutic targets, and further validate as well as guide the selection of genetically engineered mouse models for preclinical testing.
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spelling pubmed-26145012009-01-08 Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models Bennett, Christina N Green, Jeffrey E Breast Cancer Res Review The application of high-throughput genomic technologies has revealed that individual breast tumors display a variety of molecular features that require more personalized approaches to treatment. Several recent studies have demonstrated that a cross-species analytic approach provides a powerful means to filter through genetic complexity by identifying evolutionarily conserved genetic networks that are fundamental to the oncogenic process. Mouse-human tumor comparisons will provide insights into cellular origins of tumor subtypes, define interactive oncogenetic networks, identify potential novel therapeutic targets, and further validate as well as guide the selection of genetically engineered mouse models for preclinical testing. BioMed Central 2008 2008-09-11 /pmc/articles/PMC2614501/ /pubmed/18828875 http://dx.doi.org/10.1186/bcr2125 Text en Copyright © 2008 BioMed Central Ltd
spellingShingle Review
Bennett, Christina N
Green, Jeffrey E
Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models
title Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models
title_full Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models
title_fullStr Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models
title_full_unstemmed Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models
title_short Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models
title_sort unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2614501/
https://www.ncbi.nlm.nih.gov/pubmed/18828875
http://dx.doi.org/10.1186/bcr2125
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